Fuzzy multiobjective model for distributed generation expansion planning in uncertain environment

Uncertainty is one of the important factors that increase risk of exact decision makings. Although power systems behave more probabilistic today and system risk cannot be avoided completely, it can be evaluated and managed to an acceptable extent in planning, design, and operation activities. This paper presents a fuzzy multiobjective model for distributed generation planning so that uncertainties are modeled using fuzzy numbers (trapezoidal form). The proposed fuzzy model is based on the risk of economic, technical, and environmental objectives as well as fuzzy values of investment and operation cost of DG units due to technology's progress and fuel price fluctuations in the future. This model determines the optimal time, location, size, and type of DG units in distribution networks, using a multiobjective genetic algorithm (NSGA-II). The technologies which are considered in this study are photovoltaic (PV), wind turbine (WT), fuel cell (FC), microturbine (MT), gas turbine (GT), and diesel engine (DE). The proposed model is applied on a typical distribution system (IEEE 37 node test feeder) to assess the efficiency of the approach. Copyright (C) 2010 John Wiley & Sons, Ltd.