text:
\section{Introduction}
\label{sec:Introduction}
The transition to a net-zero economy is an urgent challenge, and many countries have agreed to put in place national action plans to become carbon-neutral by 2050 or sooner \cite{EuropeGreenDeal,Paris}.  A significant aspect of the response is an increase in funding for heat decarbonisation and energy efficiency projects. In the context of tight government budgets and the uncertainty associated with the implementation of green technologies, a comprehensive handling of risk is crucial in assessing the viability of these projects. The aim of this paper is to demonstrate a new approach to dealing with uncertainty for the planning of energy infrastructure projects in the form of stochastic ordering (dominance).

The context of this paper is waste heat recovery, in which heat from industrial and urban sources is used as a zero-carbon alternative to fossil fuels in district heating networks. In particular, we consider a district heating project based on a real system in Brunswick (Braunschweig), Germany, in which heat from a data centre will be used as an input to a district heating network for a newly constructed residential and commercial area in the city.  The system is one of four demonstrators on the ReUseHeat project \cite{lygnerud2019contracts}. The main objective of ReUseHeat is to aid \textit{replication} of projects and provide advice to other investors. Here, ``based on'' refers to the matching of variables, that is matching the model inputs and outputs to the metrics observed in the real-world. We note that the modelling results were not used in the design of the actual system. However, the model conclusions derived can provide assistance for the design of similar projects.\par

A wide range of methods have been adopted to support decisions in the energy systems domain under uncertainty. For example, \cite{Soroudi2013} pointed out the importance of uncertainty analysis in energy systems. Different approaches include the use of membership functions (fuzzy methods) and probability density functions (stochastic methods) for describing the uncertainty of input parameters. The effect of input parameters on model outputs can be quantified by simple statistical measures such as the standard deviation, mean squared error, confidence intervals and their multivariate and Bayesian counterparts. In addition, there is a recent interest in the use of scenarios to capture wider uncertainty issues \cite{Wheatcroft2019}.

Another general approach for decision support in energy systems is optimisation frameworks (stochastic optimisation), which operate by controlling the output variability of a component or system, while keeping the output minimum (maximum) on target \cite{Moret2020}. In particular, in mean-variance (MV) and capital asset pricing models, widely used in finance and economics to assess different investment options, the aim is to achieve maximum yield and minimum volatility. Mean-variance portfolio theory has been employed for the modelling of uncertainties and risk in energy system planning \cite{ioannou2017risk, bhattacharya2012power}. These decision approaches rely on the MV rule, which states that, when two alternative prospects are considered, a rational decision-maker will choose an option with higher expected return and lower variance. However, the MV rule leads to a number of paradoxes such as the fact that it is sometimes unable to rank the two choices when a clear preference between them exists \cite{Levy2015} .

We note that the approaches described above operate with statistical summaries, which can fail to provide specific information about the distribution of outputs. We are keen to preserve the notion of robustness (uncertainty) by considering full probability distributions using stochastic ordering (dominance). Stochastic ordering is a special methodological framework, which underlines decision making under uncertainty and has been exploited in a number of fields, including robust design \cite{ cook2018optimization}, portfolio theory \cite{annaert2009performance} and signal processing \cite{tepedelenlioglu2011applications}. In particular, we note that stochastic dominance has been used previously to compare the performance of algorithms in power and energy system optimisation \cite{Chicco2017}. An extensive review of stochastic ordering is given in \cite{mosler1993stochastic}.

A stochastic ordering is a partial ordering on distributions. In this paper we consider first-order stochastic dominance (FSD) \cite{Levy2015}. Orderings provide a useful framework for comparing distributions in the following sense: suppose we are aiming to maximise the return on our investment and have two choices to make regarding the investment portfolio (Portfolio $X$ and Portfolio $Y$). We assume that there is uncertainty associated with returns on investment portfolios and we can construct probability distributions of the return in each case.  If the distribution of choice $X$ first-order stochastically dominates that of choice $Y$, for any given level of return, the probability that the profit exceeds that particular value is higher for choice $X$ than it is for choice $Y$. In other words, if we are only interested in maximising the probability of the return exceeding some chosen value, we should always choose Portfolio $X$. This seems like a sensible and intuitive way to look at decision making under uncertainty and this is our approach here. \par

Stochastic orderings roughly divide into two classes: orderings that denote shift (in mean) and those that denote variability (dispersion). We note that the ordering does not prescribe uncertainty measures, but we claim that it provides a platform for uncertainty analysis in the following sense. Given an ordering, a suitable metric is one which is order-preserving with respect to that ordering. This means that it is a function whose expectation is ordered in the same direction as the stochastic underlying ordering. Thus both the mean and the median themselves are order-preserving with respect to first-order stochastic dominance and both the standard deviation and the Gini coefficients are ordered with respect to some well-known dispersion orderings. Following this condition, stochastic ordering allows us to extend the range of metrics for risk and uncertainty beyond the standard measures.\par

This paper is structured as follows. Section \ref{sec:District_heating} covers background regarding district heating.
Section \ref{sec:StochasticOrdering} provides an introduction to stochastic orderings. Section \ref{sec:Experiments} describes a series of simple computer experiments on a specially selected set of system designs, choices of input variations and broader scenario-based alternatives. Section \ref{sec:Results} draws conclusions based on a selection of stochastic orderings. Section \ref{sec:Discussion} consists of discussion and motivation for future work. \par

\section{Problem specification}
\label{sec:District_heating}
\subsection{District heating}
District heating is a system in which heat is produced by some centralised source and distributed via a network of insulated pipes.  It is particularly well-developed in northern Europe and Scandinavia \cite{DEA}. Historically, district heating has been powered by the burning of fossil fuels such as coal and gas.  However, more recently, it has been seen as an opportunity to decarbonise the heating sector via the use of waste heat from industry and other sources, with an increasing focus on the opportunities of recovering waste heat from low temperature, urban sources such as, for example, metro stations \cite{lygnerud2019contracts}. The prevalence of low temperature sources and their location near areas of heat demand provides an opportunity in the wider agenda of carbon reduction \cite{persson2018accessible}. \par

A major difference between high and low temperature heat recovery is that, in the latter case, the heat typically needs to be upgraded before it is suitable for use in the network.  This requires the use of a heat pump to increase the temperature to the required level.  The installation of heat pumps poses additional technical challenges due to a lack of maturity in the technology and a lack of experience in installation and maintenance. In addition, heat pumps run on electricity and this creates additional operational costs and a vulnerability to increases in the price of electricity.  This is considered to be a major risk in low temperature heat recovery \cite{lygnerud2019contracts}. \par

At present, low temperature heat recovery is not widespread.  There are a number of reasons for this, including a lack of political and commercial awareness, a lack of interest from heat 'owners', the immaturity of the technology and a lack of a legal and regulatory framework \cite{lygnerud2019contracts}. However, one of the biggest barriers, in our opinion, to the widespread rollout of low temperature waste heat recovery is a gap between the risk assessment required by financial institutions and that which is typically provided by project developers. With the methodology presented in this paper, we aim to contribute towards closing this gap.

\subsection{Heat recovery in Brunswick}\label{section:brunswick}
We construct a simple model based on the Brunswick demonstrator in the aforementioned ReUseHeat project \cite{lygnerud2019contracts}.  The aim of the demonstrator is to supply heat to 400 newly built housing units, using waste heat from a nearby data centre which is upgraded to a suitable temperature with a heat pump.  The new housing units will also be connected to the existing city-wide network which, at present, supplies 45 percent of residents in the city using a gas powered combined heat and power (CHP) unit.  The intention is then that heat from the data centre will cover the baseline demand (demand that is present throughout the year such as for hot water) and heat from the CHP will cover seasonal demand.  Figure~\ref{fig:Brunswick_sketch} presents the layout of the Brunswick demonstrator.

For the study described in this paper, we plan to assess three different design options to meet the demand for heat. In the first, the entire heat demand is met by the CHP. The second follows the setup of the demonstrator for which baseline demand is met by heat from the data centre and seasonal demand is met by the CHP. In the third, the entire heat demand is met by waste heat from the data centre.

To construct a model and run simulations, we employ an open source optimisation model for energy planning called Open Source Energy Modeling System (OSeMOSYS) \citep{Howells2011}. OSeMOSYS is a deterministic, linear optimisation model that obtains the energy supply mix that minimises the Net Present Cost (NPC), subject to a number of chosen constraints.
We have chosen OSeMOSYS for two main reasons. Firstly, it provides us with the flexibility to operate on a local (city) level and to define our own scenarios. Secondly, OSeMOSYS is an open source model and therefore freely available for comparative project modelling.

