Optimal Allocation and Sizing of BESS Based on a Reliability-Oriented Planning Approach for Transmission Systems

Planning battery energy storage systems (BESS) in transmission networks requires accounting for the effects of component failures on supply continuity. This paper proposes a reliability-oriented methodology based on a Mixed Gray Wolf Optimizer (MGWO) to determine BESS locations, rated active power capacities, and technology selection between lithium-ion (Li-ion) and vanadium redox flow (VRF) batteries. The framework incorporates stochastic reliability models for transmission lines, transformers, busbars, and BESS units. The objective is to minimize the equally weighted average of annual energy not supplied (ENS) across single-generator-outage scenarios, subject to technical constraints and an investment budget. BESS sizing refers to rated power in MW; energy capacity and chronological state of charge are not explicitly modeled. The methodology is evaluated using the IEEE 39-bus New England test system with representative hourly demand profiles. Under a maximum investment budget of USD 300 million, the selected solution comprises 338.66 MW of installed BESS capacity, including 280.78 MW of Li-ion storage and 57.88 MW of VRF storage, at a total investment of USD 299.87 million. Relative to the reference case, SAIDI and SAIFI decrease by 13.76% and 13.11%, respectively. During optimization, the fitness value decreases from approximately 0.878 to 0.828 p.u., representing an improvement of about 6.5% relative to the initial solution. Ten independent runs yield final fitness values between 0.8213 and 0.8300 p.u. These results demonstrate the framework’s ability to identify feasible BESS configurations that improve reliability under the adopted modeling assumptions.

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Publication Details

Journal
Electricity
Published
2026-11-03
DOI
https://doi.org/10.3390/electricity7040136
Primary Topic
Power System Reliability and Maintenance
Type
article
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article

Optimal Allocation and Sizing of BESS Based on a Reliability-Oriented Planning Approach for Transmission Systems

Rafael Peña Gallardo, Jorge Iván Silva Ortega, J. Marín-Quintero, César Augusto Orozco-Henao et al.
Electricity
Power System Reliability and Maintenance
article

Optimal Allocation and Sizing of BESS Based on a Reliability-Oriented Planning Approach for Transmission Systems

Rafael Peña Gallardo, Jorge Iván Silva Ortega, J. Marín-Quintero, César Augusto Orozco-Henao, A. Herrera-Orozco, Sergio Díaz Pérez
article en

Abstract

Planning battery energy storage systems (BESS) in transmission networks requires accounting for the effects of component failures on supply continuity. This paper proposes a reliability-oriented methodology based on a Mixed Gray Wolf Optimizer (MGWO) to determine BESS locations, rated active power capacities, and technology selection between lithium-ion (Li-ion) and vanadium redox flow (VRF) batteries. The framework incorporates stochastic reliability models for transmission lines, transformers, busbars, and BESS units. The objective is to minimize the equally weighted average of annual energy not supplied (ENS) across single-generator-outage scenarios, subject to technical constraints and an investment budget. BESS sizing refers to rated power in MW; energy capacity and chronological state of charge are not explicitly modeled. The methodology is evaluated using the IEEE 39-bus New England test system with representative hourly demand profiles. Under a maximum investment budget of USD 300 million, the selected solution comprises 338.66 MW of installed BESS capacity, including 280.78 MW of Li-ion storage and 57.88 MW of VRF storage, at a total investment of USD 299.87 million. Relative to the reference case, SAIDI and SAIFI decrease by 13.76% and 13.11%, respectively. During optimization, the fitness value decreases from approximately 0.878 to 0.828 p.u., representing an improvement of about 6.5% relative to the initial solution. Ten independent runs yield final fitness values between 0.8213 and 0.8300 p.u. These results demonstrate the framework’s ability to identify feasible BESS configurations that improve reliability under the adopted modeling assumptions.

ElectricityVol. 7(4)
Universidad Industrial de Santander (CO), Autonomous University of San Luis Potosí (MX), Technological University of Pereira (CO), University of the Coast (CO)
Openalex Percentile: Top 15%
Power System Reliability and Maintenance
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