| 000 | 03708naaaa2200733uu 4500 | ||
|---|---|---|---|
| 003 | BUT | ||
| 005 | 20230414164149.0 | ||
| 006 | m o d | ||
| 007 | cr|mn|---annan | ||
| 008 | 20210501s2020 sz x |||||o ||||eng|| d | ||
| 020 | _a9783039436507 | ||
| 020 | _a9783039436491 | ||
| 020 | _a9783039436507 | ||
| 040 |
_aoapen _coapen |
||
| 041 | 0 | _aeng | |
| 042 | _adc | ||
| 080 | _a004 | ||
| 100 | 1 |
_aPinto, Tiago _4edt |
|
| 245 | 1 | 0 | _aMulti-Agent Energy Systems Simulation |
| 260 |
_aBasel, Switzerland _bMDPI - Multidisciplinary Digital Publishing Institute _c2020 |
||
| 300 | _a1 electronic resource (190 p.) | ||
| 506 | 0 |
_aOpen Access _2star _fUnrestricted online access |
|
| 520 | _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. | ||
| 540 |
_aCreative Commons _fhttps://creativecommons.org/licenses/by/4.0/ _2cc |
||
| 546 | _aEnglish | ||
| 650 | 0 |
_aИскусственный интеллект _94518 |
|
| 653 | _aEV charging | ||
| 653 | _aMulti-agent system | ||
| 653 | _aDigital twin | ||
| 653 | _aCustomer satisfaction indicator | ||
| 653 | _aSmart microgrid | ||
| 653 | _aEnergy management system | ||
| 653 | _aReal-time optimization | ||
| 653 | _aImmune system algorithm | ||
| 653 | _aEconomic dispatch | ||
| 653 | _aEnergy consumption | ||
| 653 | _aWireless sensor network | ||
| 653 | _aCooperation | ||
| 653 | _aCollaboration | ||
| 653 | _aOntology | ||
| 653 | _aEnergy sector | ||
| 653 | _aScoping review | ||
| 653 | _aDecision-aid | ||
| 653 | _aDistributed energy resources | ||
| 653 | _aDistribution system operator | ||
| 653 | _aReactive power management | ||
| 653 | _aUncertainty | ||
| 653 | _aDay-ahead market | ||
| 653 | _aBalancing market | ||
| 653 | _aBilateral trading | ||
| 653 | _aMarket design | ||
| 653 | _aVariable renewable energy | ||
| 653 | _aAgent-based simulation | ||
| 653 | _aMATREM system | ||
| 700 | 1 |
_aSoares, João _4edt |
|
| 700 | 1 |
_aLezama, Fernando _4edt |
|
| 700 | 1 |
_aPinto, Tiago _4oth |
|
| 700 | 1 |
_aSoares, João _4oth |
|
| 700 | 1 |
_aLezama, Fernando _4oth |
|
| 856 | 4 | 0 |
_awww.oapen.org _uhttps://mdpi.com/books/pdfview/book/3067 _70 _zDownload |
| 856 | 4 | 0 |
_awww.oapen.org _uhttps://directory.doabooks.org/handle/20.500.12854/69278 _70 _zDescription |
| 909 |
_c197 _dKhurliman Arzieva |
||
| 942 |
_2udc _cEE |
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| 999 |
_c6427 _d6427 |
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