پیوندهای مفید
آمار
| تعداد نشریات | 8 |
| تعداد شماره‌ها | 425 |
| تعداد مقالات | 5,552 |
| تعداد مشاهده مقاله | 6,620,373 |
| تعداد دریافت فایل اصل مقاله | 5,624,731 |
Optimal Energy Management of Microgrids using Quantum Teaching Learning Based Algorithm | ||
| AUT Journal of Electrical Engineering | ||
| مقاله 8، دوره 55، شماره 2، 2023، صفحه 225-240 اصل مقاله (1.72 M) | ||
| نوع مقاله: Research Article | ||
| شناسه دیجیتال (DOI): 10.22060/eej.2023.21881.5495 | ||
| نویسندگان | ||
| Zahra Esmaeili1؛ Seyed Hamid Hosseini* 2 | ||
| 1Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran | ||
| 2Center of Excellence in Power System Management and Control, Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran | ||
| چکیده | ||
| The most important challenge in microgrids is the coordination of distributed energy resources (DERs), due to the existence of several DERs with fugacious characteristics. In this paper, a robust frame associated with a quantum version of the Teaching-Learning-Based Optimization (quantum TLBO) algorithm is proposed for the first time for the microgrid optimal energy management problem. Uncertainties in the load and the output power of renewable energy sources are modeled using robust optimization (RO). The operation cost of the microgrid is considered as an objective function. The problem is formulated as a bi-level minimum-maximum optimization problem and is solved in two levels iteratively. First, by maximizing the operation cost of the microgrid, the worst case for the uncertain parameters is determined using Particle Swarm Optimization (PSO). Then, according to the results obtained in the first level, by minimizing the operation cost of the microgrid, the final optimal solution is obtained using the Quantum TLBO (QTLBO). This approach is applied to a grid-connected microgrid consisting of renewable energy sources, microturbines, fuel cells, and battery systems. The obtained simulation results demonstrate that the QTLBO is significantly superior to the TLBO, Differential Evolution, and Real-Coded Genetic Algorithm in terms of both achieving the final optimal solution and convergence speed. | ||
| کلیدواژه‌ها | ||
| Optimal energy management؛ Quantum Teaching-Learning-Based Optimization (QTLBO)؛ Robust Optimization (RO)؛ microgrid؛ renewable energy | ||
| مراجع | ||
|
[1] L.P. Raghav, R.S. Kumar, D.K. Raju, A.R. Singh, Optimal Energy Management of Microgrids using Quantum Teaching Learning Based Algorithm, IEEE Transactions on Smart Grid, 12(6) (2021) 4834-4842.
[2] N.-O. Song, J.-H. Lee, H.-M. Kim, Y.H. Im, J.Y. Lee, Optimal energy management of multi-microgrids with sequentially coordinated operations, Energies, 8(8) (2015) 8371-8390.
[3] M. Marzband, F. Azarinejadian, M. Savaghebi, J.M. Guerrero, An optimal energy management system for islanded microgrids based on multiperiod artificial bee colony combined with Markov chain, IEEE Systems Journal 11(3) (2015) 1712-1722.
[4] L. Igualada González, C. Corchero García, M. Cruz Zambrano, F. Heredia, Optimal energy management for a residential microgrid including a vehicle-to-grid system, IEEE transactions on smart grid, 5(4) (2013) 2163-2172.
[5] V. Murty, A. Kumar, Multi-objective energy management in microgrids with hybrid energy sources and battery energy storage systems, Protection Control of Modern Power Systems, 5(1) (2020) 1-20.
[6] T. Shekari, A. Gholami, F. Aminifar, Optimal energy management in multi-carrier microgrids: an MILP approach, Journal of Modern Power Systems Clean Energy, 7(4) (2019) 876-886.
[7] N. Anglani, G. Oriti, M. Colombini, Optimized energy management system to reduce fuel consumption in remote military microgrids, IEEE Transactions on Industry Applications, 53(6) (2017) 5777-5785.
