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作 者:刘志坚[1] 梁宁[1] 宋琪[1] 陈莎[1] 王明禹[1] 王栋栋[1]
机构地区:[1]昆明理工大学电力工程学院,云南昆明650500
出 处:《电力系统保护与控制》2015年第10期21-29,共9页Power System Protection and Control
基 金:国家自然科学基金项目(51007034);云南省自然科学基金项目(2010CD023)~~
摘 要:传统旋转备用计算模型已不再适用于含小水电群和风电接入的地区电网。以负荷损失较小、清洁能源利用率高、运行成本低为目标,基于最小火电燃料费用、最小期望停电成本、最小火电机组出力波动和最小主力水电弃水量函数模型,建立了考虑风-水-火协调运行的多目标旋转备用优化模型。采用引入粒子浓度认知的改进粒子群优化算法,通过仿真分析,验证了该模型的适用性和有效性。在不同策略下进行比较,该方法能在较低的失负荷概率情况下,得到较低的火电机组燃料费用;能随着小水电群和风电出力大小协调优化旋转备用容量。该模型及算法对存在相当规模小水电及风电的风-水-火地区电网制定旋转备用优化策略有参考价值。The conventional calculation model of spinning reserve is no longer applicable to the regional power grid group which contains small hydro and wind power access. Aiming at lower loss of load, higher utility of clean source and less cost of operation, based on the function models of the lowest thermal power fuel cost, the minimum expected outage expense, the least thermal power output fluctuation and the least abandoned water of main hydropower plants, a multi-objective optimization model is built considering the wind-water-fire power coordinated operation. The improved particle swarm optimization algorithm introducing particle concentration cognitive is used. By simulating and analyzing, the applicability and validity is verified. To compare them under different strategies, this method can get less fuel expenses of thermal power units in the case of lower loss of load probability (LOLP); optimize the spinning reserve capacity with the small hydropower and wind power output size. The model and the algorithm are helpful for drawing up optimization strategies of the reserve capacity in those regions of wind-hydro-thermal grid in which larger scale small hydropower and wind power exists.
关 键 词:小水电群 风电 旋转备用 协调优化 改进粒子群算法
分 类 号:TM73[电气工程—电力系统及自动化]
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