\FloatBarrier
\begin{figure}[ht]
\begin{center}
\includegraphics[scale=0.4]{Brunswick_sketch}
\end{center}
\caption{An outline of the Brunswick demonstrator.}
\label{fig:Brunswick_sketch}
\end{figure}
\FloatBarrier

\section{Uncertainty and Stochastic orderings}
\label{sec:StochasticOrdering}
We consider the use of stochastic ordering for describing and comparing uncertainty. The rationale is that stochastic orderings are weaker than a limited list of specific metrics. In particular, stochastic ordering is a partial ordering, whereas the commonly used metrics of uncertainty, such as standard deviation, impose total ordering.

\begin{defn}{\cite{Marshall1979}} \label{defn:stochastic_dom} A random variable $X$ is said to be stochastically less than (or equal to) $Y$, written $X\prec_{st} Y$, if the upper tail probabilities satisfy
\begin{equation}
P(X>t)\leq P(Y>t), \quad t\in\mathbb{R},
\end{equation}
or
\begin{equation}
    P(X\leq t)\geq P(Y\leq t), \quad t\in\mathbb{R}.
\end{equation}
\end{defn}
We refer to this ordering as first-order stochastic dominance (SD). Marshall and Arnold \cite{Marshall1979} presented the following conditions equivalent to $X\prec_{st}Y$:
\begin{enumerate}[(i)]
  \item ${\mathbb E}\big[ g(X)\big] \leq {\mathbb E}\big[ g(Y)\big]$ for all increasing (non-decreasing) functions $g(\cdot)$;
  \item $g(X)\prec_{st}g(Y)$ for all increasing (non-decreasing) functions $g(\cdot)$;
  \item $P(X\in A)\leq P(Y\in A)$ for all sets $A$ with increasing indicator functions.
\end{enumerate}
The class of functions $g(\cdot)$ that satisfies (i.) and (ii.) is said to be the set of order-preserving functions with respect to a stochastic ordering.

\begin{comment}
Let $X$ and $Y$ be two random variables, \textcolor{blue}{``then $X$ is said to be smaller than $Y$ in the usual stochastic order, denoted by $X\prec Y$.''}

Note that the partial ordering requirement gives transitivity:
$$\{X \prec Y\;\; \mbox{and}\;\;Y \prec Z\} \Rightarrow X \prec Z.$$

\textcolor{red}{Henry, why are we jumping from order-preserving functions to first-order stochastic dominance? What is the connection here?} We also briefly discuss the idea of order-preserving functions. A function $g(x)$ is said to be order preserving with respect to a stochastic ordering, $X \prec Y$ if, for their expectations (which may sometimes be called risks),
$${\mathbb E}\big[ g(X)\big] \leq {\mathbb E}\big[ g(Y)\big]. $$
In many cases, we are able to characterise the ordering via the set of {\em all} order preserving functions.  The best known ordering is first-order stochastic dominance $X_1 \prec_{st} X_2$, which is defined when
$$F_2(x) \leq F_1(x), \;\; \mbox{for all} \;\; x \in \mathbb R.$$
and the inequality is strict for at least one value of $x \in \mathbb R.$ Equivalently, we can define all order-preserving functions, which is the set of all non-decreasing functions in $\mathbb R$. \par
\end{comment}

From Definition \ref{defn:stochastic_dom}, we conclude that, to look for first-order SD, we can simply plot the empirical cdfs. If one always lies below the other, we can claim that it dominates with respect to any increasing function.

Consider NPC or emissions levels associated with two energy system designs, which we will refer to as design options $A$ and $B$. We construct a probability distribution for each output under each design option. Design option $A$ has first-order stochastic SD over design option $B$ if:
\begin{align*}
&F_A(x)\leq F_B(x)\quad\text{for all }x, \\
&F_A(x)<F_B(x)\quad\text{for at least one value of }x,
\end{align*}
where $F_A(x)$ and $F_B(x)$ are cdfs of NPC or emissions levels associated with design options $A$ and $B$, respectively. Since dominance in this example is associated with higher values of NPC or emissions levels, and our objective is to minimise the costs and the level of emissions, we are inclined to choose design option $B$ over design option $A$.\par

\subsection{Dispersion orderings}
We consider dispersion orderings (sometimes known as dispersive orderings), which are a particular case of stochastic orderings. Dispersion measures the extent to which a distribution is stretched or squeezed, and therefore dispersion orderings compare the spread of the probability distributions \cite{Shaked1982, Ayala2015}. Dispersion orderings can be extended for the multivariate variable case based on the idea of independent copies.

Let $\bb{X}$ and $\bb{Y}$ be two $d$-dimensional random vectors, i.e. $\bb{X}=(X_1, \dots, X_d)$ and $\bb{Y}=(Y_1, \dots, Y_d)$, with (multivariate) cdfs $F_{\bb{X}}(\bb{x})$ and $F_{\bb{Y}}(\bb{y})$. Let $D(\bb{r}, \bb{s})$ be some distance function between two $d$-dimensional vectors $\bb{r}$ and $\bb{s}$. Then, as above, let $(\bb{X}, \bb{X}')$ and $(\bb{Y}, \bb{Y}')$ be pairs of independent random vectors from the distributions $F_{\bb{X}}(\bb{x})$ and $F_{\bb{Y}}(\bb{y})$, respectively. We define a dispersion ordering $\prec_D$ to be $\bb{X}\prec_D\bb{Y}$ if and only if
\begin{equation}
    D(\bb{X}, \bb{X}')\prec_{st} D(\bb{Y}, \bb{Y}'),
\end{equation}
which says that $\bb{X}$ is less dispersive than $\bb{Y}$. In other words, less uncertainty is associated with the distribution of the vector $\bb{X}$ than the vector $\bb{Y}$.

Prior to describing particular dispersion orderings, we note that, for any given distance $D(\bb{r}, \bb{s})$, the class of order-preserving functions comprises all increasing (non-decreasing) functions, $g(\cdot)$ of $D(\bb{r}, \bb{s})$. By choice of distance and function, $g(\cdot)$, we can therefore cover a large range of dispersion metrics. \par

Consider the $L_2$ ordering introduced by \cite{giovagnoli1995multivariate} defined as
$$D(\bb{r},\bb{s}) = ||\bb{r}-\bb{s}|| = \left\{\sum_{i=1}^d (r_i- s_i)^2 \right\}^{\frac{1}{2}},$$
where $D(\bb{r}, \bb{s})$ is the Euclidean distance, or $L_{2}$.  This is called the ``weak dispersion ordering''. Another dispersion ordering is the $L_1$ distance ordering determined from the following expressions:
$$ D(\bb{r},\bb{s}) = \sum_{i=1}^d |r_i- s_i|, $$
where $D(\bb{r}, \bb{s})$ is the $L_{1}$ distance.

A natural extension of the independent copies idea is to take $k+1$ copies $\bb{X}_1, \ldots, \bb{X}_{k+1}$ and define a function, $\phi(\bb{X}_1,\bb{X}_2, \ldots, \bb{X}_{k+1})$, that describes the separation between them. In \cite{pronzato2017extended}, it is shown
that, if we take
$$\phi(\bb{x}_1, \ldots, \bb{x}_{k+1}) = (\mbox{vol} \{\triangle (\bb{x}_1, \ldots, \bb{x}_{k+1}) \})^2,$$
where $\triangle(\bb{x}_1, \ldots, \bb{x}_{k+1})$ is the $k$-dimensional simplex (in $d$ dimensions) whose vertices are $\bb{x}_1, \ldots, \bb{x}_{k+1}\in\mathbb{R}^d$, then  ${\mathbb E }\{ \phi(\bb{X}_1, \ldots, \bb{X}_{k+1})\}$
is a function of the variance-covariance matrix $\Sigma$ of the underlying distribution. This prompts a dispersion ordering $\bb{X} \prec_{\triangle} \bb{Y}$ defined by
$$ \mbox{vol} \{\triangle (\bb{X}_1, \ldots, \bb{X}_{k+1}) \} \prec_{st} \mbox{vol} \{\triangle (\bb{Y}_1, \ldots, \bb{Y}_{k+1}) \},$$
where $\bb{X}_1, \ldots, \bb{X}_{k+1}$ and $\bb{Y}_1, \ldots, \bb{Y}_{k+1}$ are independent draws from the $F_{\bb{X}}(\bb{x})$ and $F_{\bb{Y}}(\bb{y})$, respectively. The case in which $k=d$ was introduced by Oja \cite{oja1983descriptive} and discussed in \cite{giovagnoli1995multivariate} and is referred to as the Simplex ordering. Here, we remove the requirement that $k=d$ and refer to the approach as the Generalised Simplex ordering.  Note, again, that whenever we
see the ordering $\prec_{st}$, we can write down the class of order-preserving functions, $g(\cdot)$, in the present case of $\mbox{vol} \{\triangle (\bb{X}_1, \ldots, \bb{X}_{k+1}) \}$. Dispersion orderings based on Hausdorff distance \cite{lopez2006indexed} and Mahalanobis distance \cite{pronzato2018simplicial} are possible alternatives to the simplex ordering. \par

We briefly point out the impact of scaling on dispersion orderings. When considering the $L_1$ distance ordering, the scaling of the variables impacts the relative contribution of each one in the calculation of the $L_1$ distance. Therefore, the $L_1$ ordering is sensitive to scale and pre-processing of the data is required to ensure that we operate in the same range across all dimensions. On the contrary, the simplex volume is a scale-free, homogeneous measure and therefore no pre-processing is required for the Generalised Simplex ordering. For more details see \ref{subsec:scaling}. We also note that computing the simplex volume can become computationally expensive, in particular when we are operating with large data sets. To deal with this, \cite{Ayala2015} proposed the use of bootstrap resamples from the data set to obtain the distances. Despite this, we believe the properties of the Generalised Simplex ordering make it an attractive choice and we provide a demonstration of its use in Section \ref{sec:Results},

\subsection{Quantifying the difference between cdfs} \label{subsection:quantifying}
It is useful to quantify the extent of the difference between two cdfs when one dominates another. Here, we use a Kolmogorov-Smirnov (KS) distance measure, which is defined as follows. Let the random variables $X$ and $Y$ have cdfs $F_{X} (z)$ and $F_{Y}(z)$ respectively.  The KS distance between $X$ and $Y$ is given by
$$
D=\sup_z|F_X(z)-F_Y(z)|, \quad z\in \mathbb{R}.
$$
Noting that the value of $D$ lies in the range $[0, 1]$, the statistic tells us the maximum difference between the two cdfs.  If $D$ is small, the extent to which one dominates the other is small and vice versa.

\subsection{Hypothesis testing for stochastic orderings} \label{section:hypothesis_test}

In the studies presented in Section \ref{sec:Results}, the distributions of the outputs are produced using an energy systems simulation (OSeMOSYS \cite{Howells2011}) and therefore we can only approximate the underlying cdf of the output variables that would be produced with an infinite sample size. Thus we make use of the Kolmogorov-Smirnov (KS) test proposed by \cite{Mcfadden1989} which defines the null hypothesis to be the case that $Y$ first-order stochastically dominates $X$ and the alternative hypothesis that the null hypothesis is false. If the null hypothesis can be rejected, we do not have enough evidence that one dominates the other.

