Application of Combination Forecast Model in the Medium and Long term Power Load Forecast
The gain of SVC depends upon the type of reactive power load for optimum performance. As the load and input wind power conditions are variable, the gain setting of SVC needs to be adjusted or tuned. In this paper, an ANN based approach has been used to tune the gained parameters of the SVC controller over a wide range of load characteristics. The multi-layer feed-forward ANN tool with the error back-propagation training method is employed. Loads have been taken as the function of voltage. Analytical techniques have mostly been based on impedance load reduced network models, which suffer from several disadvantages, including inadequate load representation and lack of structural integrity. The ability of ANNs to spontaneously learn from examples, reason over inexact and fuzzy data and provide adequate and quick responses to new information not previously stored in memory has generated high performance dynamical system with unprecedented robustness. ANNs models have been developed for different hybrid power system configurations for tuning the proportional-integral controller for SVC. Transient responses of different autonomous configurations show that SVC controller with its gained tuned by the ANNs which provide optimum system performance for a variety of loads.
Keywords: Power Load, Combination Forecasts, Moving Average, Gray Model, Linear Regression Model
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ABOUT THE AUTHORS
Ke Zhao
Ke Zhao received the degree in Software Engineering from Nanjing University of Aeronautics and Astronautics, in 2006. he is an Associate Professor at Nanchang Hangkong University, His research interests include FACTS, Power System Dynamics and Predictive Control.
Lin Gan
College of Information Engineering, Nanchang Hangkong University, Nan Chang, Jiangxi, China
Hong Wang
College of Information Engineering, Nanchang Hangkong University, Nan Chang, Jiangxi, China
Ai Hua Ye
College of Information Engineering, Nanchang Hangkong University, Nan Chang, Jiangxi, China
Ke Zhao
Ke Zhao received the degree in Software Engineering from Nanjing University of Aeronautics and Astronautics, in 2006. he is an Associate Professor at Nanchang Hangkong University, His research interests include FACTS, Power System Dynamics and Predictive Control.
Lin Gan
College of Information Engineering, Nanchang Hangkong University, Nan Chang, Jiangxi, China
Hong Wang
College of Information Engineering, Nanchang Hangkong University, Nan Chang, Jiangxi, China
Ai Hua Ye
College of Information Engineering, Nanchang Hangkong University, Nan Chang, Jiangxi, China
