TY - BOOK ID - 133578736 TI - Distributed Energy Resources Management PY - 2019 PB - MDPI - Multidisciplinary Digital Publishing Institute DB - UniCat KW - autonomous operation KW - energy management system KW - stochastic programming KW - co-generation KW - Unit Commitment (UC) KW - distributed system KW - demand-side energy management KW - virtual power plant KW - Powell direction acceleration method KW - average consensus algorithm (ACA) KW - transmission line KW - interval optimization KW - renewable energy KW - microgrids KW - scheduling KW - business model KW - non-cooperative game (NCG) KW - domestic energy management system KW - time series KW - energy trading KW - decision-making under uncertainty KW - Demand Response Unit Commitment (DRUC) KW - real-time simulation KW - distributed generation KW - discrete wavelet transformer KW - microgrid (MG) KW - probabilistic programming KW - optimal bidding KW - ac/dc hybrid microgrid KW - building energy flexibility KW - storage KW - uncertainty KW - Cat Swarm Optimization (CSO) KW - advance and retreat method KW - multiplier method KW - microgrid KW - Demand Response (DR) KW - electricity markets KW - aggregators KW - fault localization KW - aggregator KW - consensus algorithm KW - black start KW - microgrid operation KW - local controller KW - thermal comfort KW - diffusion strategy KW - optimal operation KW - power system restoration (PSR) KW - energy flexibility KW - ARIMA KW - pricing strategy KW - clustering KW - adaptive droop control KW - multi-agent system (MAS) KW - hierarchical game KW - energy flexibility potential KW - demand response UR - https://www.unicat.be/uniCat?func=search&query=sysid:133578736 AB - At present, the impact of distributed energy resources in the operation of power and energy systems is unquestionable at the distribution level, but also at the whole power system management level. Increased flexibility is required to accommodate intermittent distributed generation and electric vehicle charging. Demand response has already been proven to have a great potential to contribute to an increased system efficiency while bringing additional benefits, especially to the consumers. Distributed storage is also promising, e.g., when jointly used with the currently increasing use of photovoltaic panels. This book addresses the management of distributed energy resources. The focus includes methods and techniques to achieve an optimized operation, to aggregate the resources, namely, by virtual power players, and to remunerate them. The integration of distributed resources in electricity markets is also addressed as a main drive for their efficient use. ER -