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Warianty tytułu
Ekonomiczny rozsył energii w zintegrowanym z energetyką wiatrową rynkiem metodą symulowanego wyżarzania
Języki publikacji
Abstrakty
This paper proposes simulated annealing (SA) algorithm to solve the bid based dynamic economic dispatch (BBDED) problem with wind energy integration to study the performance and the economic benefit of wind energy integration in a deregulated electricity market. The proposed method is tested for convergence, robustness, and efficiency applied on a 10-unit test system with 12-period load demand. The results obtained are compared with other relevant methods, considering different constraints like power balance, generation limits, and ramp rate limits.
Zaproponowano algorytm symulowanego wyżarzania problemu bazującego na ofercie ekonomicznego rozsyłu energii. Rozważano przypadek dołączonej do systemu energii wiatrowej i nieregulowanego rynku energii. Analizowano niezawodność i skuteczność na przykładzie systemu z 10 jednostkami.
Wydawca
Czasopismo
Rocznik
Tom
Strony
55--60
Opis fizyczny
Bibliogr. 22 poz., rys., tab.
Twórcy
autor
- Department of Electrical Engineering, IRECOM Laboratory, Faculty of Electrical Engineering, University of Djillali Liabes, Sidi Bel Abbes, Algeria
Bibliografia
- [1] Chinmoy, L., Iniyan, S. , Goic, R., Modeling wind power investments, policies and social benefits for deregulated electricity market–A review, Applied energy, 242 (2019), No. 1, 364-377
- [2] Aliabadi, D. E., Kaya, M., & Şahin, G. , An agentbased simulation of power generation company behavior in electricity markets under different market-clearing mechanisms, Energy Policy, 100 (2017), No. 1, 191-205
- [3] Salehizadeh, M. R., Soltaniyan, S., Application of fuzzy Q-learning for electricity market modeling by considering renewable power penetration, Renewable, and Sustainable Energy Reviews, 56 (2016), No. 1, 1172-1181
- [4] Zhao, Z., Yuan, S. , Nie, Q., Guo, W., Continuous Reinforcement Algorithm and Robust Economic Dispatching- Based Spot Electricity Market Modeling considering Strategic Behaviors of Wind Power Producers and Other Participants Journal of Electrical and Computer Engineering, (2019), 1-16
- [5] Benhamida, F., Bendaoud, A., Medles, K. , Tilmat ine, A. , Dynamic economic dispatch solution with practical constraints using a recurrent neural network, Przegląd Elektrotechniczny, 87 (2011), No. 8, 149-153
- [6] Adefarati , T. , Bansal , R.C. , Integration of renewable distributed generators into the distribution system: a review, IET Renewable Power Generation, 10 (2016), No. 7, 873-884
- [7] Ma, Y., Hao, Y. , Zhao, S., Bi, H., Security constrained economic dispatch of wind-integrated power system considering optimal system state selection, IET Generation, Transmission & Distribution, 11 (2017), No. 1, 27-36
- [8] Geetha, K., Deve, V.S. Keerthivasan, K . , Design of economic dispatch model for Gencos with thermal and wind powered generators, International Journal of Electrical Power & Energy Systems, 68 (2015), 222-232
- [9] Liao, G.C. , Integrated isolation niche and immune genetic algorithm for solving bid-based dynamic economic dispatch, International Journal of Electrical Power & Energy Systems, 42 (2012), No. 1, 264-275
- [10] Salhi , Y., Benhamida, F. , Ziane, I . Graa, A. , The Dynamic Economic Load Dispatch in Electricity Market using Genetic Algorithm, Electrotehnica, Electronica, Automatica (EEA), 65 (2017), No. 2, 54-59
- [11] Lin, W. M., Chen, S. J., Bid-based dynamic economic dispatch with an efficient interior point algorithm, International journal of electrical power & energy systems, 24 (2002), No. 1, 51-57
- [12] Zhao, B., Guo, C., Cao, Y., Dynamic economic dispatch in electricity market using particle swarm optimization algorithm, In IEEE Fifth World Congress on Intelligent Control and Automation, China, 5050-5054
- [13] Santosa, B. Rusdiansyah, A. , Cost analysis of an electricity supply chain using modification of price based dynamic economic dispatch in wheeling transaction scheme, Materials Science and Engineering, 337 (2018), No. 1, 012009
- [14] Maamri, M., Bouzeboudja, H., Tandjaoui, M. N. , The use of Grey Wolf Optimizer (GWO) for solving the economic dispatch problems based on renewable energy in Algeria a case study of “Naama Site”, Przegląd Elektrotechniczny, 95 (2019), No. 6, 32-39
- [15] Ziane, I., Benhamida, F. Graa, A., Renewable Energy Impact in the Environmental/Economic Dispatch using Simulated Annealing Algorithm, Electrotehnica, Electronica, Automatica (EEA), 64 (2016), No. 2, 177-182
- [16] Metropolis, N., Rosenbluth, A., Rosenbluth, M., Teller, A., Teller, E., Simulated annealing, Journal of Chemical Physics, 21 (1953), No. 1087, 14
- [17] Kirkpatrick, S., Gelatt , C.D. Vecchi, M.P., Optimization by simulated annealing, Science, 220 (1983), No. 4598, 671-680
- [18] Takeang, C., Aurasopon, A., Multiple of hybrid lambda iteration and simulated annealing algorithm to solve economic dispatch problem with ramp rate limit and prohibited operating zones, Journal of Electrical Engineering & Technology, 14 (2019), No. 1, 111-120
- [19] Ziane, I ., Benhamida, F., Graa, A., Simulated annealing algorithm for combined economic and emission power dispatch using max/max price penalty factor, Neural Computing and Applications, 28 (2017), No. 1, 1197-205
- [20] Orike, S. , Corne, D. , An evolutionary algorithm for bidbased dynamic economic load dispatch in a deregulated electricity market, In IEEE 2013 13th UK Workshop on Computational Intelligence (UKCI), 50 (2013), 313-320
- [21] Mohammedi, R. D., Mosbah, M., Kouzou, A., Multiobjective optimal scheduling for Adrar power system including wind power generation, Electrotehnica, Electronica, Automatica (EEA), 66 (2002), No. 4, 102
- [22] Souag, S. , Benhamida, F . , A dynamic power system economic dispatch enhancement by wind integration considering ramping constraint-application to Algerian power system, International Journal of Renewable Energy Research (IJRER), 5 (2002), No. 3, 794-805
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-bff8f9c3-d059-4fbf-945b-b9395f3f81c3