| 引用本文: | 白牧可,唐巍,吴聪,徐鸥洋,冯洪涛.基于热网-电网综合潮流的用户侧微型能源站及接入网络优化规划[J].电力自动化设备,2017,37(6): |
| BAI Muke,TANG Wei,WU Cong,XU Ouyang,FENG Hongtao.Optimal planning based on integrated thermal-electric power flow for user-side micro energy station and its integrating network[J].Electric Power Automation Equipment,2017,37(6): |
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| 摘要: |
| 提出一种考虑热网-电网综合潮流的用户侧综合能源系统的规划方法。考虑经济、节能、环保等因素，建立含风机、光伏、储能、微型燃气轮机及燃气锅炉的微型能源站二层规划模型。上层规划目标函数为年费用最小，优化变量为微型能源站安装位置、容量及接入网络；下层规划考虑储能与微型燃气轮机的优化调度，规划目标包含一次能源节约率、可控分布式能源运行费及网损费用。基于热电耦合，提出热网-电网综合潮流计算方法与流程。采用改进遗传算法和粒子群优化算法对模型进行求解。某用户侧综合能源系统算例验证了所提模型和方法的有效性。 |
| 关键词: 用户侧综合能源系统 微型能源站 热网-电网综合潮流 二层规划 优化调度 模型 |
| DOI：10.16081/j.issn.1006-6047.2017.06.012 |
| 分类号:TM732 |
| 基金项目:国家自然科学基金资助项目(51377162) |
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| Optimal planning based on integrated thermal-electric power flow for user-side micro energy station and its integrating network |
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BAI Muke, TANG Wei, WU Cong, XU Ouyang, FENG Hongtao
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College of Information and Electrical Engineering, China Agriculture University, Beijing 100083, China
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| Abstract: |
| A planning method based on the integrated thermal-electric power flow is proposed for the user-side IES(Integrated Energy System),and a bi-level planning model considering the factors of economy, energy-saving, environmental protection, etc. is built for the micro energy station with wind turbine, photovoltaic cell, energy storage, micro gas turbine and gas boiler. The upper level of the planning model takes the minimum annual cost as its optimization objective and considers the installation location, capacity and integrating network of micro energy station as its optimization variables; while the lower level of the planning model considers the optimal dispatch of energy storage and micro gas turbine and includes the primary energy saving rate, the operational cost of controllable distribution energies and the network loss in its planning objectives. The method and flowchart for calculating the integrated thermal-electrical power flow are proposed based on the interconnection of thermal and electric networks. The improved genetic algorithm and particle swarm optimization method are adopted to solve the model. A user-side IES is taken as an example to verify the effectiveness of the proposed model and method. |
| Key words: user-side integrated energy system micro energy station integrated thermal-electric power flow bi-level planning optimal dispatch models |
