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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.

History of engineering & technology --- EV charging --- multi-agent system --- digital twin --- customer satisfaction indicator --- smart microgrid --- energy management system --- real-time optimization --- immune system algorithm --- economic dispatch --- energy consumption --- wireless sensor network --- cooperation --- collaboration --- ontology --- energy sector --- scoping review --- decision-aid --- distributed energy resources --- distribution system operator --- reactive power management --- uncertainty --- day-ahead market --- balancing market --- bilateral trading --- market design --- variable renewable energy --- agent-based simulation --- MATREM system --- congestion management --- dynamic tariff --- agent-based distribution networks --- demand response --- routing protocols --- performance parameters --- Wireless Sensor Network (WSN)

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

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.

History of engineering & technology --- EV charging --- multi-agent system --- digital twin --- customer satisfaction indicator --- smart microgrid --- energy management system --- real-time optimization --- immune system algorithm --- economic dispatch --- energy consumption --- wireless sensor network --- cooperation --- collaboration --- ontology --- energy sector --- scoping review --- decision-aid --- distributed energy resources --- distribution system operator --- reactive power management --- uncertainty --- day-ahead market --- balancing market --- bilateral trading --- market design --- variable renewable energy --- agent-based simulation --- MATREM system --- congestion management --- dynamic tariff --- agent-based distribution networks --- demand response --- routing protocols --- performance parameters --- Wireless Sensor Network (WSN) --- EV charging --- multi-agent system --- digital twin --- customer satisfaction indicator --- smart microgrid --- energy management system --- real-time optimization --- immune system algorithm --- economic dispatch --- energy consumption --- wireless sensor network --- cooperation --- collaboration --- ontology --- energy sector --- scoping review --- decision-aid --- distributed energy resources --- distribution system operator --- reactive power management --- uncertainty --- day-ahead market --- balancing market --- bilateral trading --- market design --- variable renewable energy --- agent-based simulation --- MATREM system --- congestion management --- dynamic tariff --- agent-based distribution networks --- demand response --- routing protocols --- performance parameters --- Wireless Sensor Network (WSN)