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考虑入库径流和负荷需求不确定性的水库优化调度研究

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为量化水库入库径流和电网负荷需求的不确定性，分析二者对水库优化调度过程的影响，本文以三峡水库为例，引入鲁棒优化理论，建立径流和负荷的多面体不确定集合，结合k-means聚类算法对各不确定情景下随机模拟的入流和负荷情景进行聚类处理。建立以电站实际出力与计划出力偏差最小、总发电量最大和下游适宜生态流量改变度最小为目标的多目标优化调度模型。多目标粒子群算法求解结果表明:在考虑水库入流和负荷需求不确定性的前提下，各情景下的水库水位升降变化规律与实际水位变化规律基本相同，且与实际水位相比，水库能在更多时段维持较高水位运行，提高了三峡电站在蓄水期的整体发电水平。
Research on the optimal scheduling of reservoirs considering the uncertainty of inflow runoff and load demand
To quantify the uncertainty of reservoir inflow runoff and the load demand of power grids and analyze their influence on the optimization and dispatch processes of a reservoir,with the Three Gorges Reservoir as an example,a polyhedral uncertainty set of the runoff and load is established,which introduces the robust optimization theory.By combining with the k-means clustering algorithm,the randomly simulated inflow and load scenarios are clustered under various uncertainty scenarios.A multiobjective optimal dispatch model is established to minimize the devia-tion between the actual output and the planned output of the power station,maximize the total power generation,and minimize the change in the downstream suitable ecological flow.The results of the multiobjective particle swarm optimization algorithm show that considering the uncertainty of reservoir inflow and load demand,the fluctuation law of the reservoir water level in each scenario is basically the same as that of the actual water level.Moreover,com-pared with the actual water level,the reservoir can be operated while maintaining higher water levels for longer pe-riods,which improves the overall power generation level of the Three Gorges Power Station during the water storage period.

uncertaintyinflow runoffload demandoptimal scheduling of reservoirmultiobjective particle swarm optimizationk-means clustering algorithmrobust optimizationThree Gorges Reservoir

李晓英、朱克节、陈端

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河海大学 水利水电学院,江苏 南京 210098

长江水利委员会 长江科学院,湖北 武汉 430014

不确定性 入库径流 负荷需求 水库优化调度 多目标粒子群算法 k-means聚类算法 鲁棒优化 三峡水库

国家重点研发计划湖南省重大水利科技项目

2018YFC0407902XSKJ2021000-04

2024

10.11990/jheu.202206033

哈尔滨工程大学学报
哈尔滨工程大学

哈尔滨工程大学学报

CSTPCD北大核心
影响因子：0.655
ISSN：1006-7043
年,卷(期)：2024.45(9)