Cross-Correlated Scenario Generation for Renewable-Rich Power Systems Using Implicit Generative Models

Dhaval Dalal, Muhammad Bilal, Hritik Shah, Anwarul Islam Sifat, Anamitra Pal () and Philip Augustin
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Dhaval Dalal: School of Electrical, Computer, and Energy Engineering, Arizona State University, Tempe, AZ 85281, USA
Muhammad Bilal: School of Electrical, Computer, and Energy Engineering, Arizona State University, Tempe, AZ 85281, USA
Hritik Shah: School of Electrical, Computer, and Energy Engineering, Arizona State University, Tempe, AZ 85281, USA
Anwarul Islam Sifat: School of Electrical, Computer, and Energy Engineering, Arizona State University, Tempe, AZ 85281, USA
Anamitra Pal: School of Electrical, Computer, and Energy Engineering, Arizona State University, Tempe, AZ 85281, USA
Philip Augustin: Salt River Project (SRP), 6504 East Thomas Road, Scottsdale, AZ 85251, USA

Energies, 2023, vol. 16, issue 4, 1-20

Abstract: Generation of realistic scenarios is an important prerequisite for analyzing the reliability of renewable-rich power systems. This paper satisfies this need by presenting an end-to-end model-free approach for creating representative power system scenarios on a seasonal basis. A conditional recurrent generative adversarial network serves as the main engine for scenario generation. Compared to prior scenario generation models that treated the variables independently or focused on short-term forecasting, the proposed implicit generative model effectively captures the cross-correlations that exist between the variables considering long-term planning. The validity of the scenarios generated using the proposed approach is demonstrated through extensive statistical evaluation and investigation of end-application results. It is shown that analysis of abnormal scenarios, which is more critical for power system resource planning, benefits the most from cross-correlated scenario generation.

Keywords: dynamic time warping; generative adversarial network; power system planning; renewable energy; scenario generation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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