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面向提高风电接纳能力的智慧建筑能量管理策略 被引量:7

Energy Management Strategy of Smart Buildings for Improving Wind Power Accommodation Ability
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摘要 提出一种面向提高风电接纳能力的智慧建筑能量管理策略。首先,基于建筑热惯性,构建考虑建筑物内部不同制热区域的能耗预测模型;其次,基于支路潮流模型与二阶锥松弛方法,构建集成智慧建筑的主动配电网(active distribution network,ADN)统一数学模型。随后,基于模型预测控制方法,在保证用户舒适性前提下,对ADN进行能量管理;最后,基于冬季制热场景,通过多种暖通空调(heating,ventilation and air conditioning,HVAC)调控方案对智慧建筑参与ADN优化调度进行分析验证。算例表明,与未考虑ADN与智慧建筑集成的模型及方法相比,所提方法基于集成智慧建筑的ADN统一模型,充分利用了HVAC设备运行模式灵活性和居民舒适温度区间,在保障居民温度舒适性的同时,进一步提高电网的风电接纳能力,并保证ADN的经济安全运行。 An energy management strategy of smart buildings for improving wind power accommodation ability is proposed.Firstly,based on the thermal inertia of buildings,the energy consumption prediction model considering the different heating zones in the building is constructed.Secondly,based on the branch flow model and the second-order conic relaxation,a unified mathematical model of the active distribution network(ADN)with integrated smart buildings is further constructed.Then,based on the model predictive control method,under the premise of ensuring the comfort temperature for the residents,the energy management of the ADN is achieved.Finally,based on the winter heating scenario,various control schemes for the HVAC systems are used to analyze and verify the participation of smart buildings in the ADN optimal scheduling.Numerical studies demonstrate that,compared with the model and method without considering the integration of ADN and smart buildings,the proposed method,based on the unified model of ADN with integrated smart buildings,can fully utilize the flexibility of operational modes of the HVAC systems and the residents’comfortable temperature range.While ensuring the comfort temperature for the residents,the wind power accommodation ability of the power grid is further improved,and the economic and secure operation of the ADN is guaranteed.
作者 李泽宁 苏粟 靳小龙 陈厚合 韦存昊 赵梓期 LI Zening;SU Su;JIN Xiaolong;CHEN Houhe;WEI Cunhao;ZHAO Ziqi(National Active Distribution Network Technology Research Center,Beijing Jiaotong University,Haidian District,Beijing 100044,China;Center for Electric Power and Energy,Technical University of Denmark,2800 Kgs.Lyngby,Denmark;Department of Electrical Engineering,Northeast Electric Power University,Jilin 135012,Jilin Province,China;Baishan Power Supply Company,State Grid Jilin Power Co.,Ltd.,Baishan 134300,Jilin Province,China)
出处 《电网技术》 EI CSCD 北大核心 2021年第6期2288-2298,共11页 Power System Technology
基金 国家自然科学基金项目(51677004)。
关键词 主动配电网 智慧建筑 暖通空调系统 二阶锥松弛 模型预测控制 active distribution network smart building heating, ventilation and air conditioning system second-order cone relaxation model predictive control
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