eISSN: 3087-4300 editor@aimjournals.com
All Journals
Submit your article

International Journal of Renewable, Green, and Sustainable Energy

Open Access Peer Review International
Open Access

STOCHASTIC MULTI-OBJECTIVE DISPATCH OPTIMIZATION AND DECISION-MAKING FOR INTEGRATED ELECTRIC AND THERMAL ENERGY SYSTEMS

DOI https://doi.org/10.55640/ijrgse-v02i06-02
PDF
Dr. Jonas Müller 1 , Dr. Fabian Keller 1 ,
4 Institute of Power Systems and Power Economics, RWTH Aachen University, Aachen, Germany
4 Chair of Energy Management and Sustainability, University of Stuttgart,Stuttgart, Germany

Abstract

This research presents a stochastic multi-objective optimization framework for the dispatch and decision-making processes in integrated electric and thermal energy systems (IETES). The approach considers uncertainties in renewable energy generation, load demands, and market prices to ensure reliable and efficient energy management. A multi-objective evolutionary algorithm is employed to simultaneously minimize operational cost, emission levels, and unmet energy demand. The model integrates both electric and thermal subsystems, including combined heat and power (CHP) units, boilers, and energy storage devices. Pareto-optimal solutions are evaluated using a decision-making tool to identify the best trade-offs among conflicting objectives. The results demonstrate the proposed framework’s robustness under stochastic conditions and its potential to support sustainable and economically viable energy planning in modern smart grids.

