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Short-term load forecast is an essential part of electric power system planning and operation. Forecasted values of system load affect the decisions made for unit commitment and security assessment, which have a direct impact on operational costs and system security. Conventional regression methods are used by most power companies for load forecasting. However, due to the nonlinear relationship between...
Neural network can increase forecasting accuracy of power system load , but canpsilat provide explanation for forecast reason, so this paper proposes a short-period load forecasting method based on structural neural network. The paper respectively set up such models as historical load data forecasting model, weather forecasting model and date type model. First three models are respectively learned...
The authors present a new approach to power load forecasting under abnormal weather conditions using artificial neural networks (ANN). Accurate forecasting for cold fronts and warm fronts is of special importance to utility companies for monetary reasons and planning reasons. Temperatures below 50 degrees F are treated as cold fronts and temperatures above 90 degrees F are treated as warm fronts in...
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