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Renewable Energy Curtailment: Prediction Using a Logic-Based Forecasting Method and Mitigation Measures in Kyushu, Japan

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  • Alex Bunodiere

    (Graduate School for International Development and Cooperation (IDEC), Hiroshima University, 1-5-1 Kagamiyama, Higashi-Hiroshima, Hiroshima 739-8529, Japan)

  • Han Soo Lee

    (Transdisciplinary Science and Engineering Program, Graduate School of Advanced Science and Engineering, Hiroshima University, Hiroshima 739-8529, Japan)

Abstract

High variable renewable energy (VRE) penetration led to the first-ever VRE curtailment in Japan, occurring in Kyushu in October 2018. Since then, there has been an average of 3% solar curtailment, with a peak of 13.7% in April 2019, resulting in approximately ¥9.6 billion of wasted energy. The VRE curtailment is expected to worsen as VRE penetration continues to increase along with nuclear energy increment in line with Japan’s 2030 energy goals. To prevent this curtailment and increase energy stability, a novel, logic-based forecasting method using hourly supply/demand data was developed. Initially, inaccurate results were returned; however, after several rounds of calibration that adjusted the quartile value of the max/min operating windows, the overall accuracy of this method was increased to 97% of real curtailment. This calibrated model was then used to test several curtailment mitigation scenarios. Some scenarios increased curtailment, while the two most successful scenarios, which reduced the installed nuclear capacity either seasonally or totally, limited curtailment by 95% and 97%, respectively. Another scenario with increased grid interconnection between regions reduced curtailment by 79%. Moreover, it would provide other benefits by unifying the national grid thereby increasing disaster resistance, reducing curtailment, improving grid flexibility and allowing for higher VRE penetrations. Currently, the situation is worsening, and some actions are required to reduce the curtailment and to achieve its 2030 energy goals in Japan. The mitigation measures studied by the logic method could be recommended to be referred to.

Suggested Citation

  • Alex Bunodiere & Han Soo Lee, 2020. "Renewable Energy Curtailment: Prediction Using a Logic-Based Forecasting Method and Mitigation Measures in Kyushu, Japan," Energies, MDPI, vol. 13(18), pages 1-26, September.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:18:p:4703-:d:411177
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    References listed on IDEAS

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    Cited by:

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    2. Julia Morgan & Casey Canfield, 2021. "Comparing Behavioral Theories to Predict Consumer Interest to Participate in Energy Sharing," Sustainability, MDPI, vol. 13(14), pages 1-17, July.
    3. Samuel Matthew G. Dumlao & Keiichi N. Ishihara, 2021. "Weather-Driven Scenario Analysis for Decommissioning Coal Power Plants in High PV Penetration Grids," Energies, MDPI, vol. 14(9), pages 1-23, April.

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