Optimal Scheduling in Active Distribution Network Considering Coordinated Interactions among Source-Network-Load-Storage

With the ever-increasing penetration of distributed generations (DGs), traditional distribution networks (DNs) are facing issues such as two-way power flow, increased voltage fluctuations and complex operating control, which need to be properly addressed. While on the other hand, the active distribution network (ADN) could effectively dispatch DGs, energy storage devices, and demand-side loads, and address these issues. To develop an optimal operation strategy considering interactions among source-network-load-storage in an ADN has become a problem with extensive concerns, and is the subject of this work. The objective is to minimize the total operating cost and the variance of the load curve for a given time period. Then, the well-established NSGA-II algorithm is employed to solve the developed multiple-objective optimization model. Furthermore, the entropy weight method is utilized to weight each term in the objective function, so as to avoid the involvement of the subjective preferences of decision-makers. Case studies are employed to demonstrate the proposed method, and it is shown by simulation results that the attained optimal scheduling strategies can enhance the scheduling flexibility of the ADN by coordinated interactions among source-network-load-storage, and hence the total operating cost and the fluctuation of the load curve are reduced.