Strength Pareto Evolutionary Algorithm for the Dynamic Economic Emission Dispatch Problem incorporating Wind Farms and Energy Storage Systems
Abstract
Intermittent and stochastic characteristics of wind energy sources cause many challenges for the existing power networks. One of these challenges is the violation of the energy balance constraint due to the high penetration of wind power. The use of Energy Storage Systems (ESS) can facilitate the high penetration of wind power and mitigate the effect of its intermittency. Within this context, ESS incorporate the Dynamic Economic Emission Dispatch (DEED) problem. The problem is formulated as a multi-objective problem and the Strength Pareto Evolutionary Algorithm (SPEA) is used for its resolution. Simulations were carried out on a well-known ten-unit system and the results show the importance of using ESS in reducing the total production cost of electricity and total emissions.
Keywords:
dynamic dispatch, wind energy, energy storage systems, evolutionary algorithmDownloads
References
L. Han, R. Zhang, K. Chen, “A coordinated dispatch method for energy storage power system considering wind power ramp event”, Applied Soft Computing, Vol. 84, Article ID 105732, 2019 DOI: https://doi.org/10.1016/j.asoc.2019.105732
W. Wang, R. Ma, H. Xu, H. Wang, K. Cao, L. Chen, Z. Ren, “Method of energy storage system sizing for wind power generation integration”, IEEE PES Asia-Pacific Power and Energy Engineering Conference, Xi'an, China, October 25-28, 2016 DOI: https://doi.org/10.1109/APPEEC.2016.7779682
J. Wu, Y. Lin, “Economic dispatch including wind power injection”, in: Proceedings of ISES World Congress 2007, Vol. I-V, Springer, 2007 DOI: https://doi.org/10.1007/978-3-540-75997-3_474
F. Benhamida, Y. Salhi, I. Ziane, S. Souag, R. Belhachem, A. Bendaoud, “A PSO algorithm for the economic load dispatch including a renewable wind energy”, 3rd International Conference on Systems and Control, Algiers, Algeria, October 29-31, 2013 DOI: https://doi.org/10.1109/ICoSC.2013.6750992
K. K. Vishwakarma, H. M. Dubey, “Simulated annealing based optimization for solving large scale economic load dispatch problems”, International Journal of Engineering Research & Technology, Vol. 1, No. 3, pp. 1-8, 2012
R. V. Pandi, B. K. Panigrahi, “Dynamic economic load dispatch using hybrid swarm intelligence base harmony search algorithm”, Expert Systems with Applications, Vol. 38, No. 7, pp. 8509-8514, 2011 DOI: https://doi.org/10.1016/j.eswa.2011.01.050
M. Younes, R. L. Kherfene, F. Khodja, “Environmental/economic power dispatch problem/renewable energy using firefly algorithm”, International Conference on Environment, Energy, Ecosystems and Development, Venice, Italy, September 28-30, 2013
P. K. Roy, S. Hazra, “Economic emission dispatch for wind-fossil-fuel-based power system using chemical reaction optimisation”, International Transactions on Electrical Energy Systems, Vol. 25, No. 12, pp. 3248-3274, 2014 DOI: https://doi.org/10.1002/etep.2033
Z. Wang, C. Shen, F. Liu, “A conditional model of wind power forecast errors and its application in scenario generation”, Applied Energy, Vol. 212, pp. 771-785, 2018 DOI: https://doi.org/10.1016/j.apenergy.2017.12.039
L. Han, R. Zhang, X. Wang, Y. Dong, “Multi-time scale rolling economic dispatch for wind/storage power system based on forecast error feature extraction”, Energies, Vol. 11, No. 8, Article ID 2124, 2018 DOI: https://doi.org/10.3390/en11082124
Q. Wang, Y. Guan, J. Wang, “A chance-constrained two-stage stochastic program for unit commitment with uncertain wind power output”, IEEE Transactions on Power Systems, Vol. 27, No. 1, pp. 206-215, 2012 DOI: https://doi.org/10.1109/TPWRS.2011.2159522
