新能源大基地风光储容量协调优化配置

大型新能源基地需要协调配置风光火储容量以满足外送要求，其中火电容量及外送通道的容量通常预先确定，从而风电、光伏、储能的容量配置成为影响新能源外送效果的重要因素。为此，针对大型新能源基地，研究了风光储容量优化配置问题，提出了基于新能源外送可靠性的容量配置方法。基于需求侧的负荷曲线，提出了一种聚类方法来优化直流通道的计划传输功率；基于直流计划功率，提出了衡量新能源外送可靠性的送电置信概率指标；基于送电置信概率等约束，构建了风光储容量优化配置的基本规划模型。为了进一步保证在不同的场景下新能源能可靠外送，在基本规划模型的基础上加入场景分布不确定性，提出了风光储容量配置的分布鲁棒规划模型。考虑到分布鲁棒约束包含整数变量，提出了一种迭代算法用于该分布鲁棒规划模型的求解。实际算例验证了所提方法的有效性。

Coordinated optimal configuration of wind-photovoltaic-energy storage capacity for large-scale renewable energy bases

The large-scale renewable energy bases need to coordinate the capacity configuration of wind-photovoltaic-thermal-energy storage to meet the power delivery requirements, the thermal power capacity and the delivery channel capacity are usually predetermined, so the capacity configuration of wind power, photovoltaic and energy storage has become an important factor affecting the delivery effect of renewable energy. Therefore, aiming at the large-scale renewable energy bases, the optimal configuration of wind-photovoltaic-energy storage capacity is studied and a capacity configuration method based on the reliability of renewable energy power delivery is proposed. Based on the demand side load curve, a clustering method is proposed to optimize the planned transmission power of the direct current channels. Based on the planned direct current power, a transmission confidence probability index is proposed to measure the reliability of renewable energy power delivery. Based on the transmission confidence probability and other constraints, the basic planning model of wind-photovoltaic-energy storage capacity optimization configuration is constructed. In order to further ensure the reliable power delivery of renewable energy under different scenarios, adding the uncertainty of scenario distribution on the basis of the basic planning model, a distributionally robust planning model for wind-photovoltaic-energy storage capacity configuration is proposed. Considering that the distributionally robust constraints contain integer variables, an iterative algorithm is proposed to solve the distributionally robust planning model. The effectiveness of the proposed method is verified by a practical example.