Two-Objective Participation of Energy Hubs and Distribution Networks in the Wholesale and Retail Energy Markets Based on Fuzzy Decision
Subject Areas : Electricity marketOmid Kohansal 1 , Mahmoud Zadehbagheri 2 , Mohammadjavad Kiani 3 , Samad Nejatian 4
1 - Department of Electrical Engineering- Yasuj Branch, Islamic Azad University, Yasuj, Iran
2 - Department of Electrical Engineering- Yasuj Branch, Islamic Azad University, Yasuj, Iran
3 - Department of Electrical Engineering- Yasuj Branch, Islamic Azad University, Yasuj, Iran
4 - Department of Electrical Engineering- Yasuj Branch, Islamic Azad University, Yasuj, Iran
Keywords: fuzzy decision, Wholesale and retail markets, Day-ahead energy market, Grid-connected energy hub, private distribution company, Two-objective optimization,
Abstract :
This paper presents the optimal participation of distribution networks and energy hubs in the day-ahead wholesale and retail energy markets. The proposed scheme is a two-objective optimization model. In one objective function, it minimizes the energy cost of electricity, gas, and heating network as private distribution companies in the mentioned markets. In another objective function, it minimizes the energy cost (equal to the difference between selling and purchasing energy) of hubs in the retail market. This scheme is subject to optimal power flow formulation in the mentioned networks, and the operation model of sources and active loads in a hub format. Then, the Pareto optimization based on the weighted functions method according to the fuzzy decision is used to achieve the optimal compromise solution. Finally, by implementing the proposed scheme on a system test, the obtained simulation results confirm the capabilities of the scheme in improving the economy of energy hubs and the economic and operation situation of the mentioned networks.
[1] F. Khalafian, “Robust planning of the islanded hybrid system including renewable and non-renewable sources and stationary and mobile storages”, Journal of Intelligent Procedures in Electrical Technology, vol. 14, no. 53, pp. 15-32, Sept. 2022 (in Persian) (dor: 20.1001.1.23223871.1402.14.53.2.6).
[2] O. Kohansal, M. Zadehbagheri, M.J. Kiani, S. Nejatian, “Participation of grid-connected energy hubs and energy distribution companies in the day-ahead energy wholesale and retail markets constrained to network operation indices”, International Trans. on Electrical Energy Systems, vol. 2022, Article Number: 2463003, Aug. 2022 (doi: 10.1155/2022/2463003).
[3] M. Kazemi, T. Niknam, B. Bahmani-Firouzi, M. Nafar, “Coordinated energy management strategy in scheme of flexible grid-connected hubs participating in energy and reserve markets”, Journal of Intelligent and Fuzzy Systems, vol. 41, no. 2, pp. 4005-4020, May 2021 (doi: 10.3233/JIFS-201284).
[4] M. Enayati, G. Derakhshan, S.M. Hakimi, “Optimal energy scheduling of storage-based residential energy hub considering smart participation of demand side”, Journal of Energy Storage, vol. 49, Article Paper: 104062, May 2022 (doi: 10.1016/j.est.2022.104062).
[5] Y. Zhou, M. Shahidehpour, Z. Wei, G. Sun, S. Chen, “Multistage robust look-ahead unit commitment with probabilistic forecasting in multi-carrier energy systems”, IEEE Trans. on Sustainable Energy, vol. 12, no. 1, pp. 70-82, Jan. 2021 (doi: 10.1109/TSTE.2020.2979925).
[6] H. Zafarani, S.A. Taher, M. Shahidehpour, “Robust operation of a multicarrier energy system considering EVs and CHP units”, Energy, vol. 192, Article Number: 116703, Feb. 2020 (doi: 10.1016/j.energy.2019.116703).
[7] A. Heidari, S.S. Mortazavi, R.C. Bansal, “Stochastic effects of ice storage on improvement of an energy hub optimal operation including demand response and renewable energies”, Applied Energy, vol. 261, Article Number: 14393, March 2020 (doi: 10.1016/j.apenergy.2019.114393).
