Joint Optimization between Power Sources and Transmission Expansion Planning Considering Integration of Large Scale Wind Power


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Abstract


Renewable energy sources such as wind power have been rapidly developed worldwide. However, due to the intermittence of wind power, the large scale exploitation and grid integration of wind power have imposed many challenges in planning of both power sources and transmission expansion. To maximize the penetration of wind power in the transmission system, it not only needs to have enough transmission capacity which can be achieved from the transmission expansion, but also optimal power source configuration. Therefore, there is a requirement for joint optimization method that can achieve simultaneously both optimal power source configuration with peak regulation capacity and optimal transmission planning, in order to reduce the total cost for the integration of large wind power. In this context, this paper mainly focuses on the development of optimization method with joint considering both power source configuration and transmission expansion requirement. A complicated nonlinear mixed integer planning model is proposed for this problem and Benders Decomposition technique together with QPSO algorithm is used to solve this model. The proposed method and model are applied to both a modified IEEE 39-bus test system and an actual power system in China. The results show that the method and model are correct and effective.
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Keywords


Wind Power; Power Sources; Transmission Expansion Planning; Joint Planning; Non-Linear Mixed Integer Planning Model; Benders Decomposition; QPSO Algorithm

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References


Perez PS, Van Hertem D, Driesen J, Belmans R. Wind power in the European Union: grid connection and regulatory issues[C]. Power Systems Conference and Exposition, IEEE PES, 2006.

Zhang Jian-hua, Xu Xiao-kang, Feltes JW. Development and planning of wind power in China[C]. Power and Energy Society General Meeting, 2010 IEEE.

Richard Piwk, Dale Osborn. Wind energy delivery issues[J]. IEEE Power & Energy Magazine, 2005, 3(6): 47-56.

Zhang Xin-song, Yuan Yue, Wu Bo-weng, et al. A Novel Algorithm for Power System Planning Associated with Large-scale Wind Farms in Deregulated Environment. Electric Utility Deregulation and Restructuring and Power Technologies (DRPT), 2011 4th International Conference. P1613-1617.

Zhang Qian, Wang Zhi-wei, Xie Zhen-jian, et al. 10000MW Wind Power in Jiangsu Power System in 2020. Electricity Distribution (CICED), 2010 China International Conference. P1-5.

Yu Han, Chung C-Y, Wong K-P, et al. A chance constrained transmission network expansion planning method associated with load and wind farm variations[J]. Automation of Electric Power Systems, 2009, 33(2): 20- 24.

Mosayebian, M.E., Monsef, H., Reliability evaluation in power system integrated with wind power, (2010) International Review on Modelling and Simulations (IREMOS), 3 (3), pp. 368-372.

Gao Ci-wei, He Yeo. Transmission planning considering the integration of wind energy[J]. Electric Power Science and Technology, 2009, 24(4): 19-24(in Chinese).

Lu Bing. Static Voltage Stability Study on Planning Method Research of Transmission Network with Wind Farms [D]. Hangzhou: Zhejiang University, 201 O(in Chinese).

Yu Yi-xin, Zhou Jin-hui, Qin Chao. Value-based Evaluation of Power System Planning Alternatives with Large-Scale Wind Power [J]. Journal of Tianjin University, 2011, 44(11): 941-947 (in Chinese).

Zhou Tian-rui, Wang Xu, Zhang Qian, et al. Empirical research on impact of large-scale wind power on Jiangsu power system planningb[J]. ELECTRIC POWER, 2010, 43(2): 11-15(in Chinese).

Omidvar, M., Haghifam, M.R., Somayeh Mousavi, B., A novel wind farm modeling to improve reliability assessment of power system, (2011) International Review on Modelling and Simulations (IREMOS), 4 (4), pp. 1791-1798.

Yuan Yue, Wu Bo-wen, Li Zhen-jie, et al. Flexible planning of transmission system with large wind farm based on multi-scenario probabilityb[J]. Electric Power Automation Equipment, 2009, 29(10): 8-12(in Chinese).

Zhou Jin-hui, Yu Yi-xin, Zeng Yuan. Heuristic Optimization Algorithm for Transmission Network Expansion Planning with Large-scale Wind Power Integration. Automation of Electric Power Systems, 2011, 35(22): 66-70 (in Chinese).

Zeng Ming, Lv Chun-quan, Qiu Liu-qing, et al. A Demand-Side Response-Based Transmission Planning Model With Grid- Connected Wind Farms[J]. Power System Technology, 2011, 35(4): 129-134(in Chinese).

Billinton R, Wangdee W. Reliability-based transmission reinforcement planning associated with large scale wind farms [J]. IEEE Trans on Power Systems, 2007, 22(1): 34-41.

