Multiple Objective Compromised Method for Power Management in Virtual Power Plants

Energies - Tập 4 Số 4 - Trang 700-716
Jinxia Gong1, Da Xie1, Chuanwen Jiang1, Yanchi Zhang2
1School of Electronic, Information and Electrical Engineering, Shanghai Jiao Tong University, No. 800, Dongchuan Road, Minhang, Shanghai 200240, China
2Department of Automation, East China University of Science and Technology, Shanghai 200237, China

Tóm tắt

In practical optimization, a priority requirement for different objectives of multiple objective optimization problems should be considered. In this paper, the distributed power management of a Virtual Power Plant (VPP) with priority requirement is optimized by the compromised method. The operation optimization model of VPP is formulated as a fuzzy multiple objective optimization problem considering the satisfaction of customers and suppliers, the system stability, the power quality, and costs with operation limitations. The multiple objective optimization algorithm with the compromise of the satisfactory degree and the priority of objectives is studied based on the principle of two-step interactive satisfactory optimization. This method is also applied in a test system.

Từ khóa


Tài liệu tham khảo

Bignucolo, F., Caldon, R., Prandoni, V., Spelta, S., and Vezzola, M. (2006, January 6–8). The Voltage Control on MV Distribution Networks with Aggregated DG Units (VPP). Proceedings of the 41st International Universities Power Engineering Conference, Newcastle-Upon-Tyne, UK.

Provoost, F., Myrzik, J.M.A., and Kling, W.L. (2006, January 6–8). Optimizing LV Voltage Profile by Intelligent MV Control in Autonomously Controlled Networks. Proceedings of the 41st International Universities Power Engineering Conference, Newcastle-Upon-Tyne, UK.

Pudjianto, 2007, Virtual power plant and system integration of distributed energy resources, IET Renew. Power Gener., 1, 10, 10.1049/iet-rpg:20060023

Bakari, K.E., and Kling, W.L. (2010, January 10–13). Virtual Power Plants: An Answer to Increasing Distributed Generation. Proceedings of Innovative Smart Grid Technologies Conference Europe, Gotheburg, Sweden.

Lukovic, S., Kaitovic, I., Mura, M., and Bondi, U. (2010, January 5–8). Virtual Power Plant as a Bridge between Distributed Energy Resources and Smart Grid. Proceedings of 43rd Hawaii International Conference on System Sciences, Koloa, Kauai, HI, USA.

EI Bakari, K., Myrzik, J.M.A., and Kling, W.L. (2009, January 1–4). Prospects of a Virtual Power Plant to Control a Cluster of Distributed Generation and Renewable Energy Sources. Proceedings of the 44th International Universities Power Engineering Conference, Glasgow, Scotland.

Braun, M. (2009, January 8–11). Virtual Power Plant Functionalities Demonstrations in a Large Laboratory for Distributed Energy Resources. Proceedings of 20th International Conference and Exhibition on Electricity Distribution—Part 1, Prague, Czech Republic.

Salmani, M.A., Anzalchi, A., and Salmani, S. (2010, January 24–26). Virtual Power Plant: New Solution for Managing Distributed Generations in Decentralized Power Systems. Proceedings of International Conference on Management and Service Science, Wuhan, China.

Caldon, R., Patria, A.R., and Turri, R. (2004, January 6–8). Optimisation Algorithm for a Virtual Power Plant Operation. Proceedings of 39th International Universities Power Engineering Conference, Bristol, UK.

Salmani, M.A., Tafreshi, S.M.M., and Salmani, H. (2009, January 28–30). Operation Optimization for a Virtual Power Plant. Proceedings of IEEE PES/IAS Conference on Sustainable Alternative Energy, Valencia, Spain.

Aggelogiannaki, 2007, A simulated annealing algorithm for prioritized multi-objective optimization-implementation in an adaptive model predictive control configuration, IEEE Trans. Syst. Man Cybern., 4, 902, 10.1109/TSMCB.2007.896015

A, 2005, A distribution company energy acquisition market model with integration of distributed generation and load curtailment options, IEEE Trans. Power Syst., 4, 1718

Miettinnen, K. (1999). Nonlinear Multiobjective Optimization, Kluwer.

Tiwari, 1986, Priority structure in fuzzy goal programming, Fuzzy Sets Syst., 19, 251, 10.1016/0165-0114(86)90054-0

Tao, Y., Lv, X.Q., Han, S.J., Yang, W.L., and Zhang, X. (2007, January 24–27). Symmetrical Fuzzy Collaborative Optimization Using Satisficing and Sufficiency Degree Model. Proceedings of 4th International Conference on Fuzzy Systems and Knowledge Discovery, Hainan, China.

Chen, 2001, Fuzzy goal programming with different importance and priorities, Eur. J. Oper. Res., 133, 548, 10.1016/S0377-2217(00)00201-0

Li, 2007, Two-step interactive satisfactory method for fuzzy multiple objective optimization with preemptive priorities, IEEE Trans. Fuzzy Syst., 15, 417, 10.1109/TFUZZ.2006.887463

Musio, M., Lombardi, P., and Damiano, A. (2010, January 6–8). Vehicles to Grid (V2G) Concept Applied to a Virtual Power Plant Structure. Proceedings of XIX International Conference on Electrical Machines (ICEM), Rome, Italy.

Cerda, 2005, A distribution company energy acquisition market model with integration of distributed generation and load curtailment options, IEEE Trans. Power Syst., 20, 1718, 10.1109/TPWRS.2005.857284

Bolsens, 2007, A voltage and frequency droop control method for parallel inverters, IEEE Trans. Power Electron., 22, 1107, 10.1109/TPEL.2007.900456

Ruiz, 2009, A direct load control model for virtual power plant management, IEEE Trans. Power Electron., 24, 959

Majumder, 2010, Power management and power flow control with back-to-back converters in a utility connected microgrid, IEEE Trans. Power Electron., 25, 821

Teng, 2003, A direct approach for distribution system load flow solutions, IEEE Trans. Power Deliv., 18, 882, 10.1109/TPWRD.2003.813818

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Energies

Tập 4 Số 4

700-716

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