Analytic Neural Network Gaussian Process Enabled Chance-Constrained Voltage Regulation for Active Distribution Systems with PVs, Batteries and EVs

Su, Tong; Zhao, Junbo; Pei, Yansong; Yao, Yiyun; Ding, Fei

doi:10.1109/TPWRS.2024.3502114

Analytic Neural Network Gaussian Process Enabled Chance-Constrained Voltage Regulation for Active Distribution Systems with PVs, Batteries and EVs

Journal Article · Tue Nov 19 04:00:00 EST 2024 · IEEE Transactions on Power Systems

DOI:https://doi.org/10.1109/TPWRS.2024.3502114· OSTI ID:2480814

Su, Tong; Zhao, Junbo; Pei, Yansong; ; Ding, Fei

This paper proposes an analytic neural network Gaussian process (NNGP)-based chance-constrained real-time voltage regulation method for active distribution systems with photovoltaics (PVs), batteries, and electric vehicles (EVs). NNGP can utilize historical measurement data to achieve real-time probabilistic node voltage estimation through Bayesian inference. Then, NNGP is fully analytically embedded into the optimal power flow model to perform voltage regulation and adapt to various topological changes. The uncertainties of voltage estimations are easily considered via the chance constraint, and it has been shown that the adoption of this chance constraint can significantly improve the reliability of voltage regulation under various scenarios. The comparison results with other methods, carried out on a real 759-node distribution system located in western Colorado, U.S., show that the proposed method can achieve accurate voltage estimation across different topologies and reliably perform voltage regulation considering PVs, batteries, and EVs.

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:: 2480814

Report Number(s):: NREL/JA-5D00-92415; MainId:94196; UUID:8c8de432-fa5c-422a-a840-3178cecd4d81; MainAdminId:75474

Journal Information:: IEEE Transactions on Power Systems, Journal Name: IEEE Transactions on Power Systems Journal Issue: 3 Vol. 40

Country of Publication:: United States

Language:: English

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Analytic Neural Network Gaussian Process Enabled Chance-Constrained Voltage Regulation for Active Distribution Systems with PVs, Batteries and EVs

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