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成果報告書詳細
管理番号20190000000213
タイトル*平成30年度中間年報 地熱発電技術研究開発 地熱エネルギーの高度利用化に係る技術開発 IoTーAI適用による小規模地熱スマート発電&熱供給の研究開発
公開日2019/5/22
報告書年度2018 - 2018
委託先名一般財団法人エンジニアリング協会 一般財団法人電力中央研究所 国立大学法人熊本大学 伊藤忠テクノソリューションズ株式会社
プロジェクト番号P13009
部署名新エネルギー部
和文要約
英文要約Title: Research and development of small-scale geothermal smart power generation & heat supply by IoT-AI application (FY2018-FY2020) FY2018 Annual Report

The objective of this project is to apply IoT-AI technology to small-scale geothermal power generation and heat supply systems, reduce the occurrence rate of troubles at power plants and heat utilization facilities by 20%, and improve calendar day utilization rate by 10%. The results for this fiscal year are as follows.
(1) Evaluation and monitoring of existing wells: Fundamental well data such as water temperature and flow mass had also collected. Futhermore, an instrument measuring temperature and pressure in the vapour phase and electrical conductivity in the liquid phase.to monitor the production well condition. Data are recorded in every minitue and are available through an internet cloud service.
(2) Business evaluation and management: Profitability Evaluation and coexistence with local community to evaluate the business profitability and the coexistence with local community, we have collected and analyzed the cost data and related information from small-scale geothermal power plants and heat utilization facilities. As the results, it was suggested that the action support of risk measures by visualizing the cost data contribute the capacity factor improvement.
(3) Operation control: From the questionnaires and interviews with small-scale geothermal power plants and heat utilization facilities etc., it was possible to grasp the current status of calendar day utilization rate, classification of trouble cause and incidence rate. We have developed a plant performance evaluation system by using EnergyWinTM and AI technology for small-scale binary power plant and analyzed the plant performance using the actual operation data. As a result, we found that the numerical data from attached display on the power generator is very useful to make maintenance easy and lower maintenance cost. We visualized the operation status and detected a sign that the cooling water flow rate would decrease three days or more before the stop of power generation. It was determined that utilization could be improved if generation interruption could be avoided by appropriate maintenance work at the stage when an abnormality sign was detected.
(4) IoT-AI system: We started POC (hypothesis verification) targeting six small-scale geothermal power plants, and showed that it could detect anomaly signs by applying predictive detection software Predict-It at four of them. In order to show the possibility of cooperation with EnergyWinTM, statistics and statistical model were built by AI development platform ReNom, and the effectiveness of IoT-AI systemization in small scale geothermal development was shown.
(5) As conclusion: Feasibility study of this year was successfully completed by executing POC of small-scale geothermal power plants.
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