Abstract
This paper gives a brief description of current situation of distributed generation system, and points out that microgrid can run in two kinds of operation modes. The key problems which need to be cautiously considered exist in each operation mode are summarized, and advanced artificial intelligence techniques are adopted to solve those problems as effective tools. The application situation and research status of multi-agent system, artificial neural network, genetic algorithm, fuzzy logic in distributed generation system home and abroad are summarized detailedly. The existing problems and solving thoughts of each artificial intelligence technique are analyzed, and developing directions of artificial intelligence applications in distributed generation system in the future are also prospected.
This work is supported by National Natural Science Foundation of China(NSFC) (50777057).
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References
Zhang, H.X., Yan, Q.: Application of Multi-agent Technology in Power System. J. Journal of Chongqing University 29, 53–57 (2006)
Tsuji, T., Hara, R., Oyama, T., Yasuda, K.: Autonomous Decentralized Voltage Profile Control of Super-distributed Energy System Using Multi-agent Technology. J. Electrical Engineering in Japan 164, 43–52 (2008)
Zeng, X.J., Li, K.K., Chan, W.L., Su, S.: Multi-agents Based Protection for Distributed Generation Systems. In: Proceedings of the 2004 IEEE International Conference on Electric Utility Deregulation, Restructuring and Power Technologies, Hong Kong, China, pp. 393–397 (2004)
Wang, S.X., Li, X.J., Xiao, Z.X., Wang, C.S.: Multi-agent Approach for Service Restoration of Distribution System Containing Distributed Generations. J. Automation of Electric Power Systems 31, 61–65 (2007)
Al-Hinai, A., Feliachi, A.: Application of Intelligent Control Agents in Power Systems with Distributed Generators. In: 2004 IEEE PES Power Systems Conference and Exposition, New York, United States, pp. 1514–1519 (2004)
Sinha, A.B., Lahiri, A.K., Chowdhury, R.N., Chowdhury, S., Crossley, S.P., Peter, A.: Setting of Market Clearing Price (MCP) in Microgrid Power Scenario. In: IEEE Power and Energy Society 2008 General Meeting, Pittsburgh, United States, pp. 1–8 (2008)
Pan, L., Su, G.: A New Principle and Control Method of Maximum Power Point Tracing. J. Journal of China Coal Society 33, 956–960 (2008)
Lan, Q.L., Wu, Y.C.: Review of Solar Photovoltaic Intelligent Diagnosis System. J. Journal of Wuhan University of Science and Engineering 21, 23–26 (2008)
Rezaei, N., Haghifam, M.R.: Protection Scheme for a Distribution System with Distributed Generation Using Neural Networks. J. International Journal of Electrical Power and Energy Systems 30, 235–241 (2008)
Bathaee, S.M.T., Abdollahi, M.H.: Fuzzy-neural Controller Design for Stability Enhancement of MicroGrids. In: 42nd International Universities Power Engineering Conference, Brighton, United Kingdom, pp. 562–569 (2007)
Pilo, F., Pisano, G., Soma, G.G.: Neural Implementation of MicroGrid Central Controllers. In: INDIN 2007 Conference Proceedings 5th IEEE International Conference on Industrial Informatics, Brighton, Vienna, Austria, pp. 925–930 (2007)
Hou, H., You, D.H., Yin, X.G., Guan, G.Z.: Application of Artificial Intelligence Technique to Power Quality Control. J. Engineering Journal of Wuhan University 37, 114–118 (2004)
Tang, X.B., Tang, G.Q.: Multi-objective Planning for Distributed Generation in Distribution Network. In: 3rd International Conference on Deregulation and Restructuring and Power Technologies, DRPT 2008, Nanjing, China, pp. 2664–2667 (2008)
Harrison, G.P., Siano, P., Piccolo, A., Wallace, A.R.: Distributed Generation Capacity Evaluation Using Combined Genetic Algorithm and OPF. J. International Journal of Emerging Electric Power Systems 8, 1–7 (2007)
Olamaei, J., Niknam, T., Gharehpetian, G.: Impact of Distributed Generators on Distribution Feeder Reconfiguration. In: 2007 IEEE Lausanne POWERTECH, Proceedings, Lausanne, Switzerland, pp. 1747–1751 (2007)
Ding, M., Bao, M., Wu, H.B.: Economic Dispatching on Distributed Energy Supply System. J. Journal of Electric Power Science and Technology 23, 13–17 (2008)
Chen, H.Y., Chen, J.F., Duan, X.Z.: Reactive Power Optimization in Distribution System With Wind Power Generators. J. Proceedings of the CSEE 28, 40–45 (2008)
Tang, M., Ren, Q., Xia, D.W.: The Maximum Power Point Study of Solar Cell Based on Genetic Algorithm. J. Power Electronics 42, 39–40 (2008)
Marei, M.I., El-Saadany, E.F., Salama, M.M.A.: A Novel Control Algorithm for the DG Interface to Mitigate Power Qality Pblems. J. IEEE Transactions on Power Delivery 19, 1384–1392 (2004)
Yang, J.H., Li, J.H., Wu, J., Yang, J.M.: Fuzzy Adaptive Control of Novel Brushless Doubly2fed Wind Turbine. J. Electric Machines and Control 10, 346–350 (2006)
Wang, Z.G., Ma, Y.T., Yang, Z., Lu, W.: Fuzzy Comprehensive Evaluation Method of Wind Power Generation Unit. J. Acta Energiae Solaris Sinica 25, 177–181 (2004)
Yan, H., Wu, J., Ma, Z.Q., Wu, L.X.: Application of Fuzzy Set Theory to Short-term Load Forecasting in Power system. J. Automation of Electric Power Systems, 67–72 (2000)
Salman, S.K., Wan, Z.G.: Voltage Control of Distribution Network with Distributed/embedded Generation Using Fuzzy Logic-based AVC Relay. In: Conference Proceedings 42nd International Universities Power Engineering Conference, UPEC 2007, Brighton, United Kingdom, pp. 576–579 (2007)
Capizzi, G., Tina, G.: Long-term Operation Optimization of Integrated Generation Systems by Fuzzy Logic-based Management. J. Energy 32, 1047–1054 (2007)
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Weng, G., Zhang, Y., Hu, Y. (2009). Application of Artificial Intelligence Technique in Distributed Generation System. In: Yu, W., He, H., Zhang, N. (eds) Advances in Neural Networks – ISNN 2009. ISNN 2009. Lecture Notes in Computer Science, vol 5552. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01510-6_19
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DOI: https://doi.org/10.1007/978-3-642-01510-6_19
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