TITLE:
Coordinated Low-Carbon Demand Response of Customer Directrix Load with Cross-Elastic Incentives
AUTHORS:
Qibo Luo, Dong Han
KEYWORDS:
Customer Directrix Load, Low-Carbon Demand Response, Dynamic Carbon Emission Factor, Cross-Elasticity Matrix
JOURNAL NAME:
Journal of Power and Energy Engineering,
Vol.14 No.3,
March
26,
2026
ABSTRACT: As the low carbon transition of power systems accelerates, low carbon demand response, characterized by both environmental orientation and behavioral incentives, has become a key mechanism for enhancing grid flexibility and an important collaborative approach for optimizing carbon emissions. This paper proposes an optimization strategy for customer directrix load based demand response founded on an electricity carbon incentive cross elasticity matrix. First, a similarity evaluation metric is constructed based on actual response contributions to assess the effectiveness of users’ direct participation in customer directrix load demand response. At the same time, an actual response volume metric is introduced to quantify response contributions, forming a comprehensive response indicator. On this basis, a segmented incentive price function is designed to more fairly reflect the response contributions of different users. Second, differentiated penalty factors are incorporated into the incentive price function according to the temporal scale of varying carbon emission levels. This approach establishes an incentive cross elasticity matrix that incorporates users’ low carbon behaviors, thereby encouraging load curve adjustments while promoting low carbon electricity consumption. Finally, an optimization model for load curve based low carbon demand response is developed with the objective of minimizing users’ total energy costs under constraints including response capacity limits and electricity balance. The results demonstrate that the proposed strategy effectively guides users to proactively adjust their electricity consumption behavior. It reduces overall costs while suppressing peak valley differences and optimizing carbon emissions, highlighting synergistic advantages in economic efficiency, low carbon performance, and controllable response behavior.