[8] M. Marzband, H. Alavi, S.S. Ghazimirsaeid, H. Uppal, T. Fernando, Optimal energy management system based on stochastic approach for a home Microgrid with integrated responsive load demand and energy storage, Sustainable cities society, 28 (2017) 256-264.
[9] S.E. Ahmadi, N. Rezaei, A new isolated renewable based multi microgrid optimal energy management system considering uncertainty and demand response, International Journal of Electrical Power & Energy Systems, 118 (2020) 105760.
[10] M.S. Taha, H.H. Abdeltawab, Y.A.-R.I. Mohamed, An online energy management system for a grid-connected hybrid energy source, IEEE Journal of Emerging Selected Topics in Power Electronics, 6(4) (2018) 2015-2030.
[11] A. Parisio, E. Rikos, L. Glielmo, Stochastic model predictive control for economic/environmental operation management of microgrids: An experimental case study, Journal of Process Control, 43 (2016) 24-37.
[12] P.P. Vergara, J.C. López, L.C. da Silva, M.J. Rider, Security-constrained optimal energy management system for three-phase residential microgrids, Electric Power Systems Research, 146 (2017) 371-382.
[13] S. Dorahaki, R. Dashti, H.R. Shaker, Optimal energy management in the smart microgrid considering the electrical energy storage system and the demand-side energy efficiency program, Journal of Energy Storage, 28 (2020) 101229.
[14] M. Shamshirband, J. Salehi, F.S. Gazijahani, Decentralized trading of plug-in electric vehicle aggregation agents for optimal energy management of smart renewable penetrated microgrids with the aim of CO2 emission reduction, Journal of Cleaner Production, 200 (2018) 622-640.
[15] N.A. Luu, Q.-T. Tran, S. Bacha, Optimal energy management for an island microgrid by using dynamic programming method, in: 2015 IEEE Eindhoven PowerTech, IEEE, 2015, pp. 1-6.
[16] W. Hu, P. Wang, H.B. Gooi, Toward optimal energy management of microgrids via robust two-stage optimization, IEEE Transactions on smart grid, 9(2) (2016) 1161-1174.
[17] M.I.S.L. Purage, A. Krishnan, E.Y. Foo, H.B. Gooi, Cooperative bidding-based robust optimal energy management of multimicrogrids, IEEE Transactions on Industrial Informatics, 16(9) (2019) 5757-5768.
[18] S. Ganesan, S. Padmanaban, R. Varadarajan, U. Subramaniam, L. Mihet-Popa, Study and analysis of an intelligent microgrid energy management solution with distributed energy sources, Energies, 10(9) (2017) 1419.
[19] S.M. Hosseini, R. Carli, M. Dotoli, Robust optimal energy management of a residential microgrid under uncertainties on demand and renewable power generation, IEEE Transactions on Automation Science and Engineering, 18(2) (2020) 618-637.
[20] L.I. Minchala-Avila, L. Garza-Castanon, Y. Zhang, H.J.A. Ferrer, Optimal energy management for stable operation of an islanded microgrid, IEEE Transactions on Industrial Informatics, 12(4) (2016) 1361-1370.
[21] A. Parisio, L. Glielmo, Energy efficient microgrid management using model predictive control, in: 2011 50th IEEE Conference on Decision and Control and European Control Conference, IEEE, 2011, pp. 5449-5454.
[22] A. Parisio, C. Wiezorek, T. Kyntäjä, J. Elo, K. Strunz, K.H. Johansson, Cooperative MPC-based energy management for networked microgrids, IEEE Transactions on Smart Grid, 8(6) (2017) 3066-3074.
[23] A.M. Dizqah, A. Maheri, K. Busawon, A. Kamjoo, A multivariable optimal energy management strategy for standalone dc microgrids, IEEE transactions on power systems, 30(5) (2014) 2278-2287.