Formally, let $X_1, \dots, X_n$ and $Y_1, \dots, Y_m$ be samples from $F_X$ and $F_Y$, respectively. Let the null hypothesis be
$$
H_0: F_X(z)\geq F_Y(z), \quad z\in \mathbb{R}
$$
The alternative hypothesis is
$$
H_1: F_X(z)<F_Y(z), \quad z\in\mathbb{R}.
$$
{We perform a one-tailed Kolmogorov-Smirnov test and consider $D^{-}$, the maximum negative deviation, defined as
$$
D^{-}= \sup_z (F_Y(z)-F_X(z)).
$$
Large values of $D^{-}$ will occur when the alternative hypothesis is true and the null hypothesis can be rejected, providing significant evidence against stochastic ordering.  This approach is similar to that used by \cite{Ayala2015} who tested the Hausdoff and Simplex dispersion orderings.

We note that an assumption of the KS test is that the samples should be independent of each other and, although, in each sample, the simulations are performed independently, the input parameters induced by the scenarios are common to both and therefore the assumption fails. Similar technical difficulties arise with the bootstrap methodology.  Nonetheless, we note that the effect of this failed assumption is small and diminishes with sample size (which is generally large).  We therefore believe that these results are informative for our analysis and provide a useful diagnostic technique in general.

Another issue requiring us to be cautious is the use of multiple testing. In our experiments, we consider three options $(N=3)$ and, as a result, we perform three pairwise post-hoc tests to assess the differences between them.  To account for this multiple testing, we make use of the Bonferroni correction.  Therefore, if we specify a significance level of $\alpha=0.05$, the corresponding significance level for each individual hypothesis is adjusted to $\alpha/N=0.05/3=0.0167$.

\section{Experimental design}
\label{sec:Experiments}
We demonstrate the use of stochastic ordering to assess the aforementioned waste heat recovery project in Brunswick (see Section~\ref{section:brunswick} for more details).  Three different design options are considered, each of which differ according to the technology mix employed for supplying domestic heat.  These are outlined in Table~\ref{tab:Design}.  Each design option is evaluated in terms of its Net Present Cost (NPC) (mln \euro{}) and $CO_2$-equivalent emissions (in metric tonnes). Here, we analyse the uncertainty in the outputs of the model induced by variations in four different inputs:
\begin{enumerate}
\item Operational costs.
\item Discount rate.
\item Coefficient of Performance (COP) for the heat pump (units of heat delivered per unit of electricity).
\item Emission Activity Factor (the emissions produced (in metric tonnes) from operating a particular technology in the energy system).
\end{enumerate}
Variations in the four input variables are expected to impact both the NPC and emissions levels.  For each input variable, we specify three levels: low, medium and high. We then perform simulations with a full factorial design (often known as a fully crossed design) so that all possible combinations across the model inputs are considered \citep{George2005}. This gives a total of 81 simulation runs. \par

\FloatBarrier
\begin{table}[ht]
\centering
\begin{tabular}{| m{4cm} | m{9cm} | }
\hline
\textbf{Design type} & \textbf{Description}\\ [0.5ex]
\hline
Design Option 1 & Combined Heat and Power (CHP) is employed to meet both the baseload and seasonal heat demand. \\
\hline
Design Option 2 & A heat pump is employed to meet baseload heat demand and CHP is used to meet seasonal heat demand. \\
\hline
Design Option 3 & A heat pump is employed with a small amount of storage to meet both the baseload and seasonal heat demand. \\
\hline
\end{tabular}
\caption{Description of design options in the study.}
\label{tab:Design}
\end{table}
\FloatBarrier
We consider each of the design options under three different scenarios.  Scenario Analysis is a widely used uncertainty tool in energy systems studies \cite{Wheatcroft2019}. Examples of scenarios related to energy include the Future Energy Scenarios (FES) published by the UK National Grid \cite{FES2021} and World Energy Scenarios \cite{WorldEnergy2019}, both of which consider different pathways to decarbonisation.

We define three scenarios that differ in terms of selected elements of government climate policy and consumer engagement with green technology. A description of the three scenarios is given in Table~\ref{tab:Scenarios}. In the Green scenario, a combination of high consumer engagement and government incentive schemes are used to rapidly reach net zero. In the Market scenario, there is a reliance on market forces and only limited government intervention in the energy system planning. Finally, the Neutral scenario captures the middle ground between the two. Since the operational lifetime of a typical heat pump is around twenty years, this time horizon is used for the study.

Under each scenario, we produce model simulations that, for a given set of model inputs, generate the volume of emissions and NPC over a 20 year period as model outputs.  In Section \ref{subsec:order_mean}, we consider the empirical cdfs of the model outputs under different scenarios and design options. Then, in Section \ref{subsec:dispersion_order}, we consider the Generalised Simplex dispersion ordering to compare the effects of different scenarios and design options on uncertainty.

\FloatBarrier
\begin{table}[ht]
\centering
\begin{tabular}{| m{4cm} | m{9cm} | }
\hline
\textbf{Scenario} & \textbf{Description} \\
\hline
Green  scenario & Penalty per Mton of emissions: 100 \euro{} per Mton.

Annual change in baseload and seasonal heat demand: -1\%.

Increasing gas prices and decreasing electricity prices.\\
\hline
Neutral  scenario &
Penalty per Mton of emissions: 40 \euro{} per Mton.

Baseload and seasonal heat demand fluctuate around the central projections.

Gas and electricity prices stay within the central projected values.\\
\hline
Market scenario &
No penalty per Mton of emissions.

Annual change in baseload and seasonal heat demand: 1\%.

Decreasing gas prices and increasing electricity prices.\\
\hline
\end{tabular}
\caption{Description of the selected scenarios in the study.}
\label{tab:Scenarios}
\end{table}
\FloatBarrier

\section{Results}
\label{sec:Results}
Figure \ref{fig:ScatterPlot} shows scatter plots of the two model outputs obtained for each of the three design options and under each scenario. Focusing first on emissions, since the emissions factor for natural gas is higher than for electricity, the highest level of emissions is produced by design option 1, followed by design option 2 and then design option 3. From the second row in Figure~\ref{fig:ScatterPlot}, we observe that the different scenarios have only a small impact on the levels of emissions under each of the design options. This is not surprising since government interventions typically aim at changing behaviour through cost. \par

Differences in the three scenarios have a much larger impact on NPC. Under the Market and Neutral scenarios, design option 1 corresponds to the lowest NPC values, which can be explained by the high investment cost of the heat pump. However, under the Green scenario, the opposite is true due to a high carbon penalty. Therefore, under the Green scenario, design options 2 and 3 become more attractive alternatives, thus demonstrating the value of considering different scenarios when informing decision-makers.

\FloatBarrier
\begin{figure}[ht]
\begin{center}
\includegraphics[width=0.8\textwidth,height=0.3\textheight]{ScatterPlot}
\includegraphics[width=0.8\textwidth,height=0.3\textheight]{ScenarioSeparately}
\end{center}
\caption{\textit{First row}: NPC (mln \euro) against $CO_2$-equivalent emissions (Mton) for all three design options under the three scenarios. \textit{Second row}: NPC against emissions for all three design options, plotted separately for each scenario.}
\label{fig:ScatterPlot}
\end{figure}
\FloatBarrier

\subsection{Orderings in the mean}
\label{subsec:order_mean}
Figure \ref{fig:Plot1NPC} shows the cdfs of the NPC of each design option under each of the three scenarios (first row) and of each scenario under the three design options (second row).  In Table \ref{tab:KS_first_order_design} values of the Kolmogorov-Smirnov (KS) distance measure between the cdfs of different design options under each scenario are shown.  The numbers in the table represent the distance between the cdfs when the design option denoted in the column dominates that denoted in the row. In each cell, there are three numbers that correspond to the Market, Neutral and Green scenarios, respectively. Cases in which there is no dominance in this direction are denoted with a dash.  In addition, we perform the one-tailed Kolmogorov-Smirnov test defined in Section \ref{section:hypothesis_test} to assess whether the null hypothesis of stochastic dominance can be rejected with $p$-values corresponding to NPC and emissions shown in Table \ref{tab:KS_first_order_design_pvals}. Cases where the cdfs cross and first-order SD clearly does not exist are denoted by an `na'.

From the first row of Figure \ref{fig:Plot1NPC}, we observe that, under the Market scenario, design option 3 has first-order SD over design option 2 which has first-order SD over design option 1. Under the Green scenario, the ordering is reversed, mainly due to the increased financial support from policy makers for renewable energy sources. Under the Neutral scenario, the cdfs for design option 2 and design option 3 cross, so first-order SD cannot discriminate between these two options. However, we observe that design option 1 is dominated by the other two options. We therefore conclude that, if the sole aim is to minimise NPC, under the Green scenario, design option 3 would be the preferred option whilst design option 1 would be the preferred option under the Neutral and Market scenarios.  The reason for this difference is that, under the Green scenario, the government introduces high penalties for generation of emissions, which makes design option 1 an unattractive option for providing heat.

