储能-机组联合调频的动态经济环境跨区灵活性鲁棒优化调度

Cross-regional Flexible Robust Optimal Scheduling in Dynamic Economic Environment with Joint Frequency Regulation of Energy Storage and Units

针对大规模可再生能源并网导致的系统惯性和频率响应能力下降、调频需求增加以及可再生能源不确定性等问题,提出一种计及源端可再生能源出力不确定性的动态经济环境跨区鲁棒优化调度模型。该模型为双层优化模型,在传统鲁棒理论中加入可再生能源的空间集群效应构建随机变量的不确定集,以弥补其过于保守的缺点。在此基础上,双层优化得到最优机组组合并满足调频需求以及火电机组的动态频率约束,通过火电机组与送端储能共同参与调频,使得跨区电力系统能够达到鲁棒性和经济性的平衡。同时针对模型特点,分别采用飞蛾扑火算法和基于滤子技术的自适应蝴蝶算法对模型进行分层求解。研究结果表明,较小的置信概率会使得系统经济效益更好,且空间约束参数对于调度结果和运行方案影响显著。

Aiming at the problems such as the decline of system inertia and frequency response capacity,the increase of frequency regulation demand and the uncertainty of renewable energy source caused by the integration of large-scale renewable energy source,a cross-regional robust optimal scheduling model in dynamic economic environment considering the uncertainty of renewable energy source output at the source end is proposed.The model is a two-level optimization model.By adding the spatial cluster effect of renewable energy source into the traditional robust theory,the uncertainty set of random variables is constructed to make up for its over-conservativeness.On this basis,the optimal unit commitment is obtained by two-level optimization and meets the frequency regulation demand and the dynamic frequency constraints of thermal power units.By the joint participation of thermal power units and sending-end energy storage in frequency regulation,the cross-regional power system can achieve the balance of robustness and economy.At the same time,according to the characteristics of the model,moth extinguishing fire algorithm and adaptive butterfly algorithm based on filter technology are used to solve the model hierarchically.The results show that a small confidence probability will make the system economic benefit better,and the spatial constraint parameters have a significant impact on the scheduling results and operation schemes.