A multi-agent-based energy-coordination control system for grid-connected large-scale wind-photovoltaic energy storage power-generation units

Solar Energy

Volumn 107, Issue , 2014, Pages 245-259

  Wu, Kehe ^a   Zhou, Huan ^a  

^a NORTH CHINA ELECTRIC POWER UNIVERSITY   (China)

Author keywords

Contract net protocol; Energy coordination; Particle swarm algorithm; Wind PV energy storage

Indexed keywords

ALGORITHMS; CONTROL SYSTEMS; ECONOMICS; OPTIMIZATION;

BEHAVIOR CHARACTERISTIC; CONTRACT NET PROTOCOLS; COOPERATIVE MECHANISMS; DIFFERENT EQUIPMENT; ENERGY-COORDINATION; OPERATION EFFICIENCIES; OPTIMIZATION ALGORITHMS; PARTICLE SWARM ALGORITHM;

ENERGY STORAGE;

ALGORITHM; ECONOMIC ANALYSIS; ENERGY EFFICIENCY; NUMERICAL MODEL; OPERATIONS TECHNOLOGY; PHOTOVOLTAIC SYSTEM; POWER GENERATION; WIND POWER;

EID: 84903435909     PISSN: 0038092X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.solener.2014.05.012     Document Type: Article

References (28)

1. Askarzadeh A. Developing a discrete harmony search algorithm for size optimization of wind-photovoltaic hybrid energy system. Sol. Energy 2013, 98:190-195.
2. Bayod-Rújula Á.A., Haro-Larrodé M.E., Martínez-Gracia A. Sizing criteria of hybrid photovoltaic-wind systems with battery storage and self-consumption considering interaction with the grid. Sol. Energy 2013, 98:582-591.
3. Campoccia A., Dusonchet L., Telaretti E., Zizzo G. Comparative analysis of different supporting measures for the production of electrical energy by solar PV and wind systems: four representative European cases. Sol. Energy 2009, 83(3):287-297.
4. Chekired F., Mellit A., Kalogirou S.A., et al. Intelligent maximum power point trackers for photovoltaic applications using FPGA chip: a comparative study. Sol. Energy 2014, 101:83-99.
5. da Rosa M.A., Leite da Silva A.M., Miranda V. Multi-agent systems applied to reliability assessment of power systems. Int. J. Electr. Power Energy Syst. 2012, 42(1):367-374.
6. Dimeas A.L., Hatziargyriou N.D. Operation of a multiagent system for microgrid control. IEEE Trans. Power Syst. 2005, 20(3):1447-1455.
7. Ding M., Luo K., Bi R. An energy coordination control strategy for islanded microgrid based on a multi-agent system. Dianli Xitong Zidonghua (Automat. Electr. Power Syst.) 2013, 37(5).
8. Dufo-Lopez R., Bernal-Agustin J.L. Multi-objective design of PV-wind-diesel-hydrogen-battery systems. Renew. Energy 2008, 33(12):2559-2572.
9. Eberhart, R., Kennedy, J., 1995. A new optimizer using particle swarm theory. In: Micro Machine and Human Science. MHS'95, Proceedings of the Sixth International Symposium on IEEE, 1995, pp. 39-43.
10. Golovanov N., Lazaroiu G.C., Roscia M., Zaninelli D. Power quality assessment in small scale renewable energy sources supplying distribution systems. Energies 2013, 6(2):634-645.
11. Java Agent Development Framework. http://www.jade.tilab.com/.
12. Jiang Z. Agent-based power sharing scheme for active hybrid power sources. J. Power Sources 2008, 177(1):231-238.
13. Jun Z., Junfeng L., Jie W., Ngan H.W. A multi-agent solution to energy management in hybrid renewable energy generation system. Renew. Energy 2011, 36(5):1352-1363.
14. Kazem H.A., Khatib T. A novel numerical algorithm for optimal sizing of a photovoltaic/wind/diesel generator/battery microgrid using loss of load probability index. Int. J. Photoenergy 2013.
15. Kremers E., Gonzalez de Durana J., Barambones O. Multi-agent modeling for the simulation of a simple smart microgrid. Energy Convers. Manage. 2013, 75:643-650.
16. Lagorse J., Simões M.G., Miraoui A. A multiagent fuzzy-logic-based energy management of hybrid systems. IEEE Trans. Ind. Appl. 2009, 45(6):2123-2129.
17. Lagorse J., Paire D., Miraoui A. A multi-agent system for energy management of distributed power sources. Renew. Energy 2010, 35(1):174-182.
18. Li J., Wei W., Xiang J. A simple sizing algorithm for stand-alone PV/wind/battery hybrid microgrids. Energies 2012, 5(12):5307-5323.
19. Logenthiran, T., Srinivasan, D., Wong, D., 2008. Multi-agent coordination for DER in MicroGrid. In: IEEE International Conference on Sustainable Energy Technologies, 2008. ICSET, 2008, pp. 77-82.
20. Logenthiran T., Srinivasan D., Khambadkone A.M. Multi-agent system for energy resource scheduling of integrated microgrids in a distributed system. Electr. Power Syst. Res. 2011, 81(1):138-148.
21. Long Q., Lin J., Sun Z. Agent scheduling model for adaptive dynamic load balancing in agent-based distributed simulations. Simul. Model. Pract. Theory 2011, 19(4):1021-1034.
22. Merei G., Berger C., Sauer D.U. Optimization of an off-grid hybrid PV-wind-diesel system with different battery technologies using genetic algorithm. Sol. Energy 2013, 97:460-473.
23. Mohammadi M., Hosseinian S.H., Gharehpetian G.B. Optimization of hybrid solar energy sources/wind turbine systems integrated to utility grids as microgrid (MG) under pool/bilateral/hybrid electricity market using PSO. Sol. Energy 2012, 86(1):112-125.
24. Pipattanasomporn M., Feroze H., Rahman S. Securing critical loads in a PV-based microgrid with a multi-agent system. Renew. Energy 2012, 39(1):166-174.
25. Roche R., Idoumghar L., Suryanarayanan S., Daggag M., Solacolu C.A., Miraoui A. A flexible and efficient multi-agent gas turbine power plant energy management system with economic and environmental constraints. Appl. Energy 2012.
26. Smith R.G. The contract net protocol: high-level communication and control in a distributed problem solver. IEEE Trans. Comput. 1980, 100(12):1104-1113.
27. Yang H., Lu L., Zhou W. A novel optimization sizing model for hybrid solar-wind power generation system. Sol. Energy 2007, 81(1):76-84.
28. Yang H., Wei Z., Chengzhi L. Optimal design and techno-economic analysis of a hybrid solar-wind power generation system. Appl. Energy 2009, 86(2):163-169.