Enhancing Power Grid Resilience Through Energy Storage And Demand Response
Abstract
The resilience of power grids is increasingly essential in the face of climate change, extreme weather events, and the growing complexity of energy systems. To ensure continuous electricity supply during outages and stress events, utilities and grid operators are exploring innovative solutions. This paper examines two key strategies — energy storage systems (ESS) and demand response (DR) — for enhancing grid resilience. Energy storage technologies allow grid operators to store excess electricity during periods of low demand and release it during peak usage or disturbances.
Meanwhile, demand response programs encourage consumers to adjust their energy consumption patterns in response to grid needs, improving operational flexibility and reducing stress on the infrastructure. This paper examines the combined potential of ESS and DR in improving grid stability, mitigating the effects of system failures, and optimising energy usage. We present a framework for integrating both technologies into grid operations and evaluate case studies of successful deployments. Results indicate that combining ESS with DR programs supports immediate grid reliability and contributes to long-term sustainability by reducing operational costs and enhancing system flexibility.Keywords
Full Text:
PDFReferences
1. Hossain, E., Faruque, H. M. R., Sunny, S. H., Mohammad, N., & Nawar, N. (2020). A Comprehensive Review of Energy Storage Systems: Types, Comparison, Current Scenario, Applications, Barriers, Potential Solutions, Policies, and Future Prospects. Energies, MDPI, 13(14), 1-127.
2. Lund, H., Arler, F., Østergaard, P., Hvelplund, F., Connolly, D., Mathiesen, B., & Karnøe, P. (2017). Simulation versus Optimisation: Theoretical Positions in Energy System Modelling. Energies, 10(7), 840. doi: 10.3390/en10070840
3. Erenoğlu, A. K., Sengor, I., & Erdinç, O. (2024). Power System Resiliency: A Comprehensive Overview from Implementation Aspects and Innovative Concepts. Energy Nexus, 15, 100311. doi: 10.1016/j.nexus.2024.100311
4. Mateo, C., Postigo, F., & Sánchez-Miralles, Á. (2020). The impact of distributed energy resources on the networks. In Springer eBooks (pp. 185–200). doi: 10.1007/978-3-030-49428-5_8
5.Garmabdari, R., Moghimi, M., Yang, F., Lu, J., Li, H., & Yang, Z. (2017b). Optimisation of battery energy storage capacity for a grid-tied renewable microgrid. IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia), 1–6. doi: 10.1109/isgt-asia.2017.8378391
6. Ezzat, M., & Dincer, I. (2019). Energy and exergy analyses of a novel ammonia combined power plant operating with gas turbine and solid oxide fuel cell systems. Energy, 194, 116750. doi: 10.1016/j.energy.2019.116750
7. Nojavan, S., & Zare, K. (2020). Demand response application in smart Grids. In Springer eBooks. doi: 10.1007/978-3-030-31399-9
8. Kushawaha, V., Gupta, G., & Singh, L. (2024). Enhancing energy efficiency: Advances in smart grid optimisation. International Journal of Innovative Research in Engineering & Management, 11(2), 100–105. doi: 10.55524/ijirem.2024.11.2.20
9. Amin, S. M., & Wollenberg, B. (2005). Toward a smart grid: power delivery for the 21st century. IEEE Power and Energy Magazine, 3(5), 34–41. doi: 10.1109/mpae.2005.1507024
10. Kumar, M., & Patra, B. (2020). Smart Grid Technologies: A Comprehensive Review. Türk Bilgisayar Ve Matematik Eğitimi Dergisi, 11(3), 2895–2899. doi: 10.61841/turcomat.v11i3.14656
11. Mimica, M., Sinovčić, Z., Jokić, A., & Krajačić, G. (2021). The role of the energy storage and the demand response in the robust reserve and network-constrained joint electricity and reserve market. Electric Power Systems Research, 204, 107716. doi: 10.1016/j.epsr.2021.107716
12. Beveridge, R., & Kern, K. (2013). The Energiewende in Germany: Background, Developments and Future Challenges. Special Issue: Energy Grids And Infrastructure, 4(1), 3-12
13. Giarola, S., Molar-Cruz, A., Vaillancourt, K., Bahn, O., Sarmiento, L., Hawkes, A., & Brown, M. (2021). The role of energy storage in the uptake of renewable energy: A model comparison approach. Energy Policy, 151, 112159. doi: 10.1016/j.enpol.2021.112159
14. Deng, R., Yang, Z., Chow, M., & Chen, J. (2015). A survey on Demand Response in Smart Grids: Mathematical Models and Approaches. IEEE Transactions on Industrial Informatics, 11(3), 570–582. doi: 10.1109/tii.2015.2414719
Article Metrics
Metrics powered by PLOS ALM
Refbacks
- There are currently no refbacks.
Copyright (c) 2025 Oluwafemi Tayo Ojo, Muhammad Bolakale Salman, Ijeoma Lilian Agbanusi, Chinedu Hilary Azubuike, Tosin Gideo Olaleye, Ayodele Oyesanya, Joshua Adenrele Ajiboye

This work is licensed under a Creative Commons Attribution 4.0 International License.



