Energy Management in Microgrids Using Compensators, Energy Storage Systems, Demand Response, and Integration of Renewable Energies

Subject Areas : Electrical and Computer Engineering

Hamid  Hematian ¹ (Department of Electrical Engineering, Semnan Branch, Islamic Azad University, Semnan, Iran)
Mohammad  Tolou Akari ² (Department of Electrical Engineering, Semnan Branch, Islamic Azad University, Semnan, Iran)
Meysam  AmirAhmadi ³ (Department of Electrical Engineering, Semnan Branch, Islamic Azad University, Semnan, Iran)
Mahmoud  Samiei Moghaddam ⁴ (Department of Electrical Engineering, Damghan Branch, Islamic Azad University, Damghan, Iran)
Majid  Babaeinik ⁵ (Department of Electrical Engineering, Semnan Branch, Islamic Azad University, Semnan, Iran)

Received: 2024-03-24 Accepted : 2024-06-28 Published : 2025-06-20

Keywords: Microgrid, Battery, Demand side management, Renewable energy sources,

Abstract :

This article examines the challenges of energy management in microgrids, considering the uncertainties associated with renewable energy sources, dynamic demand, and the presence of various devices such as batteries, distributed generation sources, and electric vehicles. The article introduces a complex optimization model designed for microgrid operations. This model focuses on mitigating the challenges of integrating power electronic generation units, managing demand within microgrids, and incorporating small-scale renewable energy sources. The goal of this model is to minimize various costs associated with energy losses, electricity purchases, load reduction, distributed generation operations, and battery costs over a 24-hour period. Simulations conducted on a test system demonstrate that the proposed model is effective, achieving up to a 20% reduction in microgrid operational costs. This approach provides an effective framework for enhancing the flexibility and efficiency of microgrid energy management, and the findings indicate that it outperforms comparative methods by a margin of at least 8%, demonstrating its effectiveness in improving critical indices in the microgrid system.

References:

