Optimal dynamic expansion planning of distribution systems considering non-renewable distributed generation using a new heuristic double-stage optimization solution approach

This paper presents a dynamic (i.e., time-based) model for distribution system expansion planning (DSEP) considering distributed generation. The proposed model optimizes both investment and operation costs of distribution system. It determines the optimal location and size of distributed generators as well as the reinforcement strategy for primary (i.e., medium voltage) distribution feeders along a specified planning horizon. Besides, the dynamic feature of this model enables it to determine the time of each investment. The investment costs consist of installation cost of distributed generators and reinforcement cost of primary distribution feeders. Similarly, the operation costs comprise the cost of energy losses, operation and maintenance cost of the equipment and cost of power purchased from upstream grid (i.e., sub-transmission or transmission grid). The introduced model is solved using a combination of two efficient heuristic methods of Modified Integer-coded Harmony Search (MIHS) to find the optimal expansion scheme and Enhanced Gravitational Search Algorithm (EGSA) to optimize the operation costs. Furthermore, the suggested solution approach also incorporates an efficient mechanism for coding the candidate solutions in MIHS algorithm. The effectiveness of the proposed method and coding mechanism is extensively demonstrated by testing on two radial distribution systems and comparing the obtained results with the results of several other solution techniques.