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Flexible Demand Management Using District Cooling Systems for Smart Grid Optimization in Saudi Arabia
Subject area: Science,Engineering and Technology · Area of research: District Cooling Systems
DOI: 10.64388/IREV10I2-1722645
Abstract
District cooling systems (DCSs) are often considered efficient alternatives to individually installed air-conditioning, however, their importance for providing flexibility to power systems has not been sufficiently addressed in the planning of hot climates. This review looks at how chilled water and ice storage, predictive control, digital sensing, variable cooling prices, the thermal inertia of buildings and coordination with renewable energy can make DCSs dispatchable demand-side resources for smart-grid optimization in Saudi Arabia. A structured integrative review of 30 peer-reviewed publications published from 2020 to 2025 was conducted, covering technical, economic, environmental, comfort and implementation aspects. Statistical pooling was not carried out as the system scopes and performance indicators vary widely across the studies. The literature shows that operational rescheduling, storage dispatch, model predictive control, and demand-response coordination can both reduce peak electrical demand and lower operating costs while at the same time improving the use of renewable energy. Saudi-specific studies also indicate that cooling demand is very sensitive to the properties of the building envelope, the climate zone, the accuracy of the forecasts, and the indoor set-point policy. The review suggests a layered flexibility architecture that connects buildings, thermal networks, plant equipment, cold storage, digital frameworks, and grid signals. It concludes that when deploying district cooling in Saudi Arabia the priority should be given to interoperable telemetry, dispatch based on forecasts, explicit comfort constraints, time varying incentives, and field validation during periods of extreme heat. District cooling should therefore be regarded not only as an efficient infrastructure but also as a controllable thermal battery capable of helping to balance the grid and assisting with urban decarbonisation.
References
[1] Abd Majid, M.A., Muhammad, M., Hampo, C.C. and Akmar, A.B. (2020) ‘Analysis of a Thermal Energy Storage Tank in a Large District Cooling System: A Case Study’, Processes, 8(9), 1158. Crossref.
[2] Alghool, D.M., Elmekkawy, T.Y., Haouari, M. and Elomri, A. (2020) ‘Optimization of design and operation of solar assisted district cooling systems’, Energy Conversion and Management: X, 6, 100028. Crossref.
[3] Shao, Y.L., Soh, K.Y., Wan, Y.D., Kumja, M., Khin, Z., Islam, M.R. and Chua, K.J. (2020) ‘Simulation and experimental study of thermal storage systems for district cooling system under commercial operating conditions’, Energy, 203, 117781. Crossref.
[4] Anderson, A., Rezaie, B. and Rosen, M.A. (2021) ‘An innovative approach to enhance sustainability of a district cooling system by adjusting cold thermal storage and chiller operation’, Energy, 214, 118949. Crossref.
[5] Mazzoni, S., Sze, J.Y., Nastasi, B., Ooi, S., Desideri, U. and Romagnoli, A. (2021) ‘A techno-economic assessment on the adoption of latent heat thermal energy storage systems for district cooling optimal dispatch & operations’, Applied Energy, 289, 116646. Crossref.
[6] Alaboud, M. and Gadi, M. (2022) ‘Evaluation of Indoor Thermal Environmental Conditions of Residential Buildings in Saudi Arabia’, Energies, 15(5), 1603. Crossref.
[7] Alayed, E., Bensaid, D., O’Hegarty, R. and Kinnane, O. (2022) ‘Thermal mass impact on energy consumption for buildings in hot climates: A novel finite element modelling study comparing building constructions for arid climates in Saudi Arabia’, Energy and Buildings, 271, 112324. Crossref.
[8] Farouk, N., Alotaibi, A.A., Alshahri, A.H. and Almitani, K.H. (2022) ‘Using PCM in buildings to reduce HVAC energy usage taking into account Saudi Arabia climate region’, Journal of Building Engineering, 50, 104073. Crossref.
