发电技术

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考虑多重不确定性与电碳耦合交易的多园区综合能源系统混合博弈优化调度

王贵召1,程静1,2*   

  1. 1.新疆大学电气工程学院,新疆维吾尔自治区 乌鲁木齐市 830047;2.可再生能源发电与并网技术控制教育部工程研究中心(新疆大学),新疆维吾尔自治区 乌鲁木齐市 830047

  • 基金资助:
    新疆维吾尔自治区重大科技专项(2022A01001-4);新疆维吾尔自治区重点研发项目(2022B01003-3)

WANG Guizhao1, CHENG Jing1,2*   

  1. 1.School of Electrical Engineering, Xinjiang University, Urumqi 830047, Xinjiang Uygur Autonomous Region, China; 2.Engineering Research Centre of Renewable Energy Power Generation and Grid-Connected Control (Xinjiang University), Ministry of Education, Urumqi 830047, Xinjiang Uygur Autonomous Region, China
  • Supported by:
    Major Science and Technology Special Project of Xinjiang Uygur Autonomous Region(2022A01001-4); Key R&D Project of Xinjiang Uygur Autonomous Region(2022B01003-3)

摘要: 【目的】随着能源互联网战略的深入推进,可再生能源与多园区的参与度不断持续攀升,系统中的不确定性显著增加,各参与主体之间的合作与竞争关系也愈加复杂多变。为此,提出一种考虑多重不确定性与电碳耦合交易的多园区综合能源系统混合博弈优化调度方法。【方法】首先,构建了一种以园区综合能源系统(community integrated energy system,CIES)运营商为领导者,用户为跟随者的主从博弈模型,以及在CIES间进行电碳耦合交易的双层混合博弈优化模型;然后,采用Wasserstein距离的模糊集分别构建了电网电价、可再生能源出力的不确定性模型;最后,利用交替方向乘子法(alternating direction multiplier method,ADMM)结合对偶原理对模型进行分布式求解,并在算例中进行了验证。【结果】所提模型与方法能够有效提升各主体利益,降低系统碳排放。【结论】该方法有效协调了多园区系统的利益冲突,实现了多重不确定性下的电-碳协同优化,对推动高比例可再生能源接入的园区系统优化运行具有重要意义。

关键词: 分布鲁棒优化, 园区综合能源系统(CIES), 主从博弈, 合作博弈, 双层优化, 电碳耦合交易, 分布式算法, Wasserstein距离

Abstract: [Objective] With the deepening of the energy Internet strategy, the participation of renewable energy and multiple communities continues to rise, the uncertainties in the system increase significantly, and the cooperation and competition between the participating entities become more complex and volatile. Therefore, a hybrid game optimization scheduling method for a multi-community integrated energy system considering multiple uncertainties and electricity-carbon coupling trading is proposed. [Methods] Firstly, a Stackelberg game model with community integrated energy system (CIES) operators as leaders and users as followers, as well as a two-layer hybrid game optimization model for electricity-carbon coupling trading between CIESs, are constructed. Then, the uncertainty models of grid electricity price and renewable energy output are constructed using fuzzy sets based on the Wasserstein distance. Finally, the alternating direction multiplier method (ADMM) combined with the duality principle is used to solve the model in a distributed manner, and the effectiveness of the model is verified through case studies. [Results] The proposed model and method can effectively improve the benefits of participating entities and reduce the carbon emissions of the system. [Conclusions] This method effectively coordinates the conflicts of interest of multi-community systems, realizes the coordinated optimization of electricity and carbon under multiple uncertainties, and is of great significance to promote the optimal operation of community systems with high penetration of renewable energy

Key words: distributionally robust optimization, community integrated energy system (CIES), Stackelberg game, cooperative game, bi-level optimization, electricity-carbon coupling trading, distributed algorithm, Wasserstein distance