Regenerative Grid-Forming Inverter with Energy Storage for Next-Generation Power Systems

With the high penetration of renewable energy sources, the next-generation power grid has become more sensitive to frequency and voltage fluctuations due to low inertia. Implementing a battery energy storage system (BESS) as an energy source provides a flexible and scalable solution to support grid frequency, manage peak and off-peak demand, and address load disturbances in a power electronic-dominated grid (PEDG). However, integrating BESS into such grids presents several challenges in efficiently controlling charging and discharging operations while maintaining battery health. To address this issue, this paper presents an algorithm for incorporating the BESS into a PEDG using a grid-forming inverter to act as an electric spring to maintain stable grid frequency and voltage levels during disruptions and high demand. The proposed algorithm can seamlessly switch from voltage to current control when charging the batteries and vice versa during the nominal operation to support the grid frequency. Based on the power reserve in the PEDG, load disturbances, and the battery's state of charge (SoC), the proposed power electronics for BESS act as an electric spring during load/generation disturbances, peak, and off-peak hours. Moreover, based on the SoC, the proposed electric spring algorithm (PESA) controls the amount of power injections or absorption to discharge or charge the batteries optimally. Multiple case studies are simulated to demonstrate the PESA's effectiveness in improving the frequency response during load/generation disturbances and seamlessly switching between power injection, absorption, and standby modes.

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Published
2025-06-20
DOI
https://doi.org/10.1109/isie62713.2025.11124730
Primary Topic
Electric Power Systems and Control
Type
article
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article

Regenerative Grid-Forming Inverter with Energy Storage for Next-Generation Power Systems

Mohammad B. Shadmand, Uzair Asif, Michael Lteif
Electric Power Systems and Control
article

Regenerative Grid-Forming Inverter with Energy Storage for Next-Generation Power Systems

Mohammad B. Shadmand, Uzair Asif, Michael Lteif
article en

Abstract

With the high penetration of renewable energy sources, the next-generation power grid has become more sensitive to frequency and voltage fluctuations due to low inertia. Implementing a battery energy storage system (BESS) as an energy source provides a flexible and scalable solution to support grid frequency, manage peak and off-peak demand, and address load disturbances in a power electronic-dominated grid (PEDG). However, integrating BESS into such grids presents several challenges in efficiently controlling charging and discharging operations while maintaining battery health. To address this issue, this paper presents an algorithm for incorporating the BESS into a PEDG using a grid-forming inverter to act as an electric spring to maintain stable grid frequency and voltage levels during disruptions and high demand. The proposed algorithm can seamlessly switch from voltage to current control when charging the batteries and vice versa during the nominal operation to support the grid frequency. Based on the power reserve in the PEDG, load disturbances, and the battery's state of charge (SoC), the proposed power electronics for BESS act as an electric spring during load/generation disturbances, peak, and off-peak hours. Moreover, based on the SoC, the proposed electric spring algorithm (PESA) controls the amount of power injections or absorption to discharge or charge the batteries optimally. Multiple case studies are simulated to demonstrate the PESA's effectiveness in improving the frequency response during load/generation disturbances and seamlessly switching between power injection, absorption, and standby modes.

University of Illinois Chicago (US), University of Chicago (US)
Affordable and clean energy
Openalex Percentile: Top 79%
Electric Power Systems and Control
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Regenerative Grid-Forming Inverter with Energy Storage for Next-Generation Power Systems — Mohammad B. Shadmand, Uzair Asif, et al. · (2025) | TGRS Research Map | TGRS