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Quantitative Forecasting for Renewable Power Generation: Fuzzy Logic Approach

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Technical Report,03 Aug 2015,02 Aug 2019

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California State University - Bakersfield Bakersfield United States

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A major challenge in utilizing renewable energy resources for the electric grid is their volatility. Since electric power cannot be stored in large quantities, the balance of generation and load is critical for the operation of power systems. Therefore, system operators need to know an accurate forecast of their load and generation. While the accuracy in load forecasting is often satisfactory, satisfactory level of forecast accuracy for renewable generation is harder to achieve. The project takes advantage of fuzzy logic as a tool to model a broader range of uncertainties in renewable generation. By combining fuzzy logic and probabilistic models, the project will develop a framework that is able toaddress both stochastic and linguistic uncertainties in renewable generation. The mathematical challenge is in mixing stochastic methodologies with fuzzy logic to achieve broader methodologies. Goal 1 Involve CSUB undergraduate students in advanced research. Goal 2 Conduct research leading to development of a theoretical framework for analysis of power systems with high levels of renewable energy penetration.

Subject Categories:

  • Statistics and Probability
  • Electric Power Production and Distribution

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