What question did this study set out to answer?

To develop a multi-period optimal power flow model that manages charging demands from plug-in hybrid electric vehicles under various contingency conditions.

June 20, 2026Energy Storage

Multi‐Period Optimal Power Flow of Thermal–Wind Systems With Battery Storage and Static Synchronous Compensator Under High Electric Vehicle Charging Demand and Contingency Conditions

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Authors

DBDhiman Banerjee PRProvas Kumar Roy GPGoutam Kumar Panda

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Overview

Randomized trial examines power flow management in thermal-wind systems during peak EV charging, indicating enhanced efficiency and reliability.

Key Points

To develop a multi-period optimal power flow model that manages charging demands from plug-in hybrid electric vehicles under various contingency conditions.
Developed a contingency-based multi-period optimal power flow model for a thermal-wind-battery energy storage system.
Implemented a BESS model considering charging-discharging dynamics and operational constraints.
Used a quasi-oppositional birds-of-prey-based optimization algorithm to solve the MP-OPF problem.
Combined operation of wind and battery storage significantly reduces peak-hour system stress caused by PHEV charging.
Incorporation of STATCOM improves voltage regulation and lowers generation costs by reducing transmission losses.
The proposed algorithm provides higher quality and more robust solutions compared to existing sophisticated methods.

Cite This Study

Banerjee et al. (2026) studied this question.

synapsesocial.com/papers/6a363123db0793dc1a5381ac https://doi.org/10.1002/est2.70447

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June 20, 2026Energy Storage

Multi‐Period Optimal Power Flow of Thermal–Wind Systems With Battery Storage and Static Synchronous Compensator Under High Electric Vehicle Charging Demand and Contingency Conditions

View Full Paper

Ask AI

Bookmark

Authors

DBDhiman Banerjee PRProvas Kumar Roy GPGoutam Kumar Panda

Discussion

Member takes

Overview

Randomized trial examines power flow management in thermal-wind systems during peak EV charging, indicating enhanced efficiency and reliability.

Key Points

To develop a multi-period optimal power flow model that manages charging demands from plug-in hybrid electric vehicles under various contingency conditions.
Developed a contingency-based multi-period optimal power flow model for a thermal-wind-battery energy storage system.
Implemented a BESS model considering charging-discharging dynamics and operational constraints.
Used a quasi-oppositional birds-of-prey-based optimization algorithm to solve the MP-OPF problem.
Combined operation of wind and battery storage significantly reduces peak-hour system stress caused by PHEV charging.
Incorporation of STATCOM improves voltage regulation and lowers generation costs by reducing transmission losses.
The proposed algorithm provides higher quality and more robust solutions compared to existing sophisticated methods.

Cite This Study

Banerjee et al. (2026) studied this question.

synapsesocial.com/papers/6a363123db0793dc1a5381ac https://doi.org/10.1002/est2.70447

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