计及风光时空集群效应的储能容量配置

解决区域内风光资源大规模并网对电力系统的稳定性和灵活性造成威胁的问题，关键在于对储能容量的合理配置。为此本文构造了计及风光时空集群效应的储能鲁棒模型。在描述风光集群发电系统出力的多面体不确定集中加入时间平滑约束和空间集群约束以缩小集合边界，降低模型的保守性；把不确定性问题利用数学推理转换为确定性问题，并且讨论了违反概率约束与不确定性置信度关系；基于碳交易对系统的经济性进行分析。提出利用双种群伪并行SSA-DE(sparrow search algorithm-diffferential evolution)算法来求解模型。验证结果表明，考虑时空集群效应得到的储能配置方案可以更好的均衡系统的经济性和鲁棒性；将碳交易纳入考虑因素将降低系统的成本；不确定度置信概率与违反安全约束概率呈负相关性，与系统经济性呈正相关性。

Energy Storage Capacity Configuration of Clustering Photovoltaic-wind Joint Power Generation Considering the Temporal and Spatial Clustering Effect

The key to solving the problem of large-scale regional wind and photovoltaic connections to the grid, which pose a threat to the stability and flexibility of the power system, lies in the rational configuration of energy storage capacity. In this paper, a robust model of energy storage was constructed for the clustering photovoltaic-wind joint power generation taking into account the temporal and spatial clustering effect. Added temporal and spatial clustering constraints to the polyhedron uncertainty set describing the wind and solar output to shrink the set boundary and reduce the conservativeness of the model; used mathematical reasoning to transform the uncertainty problem into a deterministic problem, then the relationship between the probability of violation and the confidence level of uncertainty was discussed, and the economics of the system was analyzed based on carbon trading. The model was solved using a double swarm peudo parallelism sparrow search algorithm and differential evolution. The results show that the energy storage configuration scheme obtained by considering the temporal and spatial clustering effect can better balance the economy and robustness of the system; taking carbon trading into account will reduce the cost of the system; uncertainty confidence probabilities are negatively correlated with the probability of violating safety constraints and positively correlated with system economics.