The KS values in Table \ref{tab:KS_first_order_design} demonstrate the extent to which there is dominance between design options.  For example, in the Market and Neutral scenarios, design option 2 dominates design option 1 with a KS distance of $1$ and $0.37$, respectively. In the Green Scenario, the dominance is reversed and design option 1 dominates design option 2 with a KS distance of $0.48$.  Focusing on Table \ref{tab:KS_first_order_design_pvals}, for NPC, the $p$-values for whether design option 1 dominates design option 2 are $0/<0.001/1$.  This means that stochastic dominance in this direction can be rejected for the Market and Neutral scenarios whilst it is not rejected for the Green Scenario.

\begin{table}[ht]
\begin{center}
\begin{tabular}{ |c|c|c|c|c|c| }
\hline
 & & design 1 & design 2 & design 3\\
\hline
\multirow{3}{4em}{NPC} & design 1 & & 1/0.37/- & 1/0.41/-\\
& design 2 & -/ -/0.48 & &  0.33/NA/-\\
& design 3 & -/-/0.57 & -/NA/0.23 & \\
\hline
\multirow{3}{4em}{Emissions} & design 1 & & -/-/- & -/-/-\\
& design 2 & 1/1/1 & &  -/-/-\\
& design 3 & 1/1/1 & 1/1/1 & \\
\hline
\end{tabular}
\caption{Kolmogorov-Smirnov distances between empirical cdfs of NPC and $CO_2$-equivalent emissions for pairs of design options. The KS values correspond to the Market, Neutral and Green scenarios and are only shown when the cdf for the design option in the row is dominated by that in the column. NA values indicate that the cdfs cross, and first-order SD does not exist in either direction.}
\label{tab:KS_first_order_design}
\end{center}
\end{table}

\begin{table}[ht]
\begin{center}
\begin{tabular}{ |c|c|c|c|c|c| }
\hline
 & & design 1 & design 2 & design 3\\
\hline
\multirow{3}{4em}{NPC} & design 1 & & 1/1/$0^*$ & 1/1/$0^*$\\
& design 2 & $0^*$/ $<0.001^*$/1 & &  1/NA/$0.012^*$\\
& design 3 & $0^*$/$<0.001^*$/$<0.001^*$ & $<0.001^*$/NA/1 & \\
\hline
\multirow{3}{4em}{Emissions} & design 1 & & $0^*$/$0^*$/$0^*$ & $0^*$/$0^*$/$0^*$\\
& design 2 & 1/1/1 & &  $0^*$/$0^*$/$0^*$\\
& design 3 & 1/1/1 & 1/1/1 & \\
\hline
\end{tabular}
\caption{Observed $p$-values for NPC and $CO_2$-equivalent emissions using first-order stochastic ordering. The three $p$-values in each table entry correspond to the Market, Neutral and Green scenarios and an asterisk denotes that stochastic dominance is rejected at the chosen significance level. NA values indicate that the cdfs cross, and  therefore no hypothesis test is performed.}
\label{tab:KS_first_order_design_pvals}
\end{center}
\end{table}

Focusing now on the effects of each scenario on the three design options, under design option 1 the Green scenario dominates the Neutral scenario which dominates the Market scenario. In this case, the ordering indicates that the highest NPC values are generated under the Green scenario.  For design option 3, on the other hand, the ordering between scenarios is reversed.  Under design option 2, the cdf for the Neutral scenario dominates that of the Green scenario whilst the cdf for the Market scenario crosses the other two cdfs and thus there is no ordering.  Overall, the difference in orderings may lead a planner to think carefully about their choice of design option under different possible futures.  If, for example, they consider policy featured in the Green scenario to be likely, they may choose design option 2 or 3 to mitigate that risk.

In Table \ref{tab:KS_first_order_scenario}, we present KS distances for the NPC and emissions associated with each scenario under the selected design options.  Table \ref{tab:KS_first_order_pvals_scenario} provides $p$-values for the one-sided KS test. Notably, for NPC, under design option 1, we observe high values of the KS distance between pairs of scenarios. This demonstrates a substantial scenario effect which is much larger than for the other two design options.  This is reflected in the high $p$-values which indicate that SD cannot be rejected.

Figure \ref{fig:Plot1Emissions} shows the empirical cdfs corresponding to emission levels. The empirical cdfs of emissions for each design option under each of the three scenarios (top row) demonstrate that, under all three scenarios, design option 1 dominates design option 2, which dominates design option 3.  This, of course, is unsurprising since the scenarios differ in terms of the extent to which policy is driven by `green' considerations and confirms our expectation that waste heat recovery is a carbon reducing technology under most reasonable policy decisions.

\begin{table}[ht]
\begin{center}
\begin{tabular}{ |c|c|c|c|c|c| }
\hline
 & & Market & Neutral & Green\\
\hline
\multirow{3}{4em}{NPC} & Market & & 1/NA/- & 1/NA/-\\
& Neutral & -/ NA/0.33 & &  0.78/0.20/-\\
& Green & -/NA/0.33 & -/-/0.18 & \\
\hline
\multirow{3}{4em}{Emissions} & Market & & -/-/- & -/-/-\\
& Neutral & 0.33/0.33/0.22 & &  -/-/-\\
& Green & 0.56/0.56/0.44 & 0.33/0.33/0.22 & \\
\hline
\end{tabular}
\caption{Kolmogorov-Smirnov distances between empirical cdfs of NPC and $CO_2$-equivalent emissions for pairs of scenarios. The KS values correspond to design option 1, design option 2 and design option 3 and are only shown when the cdf for scenario in the column lies below that in the row. NA values indicate that cdfs cross, and first-order SD does not exist.}
\label{tab:KS_first_order_scenario}
\end{center}
\end{table}

\begin{table}[ht]
\begin{center}
\begin{tabular}{ |c|c|c|c|c|c| }
\hline
 & & Market & Neutral & Green\\
\hline
\multirow{3}{4em}{NPC} & Market & & 1/NA/$<0.001^*$ & 1/NA/$<0.001^*$\\
& Neutral & $0^*$/NA/1 & &  1/1/0.06\\
& Green & $0^*$/NA/1 & $0^*$/0.042/1 & \\
\hline
\multirow{3}{4em}{Emissions} & Market & & $<0.001^*$/$<0.001^*$/0.018 & $0^*$/$0^*$/$0^*$\\
& Neutral & 1/1/1 & &  $<0.001^*$/$<0.001^*$/0.018\\
& Green & 1/1/1 & 1/1/1 & \\
\hline
\end{tabular}
\caption{Observed $p$-values for NPC and $CO_2$-equivalent emissions using first-order stochastic ordering. The $p$-values correspond to design option 1, design option 2 and design option 3, where $p$-values with asterisk are less than or equal to significance level. NA values indicate that cdfs cross, and first-order SD does not exist and we cannot perform hypothesis tests.}
\label{tab:KS_first_order_pvals_scenario}
\end{center}
\end{table}

\FloatBarrier
\begin{figure}[ht]
\begin{center}
\includegraphics[width=0.95\textwidth,height=0.3\textheight]{Plot1ScenarioNPC}
\includegraphics[width=0.95\textwidth,height=0.3\textheight]{Plot1DesignNPC_unscaled}
\end{center}
\caption{Empirical cdfs for NPC for (i) all three design options plotted together for each individual scenario (\textit{first row}), (ii) all three scenarios plotted together for each individual design option (\textit{second row}).}
\label{fig:Plot1NPC}
\end{figure}
\FloatBarrier

\FloatBarrier
\begin{figure}[ht]
\begin{center}
\includegraphics[width=0.9\textwidth,height=0.25\textheight]{Plot1ScenarioEmissions}
\includegraphics[width=0.9\textwidth,height=0.25\textheight]{Plot1SDesignEmissions_unscaled}
\end{center}
\caption{Empirical cdfs for $CO_2$-equivalent emissions for (i) all three design options plotted together for each individual scenario (\textit{first row}), (ii) all three scenarios plotted together for each individual design option (\textit{second row}).}
\label{fig:Plot1Emissions}
\end{figure}
\FloatBarrier

\subsection{Generalised Simplex dispersion ordering}
\label{subsec:dispersion_order}
In Section \ref{subsec:order_mean}, we demonstrated how to assess the impacts of different design options by considering orderings in the mean. We now focus on dispersion, and note that a dispersive probability distribution indicates a high level of uncertainty (risk), which is assumed to be a negative attribute.  Here, we focus primarily on the effects of scenarios on each of the design options.

Figure \ref{fig:Plot4} displays empirical cdfs for the Generalised Simplex ordering.  Those of the three design options under each of the three different scenarios are shown in the top row, whilst those of the three scenarios under each of the three design options are shown in the second row. Table \ref{tab:KS_GS_design} shows the KS distances between the empirical cdfs associated with the pairs of design options under the Market, Neutral and Green scenarios, respectively, and the $p$-values in Table \ref{tab:pvals_GS_design} correspond to the KS tests of the dispersion ordering.

Under the Green and Neutral scenarios there is a clear ordering: design option 3 is lesser than design option 2 which is lesser than design option 1 in the Generalised Simplex dispersion order. Under the Market scenario, design option 3 is dominated by the other two design options, though the cdfs of design options 1 and 2 cross. Under the Generalised Simplex ordering, design option 3 therefore shown to be the most robust option under all three scenarios, whilst, in the Green and Neutral scenarios, design option 2 is more robust than design option 1. The KS distances between the design options in Table \ref{tab:KS_GS_design} are smallest under the Market Scenario and largest under the Green Scenario, suggesting that the difference in robustness is largest for the case in which government prioritise green issues. In all cases in which SD is demonstrated, the difference according to the KS test is significant.

For a planner, the above results are informative in that they demonstrate the relative robustness of different design options under each of the three scenarios, which is an important criterion for decision-makers.
\begin{table}[ht]
\begin{center}
\begin{tabular}{|c|c|c|c|c| }
\hline
& design 1 & design 2 & design 3\\
\hline
design 1 & & NA/-/- & -/-/-\\
design 2 & NA/0.33/0.49 & &  -/-/-\\
design 3 & 0.19/0.49/0.63 & 0.19/0.21/0.24 & \\
\hline
\end{tabular}
\caption{Kolmogorov-Smirnov distances between Generalised Simplex empirical cdfs for pairs of design options. The KS values correspond to the Market, Neutral and Green scenarios and are only shown when the cdf for design option in the column lies below that in the row. NA values indicate that cdfs cross, and first-order SD does not exist.}
\label{tab:KS_GS_design}
\end{center}
\end{table}

\begin{table}[ht]
\begin{center}
\begin{tabular}{|c|c|c|c|c|}
\hline
& design 1 & design 2 & design 3\\
\hline
design 1 & & NA/$0^*$/$0^*$ & $0^*$/$0^*$/$0^*$\\
design 2 & NA/0.98/1 & &  $0^*$/$0^*$/$0^*$\\
design 3 & 1/1/1 & 1/1/1 & \\
\hline
\end{tabular}
\caption{Observed $p$-values for different design options using the Generalised Simplex dispersion ordering. The $p$-values correspond to the Market, Neutral and Green scenarios, where those with an asterisk are less than or equal to the chosen significance level. NA values indicate that cdfs cross, and first-order SD does not exist and we cannot perform hypothesis tests.}
\label{tab:pvals_GS_design}
\end{center}
\end{table}

\FloatBarrier
\begin{figure}[ht]
\begin{center}
\includegraphics[width=1\textwidth,height=0.25\textheight]{Plot4Scenario}
\includegraphics[width=1\textwidth,height=0.25\textheight]{Plot4Design}
\end{center}
\caption{\textit{First row}: empirical cdfs of the Generalised Simplex metric for all three design options plotted together for each individual scenario. \textit{Second row}: empirical cdfs of the Generalised Simplex metric for all three scenarios plotted together for each individual design option.}
\label{fig:Plot4}
\end{figure}
\FloatBarrier

\section{Discussion} \label{sec:Discussion}
The importance of informing decision-makers and stakeholders about the uncertainty associated with design choices is increasingly recognised in energy systems \cite{Soroudi2013}. The present paper demonstrates the use of stochastic ordering (dominance) in the context of local energy planning under uncertainty. In particular, we have introduced variability at two levels: local variability in inputs and more general scenarios to account for changes in consumer behaviour and the political environment. Based on a generated data set, we have considered stochastic orderings both in shift and dispersion.

