Optimal Dispatching Strategy of Active Distribution Network for Promoting Local Consumption of Renewable Energy - Xie, Hua; Wang, Wei; Wang, Weixing; Tian, Lulu (Frontiers in Energy Research, 2022)
Large-scale renewable energy sources (RESs) have been integrated into the active distribution network (ADN). For promoting local consumption of RESs within ADN, an optimal dispatching strategy was proposed with two-stage hierarchical energy management framework. On the spatial boundary, a two-layer energy management framework was designed with the local optimization layer and the global optimization layer. The local optimization layer was for the optimal power flow in branch feeder with the objective functions of minimize operation costs and maximize the consumption of RESs. The global optimization layer was for the optimal power flow in main feeder with the objective functions of to minimize power loss and voltage deviation of nodes. On the time scale, two-stage optimal dispatching models were established including the day-ahead optimal models and intra-day optimal models. The day-ahead optimal models identified the operation status of the controllable units, and then the intra-day optimal models were updated with the ultra-short-term forecast results. The risk indicator was introduced to quantify the uncertainty of RES and the non-dominated sorting genetic algorithm with elite strategy was adopted to solve the multi-objective nonlinear programming problem. An actual project in northern China was used as the tested system. The results of case studies verify that the proposed strategy can effectively realize the maximum local consumption of RESs and support the economic operation of ADN.