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作 者:刘亚鑫 蔺红[1] LIU Yaxin;LIN Hong(School of Electrical Engineering,Xinjiang University,Urumqi 830047,China)
机构地区:[1]新疆大学电气工程学院,新疆乌鲁木齐830047
出 处:《电力工程技术》2023年第6期179-188,共10页Electric Power Engineering Technology
基 金:新疆维吾尔自治区重点研发专项(2022B01020-3)。
摘 要:为探索虚拟电厂(virtual power plant,VPP)兼顾经济性与低碳性的竞价策略,从VPP作为价格制定者的角度提出一种计及碳交易与风险的VPP参与电能量市场和备用市场的主从博弈竞价模型。以含风电、光伏的VPP为研究对象,首先,采用基准线法为VPP无偿分配碳排放配额,建立VPP的碳交易模型;之后建立了基于主从博弈理论的双层竞价模型,上层领导者为参与碳、电、备用市场的VPP运营商,下层跟随者为电力市场运营商;同时,运用条件风险值(conditional value at risk,CVaR)将上层问题转化为计及风险的多目标优化问题;最后采用遗传算法和求解器联合求解。算例表明该模型可以在多市场的环境下提供经济、低碳的竞价策略及不同市场的出力计划,并分析了不同市场类型、碳交易的加入、不同风险厌恶系数对VPP竞价结果的影响,为提高VPP运营商收益提供了新思路。To explore the bidding strategy of a virtual power plant(VPP)that combines economy and low-carbon,a two-level Stackelberg game bidding model is proposed from the point of view of VPP as the price maker,which takes into account carbon trading and risk to participate in the energy market and spinning reserve market.Taking VPP including wind power and photovoltaic as the research object,the base-line method is firstly used to allocate a free carbon emission quota to VPP,and the carbon trading model of VPP is established.Secondly,a two-level bidding model based on the Stackelberg game theory is established.The upper-level is the VPP operator participating in the carbon,energy power,and spinning reserve markets.The lower-level follower is the electricity market operator.At the same time,conditional value at risk(CVaR)is used to transform the upper-level problem into a multi-objective optimization problem taking risk into account.Finally,the genetic algorithm and solver are combined to solve the problem.The example shows that the model can provide economical and low-carbon bidding strategies in multi-market environments,and it can also provide output plans for different markets.The influence of different market types,carbon trading and different risk aversion coefficients on VPP bidding results are analyzed,which provides a new way to improve the revenue of VPP operators.
关 键 词:虚拟电厂(VPP) 价格制定者 碳交易 主从博弈 电能量市场 备用市场 条件风险值(CVaR) 遗传算法
分 类 号:TM743[电气工程—电力系统及自动化]
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