[8] M.H. Shams, M. Shahabi, M.M. Lakouraj, M.R. Shafie-khah, J.P.S. Catalao, “Adjustable robust optimization approach for two-stage operation of energy hub-based microgrids”, Energy, vol. 222, Article Number: 119894, May 2021 (doi: 10.1016/j.energy.2021.119894).
[9] M. Jalilia, M. Sedighizadeha, A. SheikhiFinib, “Stochastic optimal operation of a microgrid based on energy hub including a solar-powered compressed air energy storage system and an ice storage conditioner”, Journal of Energy Storage, vol. 33, Article Number: 102089, Jan. 2021 (doi: 10.1016/j.est.2020.102089).
[10] M. Zare-Oskouei, B. Mohammadi-Ivatloo, M. Abapour, M. Shafiee, A. Anvari-Moghaddam, “Techno-economic and environmental assessment of the coordinated operation of regional grid-connected energy hubs considering high penetration of wind power”, Journal of Cleaner Production, vol. 280, Article Number: 124275, Jan. 2021 (doi: 10.1016/j.jclepro.2020.124275).
[11] J. Faraji, H. Hashemi-Dezaki, A. Ketabi, “Stochastic operation and scheduling of energy hub considering renewable energy sources uncertainty and N-1 contingency”, Sustainable Cities and Society, vol. 65, Article Number: 102578, Feb.2021 (doi:10.1016/j.scs.2020.102578).
[12] K. Afrashi, B. Bahmani-Firouzi, M. Nafar, “Multicarrier energy system management as mixed integer linear programming”, Iranian Journal of Science and Technology, Transactions of Electrical Engineering, vol. 45, pp. 619–631, June 2021 (doi:10.1007/s40998-020-00373-x).
[13] K. Afrashi, B. Bahmani-Firouzi, M. Nafar, “IGDT-based robust optimization for multicarrier energy system management” , Iranian Journal of Science and Technology, Transactions of Electrical Engineering, vol. 45, pp. 155–169, March 2021(doi:10.1007/s40998-020-00356-y).
[14] A. Dini, S. Pirouzi, M.A. Norouzi, M. Lehtonen, “”, Energy, vol. 188, pp. 1-12, Grid-connected energy hubs in the coordinated multi-energy management based on day-ahead market framework Dec. 2019 (doi: 10.1016/j.energy.2019.116055).
[15] R. Li, W. Wei, S. Mei, Q. Hu and Q. Wu, “Participation of an energy hub in electricity and heat distribution markets: An MPEC approach”, IEEE Trans. on Smart Grid, vol. 10, no. 4, pp. 3641-3653, July 2019 (doi: 10.1109/TSG.2018.2833279).
[16] T. Zhao, X. Pan, S. Yao, C. Ju, L. Li, “Strategic bidding of hybrid AC/DC microgrid embedded energy hubs: A two-stage chance constrained stochastic programming approach”, IEEE Trans. on Sustainable Energy, vol. 11, no. 1, pp. 116-125, Jan. 2020 (doi: 10.1109/TSTE.2018.2884997).
[17] S. Moazeni, A.H. Miragha , B. Defourny, “A risk-averse stochastic dynamic programming approach to energy hub optimal dispatch”, IEEE Trans. on Power Systems, vol. 34, no. 3, pp. 2169-2178, May 2019 (doi: 10.1109/TPWRS.2018.2882549).
[18] M.R. AkbaiZadeh, T. Niknam, A. Kavousi-Fard, “Adaptive robust optimization for the energy management of the grid-connected energy hubs based on hybrid meta-heuristic algorithm”, Energy, vol. 235, Article Number: 12117, Nov. 2021 (doi:10.1016/j.energy.2021.121171).
[19] A. Dini, A.R. Hassankashi, S. Pirouzi, M. Lehtonen, B. Arandian, A.A. Baziar , “A flexible-reliable operation optimization model of the networked energy hubs with distributed generations energy storage systems and demand response”, Energy, vol. 239, Article Number: 121923, Jan. 2022 (doi: 10.1016/j.energy.2021.121923).
[20] S.M.H. Zanjani, H. Shahinzadeh, Z. Pourmirza, E. Kabalci, S.M. Muyeen, M. Benbouzid, “Optimal operation of a residential energy hub in the presence of an electric vehicle using whale optimization algorithm”, Proceeding of the EPDC, pp. 84-89, Tehran, Iran, May 2022 (doi: 10.1109/EPDC56235.2022.9817265).
