Low-Carbon Economic Dispatch of Power Systems Considering Multi-Agent Game on Carbon Emission Utility
Source abstract
Abstract
During the transformation of power systems toward a high proportion of renewable energy, thermal power units remain the core support for ensuring a stable power supply. Controlling carbon emissions and allocating resource utility are the keys to economic dispatch optimization. Most existing economic dispatch optimization models focus on cost and total carbon emission control, but ignore the utility balance of carbon emission resources among different units. Based on the envy-free fairness theory, this paper establishes an economic dispatch optimization model for thermal power-integrated power systems that considers the carbon emission utility game among multiple agents. By constructing a mixed-integer programming model that minimizes the mean absolute error, this study obtains a piecewise linear scheme for the power generation–coal consumption and carbon emission utility of thermal power units. The standard linear programming form of this scheme is also derived. Based on the principle of almost envy-free fair distribution, carbon emission utility game constraints are proposed. On this basis, combining the above models and constraints, an economic dispatch model aiming to minimize the total power generation cost of the system is proposed. Case study verification shows that the mean absolute error of the proposed linear fitting method is lower than that of existing methods. The economic dispatch optimization model ensures optimal cost while satisfying the source-load power balance. Meanwhile, with a slight increase in total power generation cost, the carbon emission utility balance of each unit is achieved, thereby promoting the fairness of carbon emission reduction responsibilities among multiple units.
Source: crossref · Quality: baseline
Affiliations
School of Economics and Management, North China Electric Power University, Hui Long Guan, Chang Ping District, Beijing 102206, China
Funding
the Postdoctoral Fellowship Program of CPSF · the Fundamental Research Funds for the Central Universities · China Postdoctoral Science Foundation
References (41)
Show source-provided references
1. Integrating more renewable electricity into the power system may increase carbon emissions
2. Role and Development of Thermal Power Units in New Power Systems10.1109/JRFID.2022.3205465 ↗
3. Performance of the Walrus Optimizer for solving an economic load dispatch problem10.3934/math.2024494 ↗
4. Dynamic economic load dispatch in microgrid using hybrid moth-flame optimization algorithm10.1007/s00202-023-02183-w ↗
5. Hybrid Dynamic Coal Blending Method to Address Multiple Environmental Objectives Under a Carbon Emissions Allocation Mechanism10.1016/j.energy.2022.124297 ↗
6. Optimization of cost and emission for dynamic load dispatch problem with hybrid renewable energy sources10.1007/s00500-023-08584-0 ↗
7. A Review of Hybrid Renewable/Alternative Energy Systems for Electric Power Generation: Configurations, Control, and Applications10.1109/TSTE.2011.2157540 ↗
8. Low-carbon development in power systems based on carbon emission analysis models: A comprehensive review
9. Low-carbon economic dispatching strategy based on feasible region of cooperative interaction between wind-storage system and carbon capture power plant10.1016/j.renene.2024.120706 ↗
10. Optimization of Low-Carbon Integrated Energy Systems with Efficient Hydrogen Use and Flexible CCPP-MR-HCHP Operations10.1155/etep/1924852 ↗
11. A Computationally Efficient Mixed-Integer Linear Formulation for the Thermal Unit Commitment Problem10.1109/TPWRS.2006.876672 ↗
12. Chen, Z., Cen, B., Zhao, J., Wu, H., Wang, H., and Fu, Z. (2025). Optimal Dispatch Model for Hybrid Energy Storage in Low-Carbon Integrated Energy Systems. Energies, 18.10.20944/preprints202509.2162.v1 ↗
13. Han, H., Wei, T., Wu, C., Xu, X., Zang, H., Sun, G., and Wei, Z. (2022). A Low-Carbon Dispatch Strategy for Power Systems Considering Flexible Demand Response and Energy Storage. Front. Energy Res., 10.10.3389/fenrg.2022.883602 ↗
