电力系统自动化
電力繫統自動化
전력계통자동화
AUTOMATION OF ELECTRIC POWER SYSTEMS
2014年
21期
7-12
,共6页
王晶%王宗礼%陈骏宇%王雪锋%王肖杰%田磊
王晶%王宗禮%陳駿宇%王雪鋒%王肖傑%田磊
왕정%왕종례%진준우%왕설봉%왕초걸%전뢰
微网(微电网)%容量配置%博弈模型%萤火虫算法%Shapley值法
微網(微電網)%容量配置%博弈模型%螢火蟲算法%Shapley值法
미망(미전망)%용량배치%박혁모형%형화충산법%Shapley치법
microgrid%capacity allocation%game model%firefly algorithm%Shapley value method
以实现微网负荷间利益最大化和微源容量配置经济高效为策略,提出基于萤火虫优化算法的微网源-荷博弈方法。首先,在充分考虑微源成本、微源容量、负荷成本、负荷用电量之间相互关系的基础上,建立了具有博弈关系的微源和负荷博弈模型,以及非合作和合作博弈下的目标函数。然后,设计了萤火虫优化算法在博弈迭代中的应用流程,利用吸引度和亮度参数对各博弈者的策略进行更新,实现了目标函数的最优。最后,提出利用收益微调系数和稳定指标进行搜索的改进Shapley值法,对合作后的收益进行重新分配,保证了合作全联盟的稳定性。通过对微源博弈者和负荷博弈者的收益分析,验证了所提博弈模型在负荷优化中的可行性,及萤火虫优化算法在求解博弈均衡解时的有效性。
以實現微網負荷間利益最大化和微源容量配置經濟高效為策略,提齣基于螢火蟲優化算法的微網源-荷博弈方法。首先,在充分攷慮微源成本、微源容量、負荷成本、負荷用電量之間相互關繫的基礎上,建立瞭具有博弈關繫的微源和負荷博弈模型,以及非閤作和閤作博弈下的目標函數。然後,設計瞭螢火蟲優化算法在博弈迭代中的應用流程,利用吸引度和亮度參數對各博弈者的策略進行更新,實現瞭目標函數的最優。最後,提齣利用收益微調繫數和穩定指標進行搜索的改進Shapley值法,對閤作後的收益進行重新分配,保證瞭閤作全聯盟的穩定性。通過對微源博弈者和負荷博弈者的收益分析,驗證瞭所提博弈模型在負荷優化中的可行性,及螢火蟲優化算法在求解博弈均衡解時的有效性。
이실현미망부하간이익최대화화미원용량배치경제고효위책략,제출기우형화충우화산법적미망원-하박혁방법。수선,재충분고필미원성본、미원용량、부하성본、부하용전량지간상호관계적기출상,건립료구유박혁관계적미원화부하박혁모형,이급비합작화합작박혁하적목표함수。연후,설계료형화충우화산법재박혁질대중적응용류정,이용흡인도화량도삼수대각박혁자적책략진행경신,실현료목표함수적최우。최후,제출이용수익미조계수화은정지표진행수색적개진Shapley치법,대합작후적수익진행중신분배,보증료합작전련맹적은정성。통과대미원박혁자화부하박혁자적수익분석,험증료소제박혁모형재부하우화중적가행성,급형화충우화산법재구해박혁균형해시적유효성。
To maximize the benefits among loads and to economically allocate the capacities of distributed generators (DGs),a game model for DGs-loads in microgrid based on the firefly algorithm (FA) is proposed.Firstly,the game model for DGs-loads as well as the obj ective functions under non-cooperative and cooperative games,is developed after careful consideration of the relationships between DGs costs,DGs capacities,loads costs and load electricity consumptions.Then,the application of FA in the game iterative process is designed.The parameters of attraction and brightness in FA are applied to update the game strategy for optimizing the obj ective functions.Finally,the improved Shapley method is proposed to redistribute the total income in order to ensure the stability of cooperation.The two coefficients income fine-tuning coefficient and stability index are presented to find the optimal distribution solution.The feasibility of the game model in load optimization and effectiveness of FA in solving game equilibrium are validated through an analysis of benefits between DGs and loads.