[24] U.B. Tayab, F. Yang, M. El-Hendawi, J. Lu, Energy management system for a grid-connected microgrid with photovoltaic and battery energy storage system, in: 2018 Australian & New Zealand Control Conference (ANZCC), IEEE, 2018, pp. 141-144.
[25] P. Firouzmakan, R.-A. Hooshmand, M. Bornapour, A. Khodabakhshian, A comprehensive stochastic energy management system of micro-CHP units, renewable energy sources and storage systems in microgrids considering demand response programs, Renewable and Sustainable Energy Reviews, 108 (2019) 355-368.
[26] J. Radosavljević, M. Jevtić, D. Klimenta, Energy and operation management of a microgrid using particle swarm optimization, Engineering Optimization, 48(5) (2016) 811-830.
[27] A.T. Eseye, D. Zheng, J. Zhang, D. Wei, Optimal energy management strategy for an isolated industrial microgrid using a modified particle swarm optimization, in: 2016 IEEE international conference on power and renewable energy (ICPRE), IEEE, 2016, pp. 494-498.
[28] H. Li, A.T. Eseye, J. Zhang, D. Zheng, Optimal energy management for industrial microgrids with high-penetration renewables, Protection Control of Modern Power Systems, 2(1) (2017) 1-14.
[29] A. Baziar, A. Kavousi-Fard, Considering uncertainty in the optimal energy management of renewable micro-grids including storage devices, Renewable Energy, 59 (2013) 158-166.
[30] L. Luo, S.S. Abdulkareem, A. Rezvani, M.R. Miveh, S. Samad, N. Aljojo, M. Pazhoohesh, Optimal scheduling of a renewable based microgrid considering photovoltaic system and battery energy storage under uncertainty, Journal of Energy Storage, 28 (2020) 101306.
[31] H. Wu, H. Li, X. Gu, Optimal energy management for microgrids considering uncertainties in renewable energy generation and load demand, Processes, 8(9) (2020) 1086.
[32] E. Shahryari, H. Shayeghi, B. Mohammadi-Ivatloo, M. Moradzadeh, Optimal energy management of microgrid in day-ahead and intra-day markets using a copula-based uncertainty modeling method, Journal of Operation Automation in Power Engineering, 8(2) (2020) 86-96.
[33] B. Papari, C.S. Edrington, I. Bhattacharya, G. Radman, Effective energy management of hybrid AC–DC microgrids with storage devices, IEEE transactions on smart grid, 10(1) (2017) 193-203.
[34] E.E. Elattar, S.K. ElSayed, Probabilistic energy management with emission of renewable micro-grids including storage devices based on efficient salp swarm algorithm, Renewable Energy, 153 (2020) 23-35.
[35] A. Kavousi-Fard, A. Abunasri, A. Zare, R. Hoseinzadeh, Impact of plug-in hybrid electric vehicles charging demand on the optimal energy management of renewable micro-grids, Energy, 78 (2014) 904-915.
[36] R.A. Swief, N.H. El-Amary, M.Z. Kamh, Optimal energy management integrating plug in hybrid vehicle under load and renewable uncertainties, IEEE Access, 8 (2020) 176895-176904.
[37] Z. Bektas, M.O. Kayalıca, G. Kayakutlu, A hybrid heuristic algorithm for optimal energy scheduling of grid-connected micro grids, Energy Systems, (2020) 1-17.
[38] 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 & Distribution, 15(9) (2021) 1451-1462.
[39] H. Vahedi, R. Noroozian, S. Hosseini, Optimal management of MicroGrid using differential evolution approach, in: 2010 7th International Conference on the European Energy Market, IEEE, 2010, pp. 1-6.
[40] N. Tiwari, L. Srivastava, Generation scheduling and micro-grid energy management using differential evolution algorithm, in: 2016 International Conference on Circuit, Power and Computing Technologies (ICCPCT), IEEE, 2016, pp. 1-7.
[41] S. Mandal, K.K. Mandal, Optimal energy management of microgrids under environmental constraints using chaos enhanced differential evolution, Renewable Energy Focus, 34 (2020) 129-141.
