Research Article

A Novel Framework for Sustainable Hybrid Energy Distribution Network Using Distributed Decision Protocols

Volume: 17 Number: 2 July 15, 2025
TR EN

A Novel Framework for Sustainable Hybrid Energy Distribution Network Using Distributed Decision Protocols

Abstract

Nowadays, population growth and technological advancements are contributing to the growth of global electricity demand. The aim of this research is to form a new distributed decision-making protocol (DDM) to increase the reliability and sustainability of HES. Using this DDM, it is intended to minimize the effects of planned and unplanned production interruptions on the independent and autonomous energy producers within the HES. By implementing this protocol, energy producers in the HES are intended to collaborate and achieve mutual benefits in cases where they are not able to fulfill the needs of their customers. As a case study, there are sixteen independent power plants that are simulated as CN enterprises in four independent communities. The DDM protocol aims to manage the collaboration among independent energy producers, to use the sources of the producers effectively, to increase the profit rates, and to optimize the sustainability of the energy supply for each community. The results demonstrates that the proposed protocol gives satisfying results under the criteria of profit, demand fulfillment rate, sustainability, and resource utilization both for each energy producers and entire HES. Moreover, the increase in collaboration rate within each community increased these parameters by average of 90%.

Keywords

Distributed decision-making , Decentralized optimization , Systems analysis , Hybrid energy systems

References

  1. Ahmad, T., Zhang, D., & Huang, C. (2021). Methodological framework for short-and medium-term energy, solar and wind power forecasting with stochastic-based machine learning approach to monetary and energy policy applications. Energy, 231, 120911. https://doi.org/10.1016/j.energy.2021.120911
  2. Ajidarma, P., Nof, S. Y., Pradana, R. A., Nugroho, W. A., & Halim, A. H. (2022). Preemptive Demand and Capacity Sharing Learning Protocols Using Long Short-Term Memory (LSTM) Neural Network Autoencoders. IFAC-PapersOnLine, 55(10), 1798–1803. https://doi.org/10.1016/j.ifacol.2022.09.659
  3. Al-Abri, A., & Okedu, K. E. (2023). Overview of the Global Electricity System in Oman Considering Energy Demand Model Forecast. Energy Engineering: Journal of the Association of Energy Engineering, 120(2), 409–423. https://doi.org/10.32604/ee.2023.020375
  4. Al-khaykan, A., Al-kharsan, I. H., Ali, M. O., Alrubaie, A. J., Fakhruldeen, H. F., & Counsell, J. M. (2023). Impact of Multi-Year Analysis on the Optimal Sizing and Control Strategy of Hybrid Energy Systems. 1–17.
  5. Bhargava, R., Levalle, R. R., & Nof, S. Y. (2016). A best-matching protocol for order fulfillment in re-configurable supply networks. Computers in Industry, 82, 160–169. https://doi.org/10.1016/j.compind.2016.07.001
  6. Chen, Y., Guo, M., Liu, Y., Wang, D., Zhuang, Z., & Quan, M. (2023). Energy, exergy, and economic analysis of a centralized solar and biogas hybrid heating system for rural areas. Energy Conversion and Management, 276(13), 116591. https://doi.org/10.1016/j.enconman.2022.116591
  7. Cho, H., Goude, Y., Brossat, X., & Yao, Q. (2013). Modeling and forecasting daily electricity load curves: A hybrid approach. Journal of the American Statistical Association, 108(501), 7–21. https://doi.org/10.1080/01621459.2012.722900
  8. Costoya, X., deCastro, M., Carvalho, D., & Gómez-Gesteira, M. (2023). Assessing the complementarity of future hybrid wind and solar photovoltaic energy resources for North America. Renewable and Sustainable Energy Reviews, 173(November 2022). https://doi.org/10.1016/j.rser.2022.113101
  9. Ghofrani, M., & Hosseini, N. N. (2016). Optimizing Hybrid Renewable Energy Systems: A Review. Sustainable Energy - Technological Issues, Applications and Case Studies. https://doi.org/10.5772/65971
  10. Global Futures Report - REN21. (n.d.). Retrieved May 23, 2022, from https://web.archive.org/web/20190724164150/https://www.ren21.net/reports/global-futures-report/
APA
Çağlayan, N., Yılmaz, İ., & Erdebilli, B. (2025). A Novel Framework for Sustainable Hybrid Energy Distribution Network Using Distributed Decision Protocols. International Journal of Engineering Research and Development, 17(2), 349-369. https://doi.org/10.29137/ijerad.1590147