基于RBF代理模型与动态柔性响应的虚拟电厂电-碳-绿多市场协同博弈

doi:10.19595/j.cnki.1000-6753.tces.260887

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摘要

为提升电力市场、碳交易市场与绿证市场耦合环境下虚拟电厂联盟的低碳经济运行能力,提出一种基于径向基函数（Radial Basis Function, RBF）代理模型与考虑动态柔性响应的虚拟电厂电碳绿多市场双层混合博弈方法。首先,构建配电系统运营商与虚拟电厂联盟之间的双层混合博弈模型,上层协同优化运营商收益、联盟运行成本和合作剩余,下层以联盟运行成本最小为目标,综合考虑联盟协同过程中的电碳绿属性转移关系,构建多属性压力驱动的动态意愿响应模型,并基于Nash-Shapley多维贡献度方法分配联盟合作剩余。然后,引入RBF代理模型近似拟合上层价格策略与下层联盟响应之间的非线性映射关系,并结合NSGA-III-DE和ADMM实现协同优化求解。最后,仿真算例验证了所提方法在降低双层博弈求解成本和改善联盟低碳经济运行效果方面的有效性。

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	唐靖宇
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关键词 ：虚拟电厂, 电碳绿多市场耦合, 双层混合博弈, RBF代理模型, 动态柔性响应

Abstract：

In the coupled environment of electricity, carbon trading, and green certificate markets, virtual power plant (VPP) alliances need to improve their low-carbon economic operation capability while coordinating multi-market signals and stakeholder interests. To address multi-stakeholder coordination, carbon and green certificate compliance, and computational burden in VPP alliance operation, a bi-level hybrid game framework based on a radial basis function (RBF) surrogate model and dynamic flexible-load response was established. The framework models the leader-follower pricing interaction between a distribution system operator (DSO) and a VPP alliance, together with cooperation among VPP members, and couples electricity trading, carbon responsibility transfer, green certificate attribute circulation, flexible-load response, and benefit allocation.
At the upper level, the DSO optimized time-of-use buying and selling prices by balancing three goals: DSO revenue, VPP alliance cost, and cooperative surplus. At the lower level, the VPP alliance minimized its total operating cost by coordinating renewable generation, controllable units, storage, hydrogen-linked devices, flexible loads, peer-to-peer (P2P) electricity sharing, carbon responsibility and green certificate settlement, and surplus allocation. In P2P trading, power flows carried carbon responsibility and green certificate attributes, so carbon deficits, green certificate deficits, and internal settlement prices were updated with alliance clearing results. A multi-attribute-pressure-driven flexible-load response model was constructed, in which electricity price pressure, carbon responsibility pressure, and green certificate compliance pressure updated the response boundaries of interruptible, shiftable, and air-conditioning loads. A Nash-Shapley contribution allocation method was used to assign cooperative surplus according to electricity sharing, carbon attribute, green certificate attribute, and flexibility contributions. To improve solution efficiency, the RBF surrogate model fitted the nonlinear mapping between upper-level prices and lower-level alliance responses. The non-dominated sorting genetic algorithm III with differential evolution (NSGA-III-DE) was used for upper-level multi-objective price search, while the alternating direction method of multipliers coordinated lower-level dispatch, P2P clearing, and surplus allocation. Pareto solutions screened by the RBF model were rechecked with the original lower-level model, and the final compromise solution was selected by the normalized ideal-point distance method.
Case studies with one DSO and three VPPs were conducted. The mean absolute percentage errors of the three objective predictions were below 1%. Compared with the meta-heuristic direct search method, the RBF-NSGA-III-DE method reduced lower-level model calls by 80.94% and computational time by 79.58%, with a comprehensive objective deviation of 1.79%. Compared with the scenario without cooperative game and P2P interaction, the complete hybrid game strategy reduced the VPP alliance cost by 45.38%. Meanwhile, the carbon deficit and net green certificate deficit decreased by 9.79% and 38.73%, respectively. After the multi-attribute pressure mechanism was introduced, the total flexible-load response increased by 160.61%.
These results indicate that the framework reduces repeated lower-level optimization calls, coordinates electricity-carbon-green certificate attributes in alliance trading, and improves the consistency between contribution and cooperative benefit allocation under the tested market-coupling scenarios. Further extension can focus on rolling multi-timescale coordination by incorporating intertemporal carbon and green certificate pool states and distribution-network constraints.

Key words： Virtual power plant electricity-carbon-green certificate multi-market coupling bi-level hybrid game RBF surrogate model dynamic flexible response

收稿日期: 2026-06-04

PACS:

TM73

基金资助:

辽宁省科学技术计划项目揭榜挂帅（2023JH1/10400049）、辽宁省科技计划联合计划(自然科学基金-博士科研启动项目)(2024-BSLH-159)资助

通讯作者: 金红洋男,1993年生,讲师,硕士生导师,研究方向为虚拟电厂、新能源发电、综合能源系统。mail：jinhy@sie.edu.cn

作者简介: 唐靖宇男,2001年生,硕士研究生,研究方向为虚拟电厂运行优化。E-mail：281891779@qq.com

引用本文:

唐靖宇, 金红洋, 赵琰, 李昱材, 杨鹏跃. 基于RBF代理模型与动态柔性响应的虚拟电厂电-碳-绿多市场协同博弈[J]. 电工技术学报, 0, (): 260887-. Tang Jingyu, Jin Hongyang, Zhao Yan, Li Yucai, Yang Pengyue. Coordinated Game-Based Operation of Virtual Power Plant Alliances in Electricity-Carbon-Green Certificate Markets Based on an RBF Surrogate Model and Dynamic Flexible-Load Response. Transactions of China Electrotechnical Society, 0, (): 260887-.

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