Title :
Distribution Network Reconfiguration Based on Load Forecasting
Author :
Huo, Limin ; Yin, Jinliang ; Yu, Yao ; Zhang, Liguo
Author_Institution :
Dept. of Mech. & Electron. Eng., Agric. Univ. of Hebei, Baoding
Abstract :
Line loss calculation data adopted in the previous distribution network reconfiguration was historical load data or real-time data. And that reduced the realistic significance of distribution network reconfiguration. A new method is presented. At first forecast the load, then apply the load data forecasted to the line loss calculation. By do so the decision can be made in advance that if the distribution network reconfiguration is needed at some time of the future. Load forecasting adopted genetic programming algorithm (GP). Distribution network reconfiguration adopted partheno-genetic algorithm (PGA). And the partheno-genetic algorithm was improved according to the features of the distribution network reconfiguration.
Keywords :
distribution networks; genetic algorithms; load forecasting; decision making; distribution network reconfiguration; line loss calculation data; load forecasting; partheno-genetic programming algorithm; Agricultural engineering; Automation; Computer networks; Data engineering; Distributed computing; Genetic algorithms; Genetic programming; Intelligent networks; Load forecasting; Mathematical model; distribution network reconfiguration; genetic programming algorithm; partheno-genetic algorithm; power system; short-term load forecasting;
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2008 International Conference on
Conference_Location :
Hunan
Print_ISBN :
978-0-7695-3357-5
DOI :
10.1109/ICICTA.2008.206