Multi-Objective Combinatorial Double Auction for Coupled Electricity-Carbon-Green Certificate Trading in Multi-Microgrid Systems
Huang Jingjie1, Yuan Liang2, Xie Yuzheng3, Yang Hongming1
1. State Key Laboratory of Disaster Prevention & Reduction for Power Grid Changsha University of Science & Technology Changsha 410114 China;;
2. Hunan Provincial Key Laboratory of Power Electronic Equipment and Power Electronic Power Networks Central South University Changsha 410083 China;
3. State Grid Hunan Electric Power Company Limited Economic & Technical Research Institute Changsha 410007 China
Coordinated low-carbon operation of multi-microgrid (MMG) systems increasingly requires joint participation in electricity trading, carbon emission trading (CET), and green certificate trading (GCT). In practice, fragmented attribute accounting and strategic extreme bidding may reduce renewable accommodation and weaken transaction fairness. A coupled electricity-carbon-green certificate trading framework was developed to improve market linkage and promote low-carbon benefits sharing among multiple microgrids (MGs). A two-stage market-and-operation framework was established. In the day-ahead stage, each MG acted as both buyer and seller and submitted sealed bids for electricity, carbon allowances, and green certificates to a microgrid operator (MGO). A multi-objective combinatorial double auction (CDA) clearing model was formulated to (i) maximize MMG social welfare and (ii) maximize total winning quantities across the three commodities. Auction balance constraints were enforced, and price boundary constraints were imposed to mitigate extreme bids. The multi-objective problem was solved using fuzzy membership-based satisfaction aggregation to obtain a single compromise clearing outcome. To couple CET and GCT, a carbon-green certificate mutual-recognition method was introduced by mapping renewable attributes into carbon compliance credits based on the Chinese Certified Emission Reduction (CCER) mechanism, enabling consistent settlement between certificates and carbon allowances. In the intraday stage, MG operation was optimized using mixed-integer linear programming (MILP). Day-ahead cleared quantities and settlements were embedded in the cost function, while controllable generators, energy storage, and flexible loads were dispatched to minimize operating cost under forecast errors. Residual imbalances in electricity, allowances, and certificates were settled via external markets. Compared with a baseline without coupled internal trading, the proposed framework increased renewable accommodation and reduced emissions by reallocating renewable surplus through internal transactions and by aligning environmental attributes with compliance incentives. After enabling carbon-green certificate mutual recognition, additional cost reductions were achieved for renewable-rich MGs, while renewable-deficit MGs improved renewable accommodation by 514 kWh and 472.5 kWh with corresponding emission reductions of 274.8 kg and 389.2 kg. The auction objective choice affected equity and coverage: welfare-only clearing minimized cost and emissions, volume-only clearing expanded transaction scale but increased marginal peak-hour reliance, and the proposed multi-objective rule balanced efficiency and participation. Under the multi-objective rule, the winning volume of MG4 decreased by 244.66 kWh while that of MG5 increased by 1097.8 kWh, indicating improved allocation balance. A price-bounded multi-objective CDA coupled with intraday MILP dispatch enhances renewable accommodation, lowers emissions, and improves participation equity for MMG systems engaged in electricity-carbon-green certificate co-trading. Carbon-green mutual recognition provides a practical linkage that strengthens low-carbon incentives during transitional policy periods.
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