10.57647/ijeee.2025.1601.02

Integrated Optimization of Energy Storage Systems in a Multi-Energy Hub with Waste Heat Recovery from Modular Multilevel Converter

  1. Department of Power Engineering, ST.C., Islamic Azad University, Tehran, Iran

Received: 2024-09-12

Revised: 2025-02-15

Accepted: 2025-03-31

Published in Issue 2025-03-31

How to Cite

Safavizadeh, S. P., Olamaei, J., & Abedi, S. M. (2025). Integrated Optimization of Energy Storage Systems in a Multi-Energy Hub with Waste Heat Recovery from Modular Multilevel Converter. International Journal of Energy and Environmental Engineering, 16(01). https://doi.org/10.57647/ijeee.2025.1601.02

PDF views: 66

Abstract

This paper presents a novel reliability-constrained optimization framework for the design and sizing of a Multi-Energy Hub (MEH) that integrates Combined Heat and Power (CHP), Electrical Energy Storage Systems (ESS), Thermal Storage Systems (TSS), renewable energy sources, and uniquely waste heat recovery from a Modular Multilevel Converter (MMC). The proposed energy hub model simultaneously meets the electricity and thermal demands of an industrial consumer under real tariff conditions and climate data from Phoenix, Arizona. The key innovation lies in modeling the thermal losses of the MMC as a valuable source of heat recovery, which reduces boiler fuel consumption and operational expenditures (OPEX). The optimization framework employs a Genetic Algorithm (GA) to minimize the total cost, encompassing capital expenditure (CAPEX) and OPEX, while enforcing constraints on energy balance, storage limitations, system capacity, and permissible energy shortage. Two scenarios one with MMC heat recovery and the other without are evaluated for both summer and winter conditions. The results show that incorporating MMC heat recovery reduces total cost by up to 2.3%, mainly due to reduced gas consumption in the boiler. Furthermore, a reliability-based constraint ensures that at least 95% of the energy demand is met, minimizing Energy Not Supplied (ENS) and enhancing system resilience. The proposed method provides a scalable and flexible design tool for next-generation industrial energy systems, particularly in hot climates with highly variable energy demand. Integrating waste heat from power electronics into hybrid energy systems introduces a novel dimension in thermal-electric synergy.

Keywords

  • Multi-Energy Hub,
  • Combined Heat and Power (CHP),
  • Modular Multilevel Converter (MMC),
  • Waste Heat Recovery,
  • Reliability,
  • Genetic Algorithm,
  • Energy Not Supplied (ENS),
  • OPEX/CAPEX Optimization

