Short term load forecasting using evolutionary algorithm for Tajikistan

<p>Load forecasting is a significant element in the energy management system of power systems. Precise load aids electric utilities to conduct decisions unit commitment, reduction spinning reserve capacity, and schedule device maintenance plan. Furthermore, contributes reducing generation cost, it fundamental reliability On other hand, short-term substantial for economic running. The precision directly affects reliability, economy running supplying quality system. Hence, finding required method enhance accuracy valuable precision. This paper proposed particle swarm optimization (PSO) improve working support vector machine (SVM), SVM regression model derived; also derived with PSO. Support (SVM) adopted without PSO based on historical data meteorological Tajikistan country, analysis various factors affecting forecast. be considered are normalized. two parameters significantly influenced model, therefore optimized using evolutionary algorithm.</p>