You are provided with the abstract of a scientific paper and the abstracts of the papers it references. Your task is to write a Related Work section for the main paper. This section should concisely summarize and integrate the key points from the cited abstracts, reflecting how they relate to the main paper's contributions and context. In your summary, use numerical citation markers like [1], [2], etc., to refer to the corresponding papers.

Main Abstract:
Participation in energy demand response programs requires an active role by users of residential appliances: they contribute flexibility in appliance usage as the means to adjust energy consumption and improve Smart Grid reliability. Understanding the collective potential that appliance-level flexibility has on Smart Grid reliability is challenging and complex. Physical characteristics of appliances, usage preferences, habits, and lifestyle are socio-technical factors that influence system-wide reliability coming often at the expense of users' comfort, i.e. thermal. This paper studies appliance-level flexible scheduling and specifically the following research questions: (i) How flexible are users in scheduling their appliances to improve Smart Grid reliability? (ii) How do users' comfort requirements affect the contributions of flexibility and as a result the collective action of improving Smart Grid reliability? (iii) Which appliances have the highest regulatory impact on Smart Grid? (iv) Can flexibility further improve Smart Grid reliability compared to simply operating individual appliances more efficiently? And finally, (v) what is the impact of varying users' participation on the collective action of improving reliability? To address these questions, a distributed optimisation scheme is studied to coordinate the selection of multiple appliance-level schedules representing users' self-determined flexibility. Experimental evaluation using a novel dataset shows that higher user flexibility significantly improves Smart Grid reliability with the oven having the highest system-wide potential for this. Compared to an existing efficiency scheme for kettles, flexible coordinated scheduling shows further improvements in reliability. These new findings have implications for the design of more cost-effective and granular demand response programs in participatory and decentralised Smart Grids.

Cited Abstract(s):
[1]: Since societies depend on energy and its management, extensive changes in energy-related technologies, such as the Smart Grid (SG), are likely to bring out subsequently enormous forms of social change. Imagine, there are several claims about the risks that lie ahead as conventional energy resources terminated, as populations increase, and as assumption accelerate. Therefore, the future societies will be subject to creative development and wide-ranging transformation to optimize their energy consumption. The SG can integrate an assorted set of electricity resources, containing large power plants as well as distributed renewable energy resources, electric energy storage, demand response, and electric vehicles. In line with many visions for the SG, consumers will play a more ‘active’ role in the future energy systems. Therefore, it is necessary to ensure customers’ acceptance to successfully build a SG. The eventual deployment of the SG depends on the consumers’ acceptance of SG products and services. Yet fully engaging the residential space in the SG remains a challenge. This work aims to provide energy systems researchers and decision makers with proper insight into the underlying drivers of consumer acceptance of the SG and the logical steps for their engagement to promote the SG technology and making it feasible in a timely manner.

[2]: Despite the importance of demand response (DR), there has been little exploration of its potential impact on the individual or society. To address this gap, semi-structured interviews were conducted with 21 households in the south of England, in which two DR vignettes were presented: peak pricing and remote demand control during critical peaks. Peak pricing was seen as inequitable, burdening the less affluent, the less healthy, families and working mothers. Adverse societ al outcomes may result from peak pricing, with potential for disruption of time-dependent household routines including the socially vital ritual of family mealtimes. Householders perceived their peak-time consumption to be determined by society's temporal patterns and not within their control to change. Third-party control in demand-side management was perceived to contravene householders' rights of control inside their homes. Alternative approaches to shifting peak demand, which combine technological, economic and socio-psychological ins...

[3]: Demand response is receiving increasing interest as a new form of flexibility within low-carbon power systems. Energy models are an important tool to assess the potential capability of demand side contributions. This paper critically reviews the assumptions in current models and introduces a new conceptual framework to better facilitate such an assessment. We propose three dimensions along which change could occur, namely technology, activities and service expectations. Using this framework, the socio-technical assumptions underpinning ‘bottom-up’ activity-based energy demand models are identified and a number of shortcomings are discussed. First, links between appliance usage and activities are not evidence-based. We propose new data collection approaches to address this gap. Second, aside from thermal comfort, service expectations, which can be an important source of flexibility, are under-represented and their inclusion into demand models would improve their predicative power in this area. Finally, flexibility can be present over a range of time scales, from immediate responses, to longer term trends. Longitudinal time use data from participants in demand response schemes may be able to illuminate these. The recommendations of this paper seek to enhance the current state-of-the-art in activity-based models and to provide useful tools for the assessment of demand response.

