한국전자통신학회논문지 (The Journal of the Korea institute of electronic communication sciences)

한국전자통신학회 (Korea Institute of Electronic Communication Science)
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태양광발전설비 원격 관제를 위한 빅데이터 분석 및 처리

Big Data Analysis and Processing for Remote Control of PV Facilities

  • 투고 : 2018.05.31
  • 심사 : 2018.08.15
  • 발행 : 2018.08.31
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초록

신재생에너지의 발전량 변동에 따라 기존 발전기의 발전량을 증가시키거나 감소시켜야 하는데, 발전량 증 감발에 빠르게 반응을 하는 발전기들은 상대적으로 발전비용이 크므로 태양광발전의 예측 정확도에 따라서 기동발전계획의 비용 효율성이 영향을 받게 된다. 이에 본 논문에서는 태양광 발전량 예측의 불확실성을 최소화하기 위하여 빅데이터 분석 및 처리를 적용한 태양광발전설비 원격관제 시스템을 제안하였다.

In order to increase the generation of renewable energy, it is necessary to increase or decrease the generation amount of existing generators. The generators that respond rapidly to increase / decrease the generation amount generally have high generation cost. Therefore, Cost effectiveness is affected. In this paper, we propose a PV remote control system with big data to minimize the uncertainty of solar power generation prediction.

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참고문헌

  1. H. Kim, H. Yoo, Y. Lee, and Y. Ko, "ESS Connected PV Monitoring System Supporting Redundant Communications," J. of the Korea Institute of Electronic Communication Sciences, vol. 13, no. 1, Feb. 2018, pp. 1099-1106.
  2. Y. Park, "Study on the Development Strategies of Korean-type Renewable Energy for the Environment Protection," New & Renewable Energy, vol. 12, no. 4, Dec. 2015, pp. 19-30.
  3. S. Oh, P. Ihm, and K. Lee, "Optimal Electric Generation for Fixed-Type Photovoltaic System Installed for Residential Building in Korea," Gyeonggi Research Institute REVIEW, vol. 14, no. 2, 2012, pp. 271-288.
  4. J. Joo, Y. Gee, and J. Oh, "A Study on the SPWM based Power Conversion Technology of the Three-Phase Photovoltaic Inverter Using DSP," J. of the Korea Institute of Electronic Communication Sciences, vol. 12, no. 6, Dec. 2017, pp. 29-34.
  5. D. Yang, N. Yeo, and P. Mah, "A Dynamic Piecewise Prediction Model of Solar Insolation for Efficient Photovoltaic Systems," Korean Institute of Information Scientists and Engineers Transactions on Computing Practices, vol. 23, no. 11, Nov, 2017, pp. 632-640.
  6. K. Lee and W. Kim, "Forecasting of 24_hours Ahead Photovoltaic Power Output Using Support Vector Regression", J. of Korean Institute of Information Technology, vol. 13, no.3, Mar. 2016, pp. 175-183. https://doi.org/10.14801/jkiit.2015.13.3.175
  7. D. Shin, J. Pak, and C. Kim, "Photovoltaic Generation Forecasting Using Weather Forecast and Predictive Sunshine and Radiation," J. of Advanced Navigation Technology, vol. 21, no. 6, Dec. 2017, pp. 643-650. https://doi.org/10.12673/JANT.2017.21.6.643
  8. Korea Electric Power Corporation Economy & Management Research Institute, "Research Issue," Korea Electric Power Corporation Economy & Management Research Institute Power Economy Review, Oct. 2017.
  9. Y. Lee, "Specific point weather prediction base new and renewable energy producing quantity real-time prediction method and the system," Korea Patent, no. 1010353980000, May 11, 2011.
  10. TTAK. KO-04.0179, Data Format for Monitoring of a Photovoltaic System. Telecommunications Technology Association, ICT Standardization Committee, Korea, Dec. 2013.