In our analysis of the waste heat recovery system in Brunswick, we have demonstrated that, under a Green scenario, which assumes active government policy to meet the 2050 net-zero carbon target, lower $CO_2$-equivalent emissions can be produced at a lower cost by employing a heat pump with heat from a data centre. In addition, we have found using the Generalised Simplex ordering that this design choice is more robust (less volatile) compared to the other options under all three scenarios.  We argue that, if it can be shown to be true in general, this robustness is an attractive feature of low-temperature waste heat recovery. We note that, in a number of cases, the cdfs cross and therefore first-order SD failed to discriminate between these respective choices. One possible next step is to consider higher-orders of stochastic dominance, which can be performed as an extension to the presented analysis.

We consider the proposed approach for analysing and comparing different options for providing residential heat in district heating as a competitive alternative to traditional uncertainty metrics used in energy systems.  Our non-parametric method offers orderings in uncertainty based on distribution functions, which are easy to visualise and communicate to decision-makers and other stakeholders. In addition, very limited information is required from decision-makers and experts to construct SD, contrary to the traditional mean-variance analysis where the specification of a utility function is necessary \cite{Canessa2016, Markowitz2000}. An extension to the proposed approach is to introduce new uncertainty metrics by specifying order-preserving functions of the presented orderings.

\section{Data availability}
Dataset and code related to this article can be found at \url{https://github.com/vicvolodina93/OrderHeating/tree/master}, hosted at Github.

\section{}
\label{}

\section{}
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\section{}
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redpajama_set_name: RedPajamaArXiv


text:
The weekend read: Floating on optimism
The past year has been an exciting period for proponents of floating solar. A range of new projects and pilots have been announced across the globe over the past 12 to 14 months, with IHS Markit's Solar Deal Tracker now listing floating PV installations in 24 countries throughout the world, all in varying stages of development.
March 24, 2018 Brian Publicover
A 1.2 MW floating PV project in Hyogo Prefecture, Japan. Japan has played a leading role in the development of solutions for floating PV, as it looks to maximize generation on limited space.
Image: Ciel et Terre
Floating PV was once dismissed as a quirky niche that would be largely relegated to land-scarce countries such as Japan, which has played a pioneering role in commercializing such technologies over the past few years. However, the segment now appears poised for a potential breakthrough, as East Asian markets such as China, South Korea and Taiwan increasingly demonstrate the feasibility of installing solar panels on water surfaces at scale. And new market drivers are emerging, as interest in floating systems starts to ripple beyond the region to other parts of Asia and beyond, setting the segment's early skeptics on their heels.
"Floating solar is a proven market sector now… because of success in Asia, there will be multiple gigawatts in the pipeline," argues Christine Beadle, Senior Analyst, Solar Supply Chain at IHS Markit. "It is global, but you've got the confidence now in Asia."
A number of countries have announced plans to potentially deploy massive amounts of floating solar capacity over the past year. In late 2017, for example, the Solar Energy Corporation of India (SECI) announced plans for a 10 GW floating solar tender. In December, Kerala State Electricity Board Limited completed a 500 kW floating PV system, and Indian companies such as the JSW Group and West Bengal Power Development Corporation Limited have announced new pilots, projects and pipelines in the months since. Although the question of how much capacity SECI eventually auctions off will hinge heavily on the success of these initial experiments, India nonetheless could be key to further stoking global interest in floating PV technologies in the next decade.
"If the pilots don't go well, it's not going to go in," says Beadle. "But in the next three or four years, you could see other countries come to the forefront just because you have this potential out there."
Fake floats
IHS Markit statistics suggest that global cumulative floating solar installations will reach about 400 MW by the end of the first quarter of this year. Beadle acknowledges that this "doesn't seem like much," particularly in light of some of the large projects that have been built over the past year, particularly in China. Last May, for example, Sungrow connected 40 MW of floating PV capacity to the grid in China's Anhui province. And within the next two months, China Three Gorges will connect the second part of a 150 MW array at an adjacent site. But there is a reason why the global cumulative total still has yet to surpass just half a gigawatt.
"You have to take out all this stuff that's over canals in the air in India — that's not floating… and you have to take out all the stuff on piles over fish ponds in China," Beadle explains. "That's why the numbers are so small. But the potential is huge."
Japan — where the floating sector truly started to gain momentum with the installation of multiple small projects from the midpoint of the decade — remains among the world's most active markets. And competition is heating up, with players such as Mitsubishi Electric and China's Sungrow now chipping away at the initial dominance of pioneering companies such as Kyocera TCL Solar.
"(It's) due to land constraints," says Naoaki Eguchi, partner at Baker & McKenzie in Tokyo, noting that many ponds and reservoirs are ripe for development throughout the country. The multinational law firm advised on some of Kyocera TCL Solar's earliest floating PV projects in Japan back in 2015. But Eguchi also sees new potential market drivers emerging. "Utilities are thinking about using water power dams as new floating solar spaces," he observes.
Kyocera TCL — a venture between PV module manufacturer Kyocera and Japanese leasing and financial services provider Tokyo Century Corporation — still sees "great potential" in Japan, according to a Kyocera spokesperson. At the time of publication, the developer was set to complete a 13.7 MW floating solar array on a dam reservoir in Chiba prefecture. It also plans to build 20 new floating PV projects in the country over the next three years, but it has not revealed specific capacity figures.
"The floating solar market will continue to grow in countries and regions which have abundant unused water surfaces like Japan," the Kyocera spokesperson says.
South Korea is one such country. Like Japan, the deployment of floating PV on the peninsula has largely been driven by land constraints. But the desire to put panels in the water is clear, with Korea Water Resources Corporation (K-water) — a state water-management agency — backing a number of floating PV projects in recent years.
The country is also at the forefront of introducing new technological innovations to the floating PV market. Local developer Solkiss, for example, announced plans last summer to work on a massive 80 MW floating PV project with Hanwha Q Cells. The installation will feature engine-powered rotating floating platforms to track the sun.
China has already auctioned off more than 1 GW of floating PV capacity for development under its Top Runner program. Photo: Ciel et Terre
"It's like a single-axis tracker on land, except they're moving the whole thing," Beadle enthuses. "Single-axis tracking has taken over ground mount — maybe this is something that other people will take up."
China, meanwhile, continues to lead the global floating PV sector in the development of large-scale arrays. The government has already auctioned off more than 1 GW of floating PV capacity for development under its Top Runner program. But the key catalysts for deployment differ slightly from land-scarce South Korea and Japan. The country has lots of space for ground-mount PV, but many of the best sites are situated far from the grid or points of consumption. But it holds tremendous potential to repurpose locations that have been damaged by industrial development, such as otherwise unusable coal subsidence sites.
"It's just the rehabilitation of dead space — nobody is using that land," explains Harold Meurisse, branch manager for Ciel & Terre ASEAN & Oceania.
The French floating platform supplier has expanded rapidly in recent years, with operations on every continent. However, the company — which played an instrumental role in building many of Japan's earliest forays into floating PV — has been particularly active in East Asia. Since launching operations in Taiwan a little over a year ago, it has secured a pipeline of roughly 120 MW, for example.
Fresh foundations
Now the company is making a big push into the Southeast Asian market. It is currently considering a potential pipeline of more than 300 MW throughout Thailand, Malaysia, Singapore, Vietnam and Indonesia. It has also helped to establish a new standard for projects in the region, which involves providing a main platform for the PV module and a secondary floater for O&M purposes. It hopes that this approach — which has been embraced at a 1 MW floating PV test bed launched last year by the Solar Energy Research Institute of Singapore (SERIS) — will lay the foundations for a thriving floating PV market throughout the region.
"One of the threats for us in the market is the local competition," Meurisse acknowledges. Ciel et Terre has therefore started discussing industry best practices with SERIS, in part to ensure that new market entrants do not make the kind of mistakes that could scare away potential investors in the regional market's earliest stages of development.
Since early 2017, SERIS has evaluated a range of module, floater and inverter configurations at its test bed in Singapore, which it runs in cooperation with the Economic Development Board and Public Utilities Board. The facility — which features 10 pilot projects of varying size by companies such as Sunseap, REC, Sharp and Upsolar — has already yielded data suggesting that floating PV projects generate more electricity per year because of the cooling effect of the water.
"The heat loss coefficients for those systems are generally in the range of 40 to 50 W/m² K, which is about 30-60% higher than the typical values of 30 W/m² K for a well-ventilated rooftop system," SERIS says in its 2017 annual report.
It believes that evaporation from reservoir surfaces can drive up the annual energy yield of floating PV systems by as much as 10% to 25% over ground-mounted systems. However, it also notes that the evaporative cooling effect varies significantly depending on the type of floating platform, with the greatest results seen in systems that provide the most space between the modules and the surface of the water.
SERIS says early results from the test bed also suggest that bifacial modules tend to produce more electricity on rooftops than in floating arrays. In addition, the organization — which sees terawatt-scale potential for floating PV throughout the world —is studying the effects of humidity, salt spray and fluctuating weather patterns on the output of floating solar systems. It is also looking at the translational and rotational movement of floating structures along three perpendicular axes each, as well as the potential environmental impacts of installed systems.
Asian ambition
Such research will undoubtedly help Ciel et Terre to more effectively tailor its proprietary Hydrelio floating platforms to the unique site conditions it sees throughout Southeast Asia. It plans to start producing its new Equatorial variant — which is made to lower anchoring costs by way of a more aerodynamic design that reduces wind loads — on a new, scalable production line that will launch in Thailand in May.
"We're starting with Thailand, but the pipeline of projects we are studying is quite high," says Meurisse.
Ciel et Terre also sees high potential in Malaysia, where 563 MW of solar capacity was awarded to developers in December. But it is particularly keen on Thailand, where it is mostly targeting PV projects for self-consumption purposes, because it can sidestep many of the regulatory issues that are associated with rooftop solar development in the country.
Offshore PV in the Maldives installed by Austrian developer Swimsol. Despite these, and a recent announcement by the Netherlands planning floating PV installations on the North Sea, industry players remain skeptical about the potential for solar on the open ocean. Photo: Swimsol
The company is also interested in opening a production line in Vietnam, a country that Meurisse says has big potential despite "some bankability issues with the PPAs." Ultimately, Ciel et Terre's decision to do so hinges on whether it ends up working on 50 MW of capacity at an undisclosed hydroelectric dam with a subsidiary of major utility Electricity of Vietnam (EVN). It expects the Vietnamese authorities to make a decision on whether to award the project to the EVN unit by mid-May, from which point it will start producing its standard Hydrelio floats in the country, but not the equatorial variant or another new lightweight option it has recently designed.
The potential to install floating PV arrays at hydroelectric dams is also why Ciel et Terre is tentatively exploring opportunities in Myanmar. Meurisse acknowledges that the company's activities in the country are still very much at the feasibility stage, primarily due to difficulties in securing financing and the government's ongoing reluctance thus far to commit to formal PPAs. However, he says that the potential to use floating solar to offset falling hydroelectric output during the dry season is huge. But the company is convinced that Myanmar, along with Cambodia and Laos, will "rise" at some point in the years to come. "It's very strategic for our company to be set up (in Myanmar)," he says.
Indonesia, meanwhile, is also an important target in Ciel et Terre's Southeast Asian expansion plans, for self-consumption and grid-connected projects. The company is already on board to work with Abu Dhabi-based clean energy giant Masdar, which recently signed a project development agreement with a unit of Indonesian utility PT PLN to build 200 MW of floating PV capacity on the island of Java.
Meurisse acknowledges that Indonesia's policy environment is still far from mature. But energy demand is high throughout the archipelago, and floating PV could be an ideal solution in a country in which ground-mount solar investors often struggle to identify the owners of potential development sites. "(Indonesia) has a very singular position in our strategy," he says. "More and more, solar projects are happening (there)."
Asked about recent efforts in the Netherlands to install solar panels at sites in the North Sea — as well as a handful offshore PV projects in the Maldives by Austrian floating systems specialist Swimsol — IHS, Kyocera and Ciel et Terre were unanimous in expressing measured skepticism over the potential to install solar projects on the open ocean.
"For now, I would not consider the open sea as a viable option," Meurisse says, pointing to a range of freshwater sites that are open for development such as hydroelectric dams, reservoirs, wastewater treatment ponds and even rice paddies. "The potential in Asia is crazy."
Brian Publicover
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redpajama_set_name: RedPajamaCommonCrawl


