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作 者:黄荣泽 HUANG Rongze(Dispatching Control Center,Baise New Aluminum Power Co.,Ltd.,Baise Guangxi 533000,China)
机构地区:[1]百色新铝电力有限公司调度中心,广西百色533000
出 处:《宁夏电力》2025年第1期35-42,72,共9页Ningxia Electric Power
摘 要:丰水期来水量大,梯级水电站调节能力不足,水电-新能源消纳矛盾突出,造成水电站弃水和新能源弃电增加;枯水期水量减少,水电站水库需预留充足蓄水量作为电网应急电源,造成水电站平抑新能源波动的能力减弱。针对上述两个问题,在丰水期构建梯级水电站发电量最大和剩余净负荷波动最小的多目标优化调度模型,在枯水期构建梯级水电站蓄水量最大和剩余净负荷波动最小的多目标优化调度模型,并采用法线边界交叉法(normal boundary intersection,NBI)求解多目标优化问题以获得帕累托最优解集,根据模糊隶属度和熵权法从帕累托解集中选出折中最优解作为丰水期和枯水期最优调度方案。对某一实际电网进行优化,计算结果表明所提模型的有效性,对实际调度运行具有一定指导意义。During the wet season,the substantial influx of water surpasses the adaptive capacity of cascade hydropower stations,resulting in considerable conflicts between hydropower generation and the integration of renewable energy.This leads to an increase in the curtailment of both hydropower and renewable energy.During the dry season,the reduction in incoming water requires hydropower reservoirs to conserve adequate water for emergency power supply to the grid,hence diminishing the capacity of hydropower stations to mitigate fluctuations in renewable energy output.In the wet season,a multi-objective optimization scheduling model is designed to maximize power generation and reduce residual net load fluctuations at cascade hydropower units.In the dry season,a multi-objective optimization scheduling model is developed to maximize storage capacity and minimize residual net load variability.The normal boundary intersection(NBI)method is applied to solve the multi-objective optimization problem,generating a Pareto optimal solution set.A compromise solution is selected from the Pareto set using fuzzy membership degree and entropy weighting methods,serving as the optimal scheduling plan for both the wet and dry seasons.The optimization results for a real-world power grid demonstrate the efficacy of the proposed methodology,offering significant insights for actual dispatching operations.
关 键 词:梯级水电站 新能源消纳 多目标优化 水电-新能源互补
分 类 号:TM73[电气工程—电力系统及自动化]
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