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This paper presents a comprehensive study of forecasting a day-ahead of load and locational marginal pricing (LMP) using artificial intelligent systems. An artificial neural network (ANN) is trained with a stochastic optimization technique called particle swarm optimization (PSO). This training algorithm works to adjust the network weights and biases as to minimize the error function. Wavelet transformed...
In daily power markets, forecasting electricity prices and loads is the most essential task and basis for security-constrained unit commitment (SCUC) and risk management. An approach to predict the market behavior is to use the historical prices, loads and other required information to forecast the future prices and loads. This paper forecasts the loads and prices with artificial neural networks (ANN)...
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