Title
Simultaneous Estimation of Behind-the-Meter Solar and Wind Power at the Bulk Supply Point
Abstract
The presence of distributed energy resources in private premises has observed a large deployment worldwide driven by favorable governmental policies and technology development. In Northern Ireland, the small-scale generation capacity including solar and wind power has fast-grown accounting for over 17% of peak load in 2021, which makes net demands more volatile and diminishes the accuracy of electric demand forecasting activities. Different from traditional load forecasting methods based on the relationship between heterogeneous variables and net demand fluctuation, a novel approach is proposed to separately forecast the invisible components (e.g. wind & solar power) within the net demand. The critical challenge in the separate forecasting is how to extract behind-the-meter components from the measured net demand data, namely net demand disaggregation, for which continuous wavelet transform is applied to bring out the detailed fluctuation of net demand and an iterative search algorithm is proposed to separate the components in the net demand. The results reported show that the proposed demand disaggregation method contributes to reduce the forecasting error by more than 14%. Methods like the proposed net demand disaggregation can benefit utilities and system operators in performing their daily activities regarding load forecasting in serving areas and power systems they operate.
Year
DOI
Venue
2022
10.1109/ACCESS.2022.3194674
IEEE ACCESS
Keywords
DocType
Volume
Wind power generation, Generators, Load modeling, Renewable energy sources, Hidden Markov models, Continuous wavelet transforms, Solar power generation, Behind-the-meter generation, blind source separation, continuous wavelet transforms, net demand disaggregation
Journal
10
ISSN
Citations 
PageRank 
2169-3536
0
0.34
References 
Authors
0
7
Name
Order
Citations
PageRank
Xueqin Liu110.71
Kunyu Zuo200.34
Junyong Liu3147.16
Javier Lopez-Lorente400.34
You-bo Liu523.07
Neil Johnston600.34
David John Morrow700.34