text:
Air Force Taps Lockheed Martin To Develop Air-Launched Hypersonic Weapon
By Marc Selinger |
@marcselinger
The U.S. Air Force has picked Lockheed Martin [LMT] to develop and test the air-launched Hypersonic Conventional Strike Weapon (HCSW) prototype, the service announced late April 18.
Lockheed Martin was one of three bidders for the multi-year contract, which has a value of up to $928 million.
The Air Force said it plans to award the first task order under the indefinite-delivery/indefinite-quantity contract "in the next few weeks." Lockheed Martin intends to perform the work in Huntsville, Ala.
"We are committed to the development of state-of-the-art hypersonic technologies, and we are excited to get to work on the Hypersonic Conventional Strike Weapon program," said John Snyder, Lockheed Martin's vice president of Air Force Strategic Programs.
In July, the Air Force said it envisions that both fighters and bombers could carry such a weapon to provide a prompt, precision-strike capability against high-value, time-critical, fixed and relocatable surface targets in contested environments.
Hypersonics technology has received renewed attention recently from top Pentagon officials, who fear the United States is falling behind potential adversaries, such as China. Michael Griffin, the new undersecretary of defense for research and engineering, has called hypersonics his top technical priority (Defense Daily, March 6).
Air Force To Unveil Hypersonics Acceleration Plan Soon
U.S.-Australian Hypersonics Program Nears Next Flight Test
AFMC Commander: Hypersonic Development Efforts Not Waylaid by COVID-19


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We hope you'll agree that we're the best horoscope directory on the planet, human edited! They have an affinity with Sagittarius, and Thursday is their lucky day of find out horoscope sign date birth the week.
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If you have a copy of your birth chart and know your rising sign, Moon sign, and the signs of the planets, reading about those signs will give you information that you will be able to use find out horoscope sign date birth right away. Sylvia Sky discovered and shares 12 genuine online astrologers who write true original horoscopes instead of using computerized or syndicated content. As a fellow find out horoscope sign date birth aquarian, i can tell you that libra is not best horoscope astrology first choice for a best horoscope astrology partner, either. The world is changing and traditional astrology does not provide all the answers.
Separative Tendencies-The find out horoscope sign date birth horoscope is analyzed to figure out any kind of separative elements are present in the horoscope and also for any sign of divorce. Take this free name compatibility test to know how good or bad your love relationship is predicted to fare! With a birthday on the 5th of the month you are inclined to work well with people and enjoy them.
There are a lot of original articles including celebrity astrology, sports, health, finance, a directory and free daily horoscopes by email.
Libra personal horoscope: You can balance your personal life and professional life well.
Later, sylar is recruited by arthur how to find horoscope with date of birth in telugu petrelli, who teams him february 13 birthday horoscope with an unlikely partner, elle bishop.
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14.05.2015 at 20:22:43 Encompassed all the extremes of the numbers in between, as well as their the.
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14.05.2015 at 23:51:20 The strength of its position in the with their meaning which acts ness stars hence.


text:
Q: Connect to Microsoft Access Database(.mdb) using AWS Lambda Function .Net I tried using following code to make connection but AWS Lambda Function threw an error.
using System.Data.OleDb;

OleDbConnection con = new OleDbConnection("Provider=Microsoft.Jet.OLEDB.4.0;Data Source=...");

con.Open();

Error:
System.Data.OleDb is not supported on this platform.: PlatformNotSupportedException
   at System.Data.OleDb.OleDbConnection..ctor(String connectionString)
   at AWSLambda1.Function.FunctionHandler(String input, ILambdaContext context) in C:\Users\TestUser\source\repos\AWSLambda1\AWSLambda1\Function.cs:line 35
   at lambda_method(Closure , Stream , Stream , LambdaContextInternal )

Can anyone please help? If OleDb is not supported in Lambda Function then can you please show me a way to connect to Microsoft Access Database?
Thanks in advance.

A: Is this running as x64 bit? There is no JET support for x64 bit running process.
If AWS has support for JET, then you will have to force your project to x86 (x32 bits). That means you can't use ANY CPU, nor can you use x64 for the .net project. You have to force the project as x32. However, the rest of your software running on that system, including the web server is likely running as x64 bits.
If your web server is x64, then you have to use a x64 bit version of the JET data engine. There is not x64 for JET, but there is a x64 bit version called ACE, and it can read mdb files. So right now the issue is does the container you using on AWS support JET, and if it does, then you have to ensure you force compile your .net project to x32 bits.

redpajama_set_name: RedPajamaStackExchange


Patients infected with Clostridium Difficile bacteria are extremely ill. This study documents that use of human healthy stool (FMT) is much more efficient in fighting this infection than 2 types of antibiotics, usually offered in treatment.
Parkinson´s patients have a different gut flora compared to people without this diagnose. Parkinson´s medicine has different impact on different patients, probably dependent on gut flora. For some patients, the medicine worsen the symptoms.
Not all beneficial bacteria are re-established 6 months after an almost eradication of gut flora after a 4 day antibiotic treatment. While 9 types of species lacked, some dysbiotic bacteria has made their entrance.
Why we don´t need more research. We know a lot about brain food already.
A meta study, that looks at the connection between autism spectrum disorders and gut flora.
Chris Kresser explains, why the fluent substance broth provides good health.


The Parrish Art Museum has announced the launch of Blue Star Museums, a collaboration among the National Endowment for the Arts, Blue Star Families, the Department of Defense, and more than 1,500 museums across America to offer free admission to all active duty military personnel and their families from Memorial Day through Labor Day 2012.
With Memorial Day right around the corner, this is one of the many reminders of how important the U.S. Military is to the security and the future success of the country, as well as the enormous sacrifices that it has made in the past.
A lot of our ability to operate as a free nation, even with so many different people, thoughts and opinions, has largely to do with the unity that we have around keeping America strong. Giving these guys a free ticket into a museum is the least we can do.
Don't forget what Memorial Day is really about while your enjoying your summer vacation on the East End!


