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Short-Term Deterministic Solar Irradiance Forecasting Considering a Heuristics-Based, Operational Approach

Author

Listed:
  • Armando Castillejo-Cuberos

    (Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Vicuña Mackenna 4860, Santiago 7820436, Chile)

  • John Boland

    (UniSA STEM, University of South Australia, Mawson Lakes, Adelaide, SA 5095, Australia)

  • Rodrigo Escobar

    (Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Vicuña Mackenna 4860, Santiago 7820436, Chile
    Centro del Desierto de Atacama, Pontificia Universidad Católica de Chile, Vicuña Mackenna 4860, Santiago 7820436, Chile)

Abstract

Solar energy is an economic and clean power source subject to natural variability, while energy storage might attenuate it, ultimately, effective and operationally feasible forecasting techniques for energy management are needed for better grid integration. This work presents a novel deterministic forecast method considering: irradiance pattern classification, Markov chains, fuzzy logic and an operational approach. The method developed was applied in a rolling manner for six years to a target location with no prior data to assess performance and its changes as new local data becomes available. Clearness index, diffuse fraction and irradiance hourly forecasts are analyzed on a yearly basis but also for 20 day types, and compared against smart persistence. Results show the proposed method outperforms smart persistence by ~10% for clearness index and diffuse fraction on the base case, but there are significant differences across the 20 day types analyzed, reaching up to +60% for clear days. Forecast lead time has the greatest impact in forecasting performance, which is important for any practical implementation. Seasonality in data gaps or rejected data can have a definite effect in performance assessment. A novel, comprehensive and detailed analysis framework was shown to present a better assessment of forecasters’ performance.

Suggested Citation

  • Armando Castillejo-Cuberos & John Boland & Rodrigo Escobar, 2021. "Short-Term Deterministic Solar Irradiance Forecasting Considering a Heuristics-Based, Operational Approach," Energies, MDPI, vol. 14(18), pages 1-24, September.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:18:p:6005-:d:640192
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    References listed on IDEAS

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    Cited by:

    1. Castillejo-Cuberos, A. & Cardemil, J.M. & Escobar, R., 2023. "Techno-economic assessment of photovoltaic plants considering high temporal resolution and non-linear dynamics of battery storage," Applied Energy, Elsevier, vol. 334(C).
    2. Castillejo-Cuberos, A. & Cardemil, J.M. & Escobar, R., 2024. "Temporal upscaling of solar radiation components using an analytical model for variability modeling," Renewable Energy, Elsevier, vol. 229(C).

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