|
Microgrid power scheduling considering the risk of power supply from renewable units in the presence of electric vehicles
|
Mahdi Tourani *   |
| university of Birjnad |
|
|
Abstract: (304 Views) |
Microgrids are a new concept in electrical systems that can independently supply electricity and heat (CHP) to their residents. These microgrids are capable of integrating renewable energy units with a probabilistic nature, which creates significant challenges for them. This paper addresses the timing of microgrid production, considering the risk of power supply from renewable units in the presence of electric vehicles. The aim of this study is to reduce the risk of power outage using electric vehicles, increase microgrid independence and stability, and intelligently distribute power with minimal environmental and economic costs. To this end, a probabilistic model structure is first introduced, and then the optimization problem on this model is simulated using three optimization algorithms: Gray Wolf Optimization (GWO), Firefly Algorithm (FA), and Particle Swarm Optimization (PSO). Ultimately, microgrid indices such as microgrid independence and stability, Risk level, power distribution index, and optimal environmental and economic costs are calculated. By simulating the proposed problem, in addition to reducing the risk of power outages using electric vehicles, the objectives of the problem are optimized. |
|
| Keywords: Microgrid independence, intelligent power distribution, electric vehicles, reducing gas emissions, reducing production risk, system stability |
|
|
Full-Text [PDF 939 kb]
(71 Downloads)
|
Type of Study: Research |
Received: 2024/04/27 | Accepted: 2025/04/19 | Published: 2025/05/14
|
|
|
|
|
|
|
| References |
1. [1]. S. Chandak, P. K. Rout, "The implementation framework of a microgrid: A review," International Journal of Energy Research, 45(3): 1-25, 2020. [ DOI:10.1002/er.6064] 2. [2]. M. Tasto-veliz, P. Arevalo, F. Jurado, "A comprehensive electrical-gas-hydrogen Microgrid model for energy management applications," Energy Conversion and Management, 228: 1-13, 2021. [ DOI:10.1016/j.enconman.2020.113726] 3. [3]. S. AL-Ismail, "DC Microgrid Planning, Operation, and Control: A Comprehensive Review," IEEE Access, 9: 36154- 36172, 2021. [ DOI:10.1109/ACCESS.2021.3062840] 4. [4]. SK. A.Shezan, "Feasibility analysis of an islanded hybrid wind-diesel-battery microgrid with voltage and power response for offshore Islands," Journal of Cleaner Production 288, 2021. [ DOI:10.1016/j.jclepro.2020.125568] 5. [5]. C. Huang, H. Zhang, Y. Song, L. Wang, T. Ahmad, X. Luo, "Demand response for industrial micro-grid considering photovoltaic power uncertainty and battery operational cost," IEEE Transactions on Smart Grid, Early Access, 2021. [ DOI:10.1109/TSG.2021.3052515] 6. [6]. X. Wen, D. Abbes, B. Francois, "Modeling of photovoltaic power uncertainties for impact analysis on generation scheduling and cost of an urban micro grid," Mathematics and Computers in Simulation, 183: 116-128, 2021. [ DOI:10.1016/j.matcom.2020.02.023] 7. [7]. . M. Gaber and R. A. Ibrahim, "Data-Driven Optimal Generation Scheduling Applying Uncertainty in Microgrid,", 8th International Conference on Green Energy and Applications (ICGEA), Singapore, 2024. [ DOI:10.1109/ICGEA60749.2024.10561113] 8. [8]. T. Hai, M.Aksoy, A. Rezvani, "Optimal energy management and scheduling of a microgrid considering hydrogen storage and PEMFC with uncertainties",International Journal of Hydrogen Energy, Vol. 88, 2024. [ DOI:10.1016/j.ijhydene.2024.09.140] 9. [9]. V. Dinesh Kumar, S. Siva Subramanian, V. Tamilselvan," An efficient day-ahead cost-based generation scheduling of a multi-supply microgrid using a balancing composite motion optimization (BCMO) approach", Solar Energy, Vol. 269, 2024. [ DOI:10.1016/j.solener.2023.112261] 10. [10]. A. S. Alghamdi," Microgrid energy management and scheduling utilizing energy storage and exchange incorporating improved gradient-based optimizer, Journal of Energy Storage," Vol. 97, 2024 [ DOI:10.1016/j.est.2024.112775] 11. [11]. Wang, Z. Zhang, O. Abedinia, S. Gholami-Farkoush, "Modeling and analysis of a microgrid considering the uncertainty in renewable energy resources, energy storage systems and demand management in electrical retail market," Journal of Energy Storage, 33, 2021. [ DOI:10.1016/j.est.2020.102111] 12. [12]. M. N. Acosta, F. Gonzalez-Longatt, D. Topic, M. A. Andrade, "Optimal Microgrid-Interactive Reactive Power Management for Day-Ahead Operation," Energies, 14: 1-20, 2021. [ DOI:10.3390/en14051275] 13. [13]. J. Jithendranath, D. Das, "Multi-Objective Optimal Power Flow in Islanded Microgrids with Solar PV Generation by NLTV-MOPSO," IETE Journal of Research; Taylor and & Francis, 2021. [ DOI:10.1080/03772063.2021.1886609] 14. [14]. J. Arkhangelski, M. Abdou-Tankari, G. Lefebvre, "Day-Ahead Optimal Power Flow for Efficient Energy Management of Urban Microgrid," IEEE Transactions on Industry Applications, 57(2): 1285-1293, 2021. [ DOI:10.1109/TIA.2020.3049117] 15. [15]. H. Fattahi, H. Abdi, F. Khosravi1, S. Karimi, "Numerical and Analytical Solution of Probabilistic Optimal Power Flow Problems Considering Renewable Energy Resources Uncertainty," Computational Intelligence in Electrical Engineering, 10(2): 49-72, 2019. 16. [16]. P. P. Biswas, P.N. Suganthan, G. A. J. Amaratunga, " Optimal power flow solutions incorporating stochastic wind and solar power," Energy Conversion and Management, 148: 1134-1207,2017. [ DOI:10.1016/j.enconman.2017.06.071] 17. [17]. K. S. P. Kumar, S. Gaddada, "Statistical scrutiny of Weibull parameters for wind energy potential appraisal in the area of northern Ethiopia," Renewables: Wind, Water, and Solar, 2:1-15, 2015. [ DOI:10.1186/s40807-015-0014-0] 18. [18]. M. Aien, M. Rashidinejad, M. Fotuhi Firuz-Abad," Probabilistic optimal power flow in correlated hybrid wind-PV power systems: A review and a new approach," Renewable and Sustainable Energy Reviews, Vol. 41, 2015. [ DOI:10.1016/j.rser.2014.09.012] 19. [19]. V. Vita, "Development of a Decision-Making Algorithm for the Optimum Size and Placement of Distributed Generation Units in Distribution Networks," Energies, 10:1-13, 2017 [ DOI:10.3390/en10091433] |
|
tourani M. Microgrid power scheduling considering the risk of power supply from renewable units in the presence of electric vehicles. ieijqp 2025; 14 (1) :9-18 URL: http://ieijqp.ir/article-1-995-en.html
|
