风-光-热-水互补发电优化调度策略

Optimal Scheduling Strategy for Wind-light-heat-water Complementary Power Generation

近年来,随着大规模的新能源发电机组并入电网,给电力系统调度带来了巨大的挑战。由风电、光伏、光热和水电4种能源可构成互补发电系统,在综合考虑互补系统的各个经济指标(售电效益、环境效益、运行维护成本、购电成本等)、功率波动以及电网安全运行的约束的条件下,建立了以互补系统并网效益最大和输出功率波动方差最小为目标的多目标优化模型。最后,利用改进多目标粒子群优化算法(MOPSO),通过IEEE30节点算例系统验证了所提方法的可行性和有效性。仿真结果表明,相对于风电、光伏、光热互补系统而言,水电站的参与可以提高11%的并网经济效益,减小82.2%的输出功率波动;采用改进MOPSO算法求解此多目标问题可以提高3.6%的经济效益,减小14 MW的功率波动。

In recent years, with the integration of large-scale new energy power generation into the grid, it has brought great challenges to the power schedule system. This paper uses four new energy sources including wind power, photovoltaics, solar thermal and hydropower to form a complementary power generation system. Under the condition of comprehensive consideration of each economic index of the complementary system(electricity sales benefit, environmental benefit, operation and maintenance cost, power purchase cost, etc.), power fluctuations and the constraints of the safe operation of the power grid, a multi-objective optimization model with the largest grid-connected benefit of complementary systems and the smallest variance of output power fluctuations is established. Finally, the improved multi-objective particle swarm optimization algorithm(MOPSO) is used to verify the feasibility and effectiveness of the proposed method through the IEEE30-node example system. The simulation results show that compared with wind power, photovoltaic and concentrating solar power complementary systems,the participation of hydropower stations can increase the economic benefits of grid connection by 11% and reduce the output power fluctuation by 82.2%. The improved MOPSO algorithm to solve this multi-objective problem can increase the economic benefit by 3.6% and reduce the power fluctuation of 14 MW.