现货市场环境下水电富集电网日前优化调度研究

Day-ahead optimal scheduling of hydropower-dominated power grid under spot market environment

水电富集电网中梯级水电站间紧密的水力、电力时空耦合关系以及清洁能源消纳的政策要求,极大地增加了现货市场环境下电网优化调度的挑战性。基于水电富集电网的市场特点和真实需求,探讨了促进可再生能源保障性消纳的水电富集电网日前现货市场交易机制。在此基础上,建立了以系统综合购电费用最小为目标的日前优化调度模型。针对模型中的水电站水位-库容关系、水位-耗水率关系等非线性因素,提出了相应的线性化处理策略,将原非线性模型转换为混合整数线性规划(Mixed Integer Linear Programming, MILP)模型。以云南电网10座火电站和22座水电站的日前优化调度为例对模型进行了验证,计算时间为183.6 s,系统综合购电费用为15 535万元,3个流域均无弃水产生。结果表明:提出的模型具有较高的求解精度与效率,在满足综合购电成本最小的前提下实现了水电最大化消纳,为水电富集电网的日前现货市场开展提供了科学决策的依据。

In the hydropower enrichment network,the tight time-space coupling relationship of hypower and electricity between cascade hydropower stations and the policy requirements of clean energy consumption has greatly increased the challenge of power grid optimization and dispatching in the spot market environment.Based on the market characteristics and real demand for the hydropower-dominated power grid,the day-ahead spot market trading mechanism of the hydropower enrichment grid was discussed to guarantee the absorption of renewable energy.On this basis,a day-ahead optimization scheduling model aiming at minimizing the comprehensive power purchase cost of the power system was established.The nonlinear factors in the model such as the relationship between water level and storage capacity of hydropower stations,and the relationship between water level and water-consumption rate were linearized through multiple linearization techniques.Therefore the original nonlinear model was transformed into a Mixed Integer Linear Programming(MILP)model,and the developed model was verified by 10 thermal power stations and 22 hydropower stations in Yunnan Power Grid.The calculation time was 183.6s,the comprehensive power purchase cost of the system was 155.35 million CNY,and there was no water abandonment in the three river basins.The simulation results showed that the proposed model had high solution accuracy and efficiency,and maximized the hydropower consumption under the premise of meeting the minimum comprehensive power purchase cost.The findings of this study can provide a scientific basis for the development of the day-ahead spot market of hydropower-dominated power grid.