You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: A Review of Architectures and Concepts for Intelligence in Future Electric Energy Systems 
Chapter Title:  V. DR AND ENERGY MANAGEMENT 
1. Abstract of Cited Paper (BIB001):  Energy management means to optimize one of the most complex and important technical creations that we know: the energy system. While there is plenty of experience in optimizing energy generation and distribution, it is the demand side that receives increasing attention by research and industry. Demand Side Management (DSM) is a portfolio of measures to improve the energy system at the side of consumption. It ranges from improving energy efficiency by using better materials, over smart energy tariffs with incentives for certain consumption patterns, up to sophisticated real-time control of distributed energy resources. This paper gives an overview and a taxonomy for DSM, analyzes the various types of DSM, and gives an outlook on the latest demonstration projects in this domain. 
2. Abstract of Cited Paper (BIB002):  The integration of renewable energy systems (RESs) in smart grids (SGs) is a challenging task, mainly due to the intermittent and unpredictable nature of the sources, typically wind or sun. Another issue concerns the way to support the consumers' participation in the electricity market aiming at minimizing the costs of the global energy consumption. This paper proposes an energy management system (EMS) aiming at optimizing the SG's operation. The EMS behaves as a sort of aggregator of distributed energy resources allowing the SG to participate in the open market. By integrating demand side management (DSM) and active management schemes (AMS), it allows a better exploitation of renewable energy sources and a reduction of the customers' energy consumption costs with both economic and environmental benefits. It can also improve the grid resilience and flexibility through the active participation of distribution system operators (DSOs) and electricity supply/demand that, according to their preferences and costs, respond to real-time price signals using market processes. The efficiency of the proposed EMS is verified on a 23-bus 11-kV distribution network. 
3. Abstract of Cited Paper (BIB003):  Key management for secure communications of Advanced Metering Infrastructure is an unsolved problem until now. The difficulties and their basic solutions for AMI to choose a key management scheme will be summed up after the studies of AMI system structure, business process and cyber security requirements, proposing a key management scheme based on a hybrid-tree graph for AMI. The cyber security, including key security, key freshness, forward & backward security, etc., can be satisfied by the presented scheme, while the overhead of the scheme is reasonable. Based on the analysis, the presented scheme is a possible solution for AMI. 
4. Abstract of Cited Paper (BIB004):  A hybrid optimization method for optimal allocation of wind turbines (WTs) that combines particle swarm optimization (PSO) and market-based optimal power flow (OPF) with security constraints is proposed in this paper. The method maximizes the net present value (NPV) associated with WTs investment in a distribution market environment. The PSO is used to choose the optimal size while the market-based OPF to determine the optimal number of WTs at each candidate bus. The stochastic nature of both load demand and wind power generation is modeled by hourly time series analysis considering different combinations of wind generation and load demand. The effectiveness of the method is demonstrated with an 84-bus 11.4-kV radial distribution system. 
5. Abstract of Cited Paper (BIB005):  The smart grid is conceived of as an electric grid that can deliver electricity in a controlled, smart way from points of generation to active consumers. Demand response (DR), by promoting the interaction and responsiveness of the customers, may offer a broad range of potential benefits on system operation and expansion and on market efficiency. Moreover, by improving the reliability of the power system and, in the long term, lowering peak demand, DR reduces overall plant and capital cost investments and postpones the need for network upgrades. In this paper a survey of DR potentials and benefits in smart grids is presented. Innovative enabling technologies and systems, such as smart meters, energy controllers, communication systems, decisive to facilitate the coordination of efficiency and DR in a smart grid, are described and discussed with reference to real industrial case studies and research projects.

Literature Review:
Future electric energy systems endowed with smart metering, intelligent electronic devices, and advanced ICT will be characterized by greater responsiveness and efficiency decisions by the customers and the utility provider BIB004 ,  ,  . Recent research studies have confirmed, indeed, that DR is essential for the operation of future smart grids BIB002 , BIB006 , BIB003 . DR denotes variations of the electric consumption by customers when the price of electrical energy changes over time or in presence of financial incentives or reliability signals BIB006 . Regulatory and policy frameworks, such as the Energy Policy Act of 2005 in the U.S., have been recently enacted, which promote DR and allow customers and load aggregators taking part by means of DR resources in energy, capacity, and ancillary services markets [73] -  . In addition, the FERC Order 719 contributed to remove obstacles to the participation of DR in wholesale markets by allowing load aggregators bidding DR on behalf of retail customers into markets. In 2011, FERC Order 745 determined that DR resources should be compensated at the locational marginal price for their participation in wholesale markets, thus establishing an equal treatment between demandside resources and generation  , BIB005 . In Europe, even if it is recognized that DR could play a relevant role in favoring penetration of DER BIB001 , policies are more devoted to energy efficiency and DSM, rather than DR, which is mainly considered in order to decrease the costs of load peaks.