School of Information Engineering,Guizhou Open University(Guizhou Vocational Technology Institute)
Department of Thermal Science and Energy Engineering,University of Science and Technology of China

风光火储联合调度是助力火电行业实现“双碳”目标的重要路径之一。为应对可再生能源出力不确定性对电力系统的影响,以实现总运行成本最小为优化目标,构建风、光出力不确定参数合集,建立两阶段鲁棒优化模型对风光火储联合系统进行调度优化。将不确定性优化问题解耦成包含确定性参数的第1阶段以及涉及不确定性变量的第2阶段。其中,第1阶段基于可再生能源出力预测值,求解火电机组启停状态和储能设备充放电状态,第2阶段作为灵活调控阶段,求解扰动发生后最恶劣场景下各设备的输出功率,并采用列约束生成算法结合算例进行计算。结果表明,该模型通过合理弃能和储能调峰可有效平抑火电机组净负荷波动,缓解机组调峰压力。相比确定性优化模型,该不确定性优化模型求解所得运行成本增加,表明考虑可再生能源不确定性的鲁棒优化具有更高的保守度,同时,可再生能源出力偏离度越大,其运行成本增幅相比确定性优化越小,有效降低了可再生能源出力偏差对系统经济性的干扰。

The combined dispatching and operation of wind-solar-thermal-storage is an important path to help the thermal power industryachieve carbon peaking and carbon neutrality goals. In order to cope with the impact of renewable energy output uncertainty on the powersystem, a set of uncertain parameters of wind power and photovoltaic power output was constructed to minimize the total operating cost asthe optimization goal, and a two-stage robust optimization model was established to optimize the scheduling of the combined wind-solar-thermal-storage system. The uncertainty optimization problem was decoupled into a first stage involving deterministic parameters and a second stage involving uncertain variables. In the first stage, the start-up and shutdown state of thermal power units and charging and discharging state of energy storage equipment were solved based on the predicted output of renewable energy. In the second stage, as a flexible regulation stage, the output power of each equipment under the worst scenario after disturbance occurs was solved, and the column constraint generation algorithm was used to calculate with examples. The results show that the model can effectively smooth the netload fluctuation and relieve the peak load pressure of thermal power units through reasonable energy abandonment and energy storage.Compared with the deterministic optimization model, the increase in operating cost obtained from the solution of the uncertainty optimization model indicates that the robust optimization considering the uncertainty of renewable energy has a higher conservative degree. At thesame time, the greater the deviation of renewable energy output, the smaller the increase in operating cost compared with the deterministicoptimization, effectively reducing the interference of renewable energy output deviation on system economy.

国家重点研发计划资助项目(2021YFF0601000);2024年度贵州开放大学(贵州职业技术学院)、贵州远程教育基地、贵州远程教育学会课题资助项目(2024ZD04)

宋祉慧,田军见,倪战士,等.考虑可再生能源不确定性的风光火储联合调度优化[J].洁净煤技术,2024,30(8):117-127.

SONG Zhihui,TIAN Junjian,NI Zhanshi,et al.Optimization of combined wind-solar-thermal-storage system consideringthe uncertainty of renewable energy output[J].Clean Coal Technology,2024,30(8):117-127.