[1] V. Gali, P. K. Jamwal, N. Gupta, A. Kumar, “An adaptive dynamic power management approach for enhancing operation of microgrid with grid ancillary services,” Renewable Energy, Volume 219, Part 1, 119413, 2023.
[2] F. N. Budiman, M. A.M. Ramli, H. R.E.H. Bouchekara, A. H. Milyani, “Optimal scheduling of a microgrid with power quality constraints based on demand side management under grid-connected and islanding operations,” International Journal of Electrical Power & Energy Systems, Volume 155, Part B, 109650, 2024.
[3] V. Shahbazbegian, M. Shafie-khah, H. Laaksonen, G. Strbac, H. Ameli, “Resilience-oriented operation of microgrids in the presence of power-to-hydrogen systems,” Applied Energy, Volume 348, 121429, 2023.
[4] X. Chen, J. Zhai, Y. Jiang, C. Ni, S. Wang, P. Nimmegeers, “Decentralized coordination between active distribution network and multi-microgrids through a fast decentralized adjustable robust operation framework,” Sustainable Energy, Grids and Networks, Volume 34, 101068, 2023.
[5] Özge Erol, Ümmühan Başaran Filik, “A Stackelberg game-based dynamic pricing and robust optimization strategy for microgrid operations,” International Journal of Electrical Power & Energy Systems, Volume 155, Part B, 109574, 2024.
[6] B. Cortés-Caicedo, L. F. Grisales-Noreña, O. D. Montoya, R. I. Bolaños, “Optimization of BESS placement, technology selection, and operation in microgrids for minimizing energy losses and CO2 emissions: A hybrid approach,” Journal of Energy Storage, Volume 73, Part B, 108975, 2023.
[7] Z. Li, B. Zhao, Z. Chen, C. Ni, J. Yan, X. Yan, X. Bian, N. Liu, “Low-carbon operation method of microgrid considering carbon emission quota trading,” Energy Reports, Volume 9, Supplement 2, Pages 379-387, 2023.
[8] M. H. Parvaneh, M. H. Moradi, S. M. Azimi, “The advantages of capacitor bank placement and demand response program execution on the optimal operation of isolated microgrids,” Electric Power Systems Research, Volume 220, 109345, 2023.
[9] Y. Li, X. Zhang, Y. Wang, X. Qiao, S. Jiao, Y. Cao, Y. Xu, M. Shahidehpour, Z. Shan, “Carbon-oriented optimal operation strategy based on Stackelberg game for multiple integrated energy microgrids,” Electric Power Systems Research, Volume 224, 109778, 2023.
[10] Z. Guo, W. Wei, J. Bai, S. Mei, “Long-term operation of isolated microgrids with renewables and hybrid seasonal-battery storage,” Applied Energy, 121628, Volume 349, 2023.
[11] J. Xu, Y. Yi, “Multi-microgrid low-carbon economy operation strategy considering both source and load uncertainty: A Nash bargaining approach,” Energy, Volume 263, Part B, 125712, 2023.
[12] Z. Shi, T. Zhang, Y. Liu, Y. Feng, R. Wang, S. Huang, “Optimal design and operation of islanded multi-microgrid system with distributionally robust optimization,” Electric Power Systems Research, Volume 221, 109437, 2023.
[13] D. Krupenev, N. Komendantova, D. Boyarkin, D. Iakubovskii, “Digital platform of reliability management systems for operation of microgrids,” Energy Reports, Volume 10, Pages 2486-2495, 2023.
[14] Z. Liang, Z. Dong, C. Li, C. Wu and H. Chen, “A Data-Driven Convex Model for Hybrid Microgrid Operation With Bidirectional Converters,” IEEE Transactions on Smart Grid, vol. 14, no. 2, pp. 1313-1316, March 2023.
[15] O. M. Adeyanju, P. Siano and L. N. Canha, “Dedicated Microgrid Planning and Operation Approach for Distribution Network Support With Pumped-Hydro Storage,” IEEE Transactions on Industrial Informatics, vol. 19, no. 7, pp. 8229-8241, July 2023.
[16] L. Tang, E. Shang, X. Chen, L. Li and S. Zou, “Optimization Effect Analysis of ACM-PSO Integrating Individual Adjustment and Cross Operation on Microgrid DG Technology,” IEEE Access, vol. 11, pp. 59954-59967, 2023.
[17] Y. Wang et al., “Optimal Operation Strategy for Multi-Energy Microgrid Participating in Auxiliary Service,” IEEE Transactions on Smart Grid, vol. 14, no. 5, pp. 3523-3534, Sept. 2023.
[18] D. A. Quijano, M. Vahid-Ghavidel, M. S. Javadi, A. Padilha-Feltrin and J. P. S. Catalão, “A Price-Based Strategy to Coordinate Electric Springs for Demand Side Management in Microgrids,” IEEE Transactions on Smart Grid, vol. 14, no. 1, pp. 400-412, Jan. 2023.
[19] G. Abdulnasser, A. Ali, M. F. Shaaban and E. E. M. Mohamed, “Optimizing the Operation and Coordination of Multi-Carrier Energy Systems in Smart Microgrids Using a Stochastic Approach,” IEEE Access, vol. 11, pp. 58470-58490, 2023.
[20] L. Ahmethodžić, M. Musić and S. Huseinbegović, “Microgrid Energy Management: Classification, Review and Challenges,” CSEE Journal of Power and Energy Systems, vol. 9, no. 4, pp. 1425-1438, July 2023.
[21] B. Zeng and L. Zhao, “Solving two-stage robust optimization problems using a column-and-constraint generation method,” Operations Research Letters, vol. 41, pp. 457-461, 2013.
[22] S. Dehghan, N. Amjady, and A. Kazemi, “Two-Stage Robust Generation Expansion Planning: A Mixed Integer Linear Programming Model,” IEEE Transactions on Power Systems, vol. 29, pp. 584-597, 2014.
[23] Y. Guo and C. Zhao, “Islanding-aware robust energy management for microgrids,” IEEE Transactions on Smart Grid, vol. 9, pp. 1301-1309, 2016.
[24] Y. Qu, H. Wang, J. Wu, X. Yang, H. Yin, L. Zhou, “Robust optimization of train timetable and energy efficiency in urban rail transit: A two-stage approach,” Computers & Industrial Engineering, Volume 146, 106594, 2020.
[25] H.J. Kim, M.K. Kim, J.W. 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, Volume 124, 106422, 2021.