A joint trading mechanism for energy credits and electricity in virtual power plants

Abstract

With the urgent need to achieve carbon neutrality goals and the rapid development of distributed energy resources, traditional electricity markets face challenges in effectively integrating environmental and economic values, lacking unified mechanisms to simultaneously clear energy and environmental transactions. This study proposes an energy credits–electricity joint trading mechanism for virtual power plants that achieves co-equilibrium through explicit coupling between energy and environmental value markets. First, a multi-dimensional energy credit quantification model is established, integrating energy type, time period, trading volume, and behavioral characteristics to differentiate environmental contributions. An optional reputation assessment enhancement covering prediction accuracy, fulfillment reliability, response timeliness, trading frequency, and anomaly behavior can be integrated for virtual power plant (VPP) operators requiring behavioral differentiation. Second, a unified joint clearing model is constructed that co-optimizes energy and credit trading, employing the alternating direction method of multipliers (ADMM) to decompose large-scale optimization problems into parallelizable prosumer and market coordination subproblems. Simulation results across single-day, multi-day (5-day cycle), and seasonal scenarios demonstrate that the mechanism successfully distinguishes prosumer performance: renewable energy prosumers accumulate substantial positive credits (136.2 credits over 5 days), while fossil fuel users incur credit deficits (−25.1 credits single-day), achieving system-level carbon credit balance over multi-day settlement cycles. The proposed mechanism effectively realizes the principle of “green contributors benefit, polluters pay” and provides a practical pathway for integrating environmental value in electricity markets.