M. A. O. Vazquez, D. S. Kirschen, “Estimating the spinning reserve requirements in systems with significant wind power generation penetration”, IEEE Transactions on Power Systems, Vol. 24, No. 1, pp. 114-124, 2009 DOI: https://doi.org/10.1109/TPWRS.2008.2004745
P. Xiong, P. Jirutitijaroen, C. Singh, “A distributionally robust optimization model for unit commitment considering uncertain wind power generation”, IEEE Transactions on Power Systems, Vol. 32, No. 1, pp. 39-49, 2017 DOI: https://doi.org/10.1109/TPWRS.2016.2544795
Y. Hu, Y. Li, M. Xu, L. Zhou, M. Cui, “A chance-constrained economic dispatch model in wind-thermal-energy storage system”, Energies, Vol. 10, No. 3, Article ID 326, 2017 DOI: https://doi.org/10.3390/en10030326
X. Liu, W. Xu, “Economic load dispatch constrained by wind power availability: A here-and-now approach”, IEEE Transactions on Sustainable Energy, Vol. 1, No. 1, pp. 2-9, 2010 DOI: https://doi.org/10.1109/TSTE.2010.2044817
S. Hazra, P. K. Roy, “Quasi-oppositional chemical reaction optimization for combined economic emission dispatch in power system considering wind power uncertainties”, Renewable Energy Focus, Vol. 31, pp. 45-62, 2019 DOI: https://doi.org/10.1016/j.ref.2019.10.005
H. Lan, H. Yin, S. Wen, Y. Y. Hong, D. C. Yu, L. Zhang, “Electrical energy forecasting and optimal allocation of ESS in a hybrid wind-diesel power system”, Applied Sciences, Vol. 7, No. 2, Article ID 155, 2017 DOI: https://doi.org/10.3390/app7020155
M. H. Alham, M. Elshahed, D. K. Ibrahim, E. E. D. A. E. Zahab, “A dynamic economic emission dispatch considering wind power uncertainty incorporating energy storage system and demand side management”, Renewable Energy, Vol. 96, pp. 800-811, 2016 DOI: https://doi.org/10.1016/j.renene.2016.05.012
K. Alqunun, P. A. Crossley, “Rated energy impact of BESS on total operation cost in a microgrid”, International Conference on Smart Energy Grid Engineering, Oshawa, Canada, August 21-24, 2016 DOI: https://doi.org/10.1109/SEGE.2016.7589540
B. Xiao, Y. Zhang, J. Han, D. Liu, M. Wang, G. Yan, “A multi-energy complementary coordinated dispatch method for integrated system of wind-photovoltaic-hydro-thermal-energy storage”, International Transactions on Electrical Energy Systems, Vol. 29, No. 7, Article ID e12005, 2019 DOI: https://doi.org/10.1002/2050-7038.12005
A. Torchani, A. Boudjemline, H. Gasmi, Y. Bouazzi, T. Guesmi, “Dynamic economic/environmental dispatch problem considering prohibited operating zones”, Engineering, Technology & Applied Science Research, Vol. 9, No. 5, pp. 4586-4590, 2019 DOI: https://doi.org/10.48084/etasr.2904
E. Zitzler, L. Thiele, “Multiobjective evolutionary algorithms: A comparative case study and the strength pareto approach”, IEEE Transactions on Evolutionary Computation, Vol. 3, No. 4, pp. 257-271, 1999 DOI: https://doi.org/10.1109/4235.797969
I. Marouani, A. Boudjemline, T. Guesmi, H. H. Abdallah, “A modified artificial bee colony for the nonsmooth dynamic economic/environmental dispatch”, Engineering, Technology & Applied Science Research, Vol. 8, No. 5, pp. 3321-3328, 2018 DOI: https://doi.org/10.48084/etasr.2098
M. Basu, “Dynamic economic emission dispatch using nondominated sorting genetic algorithm-II”, International Journal of Electrical Power & Energy Systems, Vol. 30, No. 2, pp. 140-149, 2008 DOI: https://doi.org/10.1016/j.ijepes.2007.06.009
N. Pandit, A. Tripathi, S. Tapaswi, M. Pandit, “An improved bacterial foraging algorithm for combined static/dynamic environmental economic dispatch”, Applied Soft Computing, Vol. 12, No. 11, pp. 3500–3513, 2012 DOI: https://doi.org/10.1016/j.asoc.2012.06.011
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