14. Wang, J., Ji, X., Meng, X., Bai, Y., and Li, M. (2025). Low-carbon economic dispatch of integrated energy system with carbon capture power plant and multiple utilization of hydrogen energy. Front. Energy Res., 12.10.3389/fenrg.2024.1447858 ↗
15. Auxiliary Service Dynamic Compensation Mechanism Design for Incentivizing Market Participants to Provide Flexibility in China10.23919/PCMP.2023.000048 ↗
16. Benchmarking and contribution analysis of carbon emission reduction for renewable power systems considering multi-factor coupling10.1016/j.energy.2024.131674 ↗
17. Albalawi, H., Wadood, A., and Park, H. (2024). Economic Load Dispatch Problem Analysis Based on Modified Moth Flame Optimizer (MMFO) Considering Emission and Wind Power. Mathematics, 12.10.3390/math12213326 ↗
18. Look-Ahead Rolling Economic Dispatch Approach for Wind-Thermal-Bundled Power System Considering Dynamic Ramping and Flexible Load Transfer Strategy10.1109/TPWRS.2023.3238035 ↗
19. Priority-Considered Load Shedding in Economic Dispatch: Distributed Optimization Approach10.1109/TCNS.2022.3231185 ↗
20. PWLU: Learning Specialized Activation Functions with the Piecewise Linear Unit10.1109/TPAMI.2023.3286109 ↗
21. A Comparison of Two Mixed-Integer Linear Programs for Piecewise Linear Function Fitting10.1287/ijoc.2021.1114 ↗
22. Piecewise Linear Function Fitting via Mixed-Integer Linear Programming10.1287/ijoc.2019.0890 ↗
23. On the Derivation of Continuous Piecewise Linear Approximating Functions10.1287/ijoc.2019.0949 ↗
24. Accuracy study of linearization methods for quadratic cost curves of thermal units in unit commitment problems10.1049/gtd2.12434 ↗
25. Piecewise linear bounding of univariate nonlinear functions and resulting mixed integer linear programming-based solution methods10.1016/j.ejor.2018.11.021 ↗
26. Online coal consumption characteristics fitting for daily economic dispatch using a data-driven hybrid sequential model10.1016/j.apenergy.2023.121127 ↗
27. Real-time emission and cost estimation based on unit-level dynamic carbon emission factor10.1049/enc2.12078 ↗
28. Low-carbon economic dispatch strategy for interconnected multi-energy microgrids considering carbon emission accounting and profit allocation10.1016/j.scs.2023.104987 ↗
29. Integrated energy system for low-carbon economic operation optimization: Pareto compromise programming and master-slave game10.1016/j.renene.2024.119946 ↗
30. Yan, Y., Xie, S., Tang, J., Qian, B., Lin, X., and Zhang, F. (2024). Transaction strategy of virtual power plants and multi-energy systems with multi-agent Stackelberg game based on integrated energy-carbon pricing. Front. Energy Res., 12.10.3389/fenrg.2024.1459667 ↗
31. Comprehensive analysis of carbon emission reduction technologies (CRTs) in China’s coal-fired power sector: A bottom-up approach10.1016/j.rser.2024.114696 ↗
32. Optimal dispatch of electricity considering shared source-load carbon responsibility10.1016/j.epsr.2023.109135 ↗
33. Carbon emission quota allocating on coal and electric power enterprises under carbon trading pilot in China: Mathematical formulation and solution technique10.1016/j.jclepro.2019.118104 ↗
34. Nan, J., Feng, J., Deng, X., Wang, C., Sun, K., and Zhou, H. (2022). Hierarchical Low-Carbon Economic Dispatch with Source-Load Bilateral Carbon-Trading Based on Aumann–Shapley Method. Energies, 15.10.3390/en15155359 ↗
35. Fair division of indivisible goods: Recent progress and open questions10.1016/j.artint.2023.103965 ↗
36. Truthful cake sharing10.1007/s00355-023-01503-0 ↗
37. Maximum Nash welfare and other stories about EFX10.1016/j.tcs.2021.02.020 ↗
38. Approximate envy-freeness in graphical cake cutting10.1016/j.dam.2024.05.029 ↗
39. Envy-Free Cake-Cutting for Four Agents10.1145/3765615 ↗
40. A Little Charity Guarantees Almost Envy-Freeness10.1137/20M1359134 ↗
41. Zhang, N., Zhang, M., Sun, L., Hu, J., Li, J., and Li, W. (2022). An Annual Electric Energy Trade Scheduling Model under the Dual Track Mode. Energies, 15.10.3390/en15145075 ↗