Abstract
To achieve carbon peaking and carbon neutrality goals, improve energy utilization efficiency, and accelerate the decarbonization of energy structure, this paper proposes a model that integrates Waste Incineration Power Plant (WIP) and Advanced Adiabatic Compressed Air Energy Storage (AA-CAES) to reduce carbon emissions and enhance system economics. First, based on the coupled WIP and Power-to-Gas (P2G) model, a waste heat recovery unit is introduced to recover exhaust heat and reduce purchase heat cost. Second, Power-to-Ammonia (P2A) technology is integrated with coal-fired generating units to enable dynamic ammonia-coal co-firing, further reducing carbon emissions and enhancing renewable energy utilization. Third, AA-CAES is incorporated to expand heat supply channels through compression heat storage and release, while absorbing heat during expansion power generation, thus achieving cross-temporal heat utilization and establishing a coordinated power and heat supply model between energy storage equipment and WIP. Finally, an improved Particle Swarm Optimization algorithm with dynamically adjusted inertia weights and learning factors, combined with a local exchange strategy, is employed for optimization. Case study results demonstrate that the proposed improved algorithm achieves lower total cost, and the coordinated operation of AA-CAES with WIP reduces the total system cost by 20.03%.
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References
Xu, W. Z., Liu, Z. X., Li, Z. & Zhang, Z. B. Low carbon oriented electric-hydrogen system multi-time scale collaborative optimal scheduling strategy considering hybrid energy storage. Energy Rep 12, 4295–4305. https://doi.org/10.1016/j.egyr.2024.10.012 (2024).
Wang, L. L. et al. Multi-timescale optimization of integrated energy system with diversified utilization of hydrogen energy under the coupling of green certificate and carbon trading. Renew Energy https://doi.org/10.1016/j.renene.2024.120597 (2024).
Gao, C. Z., Lu, H., Chen, M. Z., Chang, X. Q. & Zheng, C. X. A low-carbon optimization of integrated energy system dispatch under multi-system coupling of electricity-heat-gas-hydrogen based on stepwise carbon trading. Int J Hydrog Energy 97, 362–376. https://doi.org/10.1016/j.ijhydene.2024.11.055 (2025).
Wang, D. D. et al. Low-Carbon Control of Integrated Energy by Combining Cuckoo Search Algorithm and Particle Swarm Optimization Algorithm. Sustainability https://doi.org/10.3390/su17073206 (2025).
Pan, M. Z., Chen, X. T. & Li, X. Y. Multi-objective analysis and optimization of cascade supercritical CO2 cycle and organic Rankine cycle systems for waste-to-energy power plant. Appl Therm Eng https://doi.org/10.1016/j.applthermaleng.2022.118882 (2022).
Zhang, Y. Y. et al. Performance Analysis of a Waste-to-Energy System Integrated with the Steam-Water Cycle and Urea Hydrolysis Process of a Coal-Fired Power Unit. Appl Sci-Basel https://doi.org/10.3390/app12020866 (2022).
Wang, L. M. et al. Low-carbon economic dispatch of waste incineration power plant and biogas purification multi-energy coupling system considering power-to-gas. Energy Rep 13, 2997–3012. https://doi.org/10.1016/j.egyr.2025.02.031 (2025).
Ju, L. W. et al. Nearly-zero carbon optimal operation model and benefit allocation strategy for a novel virtual power plant using carbon capture, power-to-gas, and waste incineration power in rural areas. Appl Energy https://doi.org/10.1016/j.apenergy.2022.118618 (2022).
Khan, M. S. et al. Exergoeconomic analysis and optimization of an innovative municipal solid waste to energy plant integrated with solar thermal system. Energy Convers Manag https://doi.org/10.1016/j.enconman.2022.115506 (2022).
Dzierwa, P. et al. Technological and economical analysis of the heat recovery system from flue gas in a thermal waste treatment plant. Energy https://doi.org/10.1016/j.energy.2024.132708 (2024).
