Fuzzy generation scheduling for a generation company (GenCo) with large scale wind farms

Abstract

Wind power is a promising alternative in power generation because of its tremendous environmental and social benefits. Generation scheduling (GS) is more important in a power system integrating wind farms. Unlike conventional power generation sources, wind power generators supply intermittent power because of uncertainty in resource. This paper presents a fuzzy approach to the generation scheduling problem of a GenCo considering uncertainties in parameters or constraints such as load, reserve and available wind power generation. The modeling of constraints is an important issue in power system scheduling. A fuzzy optimization approach is an approach that can be used to obtain the generation scheduling under an uncertain environment. In this paper, a fuzzy optimization-based method is developed to solve power system GS problem with fuzzy objective and constraints. The crisp formulation of this GS problem is firstly defined and is rearranged by introduction of a membership function of some constraints and objective function. Then, this fuzzy optimization problem is converted to a crisp optimization and solved using GAMS software by mixed integer nonlinear programming. Employing the fuzzy optimization GS, it is expected that in practice a higher profit would be achieved in the operation and cost management of a real power system with large scale wind farms in different level of constraints’ satisfaction. The proposed approach is applied to a sample system (including six conventional units and two wind farms) and the results are compared with the results of crisp solution. This approach is also applied to a larger test case to demonstrate the robustness of this fuzzy optimization method.