Keywords

: Integrated energy systems, stochastic optimization, multi-objective dispatch

References

📄 Zheng, N., Zhang, H., Duan, L., and Wang, Q., “Comprehensive sustainability assessment of a novel solar-driven PEMEC-SOFC-based combined cooling, heating, power, and storage (CCHPS) system based on life cycle method,” Energy 265, 126343 (2023). https://doi.org/10.1016/j.energy.2022.126343.
📄 Liu, L. and Xu, J., “Multi-objective generation scheduling towards grid-connected hydro-solar-wind power system based the coordination of economy, management, society, environment: A case study from China,” Int. J. Electr. Power Energy Syst. 142, 108210 (2022). https://doi.org/10.1016/j.ijepes.2022.108210.
📄 Sun, J., Li, M., Zhang, Z., Xu, T., He, J., Wang, H., and Li, G., “Renewable energy transmission by HVDC across the continent: System challenges and opportunities,” CSEE J. Power Energy Syst. 3, 353–364 (2017). https://doi.org/10.17775/CSEEJPES.2017.01200.
📄 Ayesha, Numan, M., Baig, M. F., and Yousif, M., “Reliability evaluation of energy storage systems combined with other grid flexibility options: A review,” J. Energy Storage 63, 107022 (2023). https://doi.org/10.1016/j.est.2023.107022.
📄 Li, K., Wei, X., Yan, Y., and Zhang, C., “Bi-level optimization design strategy for compressed air energy storage of a combined cooling, heating, and power system,” J. Energy Storage 31, 101642 (2020). https://doi.org/10.1016/j.est.2020.101642.
📄 Oskouei, M. Z., Mohammadi-Ivatloo, B., Abapour, M., Shafiee, M., and Anvari-Moghaddam, A., “Privacy-preserving mechanism for collaborative operation of high-renewable power systems and industrial energy hubs,” Appl. Energy 283, 116338 (2021). https://doi.org/10.1016/j.apenergy.2020.116338.
📄 Xiao, Y., Dong, Y., Yang, Q., Yan, X., Qi, J., and Liu, Q., “Analysis of providing spinning reserve from renewable energy sources in renewable generation expansion planning,” in I&CPS Asia & (IEEE, 2022), pp. 497–504. https://doi.org/10.1109/CET.2011.6041489.
📄 Mariuzzo, I., Fioriti, D., Guerrazzi, E., Thomopulos, D., and Raugi, M., “Multi-objective planning method for renewable energy communities with economic, environmental and social goals,” Int. J. Electr. Power Energy Syst. 153, 109331 (2023). https://doi.org/10.1016/j.ijepes.2023.109331.
📄 Zhang, Y., Wu, Q., Ai, Q., and Catalão, J. P. S., “Closed-loop aggregated baseline load estimation using contextual bandit with policy gradient,” IEEE Trans. Smart Grid 13, 243–254 (2022). https://doi.org/10.1109/TSG.2021.3112611.
📄 Liu, J., Chen, J., Yan, G., Chen, W., and Xu, B., “Clustering and dynamic recognition based auto-reservoir neural network: A wait-and-see approach for short-term park power load forecasting,” iScience 26, 107456 (2023). https://doi.org/10.1016/j.isci.2023.107456.
📄 Xue, Y., Zhang, C., Jiang, F., Dou, W., Zhang, H., and Yang, C., “Optimal capacity allocation method of integrated energy system considering renewable energy uncertainty,” Front. Energy Res. 10, 1016756 (2022). https://doi.org/10.3389/fenrg.2022.1016756.
📄 Sun, G., Wang, W., Lu, X., Wu, Y., Hu, W., Yang, Z., and Wei, Z., “Rapid energy flow calculation method for integrated electrical and thermal systems,” Int. J. Electr. Power Energy Syst. 123, 106317 (2020). https://doi.org/10.1016/j.ijepes.2020.106317.
📄 Li, X., Gui, D., Zhao, Z., Li, X., Wu, X., Hua, Y., Guo, P., and Zhong, H., “Operation optimization of electrical-heating integrated energy system based on concentrating solar power plant hybridized with combined heat and power plant,” J. Clean Prod. 289, 125712 (2021). https://doi.org/10.1016/j.jclepro.2020.125712.
📄 Liu, X., Wu, J., Jenkins, N., and Bagdanavicius, A., “Combined analysis of electricity and heat networks,” Appl. Energy 162, 1238–1250 (2016). https://doi.org/10.1016/j.apenergy.2015.01.102.
📄 Babagheibi, M., Sahebi, A., Jadid, S., and Kazemi, A., “An integrated design of heat and power market for energy hubs considering the security constraints of the system,” Sustainable Cities Soc. 96, 104616 (2023). https://doi.org/10.1016/j.scs.2023.104616.
📄 Mu, Y., Chen, W., Yu, X., Jia, H., Hou, K., Wang, C., and Meng, X., “A double-layer planning method for integrated community energy systems with varying energy conversion efficiencies,” Appl. Energy 279, 115700 (2020). https://doi.org/10.1016/j.apenergy.2020.115700.
📄 Li, C., Wang, N., Wang, Z., Dou, X., Zhang, Y., Yang, Z., Maréchal, F., Wang, L., and Yang, Y., “Energy hub-based optimal planning framework for user-level integrated energy systems: Considering synergistic effects under multiple uncertainties,” Appl. Energy 307, 118099 (2022). https://doi.org/10.1016/j.apenergy.2021.118099.
📄 Tan, J., Li, Y., and Zhang, X., “Optimization and trading of district multi-energy system in university community considering carbon emission,” Int. J. Electr. Power Energy Syst. 137, 107450 (2022). https://doi.org/10.1016/j.ijepes.2021.107450.
📄 Shahzad, N. M., Chu, Z., Abdalla, A. N., An, H. K., Eldin, S. M., Metwally, A. S. M., Patrizia, B., and Sufyan, J. M., “Study of an optimized micro-grid's operation with electrical vehicle-based hybridized sustainable algorithm,” Sustainability 14, 16172 (2022). https://doi.org/10.3390/su142316172.
📄 Nazari-Heris, M., Mehdinejad, M., and Mohammadi-Ivatloo, B., “Combined heat and power economic dispatch problem solution by implementation of whale optimization method,” Neural Comput. Appl. 31, 421–436 (2019). https://doi.org/10.1007/s00521-017-3074-9.
📄 Li, J., Fang, J., Zeng, Q., and Chen, Z., “Optimal operation of the integrated electrical and heating systems to accommodate the intermittent renewable sources,” Appl. Energy 167, 244–254 (2016). https://doi.org/10.1016/j.apenergy.2015.10.054.
📄 Li, Y., Miao, S., Yin, B., Yang, W., Zhang, S., Luo, X., and Wang, J., “A real-time dispatch model of CAES with considering the part-load characteristics and the power regulation uncertainty,” Int. J. Electr. Power Energy Syst. 105, 179–190 (2019). https://doi.org/10.1016/j.ijepes.2018.08.024.
📄 Chen, Y., Xu, Y., Li, Z., and Feng, X., “Optimally coordinated dispatch of combined-heat-and-electrical network with demand response,” IET Gener. Transm. Distrib. 13, 2216–2225 (2019). https://doi.org/10.1049/iet-gtd.2018.6992.
📄 Zhang, Y., Meng, F., Wang, R., Kazemtabrizi, B., and Shi, J., “Uncertainty-resistant stochastic MPC approach for optimal operation of CHP microgrid,” Energy 179, 1265–1278 (2019). https://doi.org/10.1016/j.energy.2019.04.151.
📄 Huang, S., Tang, W., Wu, Q., and Li, C., “Network constrained economic dispatch of integrated heat and electricity systems through mixed integer conic programming,” Energy 179, 464–474 (2019). https://doi.org/10.1016/j.energy.2019.05.041.
📄 Lu, S., Gu, W., Zhang, C., Meng, K., and Dong, Z., “Hydraulic-thermal cooperative optimization of integrated energy systems: A convex optimization approach,” IEEE Trans. Smart Grid 11, 4818–4832 (2020). https://doi.org/10.1109/TSG.2020.3003399.
📄 Jiang, Y., Wan, C., Audun, B., Song, Y., and Mohammad, S., “Convex relaxation of combined heat and power dispatch,” IEEE Trans. Power Syst. 36, 1442–1458 (2021). https://doi.org/10.1109/TPWRS.2020.3025070.
📄 Zheng, J., Kou, Y., Li, M., and Wu, Q., “Stochastic optimization of cost-risk for integrated energy system considering wind and solar power correlated,” J. Mod. Power Syst. Clean Energy 7, 1472–1483 (2019). https://doi.org/10.1007/s40565-019-0519-4.
📄 Mobarakeh, S. I., Sadeghi, R., Saghafi, H., and Delshad, M., “Robust management and optimization strategy of energy hub based on uncertainties probability modelling in the presence of demand response programs,” IET Gener. Transm. Distrib. 16, 1166–1188 (2021). https://doi.org/10.1049/gtd2.12358.