Refining the conventional approach toward distribution networks expansion planning in metropolises by using self-adaptive particle swarm optimization

Considering load congestion, rising prices and difficulty in accessing lands suitable for substation constructions, as well as the reduction of liquidity in distribution system companies (Disco) after deregulation, and also significant loss in the low-voltage feeders which consist more than 50 percent of the total loss in the distribution level, lead us to rethink about the conventional methodology for the distribution network planning in the metropolis of Tehran. One of the most popular solutions is to use small transformers to reduce the length of the low voltage feeders in order to decline losses in these parts of the distribution networks. By analogy, in this paper, a new techno-economic method is proposed in order to contend with the aforementioned problems. The effectiveness of the method is evaluated by using several test systems. Self-adaptive PSO is selected as a metaheuristic optimization algorithm due to its high exploration and exploitation nature and fast convergence. Equivalent uniform annual cost is selected as a simple but effective tool so as to split the cost of the initial investment. The objective function is defined to minimize not only the initial investment but also the operation cost, simultaneously.