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文章摘要
考虑功率波动及储能寿命的微电网储能容量优化配置
Optimal Allocation of Microgrid Energy Storage Capacity Considering Power Fluctuation and Energy Storage Life
Received:September 10, 2019  Revised:September 10, 2019
DOI:10.19753/j.issn1001-1390.2021.10.009
中文关键词: 微电网  可再生能源  寿命因素  储能
英文关键词: microgrid  renewable energy  life factor  energy storage
基金项目:
Author NameAffiliationE-mail
zhangyue* South China University of Technology, zhangyue0350@126.com 
liuwenze South China University of Technology, liuwzh@scut.edu.cn 
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中文摘要:
      高比例接入可再生能源的独立运行微电网中,针对其出力与负荷功率的不确定和波动性、可再生能源存在浪费的情况,需要优化配置储能容量,使整个微电网的运行达到污染排放最小和经济性最高。在储能容量优化规划中采用双层优化模型,外层优化模型负责求解微电网系统储能容量规划投资问题,内层模型考虑在运行过程中运行成本、储能寿命损耗、污染气体排放问题。其中,利用雨流计数法计算储能寿命,可充分考虑影响储能设备寿命的各个因素。然后,采用粒子群双层优化算法对微电网进行储能容量优化计算,结果验证了此方法的可行性。最后,对比固定寿命、精确寿命两种计算方式以及对比排放最低模式、寿命优化模式两种优化方式,对储能容量配置及运行方式提供有效的建议。
英文摘要:
      In the independent operation of microgrid with high proportion of renewable energy, in view of uncertainties and fluctuations of its output and load power, and waste of renewable energy, it is necessary to optimize the allocation of energy storage capacity so that the operation of the whole microgrid can achieve the minimum pollution emissions and the highest economy. In the optimization planning of energy storage capacity, a two-level optimization model is adopted. The outer optimization model is responsible for solving the investment problem of energy storage capacity planning of microgrid system. The inner model considers the operation cost, energy storage life loss and pollution gas emission during operation. Among them, the rainflow counting method can be used to calculate the life of energy storage equipment, which can fully consider the factors affecting the life of energy storage equipment. Then, the particle swarm optimization algorithm is used to optimize the energy storage capacity of the microgrid, and the results verify the feasibility of this method. Finally, comparing the two calculation methods of fixed life and exact life, as well as the two optimization methods of minimum emission mode and life optimization mode, it provides effective suggestions for the allocation and operation mode of energy storage capacity.
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