MULTI-OBJECTIVE MODELING OF ROBUST MULTI-STAGE FEEDER ROUTING PROBLEM WITH CONSIDERING UNCERTAINTIES

In regard to widespread impacts of uncertainties in power system planning and operation, some strategies must be devised to incorporate the uncertainties in power system modeling, therefore achieving the best possible strategy. The most important uncertainties in long-term disfribution network planning are due to errors in forecasting of load demand and market price. This paper presents a stochastic multistage expansion planning method to consider the forecasting errors, pseudo dynamic behavior of the network parameters and geographical constraints. In this paper, the optimal routes of MV feeders as the backbone of distribution networks are obtained for both mid and long-term cases with probabilistic modeling. To enhance the accountability of the power system and improve system performance parameters simultaneously to the best possible condition, multi-objective functions are proposed and solved using NSGA II (Non-Dominated Sorting Genetic Algorithm). The employed objectives contain all economic, environmental and technical aspects of disfribution network e.g. cost of Feeders installations, active and reactive power losses cost, cost of purchased power from power market, Reliability cost, Voltage Stability enhancements, Minimization of Voltage Deviation and Emission reduction. One of the most important advantages of the proposed multi-objective formulation is obtaining non-dominated solutions and allowing system operator to exercise personal preference in selecting each of those solutions based on the system operating conditions and the costs. To validate the effectiveness of the proposed scheme, the simulations are carried out on a relatively large-scale distribution network.