[42] A. Shabanpour-Haghighi, A.R. Seifi, Multi-objective operation management of a multi-carrier energy system, Energy, 88 (2015) 430-442.
[43] A. Shabanpour-Haghighi, A.R. Seifi, T. Niknam, A modified teaching–learning based optimization for multi-objective optimal power flow problem, Energy Conversion Management, 77 (2014) 597-607.
[44] D. Yu, T. Zhang, G. He, S. Nojavan, K. Jermsittiparsert, N. Ghadimi, Energy management of wind-PV-storage-grid based large electricity consumer using robust optimization technique, Journal of Energy Storage, 27 (2020) 101054.
[45] S.A. Alavi, A. Ahmadian, M. Aliakbar-Golkar, Optimal probabilistic energy management in a typical micro-grid based-on robust optimization and point estimate method, Energy Conversion and Management, 95 (2015) 314-325.
[46] M. Rastegar, M. Fotuhi-Firuzabad, H. Zareipour, M. Moeini-Aghtaieh, A probabilistic energy management scheme for renewable-based residential energy hubs, IEEE Transactions on Smart Grid, 8(5) (2016) 2217-2227.
[47] J.D. Lara, Robust energy management systems for isolated microgrids under uncertainty, University of Waterloo, 2014.
[48] A. Hussain, V.-H. Bui, H.-M. Kim, Robust optimization-based scheduling of multi-microgrids considering uncertainties, Energies, 9(4) (2016) 278.
[49] E. Kuznetsova, C. Ruiz, Y.-F. Li, E. Zio, Analysis of robust optimization for decentralized microgrid energy management under uncertainty, International Journal of Electrical Power Energy Systems, 64 (2015) 815-832.
[50] H. Kim, M. Kim, J. Lee, A two-stage stochastic p-robust optimal energy trading management in microgrid operation considering uncertainty with hybrid demand response, International Journal of Electrical Power Energy Systems, 124 (2021) 106422.
[51] J.M. Morales, A.J. Conejo, H. Madsen, P. Pinson, M. Zugno, Integrating renewables in electricity markets: operational problems, Springer Science & Business Media, 2013.
[52] R.V. Rao, V.J. Savsani, D. Vakharia, Teaching–learning-based optimization: a novel method for constrained mechanical design optimization problems, Computer-Aided Design, 43(3) (2011) 303-315.
[53] R.V. Rao, Teaching-learning-based optimization algorithm, in: Teaching learning based optimization algorithm, Springer, 2016, pp. 9-39.
[54] Y. Li, M. Tian, G. Liu, C. Peng, L. Jiao, Quantum optimization and quantum learning: A survey, IEEE Access, 8 (2020) 23568-23593.
[55] A.A. Moghaddam, A. Seifi, T. Niknam, M.R.A. Pahlavani, Multi-objective operation management of a renewable MG (micro-grid) with back-up micro-turbine/fuel cell/battery hybrid power source, Energy, 36(11) (2011) 6490-6507.
[56] H. Ranjbar, A. Safdarian, A Robust Model for Daily Operation of Grid-connected Microgrids during Normal Conditions, Scientia Iranica, (2019).
[57] M.H. Amrollahi, S.M.T. Bathaee, Techno-economic optimization of hybrid photovoltaic/wind generation together with energy storage system in a stand-alone micro-grid subjected to demand response, Applied energy, 202 (2017) 66-77.
[58] M. Louzazni, S. Al-Dahidi, M. Mussetta, Fuel Cell Characteristic Curve Approximation Using the Bézier Curve Technique, Sustainability, 12(19) (2020) 8127.
[59] M. Korpaas, A.T. Holen, R. Hildrum, Operation and sizing of energy storage for wind power plants in a market system, International Journal of Electrical Power Energy Systems, 25(8) (2003) 599-606. | ||
|
آمار تعداد مشاهده مقاله: 520 تعداد دریافت فایل اصل مقاله: 568 |
||