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作 者:曹嘉馨 杨博 朱善迎[1,2,3] CAO Jia-xin;YANG Bo;ZHU Shan-ying(Department of Automation,Shanghai Jiao Tong University,Shanghai 200240,China;Key Laboratory of System Control and Information Processing,Ministry of Education of China,Shanghai 200240,China;Shanghai Engineering Research Center of Intelligent Control and Management,Shanghai 200240,China)
机构地区:[1]上海交通大学自动化系,上海200240 [2]系统控制与信息处理教育部重点实验室,上海200240 [3]上海工业智能管控工程技术研究中心,上海200240
出 处:《控制理论与应用》2022年第10期1781-1798,共18页Control Theory & Applications
基 金:Supported by the National Key Research and Development Program of China(2018YFB1702300);the National Natural Science Foundation of China(61731012)。
摘 要:新能源发电和负荷需求的波动性使得纳网内能源盈馀不同,从而影响本地新能源消纳水平和运行成本.本文针对纳网内暖通空调潜在的热弹性调节能力,阐述了一种基于用户舒适度偏好和环境因素的需求响应和双向定价策略,来优化纳网与公共管理中心间的能源双向交易及时均收益.所构建的双层交易随机优化模型中由于存在不确定参数和时间耦合温度队列使得长期优化问题求解复杂.为此设计了一种基于李雅普诺夫优化方法的松弛形式对原问题进行时间解耦,重构主从博弈框架来刻画参与者能量交易决策间的相互影响关系,并进一步对博弈均衡点的存在与唯一性给出严格的证明.在此基础上提出了一种优化响应算法使得决策者间能以较少的信息交换达到博弈均衡.最后通过仿真实验验证了该能量管理算法的有效性.Owing to the fluctuant renewable generation and power demand,the energy surplus or deficit in nanogrids embodies differently across time.To stimulate local renewable energy consumption and minimize long-term energy costs,some issues still remain to be explored:when and how the energy demand and bidirectional trading prices are scheduled considering personal comfort preferences and environmental factors.For this purpose,the demand response and two-way pricing problems concurrently for nanogrids and a public monitoring entity(PME)are studied with exploiting the large potential thermal elastic ability of heating,ventilation and air-conditioning(HVAC)units.Different from nanogrids,in terms of minimizing time-average costs,PME aims to set reasonable prices and optimize profits by trading with nanogrids and the main grid bi-directionally.Such bilevel energy management problem is formulated as a stochastic form in a longterm horizon.Since there are uncertain system parameters,time-coupled queue constraints and the interplay of bilevel decision-making,it is challenging to solve the formulated problems.To this end,we derive a form of relaxation based on Lyapunov optimization technique to make the energy management problem tractable without forecasting the related system parameters.The transaction between nanogrids and PME is captured by a one-leader and multi-follower Stackelberg game framework.Then,theoretical analysis of the existence and uniqueness of Stackelberg equilibrium(SE)is developed based on the proposed game property.Following that,we devise an optimization algorithm to reach the SE with less information exchange.Numerical experiments validate the effectiveness of the proposed approach.
分 类 号:TM73[电气工程—电力系统及自动化] O225[理学—运筹学与控制论]
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