Collaborative Optimization Planning Method for Distribution Network Considering “Hydropower, Photovoltaic, Storage, and Charging”

Abstract

The high proportion of distributed photovoltaic and electric vehicle access has a great impact on the distribution network. For hydropower-rich areas, the “hydropower, photovoltaic, storage and charging” collaborative planning method can effectively utilize and tap the flexible adjustment potential of small hydropower and energy storage to solve this problem. First, with the goal of optimizing economic cost, charging distance and system carbon emissions, a “hydropower, photovoltaic, storage and charging” distribution network collaborative optimization planning model is established. Secondly, the trip chain method is used to predict the charging demand of electric vehicles. The power output curve of a typical day is obtained using the K-means clustering algorithm and the hierarchical analysis method. The non-dominated sorting genetic algorithms II (NSGA-II) with elite strategy is used to solve the multi-objective model to obtain the Pareto solution set. The optimal ideal solution is used for screening to obtain the optimal planning scheme under different scenarios. Then, a comprehensive evaluation is carried out on the optimal planning schemes of different scenarios. Finally, a case analysis is carried out using the IEEE 33-bus system as an example. The simulation optimization results show that the proposed method can take into account the multi-dimensional evaluation indicators of the planning scheme, including economy, sociality, low carbon and reliability.

Keywords

• “Hydropower
• photovoltaic
• storage and charging,” distribution network planning
• collaborative optimization
• improved NSGA-II