成果報告書詳細
管理番号20120000000415
タイトル*平成22年度中間年報 蓄電複合システム化技術開発 共通基盤技術開発 蓄電池を用いたエネルギーマネジメントシステム性能評価モデルの開発 
公開日2012/6/27
報告書年度2010 - 2010
委託先名国立大学法人大阪大学 国立大学法人東京大学
プロジェクト番号P10008
部署名スマートコミュニティ部
和文要約和文要約等以下本編抜粋:
1. 研究開発の内容及び成果等
本事業は蓄電池を活用したエネルギーマネジメントシステムの性能評価モデル(図1)を開発する。評価モデルが評価する項目は以下の2点である:
・ 蓄電池による分散型電源導入時の系統電力システムへの影響の緩和効果
・ 分散型電源、蓄電池を含む次世代エネルギー・社会システムの二酸化炭素排出量削減効果
1)「建築・コミュニティエネルギー需給モデル」は蓄電池利用シーン(住宅・建物、街区など)における電力需要および分散型電源発電量をボトムアップ方式で分単位で推計する数値モデルであり、大阪大学下田・山口・矢吹が開発を担当する。
英文要約Title:
R&D of Practical and integrated Energy storage systems for smart community/ Fundamental Technology Development/ Development of Evaluation Model of Energy Management Systems using Electrical Energy Storage Systems
The purpose of this project is to develop a model to evaluate the performance of energy management systems using electrical energy storage systems. The model consists of the following sub-models:
* Building/community energy demand model
* Energy management system model
* Electrical grid system model
* Future scenario simulator
 The building/community energy demand model estimates high resolution electricity demand profile of buildings and community as well as output of distributed generators such as photovoltaics. In the fiscal year 2010, the specification of the model was developed.
 The energy management system model contains a detailed model of electrical energy storage systems in which the dynamic behavior of energy storage apparatus and storage unit is simulated. This result is used to determine the operation of installed electrical energy storage system while take into account energy demand and energy price to maximize the energy and economic performance. In the fiscal year 2010, the electrical characterization system for the modeling of packaged electrical energy storage system unit was developed. The characterization system is developed to linearize the nonlinear phenomenon occurring in the energy storage unit, which stem from the complex reaction and operation in the dynamical behavior of energy storage apparatus, and the dynamical modeling of the system became easier. The system injects small ac measurement signal into the testing energy storage module and measures the gain and phase of the response. The measurement frequency is swept for frequency characterization. Thus, the developed frequency response analyzing system enables to characterize from mHz to kHz in wide frequency band. Also, the validity of the characterization system is confirmed.
 The electrical grid system model evaluates the impact of local electricity demand/supply balance on the electrical grid system in terms of voltage control in distribution networks, frequency stability of currency and composition of electricity generation sources. In the fiscal year 2010, potential problems and methods to overcome these problems were surveyed. Additionally, to evaluate an effect of energy management systems on voltage control in distribution networks, a load flow calculation tool for the V-connected 3-phase 4-wired low voltage network as one of standard system configurations was developed.
 The future scenario simulator is used to simulate situations in the future in which a variety of socio-technical changes might have taken place. The abovementioned three sub-models use a number of external parameters that cannot be easily set up due to the uncertainty when the models are applied to future situations. The future scenario simulator generates a list of external parameters so that the parameters are coherent to other published sources such as roadmaps on key technologies and projection of population and social environment. In order to develop the specification of the simulator, in the fiscal year 2010, a scenario on diffusion of electric vehicles to be used as an energy management device has been developed. Technology roadmaps, scenarios, and other information related to electric vehicles and batteries were gathered, structured and archived. Toward developing the future scenario simulator, additional functions has been integrated into an existing tool (3S Simulator), such as design support for forecasting scenarios, what-if analysis, and support for composing scenario variants.
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