References

  1. Byeong Chan Oh, Yeong Geon Son, Moses Amoasi Acquah, Sung Yul Kim, A new framework for hierarchical multiobjective energy hub planning considering reliability, Energy, Volume 303, 15 September 2024, 131889. DOI: https://doi.org/10.1016/j.energy.2024.131889
  2. Fangxiu Wang, Weiyong Zheng, Jiemei Zhao, Hadis Forghan, Enhancing efficiency and reliability of multi-energy systems: A hybrid heuristic algorithm for interconnected energy hubs, Electric Power Systems Research, Volume 231, June 2024, 110273. DOI: https://doi.org/10.1016/j.epsr.2024.110273
  3. E. Mokaramian, H. Shayeghi, A. Younesi, M. Shafie-khah, P. Siano, Energy hubs components and operation: State-of-the-art review, Renewable and Sustainable Energy Reviews, Volume 212, April 2025, 115395. DOI: https://doi.org/10.1016/j.rser.2025.115395
  4. Hesameddin Yousefi Khasraghi, Theyab R. Alsenani, Robust energy and carbon trading model for interconnected energy hub centers in active distribution networks, Energy, Volume 321, 15 April 2025, 135303. DOI: https://doi.org/10.1016/j.energy.2025.135303
  5. K. Deb, A. Pratap, S. Agarwal, T. Meyarivan, A fast and elitist multiobjective genetic algorithm: NSGA-II, IEEE Transactions on Evolutionary Computation, vol. 6, no. 2, pp. 182–197, Apr. 2002.
  6. Okinda, V. O., Abungu, N. O., Optimal sizing and operation of a hybrid renewable energy system considering reliability and investment cost, School of Engineering and Technology, 2015. http://ir.mksu.ac.ke/handle/123456780/2103
  7. Islam, R., Rafin, S. M. S. H., Mohammed, O. A., Comprehensive Review of Power Electronic Converters in Electric Vehicle Applications, Forecasting, 2023;5(1):22–80. DOI: https://doi.org/10.3390/forecast5010002
  8. Malekijavan, A., Aslinezhad, M., Zaferani, H., Reliability-based Operation in Energy Hubs with Several Energy Networks, Int J Ind Electron Control Optim. DOI: https://doi.org/10.22111/ieco.2021.36021.1310
  9. Y. Zhou, et al., Optimal Energy Management in Energy Hubs: A Review, Applied Energy, vol. 269, p. 114915, 2020.
  10. B. Wang, C. Zhang, Z. Y. Dong, Interval optimization-based coordination of demand response and battery energy storage system considering SoC management in a microgrid, IEEE Transactions on Sustainable Energy, 2020. DOI: https://doi.org/10.1109/TSTE.2020.2982205
  11. B. Wang, L. Wang, F. Yang, W. Mu, M. Qin, F. Zhang, D. Ma, J. Wang, J. Liu, Air-cooling system optimization for IGBT modules in MMC using embedded O-shaped heat pipes, IEEE Journal of Emerging and Selected Topics in Power Electronics,
  12. vol. 9, no. 4, 2021.
  13. International Renewable Energy Agency (IRENA). Renewable Power Generation Costs in 2019. Abu Dhabi: IRENA, 2020. Available online: https://www.irena.org/publications/2020/Jun/Renewable-Power-Costs-in-2019 (accessed July 2025).
  14. National Renewable Energy Laboratory (NREL). Annual Technology Baseline (ATB): Cost and Performance Data for Power Generation Technologies. Golden, CO: NREL, 2021. Available online: https://atb.nrel.gov/electricity (accessed July 2025)
  15. U.S. Energy Information Administration (EIA). Capital Cost and Performance Characteristics of New Generating Technologies. Washington, DC: EIA, 2022. Available online: https://www.eia.gov/outlooks/aeo/assumptions/pdf/table_8.2.pd f (accessed July 2025).
  16. Davoudi, M., Barmayoon, M. H., Moeini-Aghtaie, M., Multiobjective optimal planning of a residential energy hub based on multi-objective particle swarm optimization algorithm, IET Gener Transm Distrib, 2023. DOI: https://doi.org/10.1049/gtd2.12820
  17. Arizona Public Service (APS). Electric Rate Plan. APS, 2023. Available online: https://www.aps.com (accessed July 2025).
  18. Southwest Gas. Tariff Summary. Southwest Gas Corporation, 2023. Available online: https://www.swgas.com(accessed July 2025).
  19. Bhupender Sharma, Ratna Dahiya, Jayaram Nakka, Effective grid connected power injection scheme using multilevel inverter based hybrid wind solar energy conversion system. DOI: https://doi.org/10.1016/j.epsr.2019.01.044
  20. Mazhar, A. R., Liu, S., Shukla, A., A state of art review on the performance of phase change material based thermal energy storage systems for building applications, Renewable and Sustainable Energy Reviews, vol. 81, part 1, pp. 1169–1195, Jan. 2018. DOI: https://doi.org/10.1016/j.rser.2017.08.019
  21. Dincer, I., Rosen, M. A., Thermal Energy Storage: Systems and Applications, 3rd ed., John Wiley & Sons, 2021. ISBN: 9781119713045
  22. R. Sirohi, A. Singh, A. Tarafdar, N. C. Shahi, Application of genetic algorithm in modelling and optimization of cellulase production, Bioresource Technology, vol. 270, pp. 751-754, Dec. 2018. DOI: https://doi.org/10.1016/j.biortech.2018.09.105