基于主从博弈的风光蓄网短期优化调度

考虑到电网与清洁能源发电厂之间利益冲突明显，本文建立了基于主从博弈的网源短期优化调度模型。风-光-蓄联盟依据上网电价，以自身利益最大化优化出力策略，电网在考虑联盟策略的同时，以总成本最小化动态调整上网电价，最终达到网源利益均衡。提出基于自适应负荷变化的出力生成方法和动态惯性记忆策略的布谷鸟算法进行求解。利用湖北省网进行仿真，验证了方法有效性。结果表明，模型可适应不同典型日电力调度，弃风、弃光率分别降低15% ~ 37.2%和17.4% ~ 27.9%，促进了清洁能源消纳；剩余负荷均方差减少0.64% ~ 2.75%，改善了电网运行稳定性；均衡度均值增加2.37% ~ 5.36%，显著提高了利益分配均衡度和稳健性。

Short-term optimal scheduling of wind-photovoltaic-pumped storage grid based on Stackelberg game

Considering the obvious benefit conflict between a power grid and the renewable energy power plants, a grid-power supply short-term optimal scheduling model is developed using the Stackelberg game. A wind-photovoltaic-pumped storage union optimizes its power output strategy via grid electricity prices to maximize its own benefits, while considering the union’s output strategy the grid will adjust its electricity prices dynamically at the objective of minimizing its total cost, so as to achieve a benefit balance. To solve such problems, we develop an improved cuckoo algorithm based on adaptive load changing trend and a dynamic inertia memory strategy, and verify its effectiveness by simulating the Hubei power grid. The results show that the model can adapt to different typical days of power dispatching, and its optimized schemes reduce significantly the rates of wind power curtailment and photovoltaic curtailment by 15.0% - 37.2% and 17.4% - 27.9% respectively, thus promoting the use of renewable energy. In the optimized schemes, the power grid is more stable with the mean square error of its residual load reduced by 0.64% - 2.75%, and the average balance degree is increased by 2.37% - 5.36%, a significant improvement and a more stable benefit distribution.