text:
Hundreds wear red for funeral of boy, 10, who was killed by dog
Sabrina JohnsonThursday 25 Nov 2021 8:24 pm
Hundreds of people lined the streets of Caerphilly in Wales to say goodbye to Jack Lis on Thursday (Picture: PA)
Hundreds of people lined the streets of Caerphilly in Wales today to say goodbye to Jack Lis, who was killed by a dog.
The 10-year-old died after being attacked as he played at a friend's house on November 8.
Crowds wore red and clapped as the youngster's funeral procession made its way through Caerphilly.
The procession, led by Jack's favourite cars including a Back to the Future-style DeLorean stopped outside his school, where classmates paid tribute.
It then continued on to St Martin's Church, where songs Start Over by Flame, See You Again by Wiz Kalifa, and Family Tree by Ramz were played at the service.
The Reverend Mark Greenway Robbins told the congregation: 'None of us expected to be here and no one wanted to be here, but let us take a moment to think of how we remember Jack.
'Hold onto that particular memory of him that you treasure him for and thank him for. And let's honour him for a moment in the quiet together.
'As we remember times of tears and laughter we thank God because of the love we shared for Jack.'
Crowds wore red and clapped as the youngster's funeral procession made its way through Caerphilly (Credits: PA)
The order of service showed photos of Jack playing in a park, in his school uniform and on a scooter, as well as pictures of a selection of cars.
Following his death, a fundraiser to help heartbroken mum Emma Whitfield, 32, pay for his funeral topped more than £16,400.
Jack's family asked any further donations go to the 2 Wish Upon A Star charity which helps bereaved families who have lost children.
An inquest into Jack's death, held earlier this month, heard the youngster had been 'playing with a friend' in Penyrheol when he was attacked by the dog.
The inquest heard paramedics were called but Jack's injuries were 'unsurvivable' and he was pronounced dead at the scene.
The order of service for the funeral of Jack Lis at St Martin's Church, Caerphilly (Picture: PA)
After the hearing, Jack's family paid tribute to the youngster.
In a statement, they said: 'We are absolutely heartbroken. Our lives will never be the same without Jack.
'This is not something any parent should ever have to be writing.
'We have so many words we want to say about our beautiful boy, but they do not seem enough.
'We love him more than words can describe. Our boy made us the proudest parents and family on the planet. He was the sweetest of boys.
'We will forever miss his quirky ways and his stories that he would spend so long telling us.
'He's forever in our hearts. Sweet dreams Jack, our perfect boy.'
The funeral procession was led by Jack's favourite cars including a Back to the Future-style DeLorean (Picture: PA)
Matthew Young, Emma's cousin, set up the fundraising campaign with a target of £5,000 – before doubling it following a string of donations.
He said: 'Many people have expressed their deepest condolences and have asked to contribute in some way towards the funeral costs to help the family at this very difficult and emotional time.
'So it is with extreme heartache that I write this to give those wishing to donate, a place to do so."
He added: 'Jack was a loving caring young boy who will be greatly missed, never forgotten, and always in our hearts. Fly high sweet, sweet boy'.
Get in touch with our news team by emailing us at webnews@metro.co.uk.
For more stories like this, check our news page.
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ALTAMONTE SPRINGS, Fla. - For many families of children with special needs, it can be challenging for everyone involved when it comes to having the child be involved in a sport.
But 10 years ago, a unique baseball league was created by a mother and son in Central Florida so that every child, regardless of their abilities, could enjoy a life-changing experience through baseball.
"I'm sitting there looking at my wife, looking at my mother, looking at my wife, at my mother, and tears are coming out of my eyes," Matt Morgan said about his newfound hope.
Morgan, a former professional World Wrestling Entertainment wrestler and now deputy mayor of Longwood, has a 5-year-old son with autism who doesn't speak.
During a charity event, he found out about the Central Florida Buddy Ball Baseball League.
"It's a godsend to have this in Central Florida. He can go out and play it, and he can part take in it, learn the love of the game of baseball like every other child gets to learn," Morgan said.
Two seasons in, Morgan is already seeing the impact the league has had on his son's social skills.
"He used to be by himself and isolated -- not since Buddy Ball. Buddy Ball has introduced him to the fact that he can take something and give it to one of his friends and engage with that friend. That's huge," Morgan said.
Sarah Reece, the president of the Central Florida Buddy Ball Baseball League, said the program benefits everyone involved.
"We wanted a program to not only help our special-needs population, but the buddies that come to also be a part of that program. They get as much from the program as anybody does, and our buddies come from all over," Reece said.
High school students and community members all pitch in and get results for the kids, regardless of their abilities. Every season, you'll find them at Eastmonte Park in Altamonte Springs.
"They come and they love working with these kids," Reece said.
Morgan said the most amazing part of it all is that you get a chance to see them work through things together, no matter what their selective differences are.
Seth Reece, Sarah Reece's son and the vice president of the league, got choked up and could barely hold back tears as he tried to explain what it all meant to him.
"It means a lot ... um ... give me a second here," Seth Reece said.
Ten years ago, the father of three took his team of young players to volunteer at a baseball game for differently abled children in Orlando.
"It was something that was beyond just the players on the field and how amazing it was to see them out there doing a baseball game, and to see these kids react to them and put themselves in this situation and help them out (to) get through the baseball game," Seth Reece said.
It was a home run experience that inspired him to start a league in Seminole County -- to be able to get results all the time. Then, he got his mom on board.
"We started raising money because we had to build a special field for the kids," Sarah Reece said.
They managed to raise nearly $72,000 through events with help from the city.
The same field Seth Reece once played on as a young boy was covered with rubberized material. The dugouts were also made big enough for wheelchairs.
"It's a special field so that you can push wheelchairs on it and walkers, and kids that have a gait problem can run without hurting if they fall," Sarah Reece said.
"It's getting huge results for the community. People drive from all over for this league, too. Let's be clear: It is not just Seminole County. We have somebody -- I know that for a fact -- that comes from Miami, Florida, to have their kid play in this league," Morgan said.
Sarah Reece said it brings her joy to know others find joy in the league.
"To see their faces and how they cheer and enjoy the game, watching their child play a game of baseball, is beyond words," she said.
Seth Reece said he makes sure the kids know not to take the opportunity for granted.
"I tell my kids and my baseball kids all the time, you're lucky to tie your shoes and put your cleats on and run on the field. There's so many other kids that would love to do that, and this is that opportunity for them," he said.
Morgan said his community is lucky to have the league.
"We're incredibly lucky to have it in the community, and I would argue we're lucky to have it, period, in the state of Florida," Morgan said.
The Central Florida Buddy Ball League operates through donations and with the help of volunteers.
The program is offered at no cost to families. Registration includes gear and uniforms. To contact the league, email Sarah Reece at Sarah.Reece@orlandohealth.com.


text:
Q: Grafana regex for transformation I'd like to use grafana to filter values by name:
This is an example of my keys and values:
disk_usage.root.dev.used 0 1608582030
disk_usage.root.dev.avail 7816 1608582030
disk_usage.root.dev.used_percentage 0 1608582030
disk_usage.root.run.used 147 1608582030
disk_usage.root.run.avail 1420 1608582030
disk_usage.root.run.used_percentage 10 1608582030
disk_usage.root.used 6930 1608582030
disk_usage.root.avail 214260 1608582030
disk_usage.root.used_percentage 4 1608582030
disk_usage.root.boot.efi.used 1 1608582030
disk_usage.root.boot.efi.avail 120 1608582030
disk_usage.root.boot.efi.used_percentage 1 1608582030

Now would like to show only those, whose name contains "_percentage".
I tried to use this:
/(_percentage)/

but this does not work.
However, if I do the negative lookup like
^((?!percentage).)*$

it shows all values - but not the ones, having "percentage" in it.
My question: How can I only show those values having "percentage" in it?

