Comprehensive review of energy management strategies: Considering battery energy storage system and renewable energy sources

被引:0
|
作者
Onsomu, Obed N. [1 ,2 ]
Terciyanli, Erman [2 ]
Yesilata, Bulent [1 ]
机构
[1] Ankara Yildirim Beyazit Univ, Energy Syst Engn, TR-06090 Ankara, Turkiye
[2] INAVITAS, Res & Dev, Ankara, Turkiye
关键词
distributed generation; energy management system; microgrid; optimization; virtual power plant; PREDICTIVE CONTROL FRAMEWORK; DISTRIBUTED GENERATION; OPERATION MANAGEMENT; POWER MANAGEMENT; DEMAND RESPONSE; FUEL-CELL; MICROGRIDS; OPTIMIZATION; MODEL; SCENARIO;
D O I
10.1002/eng2.12995
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The transformation of power system networks is slowly taking shape, the advent of interruptive technological platforms dealing with digitalization and real-time trading of power has gained attention based on incorporation of more renewables into the grid. The stochastic nature of renewables pauses security of supply challenges and other related stability concerns, and for this reason efficient methods are investigated in this review to build an understanding of microgrid energy management system (MG-EMS) and distribution-based energy management strategies aimed at transforming the conventional grid network into smart grid network. In essence, propagating a technological shift to microgrids which have proven to be ideal distribution networks for residential and commercial loads, have become indispensable in handling distributed energy resources (DER), such as solar, PV, wind, battery energy storage systems (BESS) and small-scale microgrids, for example in case of excess supply, energy storage system (ESS) has been formulated as a solution to curb excess supply and can offer ancillary services to the grid network. Within the perspective of electricity generation and distribution, microgrid control methodologies, distribution network (DN) management approaches and incumbent optimization strategies used to coordinate and manage grid-level uncertainties are investigated. In addition, this study proposes distributionally robust optimization (DRO), to manage and mitigate risks associated to shortage or oversupply of power from RESs.
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页数:30
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