Porrua, F., Chabar, R., Thome, L.M., et al. Incorporating Large-Scale Renewable to the Transmission Grid: Technical and Regulatory Issues. Power & Energy Society General Meeting, 2009. PES '09. IEEE. 2009, Pl-7.

Henderson, M., Coste, W., Platts, J .. ISO New England Wind Integration Studies and the New England Governor's Renewable Energy Blueprint. Power and Energy Society General Meeting, 2010 IEEE. PI-9.

Wang Xi-fan. Power system optimization and planning. Beijing: Hydraulic and Electric Power Press, 1990(in Chinese).

R. Karki, P. Hu, and R. Billinton, “Adequacy Criteria and Methods for Wind Power Transmission Planning,” IEEE Power & Ener. Soci. Gene. Meet. , pp. 1-7, July 26-30 2009.

Alguacil N, Motto A L, Conejo AJ. Transmission expansion planning: a mixed-integer LP approach [J]. IEEE Transactions on Power Systems, 2003, 18(3): 1070 – 1077.

Aghaei, J., Roosta, A., Akbari, M. A., Rabiee, A. and Gitizadeh, M. (2012), Reliability constrained multi-period generation expansion planning of electrical energy resources using MILP. Euro. Trans. Electr. Power. doi: 10.1002/etep.1632

Ding Ming, Wu Yichun. Optimal Expansion Planning of Wind-Diesel Energy System[C]. International Conference on Power System Technology, 2006.

Ji Xingquan, Wang Chengshan. Transmission dynamic expansion considering demand elasticity [J]. Proceedings of the CSEE, 2002, 22(11): 23-27.

Romero R, Monticelli AA. Hierarchical decomposition approach for transmission network expansion planning [J].IEEE Transaction on Power Systems, 1994, 9(1): 373-380.

M. Shahidehpour, H. Yamin, and Z. Li, Market Operations in Electric Power Systems: Forecasting, Scheduling and Risk Management.New York: Wiley, 2002.

Khodr, H. M., Martínez-Crespo, J., Vale, Z. A. and Ramos, C. (2010), Optimal methodology for distribution systems reconfiguration based on OPF and solved by decomposition technique. Euro. Trans. Electr. Power, 20: 730–746. doi: 10.1002/etep.353

Ciornei, I. and Kyriakides, E. (2012), Recent methodologies and approaches for the economic dispatch of generation in power systems. Euro. Trans. Electr. Power. doi: 10.1002/etep.1635

Ongsakul, W., Dechanupaprittha, S. and Ngamroo, I. (2004), Constrained economic dispatch by deterministic tabu search approach. Euro. Trans. Electr. Power, 14: 377–391. doi: 10.1002/etep.31

Annakkage U D, Numnonda T, Pahalawaththa N C. Unit commitment by Parallel simulated annealing Generation[J]. IEE Proceedings Generation, Transmission & Distribution, 1995, 142(6): 595-600

Walsh M P, Omalley M J. Augmented Hopfield network for unit commitment and economic dispatch[J]. IEEE Transactions on Power systems, 1997.12(4):1765-1774

Keles A, Etaner-Uyar A S, Turkey B. A differential evolution approach for the unit commitment Problem[C]. 5th International Conference on Electrical and Electronics Engineering, Bursa, 2007: 132-135

Yang H, Yang P, Huang C. A Parallel genetic algorithm approach to solving the unit commitment Problem: implementation on the transporter networks[J]. IEEE Transactions on power systems, 1997, 12(2):661-665

Amjady, N. and Shirzadi, A. (2009), Unit commitment using a new integer coded genetic algorithm. Euro. Trans. Electr. Power, 19: 1161–1176. doi: 10.1002/etep.297

J. Sun, B. Feng, W.B. Xu. Particle swarm optimization with particles having quantum behavior[C]. IEEE Congress on Evolutionary Computation, USA, 2004:325-331.

Sun J, Xu W B. A global search strategy of quantum-behaved particle swarm optimization[C]. Proceedings of IEEE Conference on Cybernetics and Intelligent Systems, 2004:111-116.

Kenndy J, Eberhart R. Particle swarm optimization[C]. Proceedings of IEEE International Conference on Neural Networks Perth: IEEE Press, 1995: 1942-1948.

Niknam, T., Mojarrad, H. D. and Meymand, H. Z. (2011), A new particle swarm optimization for non-convex economic dispatch. Euro. Trans. Electr. Power, 21: 656–679. doi: 10.1002/etep.468

Zhang P-X. multi-objective evolutionary algorithm and Its application in power system[D].Wuhan: Huazhong University of Science and Technology , 2004.


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