LEADER 03894nam 2200805z- 450 001 9910557296203321 005 20210501 035 $a(CKB)5400000000041077 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/69278 035 $a(oapen)doab69278 035 $a(EXLCZ)995400000000041077 100 $a20202105d2020 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aMulti-Agent Energy Systems Simulation 210 $aBasel, Switzerland$cMDPI - Multidisciplinary Digital Publishing Institute$d2020 215 $a1 online resource (190 p.) 311 08$a3-03943-649-X 311 08$a3-03943-650-3 330 $aThe 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. 606 $aHistory of engineering and technology$2bicssc 610 $aagent-based distribution networks 610 $aagent-based simulation 610 $abalancing market 610 $abilateral trading 610 $acollaboration 610 $acongestion management 610 $acooperation 610 $acustomer satisfaction indicator 610 $aday-ahead market 610 $adecision-aid 610 $ademand response 610 $adigital twin 610 $adistributed energy resources 610 $adistribution system operator 610 $adynamic tariff 610 $aeconomic dispatch 610 $aenergy consumption 610 $aenergy management system 610 $aenergy sector 610 $aEV charging 610 $aimmune system algorithm 610 $amarket design 610 $aMATREM system 610 $amulti-agent system 610 $aontology 610 $aperformance parameters 610 $areactive power management 610 $areal-time optimization 610 $arouting protocols 610 $ascoping review 610 $asmart microgrid 610 $auncertainty 610 $avariable renewable energy 610 $awireless sensor network 610 $aWireless Sensor Network (WSN) 615 7$aHistory of engineering and technology 700 $aPinto$b Tiago$4edt$01283265 702 $aSoares$b Joćo$4edt 702 $aLezama$b Fernando$4edt 702 $aPinto$b Tiago$4oth 702 $aSoares$b Joćo$4oth 702 $aLezama$b Fernando$4oth 906 $aBOOK 912 $a9910557296203321 996 $aMulti-Agent Energy Systems Simulation$93019083 997 $aUNINA