Short-term load forecasting for anomalous days based on fuzzy multi-objective genetic optimization algorithm

Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering

Volumn 25, Issue 10, 2005, Pages 29-34

  Feng, Li ^a   Qiu, Jia Ju ^a  

^a ZHEJIANG UNIVERSITY   (China)

Author keywords

Association rule mining; Electric power engineering; Fuzzy rule based classifier; Load forecasting; Multi objective genetic algorithm; Power system

Indexed keywords

ARTIFICIAL INTELLIGENCE; CLASSIFIERS; DATA MINING; ELECTRIC POWER SYSTEMS; FUZZY SETS; GENETIC ALGORITHMS; OPTIMIZATION;

ASSOCIATION RULE MINING; ELECTRIC POWER ENGINEERING; FUZZY RULE-BASED CLASSIFIER; MULTI-OBJECTIVE GENETIC ALGORITHM; PATTERN CLASSIFICATION;

ELECTRIC LOAD FORECASTING;

EID: 21444439136     PISSN: 02588013     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Article

References (18)

1. Chow T W S, Leung, C T. Neural network based short-term load forecasting using weather compensation[J]. IEEE Trans. On PWRS, 1996, 11(4): 1736-1742.
2. Xie Kaigui, Li Chunyan, Zhou Jiaqi, Research of the combination orecasting model for load based on artificial neural network[J]. Proceedings of the CSEE, 2002, 22(7): 85-89.
3. Kwang Ho Kim, Hyoung Sun Youn, Yong Cheol Kang. Short-term load forecasting for special days in anomalous load conditions using neural networks and fuzzy inference method[J]. IEEE Transactions on Power Systems, 2000, 15(2): 559-566.
4. Gianfranco Chicco, Roberto Napoli, Federico Piglione. Load pattern clustering for short-term load forecasting of anomalous days[C]. IEEE Porto Power Tech. Conference, Porto, Portugal. 10th-13th September 2001, 15(3): 12-15.
5. Lamedica R, Prudenzi A, Sforna M. A neural network based technique for short-term forecasting of anomalous load periods[J]. IEEE Transactions on Power Systems, 1996, 11(4): 1749-1756.
6. Chen Yaowu, Wang Leyu, Long Hongyu. Short-term load forecasting with modular neural networks[J]. Proceedings of the CSEE, 2001, 21(4): 79-82.
7. Wang Jianyuan, Ji Yanchao. Application of fuzzy petri nets knowledge representation in electric power transformer fault diagnosis[J]. Proceedings of the CSEE, 2003, 23(1): 121-125.
8. Zhang Jianhua, Hou Guolian, Zhang Wei et al. A research on fuzzy rules and genetic algorism based method for a condenser fault diagnosis[J]. Proceedings of the CSEE, 2004, 24(4): 205-209.
9. Chen Laijiu, Shen Jiong, Liu Zhiyuan et al. A study on fuzzy rules based and nonlinear models for thermal processes[J]. Proceedings of the CSEE, 2002, 22(11): 132-137.
10. Nakashima T, Nakai G, Ishibuchi H. A fuzzy rule-based system for ensembling classification systems[C]. In: Proceedings of IEEE International Conference on Fuzzy systems, 2002: 1432-1437.
11. Carlos M Fonseca, Peter J Fleming. An overview of evolutionary algorithms in multiobjective optimization[J]. Evolutionary Computation, 1995, 3(1): 1-16.
12. Wang Yuhuai, Wu Jianhua, Yang Shiyou et al. An improved genetic algorithm for vector optimization and its application to design optimizations of electromagnetic devices[J]. Proceedings of the CSEE, 2004, 24(7): 215-218.
13. Schaffer J D. Multiple objective optimization with vector evaluated genetic algorithms[C]. In: Proceedings of the 1st International Conference on Genetic Algorithms, 1985: 93-100.
14. Fonseca C M, Fleming P J. Genetic algorithm for multiobjective: formulation, discussion and generalization[C]. In Proceedings of the 5th International Conference on Genetic Algorithms, 1993: 416-423.
15. Shi Libao, Xu Guoyu. A self-adaptive evolutionary programming algorithm of multi-objective fuzzy optimal operation[J]. Proceedings of the CSEE, 2001, 21(3): 31-36.
16. Li Shenqing, Zhu Yingjie, Zhou Youqing, Peng Yulou et al. Optimal design of passive power filters based on interaction multi-modal genetic algorithm[J]. Transactions of China Electrotechnical Society, 2003, 18(6): 1-6.
17. Deb K, Pratap A, Agarwal S et al. A fast and elitist multiobjective genetic algorithm: NSGA-II[J]. IEEE Transactions on Evolutionary Computation, 2002, 6(2): 182-197.