TY - BOOK ID - 145174173 TI - Multi-Agent Energy Systems Simulation AU - Pinto, Tiago AU - Soares, João AU - Lezama, Fernando PY - 2020 PB - Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute DB - UniCat KW - History of engineering & technology KW - EV charging KW - multi-agent system KW - digital twin KW - customer satisfaction indicator KW - smart microgrid KW - energy management system KW - real-time optimization KW - immune system algorithm KW - economic dispatch KW - energy consumption KW - wireless sensor network KW - cooperation KW - collaboration KW - ontology KW - energy sector KW - scoping review KW - decision-aid KW - distributed energy resources KW - distribution system operator KW - reactive power management KW - uncertainty KW - day-ahead market KW - balancing market KW - bilateral trading KW - market design KW - variable renewable energy KW - agent-based simulation KW - MATREM system KW - congestion management KW - dynamic tariff KW - agent-based distribution networks KW - demand response KW - routing protocols KW - performance parameters KW - Wireless Sensor Network (WSN) KW - EV charging KW - multi-agent system KW - digital twin KW - customer satisfaction indicator KW - smart microgrid KW - energy management system KW - real-time optimization KW - immune system algorithm KW - economic dispatch KW - energy consumption KW - wireless sensor network KW - cooperation KW - collaboration KW - ontology KW - energy sector KW - scoping review KW - decision-aid KW - distributed energy resources KW - distribution system operator KW - reactive power management KW - uncertainty KW - day-ahead market KW - balancing market KW - bilateral trading KW - market design KW - variable renewable energy KW - agent-based simulation KW - MATREM system KW - congestion management KW - dynamic tariff KW - agent-based distribution networks KW - demand response KW - routing protocols KW - performance parameters KW - Wireless Sensor Network (WSN) UR - https://www.unicat.be/uniCat?func=search&query=sysid:145174173 AB - The synergy between artificial intelligence and power and energy systems is providing promising solutions to deal with the increasing complexity of the energy sector. Multi-agent systems, in particular, are widely used to simulate complex problems in the power and energy domain as they enable modeling dynamic environments and studying the interactions between the involved players. Multi-agent systems are suitable for dealing not only with problems related to the upper levels of the system, such as the transmission grid and wholesale electricity markets, but also to address challenges associated with the management of distributed generation, renewables, large-scale integration of electric vehicles, and consumption flexibility. Agent-based approaches are also being increasingly used for control and to combine simulation and emulation by enabling modeling of the details of buildings’ electrical devices, microgrids, and smart grid components. This book discusses and highlights the latest advances and trends in multi-agent energy systems simulation. The addressed application topics include the design, modeling, and simulation of electricity markets operation, the management and scheduling of energy resources, the definition of dynamic energy tariffs for consumption and electrical vehicles charging, the large-scale integration of variable renewable energy sources, and mitigation of the associated power network issues. ER -