[21] M. Kafaei, D. Sedighizadeh, M. Sedighizadeh, A.R. Sheikhi Fini, “An IGDT/scenario based stochastic model for an energy hub considering hydrogen energy and electric vehicles: A case study of Qeshm Island, Iran”, International Journal of Electrical Power and Energy Systems, vol. 135, Article Number: 107477, Feb. 2022 (doi: 10.1016/j.ijepes.2021.107477).
[22] S. Wogrin, D.F. Gayme, “Optimizing storage siting, sizing and technology portfolios in transmission-constrained networks”, IEEE Trans. on Power Systems, vol. 30, no. 6, pp. 3304-3313, Nov. 2015 (doi: 10.1109/TPWRS.2014.2379931).
[23] R. Homayoun, B. Bahmani-Firouzi, T. Niknam, “Multi‐objective operation of distributed generations and thermal blocks in microgrids based on energy management system“, IET Generation, Transmission and Distribution, vol. 15, no. 9, pp. 1451-1462, May 2021 (doi: 10.1049/gtd2.12112).
[24] P. Fortenbacher, A. Ulbig , G. Andersson, “Optimal placement and sizing of distributed battery storage in low voltage grids using receding horizon control strategies”, IEEE Trans. on Power Systems, vol. 33, no. 3, pp. 2383-2394, May 2018 (doi: 10.1109/TPWRS.2017.2746261).
[25] H. Kiani, K.L. Hesami, A. Azarhooshang, Pirouzi, S. Safaee, “Adaptive robust operation of the active distribution network including renewable and flexible sources”, Sustainable Energy, Grids and Networks, vol. 26, Article Number: 100476, June 2021 (doi: 10.1016/j.segan.2021.100476).
[26] S. Abrisham, L. Bagherzadeh, S. Pirouzi, M. Norouzi, “A new two-layer model for energy management in the smart distribution network containing flexi-renewable virtual power plant“, Electric Power Systems Research, vol. 194, Article Number: 107085, May 2021 (doi:10.1016/j.epsr.2021.107085).
[27] H. Hamidpour, J. Aghaei, S. Dehghan, S. Pirouzi, T. Niknam, “Integrated resource expansion planning of wind integrated power systems considering demand response programmers“, IET Renewable Power Generation, vol. 13, no. 4, pp. 519-529, Jan. 2019 (doi: 10.1049/iet-rpg.2018.5835).
[28] W. Jakob, C. Blume, “Pareto optimization or cascaded weighted sum: A comparison of concepts”, Algorithms, vol. 7, pp. 166-185, July 2014 (doi: 10.3390/a7010166).
[29] Z. Zhidong, O. Suzuki, N.H. March, “Clifford algebra approach of 3D Ising model”, Advances in Applied Clifford Algebras, vol. 29, no. 1, pp. 1-28, Dec. 2019 (doi:10.1007/s00006-018-0923-2).
[30] S.A. Mirjalili, S.M. Mirjalili, A. Lewis, “Grey wolf optimizer” , Advances in Engineering Software, vol. 69, pp. 46-61, 2014 (doi:10.1016/j.advengsoft.2013.12.007).
[31] K. Sarwagya, P.K. Nayak, S. Ranjan , “Optimal coordination of directional overcurrent relays in complex distribution networks using sine cosine algorithm”, Electric Power Systems Research, vol. 187, Article Number: 106435, Oct. 2020 (doi: 10.1016/j.epsr.2020.106435).
[32] A. Askarzadeh, “A novel metaheuristic method for solving constrained engineering optimization problems: Crow search algorithm (CSA)”, Computers and Structures, vol. 169, pp. 1-12, June 2016 (doi: 10.1016/j.compstruc.2016.03.001).
[33] R. Rani, D. Ramyachitra, “Krill Herd Optimization algorithm for cancer feature selection and random forest technique for classification”, Proceeding of the IEEE/ICSESS, pp. 109-113, Beijing, China, Nov. 2017 (doi: 10.1109/ICSESS.2017.8342875).
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