[9] Hinkelman, K., Wang, J., Zuo, W., Gautier, A., Wetter, M., Fan, C. and Long, N. (2022) ‘Modelica-based modeling and simulation of district cooling systems: A case study’, Applied Energy, 311, 118654. Crossref.
[10] Irshad, K., Zahir, M.H., Shaik, M.S. and Ali, A. (2022) ‘Buildings’ Heating and Cooling Load Prediction for Hot Arid Climates: A Novel Intelligent Data-Driven Approach’, Buildings, 12(10), 1677. Crossref.
[11] Jia, L., Liu, J., Chong, A. and Dai, X. (2022) ‘Deep learning and physics-based modeling for the optimization of ice-based thermal energy systems in cooling plants’, Applied Energy, 322, 119443. Crossref.
[12] Kadam, S.T., Kyriakides, A.S., Khan, M.S., Shehabi, M., Papadopoulos, A.I., Hassan, I., Rahman, M.A. and Seferlis, P. (2022) ‘Thermo-economic and environmental assessment of hybrid vapor compression-absorption refrigeration systems for district cooling’, Energy, 243, 122991. Crossref.
[13] Kim, D., Wang, Z., Brugger, J., Blum, D., Wetter, M., Hong, T. and Piette, M.A. (2022) ‘Site demonstration and performance evaluation of MPC for a large chiller plant with TES for renewable energy integration and grid decarbonization’, Applied Energy, 321, 119343. Crossref.
[14] Neri, M., Guelpa, E. and Verda, V. (2022) ‘Design and connection optimization of a district cooling network: Mixed integer programming and heuristic approach’, Applied Energy, 306, 117994. Crossref.
[15] Souayfane, F., Lima, R.M., Dahrouj, H. and Knio, O. (2022) ‘A weather-clustering and energy-thermal comfort optimization methodology for indoor cooling in subtropical desert climates’, Journal of Building Engineering, 51, 104327. Crossref.
[16] Al-Abduljabbar, A., Al-Mogbel, M., Danish, S.N. and El-Leathy, A. (2023) ‘Insulation Performance of Building Components and Effect on the Cooling Load of Homes in Saudi Arabia’, Sustainability, 15(7), 5685. Crossref.
[17] He, J., Guo, Z. and Li, Y. (2023) ‘Multi-objective optimization of district cooling systems considering cooling load characteristics’, Energy Conversion and Management, 281, 116823. Crossref.
[18] Huang, Z.F., Soh, K.Y., Islam, M.R. and Chua, K.J. (2023) ‘Development of a novel grid-free district cooling system considering blockchain-based demand response management’, Applied Energy, 342, 121152. Crossref.
[19] Khourchid, A.M., Al-Ansari, T.A. and Al-Ghamdi, S.G. (2023) ‘Cooling Energy and Climate Change Nexus in Arid Climate and the Role of Energy Transition’, Buildings, 13(4), 836. Crossref.
[20] Krarti, M., Ybyraiymkul, D., Kum Ja, M., Burhan, M., Chen, Q., Shahzad, M.W. and Ng, K.C. (2023) ‘Energy performance of hybrid evaporative-vapor compression air conditioning systems for Saudi residential building stocks’, Journal of Building Engineering, 69, 106344. Crossref.
[21] Saleem, M.U., Shakir, M., Usman, M.R., Bajwa, M.H.T., Shabbir, N., Shams Ghahfarokhi, P. and Daniel, K. (2023) ‘Integrating Smart Energy Management System with Internet of Things and Cloud Computing for Efficient Demand Side Management in Smart Grids’, Energies, 16, 4835. Crossref.
[22] Tang, H., Yu, J., Geng, Y., Liu, X. and Lin, B. (2023) ‘Optimization of operational strategy for ice thermal energy storage in a district cooling system based on model predictive control’, Journal of Energy Storage, 62, 106872. Crossref.
