Fuzzy Modeling of Uncertainties in Generation Scheduling Integrating Wind Farms and Pumped Storage Plants

This paper presents a new approach to the fuzzy generation scheduling (GS) problem, considering reserve requirement, load-generation balance and wind power generation constraints. The modeling of constraints is an important issue in power system scheduling. These constraints are therefore "fuzzy" in nature, and crisp treatment of them may lead to over conservative solutions. In this paper, a fuzzy optimization-based method is developed to solve power system GS problem using fuzzy membership functions (MFs) for objective and some constraints. This fuzzy GS problem is firstly converted to a crisp formulation and then is solved using GAMS software based on mixed integer nonlinear programming (MINLP). This problem is applied to a test system which has pumped storage power plants to modify the uncertainties of wind power output and other parameters in power system. The results of this problem are compared with the results of crisp solution results and in different aspiration values of the total profit. Numerical testing results show that near optimal schedules are obtained, and the method can provide a good balance between increasing profit and satisfying constraints.