A Fuzzy-Optimization Approach for Generation Scheduling With Wind and Solar Energy Systems

This paper presents a fuzzy-optimization approach for solving the generation scheduling problem with consideration of wind and solar energy systems. Wind and solar energy are being considered in the power system to schedule unit power output to minimize the total thermal unit fuel cost. When performing the generation scheduling problem in conventional methods, the hourly load, available water, wind speed, solar radiation must be forecasted to prevent errors. However, actually there are always errors in these forecasted values. A characteristic feature of the proposed fuzzy-optimization approach is that the forecast hourly load, available water, wind speed and solar radiation errors can be taken into account using fuzzy sets. Fuzzy set notations in the hourly load, available water, wind speed, solar radiation, spinning reserve and total fuel cost are developed to obtain the optimal generation schedule under an uncertain environment. To demonstrate the effectiveness of the proposed method, the generation scheduling problem is performed in a simplified generation system. The results show that a proper generating schedule for each unit can be reached using the proposed method.