Abstract
For the uncertainty of wind power and load, a reserve risk index is defined from minimum of load loss and maximum of utilizing wind power. Then, the index is introduced into optimizing for active power dispatch. Considering three indexes which consist of fuel cost, pollutant emission amount and the reserve risk index, a multi-objective optimization model for active power dispatch in power system with wind farms is established. For better solving model, an improved multi-objective differential evolution algorithm is proposed. This algorithm contains chaos initialization strategy, parameter adaptive strategy, dynamic non-dominated sorting strategy introduced to enhance the global searching ability. With the Pareto solution set, the entropy-based TOPSIS (technique for order performance by similarity to ideal solution) is adopted to sort the optimal solution set for the final scheme. The results and data analysis demonstrates the model is reasonable and the algorithm is valuable.
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Acknowledgements
This work was sponsored in part by National Natural Science Foundation of China (No. 51507100), and in part by Shanghai Sailing Program (No. 15YF1404600), and in part by the “Chen Guang” project supported by the Shanghai Municipal Education Commission and Shanghai Education Development Foundation (No. 14CG55).
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Xia, S., Xu, Y., Ge, X. (2017). An Improved Multi-objective Differential Evolution Algorithm for Active Power Dispatch in Power System with Wind Farms. In: Li, K., Xue, Y., Cui, S., Niu, Q., Yang, Z., Luk, P. (eds) Advanced Computational Methods in Energy, Power, Electric Vehicles, and Their Integration. ICSEE LSMS 2017 2017. Communications in Computer and Information Science, vol 763. Springer, Singapore. https://doi.org/10.1007/978-981-10-6364-0_65
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