中国农村水利水电
中國農村水利水電
중국농촌수이수전
CHINA RURAL WATER AND HYDROPOWER
2015年
6期
174-178,182
,共6页
可信性理论%梯级水电%新能源%帝国竞争算法
可信性理論%梯級水電%新能源%帝國競爭算法
가신성이론%제급수전%신능원%제국경쟁산법
credibility theory%cascade hydro power%new energy%imperialist competition algorithm
梯级水电站联合优化调度不仅能增加发电量，而且调节速度快，可以弥补风力发电、光伏发电等新能源波动性大的缺点，提高新能源的系统接纳能力。考虑到自然来水量、风电出力、光伏发电出力和负荷的不确定性，引入模糊理论，将其用梯形模糊数来表示，用梯级水电站进行优化控制，综合考虑发电燃料费用最少、碳排放收益最大以及火电机组波动最小这3个目标，允许决策在一定可信度下违反约束条件，将模糊机会约束条件转化为清晰等价类，建立基于可信性理论的模糊机会约束的多目标优化调度模型，并用改进的帝国竞争算法来求解。选择一个含风力发电和光伏发电的水火系统作为实例进行计算，算例结果表明，所提出的模型和算法有效实用。
梯級水電站聯閤優化調度不僅能增加髮電量，而且調節速度快，可以瀰補風力髮電、光伏髮電等新能源波動性大的缺點，提高新能源的繫統接納能力。攷慮到自然來水量、風電齣力、光伏髮電齣力和負荷的不確定性，引入模糊理論，將其用梯形模糊數來錶示，用梯級水電站進行優化控製，綜閤攷慮髮電燃料費用最少、碳排放收益最大以及火電機組波動最小這3箇目標，允許決策在一定可信度下違反約束條件，將模糊機會約束條件轉化為清晰等價類，建立基于可信性理論的模糊機會約束的多目標優化調度模型，併用改進的帝國競爭算法來求解。選擇一箇含風力髮電和光伏髮電的水火繫統作為實例進行計算，算例結果錶明，所提齣的模型和算法有效實用。
제급수전참연합우화조도불부능증가발전량，이차조절속도쾌，가이미보풍력발전、광복발전등신능원파동성대적결점，제고신능원적계통접납능력。고필도자연래수량、풍전출력、광복발전출력화부하적불학정성，인입모호이론，장기용제형모호수래표시，용제급수전참진행우화공제，종합고필발전연료비용최소、탄배방수익최대이급화전궤조파동최소저3개목표，윤허결책재일정가신도하위반약속조건，장모호궤회약속조건전화위청석등개류，건립기우가신성이론적모호궤회약속적다목표우화조도모형，병용개진적제국경쟁산법래구해。선택일개함풍력발전화광복발전적수화계통작위실례진행계산，산례결과표명，소제출적모형화산법유효실용。
Optimal dispatch for cascade hydropower can not only increase the generating capacity ,but also lead to faster adjustment which compensates for the disadvantage of wind power ,solar power .Reservoir inflow ,wind power output ,PV output and power load in a power system composed of wind power generation ,photovoltaic generation ,cascade hydro power and thermal power are ex‐pressed as trapezoidal fuzzy parameters according to fuzzy theory .A control function is introduced to coordinate the three objective functions ,which include coal consumption minimization ,carbon trading profit maximization and thermal power fluctuation minimiza‐tion .A multi-objective optimal dispatching model based on credibility theory and fuzzy chance constraint is presented ..Imperialist competition algorithm is presented to solve the model .A system with wind power generation ,photovoltaic generation ,cascade hydro-power and thermal power is taken as a study example and the results show that the model and the optimization algorithm are both correct .
