Considering power quality in expansion planning of distribution systems

The aim of expansion planning in distribution systems is to identify a strategy of expansion of a given system in a specified timeframe, taking info account the load growth. To find the optimal strategy, different optimization techniques can be used. In this paper, a strategy for dynamic planning is presented, which divides the overall time horizon into sub-intervals and performs multi-objective optimization for each sub-interval by using the nondominated sorting genetic algorithm (NSGA). The lowest-cost transition between two optimal solutions is then found by using the ant colony search (ACS) algorithm. Power quality and reliability are included in the planning, by considering the expected number of dips/year and the expected number of interruptions/year as objectives, next to the total cost. It is shown that the proposed strategy leads to significant savings compared to a static approach, where the system is designed for the load expected at the end of the time horizon.