Chen, H. D., Guo, S. Z., Song, X. D. & He, T. B. Design and evaluation of a municipal solid waste incineration power plant integrating with absorption heat pump. Energy https://doi.org/10.1016/j.energy.2024.131007 (2024).
Lyu, Q., Wang, R. R., Du, Y. B. & Liu, Y. H. Numerical study on coal/ammonia co-firing in a 600 MW utility boiler. Int J Hydrog Energy 48(45), 17293–17310. https://doi.org/10.1016/j.ijhydene.2023.01.232 (2023).
Li, W. H. et al. Optimal dispatching of integrated energy system with hydrogen-to-ammonia and ammonia-mixed/oxygen-enriched thermal power. Energy https://doi.org/10.1016/j.energy.2025.134514 (2025).
Zhang, Z., Zhou, M., Chen, Y. B. & Li, G. Y. Exploiting the operational flexibility of AA-CAES in energy and reserve optimization scheduling by a linear reserve model. Energy https://doi.org/10.1016/j.energy.2022.126084 (2023).
Han, Z. H. et al. Collaborative optimization method and operation performances for a novel integrated energy system containing adiabatic compressed air energy storage and organic Rankine cycle. J Energy Storage https://doi.org/10.1016/j.est.2021.102942 (2021).
Wang, X. et al. Optimal Dispatching of Ladder-Type Carbon Trading in Integrated Energy System With Advanced Adiabatic Compressed Air Energy Storage. Front Energy Res https://doi.org/10.3389/fenrg.2022.933786 (2022).
Liu, H., Wu, B. J., Maleki, A. & Pourfayaz, F. An improved particle swarm optimization for optimal configuration of standalone photovoltaic scheme components. Energy Sci Eng 10(3), 772–789. https://doi.org/10.1002/ese3.1052 (2022).
Xu, S. P., Xiong, G. J., Mohamed, A. W. & Bouchekara, H. Forgetting velocity based improved comprehensive learning particle swarm optimization for non-convex economic dispatch problems with valve-point effects and multi-fuel options. Energy https://doi.org/10.1016/j.energy.2022.124511 (2022).
Chen, X. & Tang, G. W. Solving static and dynamic multi-area economic dispatch problems using an improved competitive swarm optimization algorithm. Energy https://doi.org/10.1016/j.energy.2021.122035 (2022).
Dagal, I., Akin, B. & Akboy, E. Improved salp swarm algorithm based on particle swarm optimization for maximum power point tracking of optimal photovoltaic systems. Int J Energy Res 46(7), 8742–8759. https://doi.org/10.1002/er.7753 (2022).
Shen, Y.; Kang, Z. J.; Zhang, C. G.; Liu, Y. H. Ieee In Distributionally Robust Optimization Scheduling for Off-grid Hydrogen Systems Considering Wind and Solar Uncertainty, 7th International Conference on Renewable Energy and Power Engineering, Tsinghua University, PEOPLES R CHINA, Sep 25–27; Tsinghua University, PEOPLES R CHINA, 272–277. (2024)
Beiron, J., Montañés, R. M., Normann, F. & Johnsson, F. Combined heat and power operational modes for increased product flexibility in a waste incineration plant. Energy https://doi.org/10.1016/j.energy.2020.117696 (2020).
Li, H. J. & Tan, D. Q. Differential game analysis between government and waste incineration plants on the management of municipal solid waste classification. Kybernetes 53(6), 2069–2089. https://doi.org/10.1108/k-12-2022-1687 (2024).
Zheng, W. D. et al. Optimal dispatch of nearly-zero carbon integrated energy system considering waste incineration plant-carbon capture system and market mechanisms. Int J Hydrog Energy 48(69), 27013–27031. https://doi.org/10.1016/j.ijhydene.2023.03.305 (2023).
