Realizing the significant demand flexibility potential in deregulated power systems requires its suitable integration in electricity markets. Part I of this work has presented the theoretical, algorithmic and implementation aspects of a novel pool market mechanism achieving this goal by combining the advantages of centralized mechanisms and dynamic pricing schemes, based on Lagrangian relaxation (LR) principles. Part II demonstrates the applicability of the mechanism, considering two reschedulable demand technologies with significant potential, namely electric vehicles with flexible charging capability and electric heat pump systems accompanied by heat storage for space heating. The price response sub-problems of these technologies are formulated, including detailed models of their operational properties. Suitable case studies on a model of the U.K. system are examined in order to validate the properties of the proposed mechanism and illustrate and analyze the benefits associated with the market participation of the considered technologies.

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Scalability and privacy concerns have created significant interest in decentralized coordination of distributed energy resources (DERs) within microgrids. Previously proposed approaches, however, fail to achieve feasible solutions under flexible demand (FD) and energy storage (ES) participation. After justifying and demonstrating this challenge, this paper develops a novel Lagrangian relaxation-based mechanism achieving feasible, nearoptimal solutions in a decentralized fashion, considering both active and reactive power. A two-level iterative algorithm eliminates the infeasibility effect of FD and ES nonstrict convexities, and prevents the creation of new demand peaks and troughs by the concentration of their response at the same low-and high-priced periods. Tradeoffs associated with the design and operation of the mechanism are analyzed, and the value of additional information submission by the DER, in enabling the quantification of an optimality bound of the determined solutions and significant improvements in communication requirements, is assessed. These contributions are supported by case studies on an LV microgrid test system.

Dawei Qiu (S'18) is currently pursuing the Ph.D. degree at Imperial College London, London, U.K. His current research interests include game-theoretic and agent-based modeling in wholesale as well as retail electricity markets. Mingyang Sun (M'16) received the Ph.D. degree from Imperial College London, London, U.K., in 2017. He is currently a Research Associate in this institution. His current research interests include big data analytics and artificial intelligence in energy systems. Dimitrios Papadaskalopoulos (M'13) is a Research Fellow at Imperial College London, London, U.K. His current research focuses on the development and application of distributed and market-based approaches for the coordination of operation and planning decisions in power systems, employing optimization and game theoretic principles. Goran Strbac (M'95) is a Professor of Electrical Energy Systems at Imperial College London, London, U.K. His research interests include electricity system operation, investment and pricing, and integration of renewable generation and distributed energy resources.