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Office of Scientific and Technical Information
 

High-Resolution Synthetic Solar Irradiance Sequence Generation: An LSTM-Based Generative Adversarial Network

Conference ·
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The rapid growth of renewable energy resources penetration is bringing more challenges to power system planning and operation. Relevant renewable energy integration studies, such as the capability and dynamic performance of inverter-based resources' primary frequency response and fast frequency response, require high-resolution renewable generation output data that are representative of renewable energy resources. This paper focuses on creating synthetic but realistic solar irradiance data and proposes a long short-term memory-based generative adversarial network to generate high-resolution (second-level) solar irradiance sequences from low-resolution (minute-level) measurements. Combined with a classifier to recognize the solar irradiance patterns, the proposed model is trained using multi-loss functions to accurately capture the temporal correlations among both high-resolution and low-resolution sequences. Verification of the proposed approach is performed on the data set of the Oahu Solar Measurement Grid collected through the National Renewable Energy Laboratory. The results of the case studies demonstrate the proposed approach's capability to capture the statistical characteristics of different solar irradiance patterns and to generate high-quality synthetic solar irradiance sequences in high resolution.

Research Organization:
National Renewable Energy Laboratory (NREL), Golden, CO (United States)
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Solar Energy Technologies Office
DOE Contract Number:
AC36-08GO28308
OSTI ID:
2229081
Report Number(s):
NREL/CP-5D00-88226; MainId:89001; UUID:e9ac9aa1-8c64-472d-80a6-d81e8652c49c; MainAdminID:71234
Resource Relation:
Conference: Presented at the the 2023 IEEE Power & Energy Society General Meeting (PESGM), 16-20 July 2023, Orlando, Florida
Country of Publication:
United States
Language:
English

References (13)

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Locational Marginal Price Forecasting Using Convolutional Long-Short Term Memory-Based Generative Adversarial Network conference July 2021
Stochastic Model for Generation of High-Resolution Irradiance Data and Estimation of Power Output of Photovoltaic Plants journal April 2018
Solar PV Power Prediction Using A New Approach Based on Hybrid Deep Neural Network conference August 2019
Creation and Value of Synthetic High-Frequency Solar Inputs for Distribution System QSTS Simulations conference June 2017
A synthetic, spatially decorrelating solar irradiance generator and application to a LV grid model with high PV penetration journal May 2017
Stochastic generation of synthetic minutely irradiance time series derived from mean hourly weather observation data journal May 2015
Synthetic generation of high temporal resolution solar radiation data using Markov models journal May 2014

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POWER TRANSMISSION AND DISTRIBUTION
SOLAR ENERGY
dynamic scheduling
energy measurement
energy resolution
generative adversarial networks
power system dynamics
power system planning
renewable energy sources