Kim, Y., Oh, S., Kim, D., Hong, S. & Park, J. Development of a hybrid energy storage system for heat and electricity: Application to green hydrogen production process integrated with a municipal solid waste incinerator. Energy Convers Manag https://doi.org/10.1016/j.enconman.2024.119009 (2024).
Ozturk, M. & Dincer, I. A comprehensive review on power-to-gas with hydrogen options for cleaner applications. Int J Hydrog Energy 46(62), 31511–31522. https://doi.org/10.1016/j.ijhydene.2021.07.066 (2021).
Dang, Y. L. & Wang, W. Q. Low-Carbon Economic Scheduling of Hydrogen-Integrated Energy Systems with Enhanced Bilateral Supply-Demand Response Considering Vehicle to Grid Under Power-to-Gas-Carbon Capture System Coupling. Processes https://doi.org/10.3390/pr13030636 (2025).
del Pozo, C. A. & Cloete, S. Techno-economic assessment of blue and green ammonia as energy carriers in a low-carbon future. Energy Convers Manag https://doi.org/10.1016/j.enconman.2022.115312 (2022).
Demir, M. E. & Dincer, I. Development and assessment of a solar driven trigeneration system with storage for electricity, ammonia and fresh water production. Energy Convers Manag https://doi.org/10.1016/j.enconman.2021.114585 (2021).
Cardoso, J. S. et al. Numerical modelling of ammonia-coal co-firing in a pilot-scale fluidized bed reactor: Influence of ammonia addition for emissio. Energy Convers Manag https://doi.org/10.1016/j.enconman.2022.115226 (2022).
Li, H. W. et al. Low-Carbon Optimal Scheduling of Integrated Energy System Considering Multiple Uncertainties and Electricity-Heat Integrated Demand Response. Energies https://doi.org/10.3390/en17010245 (2024).
Yin, E. S., Li, Q. & Xuan, Y. M. Feasibility analysis of a concentrating photovoltaic-thermoelectric-thermal cogeneration. Appl Energy 236, 560–573. https://doi.org/10.1016/j.apenergy.2018.12.019 (2019).
Li, Y. W. et al. Combined Heat and Power dispatch considering Advanced Adiabatic Compressed Air Energy Storage for wind power accommodation. Energy Convers Manag https://doi.org/10.1016/j.enconman.2019.112091 (2019).
Men, J. K.; Qiu, J. L.; Chen, X. Y.; Wang, Z. P.; Yao, X. R. In Optimization method for a class of integrated energy system with compressed air energy storage, 40th Chinese Control Conference (CCC), 6868–6872. (2021)
Du, W. Y., Ma, J. & Yin, W. J. Orderly charging strategy of electric vehicle based on improved PSO algorithm. Energy https://doi.org/10.1016/j.energy.2023.127088 (2023).
Liu, Y. Y., As’arry, A., Hassan, M. K., Hairuddin, A. A. & Mohamad, H. Review of the grey wolf optimization algorithm: variants and applications. Neural Comput Appl 36(6), 2713–2735. https://doi.org/10.1007/s00521-023-09202-8 (2024).
Bai, J. F. et al. Blood-sucking leech optimizer. Adv in Eng Software https://doi.org/10.1016/j.advengsoft.2024.103696 (2024).
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This work was supported by the National Natural Science Foundation of China, grant number 51967004.
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Weijian Wang wrote the main manuscript text, Min Liu checked the main manuscript text and Haiqiang Zhao,Yuanda Wu,Yongyuan Tian prepared Figs. 1–5. All authors reviewed the manuscript.
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Wang, W., Liu, M., Zhao, H. et al. Optimized scheduling of integrated energy systems considering waste-to-power plants and advanced adiabatic air compression energy storage machines. Sci Rep (2026). https://doi.org/10.1038/s41598-026-37485-z
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DOI: https://doi.org/10.1038/s41598-026-37485-z
