成果報告書詳細
管理番号20150000000370
タイトル*平成26年度中間年報 安全・低コスト大規模蓄電システム技術開発 共通基盤研究 系統安定化用蓄電システムの劣化診断基盤技術の開発
公開日2015/6/16
報告書年度2014 - 2014
委託先名学校法人早稲田大学
プロジェクト番号P11007
部署名スマートコミュニティ部
和文要約
英文要約Development of Safety and Cost Competitive Energy Storage System for Renewable Energy
Diagnosis Technology Development of Energy Storage System for Grid Stabilization

FY2014 Annual Report (FY2014-2015)
Waseda University

This project aims to develop diagnosis technology of energy storage system for grid stabilization, and to contribute to introductions of the next generation natural energy equipment of the photovoltaic generation and wind power generation with energy storage system by the development of the diagnosis technology. In this project, "diagnosis technology development of large scale energy storage system" and "development of generation system for electric power change profile" were investigated for development of energy storage system for grid stabilization.
The capacity and the internal resistance of large-scale lithium ion batteries (LIBs) become higher and lower, respectively, for the application to electric vehicles and large-scale power storage systems. Electrochemical impedance spectroscopy (EIS) using conventional frequency response analyzer (FRA) - potentiostat systems is not easy to measure the impedance of the LIB because of its low internal resistance. In this situation, we focused on the power controller of LIB system to create a square wave for analyzing the battery health. In previous year, Square-current Electrochemical Impedance Spectroscopy (SC-EIS) was developed as a new technique for EIS using the technique of fourier transform. Thus, SC-EIS to lithium-ion batteries in operation for diagnosis technology was investigated. Operation profiles with square current for SC-EIS were made and SC-EIS measurement was carried out. As a result, impedance response was successfully obtained to be able to use high accuracy analysis of battery diagnosis. Moreover, measurement of LIB module (12 LIBs in 2 parallel, 6 series) could be also achieved by SC-EIS.
Assuming the way of using the storage battery that is located in the power system, we need a preliminary test of energy storage diagnosis under plausible charge-discharge profiles. We have developed a procedure for generating plausible synthetic residential power load profiles by using the clustering result; the generated load profiles hold the statistical properties such as yearly power usage and cluster ratio of the real-world load data so as to express regional characteristics. We have also developed methods for generating synthetic profiles of renewable energy sources generated from photovoltaic solar panels and wind turbines; the generated profiles reflects the time-series statistical structure of the real-world datasets from the viewpoint of auto-correlation function and also reflects their regional characteristics. We derived charge-discharge profiles for energy storage diagnosis by performing power flow calculation on the typical power distribution system based on the generated synthetic profiles.
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