Source-Load Coordinated Low-Carbon Planning Considering Carbon Emission Flow and Green Certificate-Carbon Trading Mechanisms

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:Useful for advancing power system planning models that couple carbon pricing, emission flow accounting, and demand-side flexibility.

🏢実務担当者:Electric utilities and grid planners can adopt the source-load coordination approach to optimize generation investments and carbon compliance costs.

🏛政策担当者:Insights for designing green certificate and carbon trading mechanisms that send coherent locational and temporal signals to both generators and consumers.

[Objective] In the context of carbon peaking and carbon neutrality goals and the ongoing construction of new-type power systems， the high penetration of renewable energy and stringent emission reduction requirements have revealed several critical deficiencies in conventional power system planning， including coarse-grained carbon accounting， poor coordination between market mechanisms and planning decisions， and insufficient low-carbon incentives on the demand side. To achieve coordinated low-carbon optimization across source-grid-load dimensions， it is imperative to develop a planning approach that can characterize nodal carbon responsibility while incorporating both green certificate trading and carbon emission trading mechanisms. Taking a regional transmission system as the research subject， this paper proposes a source-load coordinated bi-level low-carbon planning model that integrates carbon emission flow with the dual market mechanisms of green certificate trading and carbon trading. [Methods] From the perspective of the system planner， the upper-level model incorporates annualized investment costs， supply-side operating costs， and the net trading terms of carbon allowances and green certificates into a unified objective function， thereby coordinating generation expansion decisions with market signals. On the basis of carbon emission flow theory， a nodal carbon potential model is developed to characterize the spatiotemporal distribution of carbon responsibility across the network. The lower-level model formulates a differentiated demand response scheme driven by nodal carbon potential signals， which guides load shifting in both temporal and spatial dimensions toward low-carbon patterns； the source-load coupling is then solved through iterative coordination between the two levels. [Results] Case study results demonstrate that， compared with a conventional planning scheme， the proposed coordinated optimization reduces annual carbon emissions by 7.40% and total annual system cost by 1.13%， while increasing the renewable penetration rate from 51.45% to 54.98%. Under the guidance of nodal carbon potential， load is reduced during high-carbon periods and shifted to low-carbon periods， resulting in a 5.11% decrease in the demand-side carbon response assessment cost. [Conclusions] Green certificate trading and carbon emission trading reshape the power supply structure through investment incentives and emission constraints， respectively， whereas nodal carbon potential signals enable refined allocation of carbon responsibility from the system level to individual nodes. In conjunction with demand response， these mechanisms constitute a synergistic framework that effectively enhances system decarbonization performance while maintaining economic efficiency.

• openalex https://doaj.org/article/bf84f4fa88344d9e9d1954cc9c885999first seen 2026-08-02 05:18:15