| 引用本文: | 刘英培,信明垚,秦浩然,单泓元.考虑碳排放权交易风险的能源运营商-区域综合能源系统联盟混合博弈优化调度[J].电力自动化设备,2025,45(6):15-22,49. |
| LIU Yingpei,XIN Mingyao,QIN Haoran,SHAN Hongyuan.Hybrid game-based optimal scheduling of energy system operator and regional integrated energy system alliance considering risk of carbon emission right trading[J].Electric Power Automation Equipment,2025,45(6):15-22,49. |
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| 摘要: |
| 随着碳排放权交易市场的不断完善，区域综合能源系统(RIES)在参与碳排放权交易时应充分考虑碳价波动的影响。为此，构建以能源运营商为主体、RIES联盟为从体的混合博弈架构。主体以最大化自身效益为目标制定购售电价策略，从体以供能成本和碳交易成本之和最小为目标进行热能交互，建立RIES联盟合作博弈模型。碳交易成本计及碳排放权价格的不确定性，利用自回归差分移动平均模型及广义自回归条件异方差模型预测调度日的碳价，结合条件风险价值，通过设定不同的风险偏好系数及置信度对碳交易价格波动风险进行量化。基于纳什谈判模型将合作博弈问题拆分成2个子问题，在降低联盟总成本的同时，合理分配RIES联盟的合作收益。通过仿真算例结合遗传算法验证所提策略的有效性，结果表明所提模型可以有效平衡系统的经济性和低碳性，降低碳排放权价格波动风险对调度决策的影响。 |
| 关键词: 区域综合能源系统 碳排放权交易风险 混合博弈 纳什谈判 条件风险价值 自回归差分移动平均模型 广义自回归条件异方差模型 优化调度 |
| DOI：10.16081/j.epae.202409013 |
| 分类号:TM73;TK01 |
| 基金项目:国家自然科学基金资助项目(51607069) |
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| Hybrid game-based optimal scheduling of energy system operator and regional integrated energy system alliance considering risk of carbon emission right trading |
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LIU Yingpei, XIN Mingyao, QIN Haoran, SHAN Hongyuan
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School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China
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| Abstract: |
| With the continuous improvement of the carbon emission right trading market, regional integrated energy systems(RIESs) should fully consider the impact of carbon price fluctuations when participating in carbon emission trading. Therefore, a hybrid game architecture is constructed with the energy system operator as the main body and the RIES alliance as the slave. The main body develops the purchasing and selling electricity price strategies with the goal of maximizing its own benefits. The slave conducts thermal energy interaction with the goal of minimizing the sum of energy supply cost and carbon trading cost, and the cooperative game model of RIES alliance is established. The carbon trading cost takes the uncertainty of carbon emission right price into account, and the carbon price of the scheduling day is predicted by using the autoregressive integrated moving average model and the generalized autoregressive conditional heteroskedasticity model. Combined with the conditional value at risk, the risk of carbon trading price fluctuation is quantified by setting different risk preference coefficients and confidence levels. Based on Nash negotiation model, the cooperative game problem is divided into two sub-problems to reduce the total cost of the alliance and rationally distribute the cooperation benefits of RIES alliance. The effectiveness of the proposed strategy is verified by a simulation example combined with genetic algorithm. The results show that the proposed model can effectively balance the economy and low-carbon of the system, and reduce the impact of carbon emission right price fluctuation risk on scheduling decisions. |
| Key words: regional integrated energy system risk of carbon emission right trading hybrid game Nash negotiation conditional value at risk autoregressive integrated moving average model generalized autoregressive conditional heteroskedasticity model optimal scheduling |