A: Use the following filter:
/.+_percentage/


text:
Cockroach allergen (Bla g 1) in school dust
Sampson B. Sarpong, Robert A Wood, Theodore Karrison, Peyton A. Eggleston
Background: Cockroach allergen, Bla g 1, is an important indoor allergen. Although household exposure has been documented, little is known about the potential for exposure outside the home. Objective: We investigated the settled dust concentration of Bla g 1 in 147 samples collected from classrooms, kitchens, cafeterias, and other sites in four primary schools in the city of Baltimore. Methods: School authorities were questioned about characteristics of schools, teachers, and students, as well as cockroach control and cleaning procedures. Settled dust samples were collected with a hand-held vacuum cleaner from the floors of all classrooms, food-related areas, and other sites of the schools over a 3-week period. A sample collection in each school took 1 to 2 days. Dust samples from each room were pooled and analyzed as a single sample for Bla g 1 by using a two-site monoclonal ELISA. Results: One hundred two (69%) of the 147 samples had detectable Bla g 1 and were within the range reported by other investigators in inner city homes. There was no difference between the median levels of Bla g 1 in three schools: school 1 (5.2 U/gm), school 2 (3.0 U/gm), and school 4 (2.7 U/gm); but school 3 had a significantly lower level (
The Journal of Allergy and Clinical Immunology
allergen Bla g 1
cockroach allergen
Dust analysis
Sarpong, S. B., Wood, R. A., Karrison, T., & Eggleston, P. A. (1997). Cockroach allergen (Bla g 1) in school dust. The Journal of Allergy and Clinical Immunology, 99(4), 486-492. https://doi.org/10.1016/S0091-6749(97)70074-5
Cockroach allergen (Bla g 1) in school dust. / Sarpong, Sampson B.; Wood, Robert A; Karrison, Theodore; Eggleston, Peyton A.
In: The Journal of Allergy and Clinical Immunology, Vol. 99, No. 4, 1997, p. 486-492.
Sarpong, SB, Wood, RA, Karrison, T & Eggleston, PA 1997, 'Cockroach allergen (Bla g 1) in school dust', The Journal of Allergy and Clinical Immunology, vol. 99, no. 4, pp. 486-492. https://doi.org/10.1016/S0091-6749(97)70074-5
Sarpong SB, Wood RA, Karrison T, Eggleston PA. Cockroach allergen (Bla g 1) in school dust. The Journal of Allergy and Clinical Immunology. 1997;99(4):486-492. https://doi.org/10.1016/S0091-6749(97)70074-5
Sarpong, Sampson B. ; Wood, Robert A ; Karrison, Theodore ; Eggleston, Peyton A. / Cockroach allergen (Bla g 1) in school dust. In: The Journal of Allergy and Clinical Immunology. 1997 ; Vol. 99, No. 4. pp. 486-492.
@article{6fdd37cf1246481abe8a3fb4dd7f83e7,
title = "Cockroach allergen (Bla g 1) in school dust",
abstract = "Background: Cockroach allergen, Bla g 1, is an important indoor allergen. Although household exposure has been documented, little is known about the potential for exposure outside the home. Objective: We investigated the settled dust concentration of Bla g 1 in 147 samples collected from classrooms, kitchens, cafeterias, and other sites in four primary schools in the city of Baltimore. Methods: School authorities were questioned about characteristics of schools, teachers, and students, as well as cockroach control and cleaning procedures. Settled dust samples were collected with a hand-held vacuum cleaner from the floors of all classrooms, food-related areas, and other sites of the schools over a 3-week period. A sample collection in each school took 1 to 2 days. Dust samples from each room were pooled and analyzed as a single sample for Bla g 1 by using a two-site monoclonal ELISA. Results: One hundred two (69{\%}) of the 147 samples had detectable Bla g 1 and were within the range reported by other investigators in inner city homes. There was no difference between the median levels of Bla g 1 in three schools: school 1 (5.2 U/gm), school 2 (3.0 U/gm), and school 4 (2.7 U/gm); but school 3 had a significantly lower level (",
keywords = "African-American, cockroach allergen, Dust analysis, schools, urban",
author = "Sarpong, {Sampson B.} and Wood, {Robert A} and Theodore Karrison and Eggleston, {Peyton A.}",
journal = "Journal of Allergy and Clinical Immunology",
T1 - Cockroach allergen (Bla g 1) in school dust
AU - Sarpong, Sampson B.
AU - Wood, Robert A
AU - Karrison, Theodore
AU - Eggleston, Peyton A.
N2 - Background: Cockroach allergen, Bla g 1, is an important indoor allergen. Although household exposure has been documented, little is known about the potential for exposure outside the home. Objective: We investigated the settled dust concentration of Bla g 1 in 147 samples collected from classrooms, kitchens, cafeterias, and other sites in four primary schools in the city of Baltimore. Methods: School authorities were questioned about characteristics of schools, teachers, and students, as well as cockroach control and cleaning procedures. Settled dust samples were collected with a hand-held vacuum cleaner from the floors of all classrooms, food-related areas, and other sites of the schools over a 3-week period. A sample collection in each school took 1 to 2 days. Dust samples from each room were pooled and analyzed as a single sample for Bla g 1 by using a two-site monoclonal ELISA. Results: One hundred two (69%) of the 147 samples had detectable Bla g 1 and were within the range reported by other investigators in inner city homes. There was no difference between the median levels of Bla g 1 in three schools: school 1 (5.2 U/gm), school 2 (3.0 U/gm), and school 4 (2.7 U/gm); but school 3 had a significantly lower level (
AB - Background: Cockroach allergen, Bla g 1, is an important indoor allergen. Although household exposure has been documented, little is known about the potential for exposure outside the home. Objective: We investigated the settled dust concentration of Bla g 1 in 147 samples collected from classrooms, kitchens, cafeterias, and other sites in four primary schools in the city of Baltimore. Methods: School authorities were questioned about characteristics of schools, teachers, and students, as well as cockroach control and cleaning procedures. Settled dust samples were collected with a hand-held vacuum cleaner from the floors of all classrooms, food-related areas, and other sites of the schools over a 3-week period. A sample collection in each school took 1 to 2 days. Dust samples from each room were pooled and analyzed as a single sample for Bla g 1 by using a two-site monoclonal ELISA. Results: One hundred two (69%) of the 147 samples had detectable Bla g 1 and were within the range reported by other investigators in inner city homes. There was no difference between the median levels of Bla g 1 in three schools: school 1 (5.2 U/gm), school 2 (3.0 U/gm), and school 4 (2.7 U/gm); but school 3 had a significantly lower level (
KW - African-American
KW - cockroach allergen
KW - Dust analysis
KW - schools
KW - urban
JO - Journal of Allergy and Clinical Immunology
JF - Journal of Allergy and Clinical Immunology


text:
Q: How to to convert GPS coordinates from UTM SAD69 to decimal SIRGAS2000? How would be the algorithm to convert the following GPS coordinates (Java language prefered)?
From UTM/SAD69:
Latitude: 7171359,145
Longitude: 716431,81
Zone: 22
Hemisphere: South

To Decimal (Google Maps friendly):
Longitude: -48.8461461196
Latitude: -25.559740724

http://maps.google.com.br/maps?q=-25.559740724,-48.8461461196&hl=pt-BR&t=h&z=16

A: You could utilize UTMConverter.java  for that purpose, the following example:
double  easting = 716431.81;
double  northing = 7171359.145;
int zone = 22;
boolean isSouthHemishere = true;

LatLng value = UTMConverter.convertToLatLng(easting,northing,zone,isSouthHemishere);
System.out.println(value);

gives the same result (lat: -25.55933783,lng:-48.84565751) as Geographic/UTM Coordinate Converter online tool

A: Use PROJ.4 to convert from EPSG:29192 (SAD69 / UTM zone 22S) to EPSG:4326 (WGS 84).
For example here is a simple interface to transform, but there are others for command line, JavaScript, etc.


text:
'It's like the boyfriend who never commits': Why serial projects are on the rise at agencies
January 3, 2020 by Kristina Monllos
In the name of efficiency, companies have reduced agency-of-record assignments in favor of project-based work in recent years. But the pendulum is swinging back somewhat. The result: An arrangement that lands somewhere in the middle, known as "serial project assignments."
This arrangement allows brands to hire agencies for repeated projects. Agencies have some idea of how long they may be working for a brand and how many projects they may be assigned without brands having to shell out for an AOR retainer fee. The arrangement can be informal, or formalized with a contract that plans out projects, but leaves billing and scope of the projects as yet to be determined. The trend has started to catch on with midsized brands over the past six to 12 months, according to the 4A's svp of agency management services Matt Kasindorf, adding that creative agencies are the most likely to see this arrangement.
The arrangement allows brands to have consistency by continually working with certain agencies without having to pay AOR retainer fees — essentially getting the best of both the AOR and project-based work assignments. Agencies, meanwhile, have some sense of stability in terms of expected work coming in but it's murkier when it comes to financial arrangements and staffing, as agencies and brands in the serial project arrangement often haven't scoped out the work as meticulously as they do with an AOR relationship and, as Digiday previously reported, not doing so early can become a problem later.
The arrangement is another example of the ever-changing nature of the agency-client relationship, according to agency executives and industry experts, who believe that it will become more popular this year as brands don't want to make long-term commitments with agencies.
"The ongoing trend is to do more with less and be faster, smarter and less expensive," said Lisa Colantuono, president of search consultancy AAR Partners, who sees serial projects as a side effect of in-house agencies needing help from outside firms. "They're not set up to be 100 percent self-sustaining as an agency. As more clients do more work in-house they will need more help from the outside."
Serial projects may be one aspect of the shift toward a more hybrid model between in-housing and AOR, which will likely be more popular in 2020, as Digiday previously reported. The arrangement, like anything, has its pros and cons for agencies and clients. Agencies say the arrangement makes it less likely for brands to get the best work as it's harder to keep top-tier talent on staff for short-term assignments.
"On the plus side, it's good for an agency because they know they've got a continuous stream of work," said Kasindorf. "But it's harder to make financial projections, staffing becomes a little more challenging and [in some cases] there's no guarantee in terms of on-going monthly work. It's a way for clients and agencies to establish a solid ongoing relationship but it's not perfect."
"It's like the boyfriend who never commits," said a creative director at an independent creative agency that has had serial project relationships. "We keep going on dates. You come back to my family's house for Thanksgiving, we're going on vacation but never locks it in and says, 'You're the one.'"
"Serial projects are more like dating versus marrying your clients," said Joanne McKinney, CEO of Burns Group. "The relationship is viewed more short term, but as the projects move along, the relationship grows. With a typical AOR relationship, you get married and then get to know each other. With the serial project model, additional projects are a direct result of the strength of your prior project work and the growing trust of the client. We've seen a good deal of serial projects turn into great and longer-term client relationships."
Others see it as par for the course in the changing agency-client relationship. "Ultimately, serial projects aren't inherently better or worse than retainer projects in general," said Ted Nelson, CEO of Mechanica. "Sometimes you miss the depth of understanding and relationships that result from a healthy retainer relationship. At the same time, complacency can creep into long-term retainers if you're not vigilant."
Overall, agency execs and industry experts believe that the rise of serial projects is part of a realization across the industry that one-size-fits-all models no longer apply to agency-client relationships. "You can't have a one-and-done model anymore," said Colantuono. "You have to talk about individual needs and different variables that can affect that outcome when developing that financial arrangement. It does take a little more time and effort."
But for some, it's not that simple as the changing model and new popularity of serial projects has made it more difficult to get clarity from brands about payment models or any sort of long-term planning. "It's getting harder," said an independent creative agency exec who has a serial project arrangement. "[Serial projects] chips away at the agency's ability to forecast. I don't know what I need on these projects because we haven't committed to the scope or brief of what these projects are. The projectization of the work strips the agency's ability to demand certain overhead, forecast and plan."
"When a client gives us a project, we're like, 'I guess that's great, we've won the next project,'" said the creative director. "But it's constantly hand to mouth and there's no guarantee, even if you knock it out of the park. We've had that many times where we've killed it on a project, assumed there would be a next project and there wasn't. The fact that you can never count on it, that there's this structural uncertainty to it, prevents you from being true partners, which really bums me out. I think everybody is losing as a result."
'Nobody has more touch points for creators': A Q&A with Scotty Tidwell, Enthusiast Gaming's new svp of talent
Tidwell comes to the role equipped with over a decade of experience in generating engagement around endemic gaming brands.
Part of a broader social- and search-driven campaign conceived by 72andSunny and Horizon Media's Blue Hour content unit, LikeMeat launched the first-ever scavenger hunt promotion and contest on TikTok.
'Difficult to feel connected': Why some employees are using sensory deprivation tanks, rage rooms and cow hugging therapy to destress
In the midst of on-going pandemic, it's no surprise then that people are seeking out unique ways – on their own or offered by their employer – to destress.
As both brands and consumers become more familiar with the metaverse concept — and more comfortable traversing virtual spaces — the competing FOMO and burnout surrounding the concept will likely reach some sort of equilibrium.
While privacy advocates are saying this doesn't go far enough, advertisers may think this won't be targeted enough.