Sub-transmission substation expansion planning considering load center uncertainties of size and location

With regards to power consumption increase and emerging new distribution loads over the past years, substation expansion planning (SEP) is certainly an essential. However, uncertainty always causes inadequacy in long term planning. Therefore, bringing this matter under control is necessary. In this article, a new sub-transmission SEP approach is presented, in which both location and size of the horizon year load centers are formulated and considered in planning problem. In the proposed method, Genetic Algorithm (GA) is applied in order to scan all the uncertain probabilistic location area and size of loads. In each iteration, a mathematical clustering problem is solved and the results, containing size and location of possible new substations together with their needed investment costs, are recorded. The ultimate needed expansion requirements are calculated through a mathematical procedure depending on occurrence probability. Finally, a test system and afterwards a real system data are taken to show the performance of the proposed method.