A review on the integration of probabilistic solar forecasting in power systems

Li, Binghui; Zhang, Jie

doi:10.1016/j.solener.2020.07.066

A review on the integration of probabilistic solar forecasting in power systems

Journal Article · Tue Sep 15 00:00:00 EDT 2020 · Solar Energy

DOI:https://doi.org/10.1016/j.solener.2020.07.066· OSTI ID:1848714

^[1]; Zhang, Jie ^[2]

Univ. of Texas at Dallas, Richardson, TX (United States); Univ. of Texas at Dallas, Richardson, TX (United States)
Univ. of Texas at Dallas, Richardson, TX (United States)

As one of the fastest growing renewable energy sources, the integration of solar power poses great challenges to power systems due to its variable and uncertain nature. As an effective approach to promote the integration of solar power in power systems, the value of probabilistic forecasts is being increasingly recognized in the recent decade. While the current use of probabilistic forecasts in power systems is limited, enormous amount of research has been conducted to promote the adoption of probabilistic forecasts and many methods have been proposed. This paper gives a comprehensive review on how probabilistic solar forecasts are utilized in power systems to address the challenges. Potential methods to deal with uncertainties in power systems are summarized, such as probabilistic load flow models, stochastic optimization, robust optimization, and chance constraints. Additionally, specific areas where these methods can be applied are discussed and state-of-the-art studies are summarized.

View Accepted Manuscript (DOE)

Research Organization:: Johns Hopkins Univ., Baltimore, MD (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE)

Grant/Contract Number:: EE0008215

OSTI ID:: 1848714

Alternate ID(s):: OSTI ID: 1776214

Journal Information:: Solar Energy, Journal Name: Solar Energy Journal Issue: C Vol. 210; ISSN 0038-092X

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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