考虑源荷不确定性的直流配电网模糊随机日前优化调度

Fuzzy Random Day-Ahead Optimal Dispatch of DC Distribution Network Considering the Uncertainty of Source-Load

针对直流配电网中分布式可再生能源出力及典型直流类负荷的不确定性,提出了综合考虑负荷自弹性系数以及电价型需求响应的不确定性负荷模型;在考虑可再生能源随机性的基础上,通过签订日前充电合同将电动汽车这类高可调度单元转换为确定性负荷;以直流配电网与上级电网联络线功率最平滑及日前调度成本最小为优化目标,建立了模糊随机日前优化调度模型,并采用熵权法确定两者权重进行求解。以某直流配电网为例,针对不同场景、不同光伏出力、不同置信水平以及不同的电动汽车合同签订率,验证了优化调度模型的有效性、优越性。

Aiming at the uncertainty of distributed renewable energy and typical DC load in DC distribution network, the uncertainty load model considering load self elasticity coefficient and demand response of electricity price is proposed. Considering the randomness of renewable energy, the highly schedulable units such as electric vehicle is converted into deterministic load by signing a day-ahead charging contract;A fuzzy random day-ahead optimal dispatching model is established, for achieving the objective of smoothest power of line between the distribution network and upper power grid, and the objective of minimum daily dispatching cost. The entropy weight method is used to determine the weights of the two objectives. Taking a DC distribution network as an example, the effectiveness and superiority of the optimal dispatching model are verified according to different scenarios, different photovoltaic output, different confidence levels and different signing rate of electric vehicle contracts.