[4]: Reducing greenhouse gas emissions from energy consumption in the UK is increasingly linked to the introduction of uncontrollable sources of power, such as solar PV and wind, and the electrification of energy services (Darby, 2012; Department of Energy and Climate Change, 2013, 2011). Electrifying heating and personal mobility requires moving them off the gas grid and petrol pump and onto the electricity system, which in turn may have implications for the profound peak in electricity use that takes place in the early evening. While the conventional response would be to reinforce electricity networks, under conditions where there are an increasing range and diversity of sources of electricity generation that are less predictable and controllable, there is increased political and commercial interest in managing demand in these periods. Demand Side Management (DSM) enabled by smart grids promises to bring consumers of electricity into the management of the grid by asking them to provide the flexibility and responsiveness that the industry may lose in the future. In this paper we draw on 186 qualitative home tours in the UK to examine how such forms of flexibility are constituted. Rather than seeing flexibility as related to the characteristics of individuals and their behaviour, as is common in the industry and policy, we argue that it is the social practices which shape electricity demand curves that need to be at the centre of analysis. To illustrate this argument, we consider how, in what ways and for what purposes consumption of electricity may be or become flexible in response to a time of use tariff designed to reduce consumption in the early evening. We argue that the rhythmic qualities of practices and the degree to which there are socially conventional times and ways to perform particular practices can constrain or open up their ability to adapt to interventions.

[5]: Abstract The time dependence of social practices at specific points of the day shapes the timing of energy demand. This paper aims to assess how dependent energy-related social practices in the household are in relation to the time of the day. It analyses the 2005 UK Office for National Statistics National Time Use Survey making use of statistically-derived time dependence metrics for six social practice: preparing food, washing, cleaning, washing clothes, watching TV and using a computer. The focus is on social practices over temporal scales of different days of the week and months of the year. The main findings show that: washing has the highest value for the time dependence metric; using computers is the least time-dependent practice; Tuesdays, Wednesdays and Thursdays have the highest time dependence for all practices; and certain energy-related practices have higher seasonal dependence than others.

[6]: Electricity demand response refers to consumer actions that change the utility load profile in a way that reduces costs or improves grid security. The focus of demand response has mainly been on the commercial and big industrial sectors because of the large demand reduction that they can offer to the utility grid operators. Utilities are showing increasing interest in residential demand response (RDR). RDR can be treated as an energy resource which can be assessed and commercially developed, however, there are still some issues that remain to be addressed for RDR to be successful. These include price unresponsiveness of some residential consumers, equity issues and high cost of the metering infrastructure. The aim of this paper is to investigate and present some of the challenges in achieving effective voluntary demand reduction based on a review of residential demand response literature as well as the general residential energy use behaviour literature. The authors propose the use of a hybrid engineering approach using social psychology and economic behaviour models to overcome these challenges and realize the benefits of supply security and cost management.

[7]: This article analyses practices and perceptions of stakeholders on including users in smart grids experiments in the Netherlands. In-depth interviews have been conducted and smart grid projects have been analysed, using a Strategic Niche Management framework. The analysis shows that there is a clear trend to pay more attention to users in new smart grid projects. However, too much focus on technology and economic incentives can become a barrier. Some institutional barriers have been identified. New innovative business models should be developed to explore different options to involve users. The many pilot and demonstration projects that are taking shape or are being planned offer an excellent opportunity for such an exploration. Learning on the social dimensions of smart grids, and the international exchange of experiences can prevent a premature lock-in in a particular pathway.
Smart Grids and demand response programs are often considered to be technical in nature. However, recent research has emphasised the socio-technical aspects of Smart Grids [3] , and how demand response programs can be designed to be more bottom-up, and user-centred. It is argued that user flexibility does not only depend on the appliances and monetary incentives [7] ; but additionally it depends on individual characteristics and behaviour [6] , conventions [4] , and social practices involving the appliances [5] . However, capturing such information based on historical data can be very challenging. Thus, this paper utilises appliance-level day-ahead scheduling via a personalised scheduling agent for each user. Using this scheduling agent, users directly determine their schedules, flexibility, usage preference, scheduling constraints, and comfort vs. reliability preference, on a daily basis. While this approach does require a higher level of engagement from users, recent research has shown that values such as increased control and autonomy can improve users' acceptance and participation in such programs [7] [1] [2] .