[23] Zaw, K., Matsuoka, K. and Poh, T.K. (2023) ‘A real-time operational optimization of commercial district cooling systems: A practical application’, Energy and Buildings, 297, 113434. Crossref.
[24] Alqahtani, M., Alshahrani, M., Alaidroos, A. and Fageha, M.K. (2024) ‘Optimal Thermal Diffusivity of Residential Building Envelopes to Improve Cooling Energy Efficiency for Saudi Arabia’s Climate Zones’, Journal of Architectural Engineering, 30(3). Crossref.
[25] Marszal-Pomianowska, A., Motoasca, E., Pothof, I., Felsmann, C., Heiselberg, P., Cadenbach, A., Leusbrock, I., O’Donovan, K., Petersen, S. and Schaffer, M. (2024) ‘Strengths, weaknesses, opportunities and threats of demand response in district heating and cooling systems. From passive customers to valuable assets’, Smart Energy, 14, 100135. Crossref.
[26] Neri, M., Guelpa, E. and Verda, V. (2024a) ‘Trade-off between optimal design and operation in district cooling networks’, Smart Energy, 13, 100127. Crossref.
[27] Neri, M., Guelpa, E., Khor, J.O., Romagnoli, A. and Verda, V. (2024b) ‘Hierarchical model for design and operation optimization of district cooling networks’, Applied Energy, 371, 123667. Crossref.
[28] Zhu, P., Zheng, J.H., Li, Z., Wu, Q.H. and Wang, L. (2024) ‘Optimal operation for district cooling systems coupled with ice storage units based on the per-unit value form’, Energy, 302, 131730. Crossref.
[29] Huang, Z., Wang, X., Chen, W., Islam, M.R. and Chua, K.J. (2025) ‘Empowering deep urban decarbonization through smart and renewable district cooling’, Sustainable Cities and Society, 129, 106488. Crossref.
[30] Wang, T., He, J. and Li, Y. (2025) ‘Cooling demand response-based collaborative optimization on the supply and demand side of district cooling system under extreme heat’, Sustainable Cities and Society, 130, 106550. Crossref.
How to cite this paper
@article{1722645,
author = {Hatel Peera Shaik},
title = {Flexible Demand Management Using District Cooling Systems for Smart Grid Optimization in Saudi Arabia},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {10},
number = {2},
pages = {3571-3583},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1722645.pdf},
abstract = {District cooling systems (DCSs) are often considered efficient alternatives to individually installed air-conditioning, however, their importance for providing flexibility to power systems has not been sufficiently addressed in the planning of hot climates. This review looks at how chilled water and ice storage, predictive control, digital sensing, variable cooling prices, the thermal inertia of buildings and coordination with renewable energy can make DCSs dispatchable demand-side resources for smart-grid optimization in Saudi Arabia. A structured integrative review of 30 peer-reviewed publications published from 2020 to 2025 was conducted, covering technical, economic, environmental, comfort and implementation aspects. Statistical pooling was not carried out as the system scopes and performance indicators vary widely across the studies. The literature shows that operational rescheduling, storage dispatch, model predictive control, and demand-response coordination can both reduce peak electrical demand and lower operating costs while at the same time improving the use of renewable energy. Saudi-specific studies also indicate that cooling demand is very sensitive to the properties of the building envelope, the climate zone, the accuracy of the forecasts, and the indoor set-point policy. The review suggests a layered flexibility architecture that connects buildings, thermal networks, plant equipment, cold storage, digital frameworks, and grid signals. It concludes that when deploying district cooling in Saudi Arabia the priority should be given to interoperable telemetry, dispatch based on forecasts, explicit comfort constraints, time varying incentives, and field validation during periods of extreme heat. District cooling should therefore be regarded not only as an efficient infrastructure but also as a controllable thermal battery capable of helping to balance the grid and assisting with urban decarbonisation.},
month = {August},
doi = {https://doi.org/10.64388/IREV10I2-1722645}
}