Key Takeaways & Executive Findings
- •• • High-energy-consuming industrial parks contribute 42% of China's industrial carbon emissions with an emission intensity of 1.2 t CO2 per 10,000 CNY, underscoring the urgent need for integrated carbon-market mechanisms to avoid punitive carbon costs under the dual-carbon strategy. • • The proposed generation rights-carbon quota-green certificate conversion mechanism dynamically matches renewable output with self-owned plant regulation, enabling short-term generation rights trading that mitigates forecast deviations inherent in medium-to-long-term contracts and enhances renewable consumption. • • Integration of a CSP plant with thermal energy storage (TES) and an electric heater (EH) allows surplus wind/PV power to be stored as heat and dispatched during deficits, reducing the need for independent battery storage and lowering total system investment and operational costs. • • Simulation of a Jiuquan high-energy-consuming park validates that the ladder-type carbon and green certificate hybrid market design reduces carbon emissions and improves economic performance, achieving dual environmental and economic optimization compared to independent trading schemes.
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Abstract
High-energy-consuming industrial parks account for 42% of China's industrial carbon emissions, with an emission intensity of 1.2 t CO2 per 10,000 CNY, necessitating innovative market mechanisms to reduce carbon costs. This study proposes an optimal scheduling model integrating short-term generation rights trading with a ladder-type carbon emission-green certificate hybrid market mechanism for a system comprising a concentrated solar power (CSP) plant, wind power, photovoltaic (PV) generation, and a self-owned power plant in a high-energy-consuming park. The CSP thermal energy storage (TES) system enables energy time-shifting and electro-thermal coupling, constructing a multi-energy complementary power coordination model to smooth wind/PV fluctuations and enhance consumption. A joint short-term generation rights trading strategy is designed, dynamically matching renewable output with the self-owned plant's regulation demand through a generation rights-carbon quota-green certificate conversion mechanism. Simulation on a high-energy-consuming park in Jiuquan, Gansu Province, demonstrates that the proposed method effectively reduces carbon emissions and improves renewable energy consumption. The introduction of the CSP plant further lowers total park costs, achieving dual optimization of environmental and economic benefits. The model is linearized using the big-M method, transforming a mixed-integer nonlinear programming problem into a mixed-integer linear programming problem for solution. This approach addresses the mismatch between medium-to-long-term generation rights trading and short-term supply-demand fluctuations, as well as the lack of linkage among generation rights, carbon, and green certificate trading, thereby synergizing emission reduction incentives with power trading objectives.
1. Introduction
High-energy-consuming industrial parks, which account for 42% of China's industrial carbon emissions and exhibit an emission intensity of 1.2 t CO2 per 10,000 CNY, face mounting pressure under the dual-carbon strategy. Their self-owned power plants, typically coal-fired with annual coal consumption reaching millions of tons, are deeply coupled with production processes that demand continuous and high-quality energy supply. Existing scheduling approaches for these parks often rely on medium-to-long-term generation rights trading, which fails to match short-term supply-demand fluctuations due to renewable forecast uncertainties. Moreover, carbon emission rights and green certificate trading remain independent, creating a fragmented market that weakens emission reduction incentives and hinders the synergistic optimization of power trading and carbon mitigation objectives.
This study addresses these bottlenecks by proposing an integrated scheduling model that fuses short-term generation rights trading with a ladder-type carbon emission-green certificate hybrid market mechanism. A multi-energy complementary system comprising a concentrated solar power (CSP) plant with thermal energy storage, wind power, and photovoltaic generation is coordinated with the park's self-owned power plant. The CSP's thermal storage enables energy time-shifting and electro-thermal coupling, smoothing renewable fluctuations and enhancing consumption without additional battery storage. A generation rights-carbon quota-green certificate conversion mechanism dynamically matches renewable output with the self-owned plant's regulation needs, while the big-M method linearizes nonlinear constraints to enable efficient mixed-integer linear programming solution. Simulation on a Jiuquan high-energy-consuming park demonstrates reduced carbon emissions, improved renewable consumption, and lower total costs, achieving dual environmental and economic benefits.
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CHEN Wei, NIE Dacheng, WEI Zhanhong, LIN Jie (2026). Optimal Scheduling Strategy for New Energy and High-Energy-Consuming Industrial Park Self-Owned Power Plants Based on Generation Rights-Carbon-Green Certificate Trading. Acta Energiae Solaris Sinica. https://doi.org/10.19912/j.0254-0096.tynxb.202608_9712
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Frequently Asked Questions
What specific operational parameters and thresholds define the CSP plant's ability to smooth wind/PV fluctuations in this model?
The CSP plant's thermal energy storage (TES) system and electric heater (EH) enable energy time-shifting: surplus wind/PV power is converted to heat and stored, while deficits are covered by discharging TES to drive the power cycle. The model incorporates dynamic heat exchange rates (PH-T,t, PT-H,t) and net power output (PCSP,t) constrained by solar field capacity and TES state of charge. Simulation results for the Jiuquan park show that this configuration reduces renewable curtailment and improves consumption, though exact percentages depend on the park's load profile and renewable penetration.
How does the generation rights-carbon quota-green certificate conversion mechanism quantitatively reduce carbon emissions and costs compared to independent trading?
The conversion mechanism allows green certificates generated by the multi-energy system to be converted into carbon emission rights, offsetting the self-owned plant's carbon costs. Simultaneously, short-term generation rights trading enables the self-owned plant to transfer generation to renewable sources when renewable output is high, reducing coal consumption. The ladder-type carbon trading imposes higher prices for higher emission tiers, creating a strong marginal incentive. In the Jiuquan case, this integrated approach lowered total costs and carbon emissions relative to separate trading schemes, though exact figures are not disclosed in the extracted text.
What are the scalability bottlenecks and computational challenges of implementing this mixed-integer linear programming model in real-time dispatch?
The original mixed-integer nonlinear programming problem is linearized using the big-M method, transforming it into a mixed-integer linear programming (MILP) problem. While MILP is solvable with commercial solvers, scalability depends on the number of binary variables and constraints, which grow with the number of generation units, time steps, and market rules. Real-time application may require decomposition or rolling-horizon optimization. The study does not report solution times, but the linearization is critical for tractability in day-ahead or intra-day scheduling.
What is the economic trade-off between investing in CSP with TES versus independent battery storage for renewable smoothing in high-energy-consuming parks?
The study asserts that CSP with TES avoids additional battery storage investment, as the TES provides comparable energy time-shifting at potentially lower cost. However, CSP capital costs are high and depend on solar resource quality. The Jiuquan case indicates that total park costs decrease with CSP integration, but a detailed cost breakdown (e.g., LCOE, storage cost per kWh) is not provided. The economic advantage hinges on the park's heat demand, which can be met by CSP, and the avoided cost of battery storage and carbon penalties.
How does the model handle uncertainties in wind/PV output and load forecasts, and what is the impact on generation rights trading?
The short-term generation rights trading is designed to dynamically match renewable output with the self-owned plant's regulation demand, mitigating forecast deviations that plague medium-to-long-term contracts. The model likely uses scenario generation or deterministic forecasts, but the extracted text does not specify uncertainty modeling techniques. The conversion mechanism provides flexibility: when renewable output deviates, the self-owned plant can adjust its generation and the trading positions accordingly, with carbon and green certificate conversions balancing the financial impact. However, the robustness under extreme forecast errors is not quantified.
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