Charging Requirement and Grid Impact from Electric Heavy Construction Equipment

The construction sector contributes around 37 % of global CO2 emissions, highlighting the need for de-carbonization. Part of the emissions originate in the use of diesel-driven heavy equipment. Considering the fast pace of transitioning from fossil fuels to electricity in other vehicle sectors, this may be a possible path for heavy equipment, considering the introduction of electric heavy equipment on the market. This study presents a model to calculate the charging requirements of a fully electrified heavy equipment fleet, applied in the study area of Skåne in Sweden. The charging loads are created through a Monte Carlo simulation, enabling probabilistic load flow simulations. Using the actual power grid model in the study area, provided by the local grid owners, allows for the exploration of how the charging loads are correlated to other loads and generators in the system. This study shows that the charging behavior largely affects the size of the peak charging powers, reaching peaks of up to 20 MW on primary substation transformer level (135/22 kV or 135/11 kV). The aggregated heavy equipment charging loads are shown to cause overloads in 18 out of 86 substations. Furthermore, the probabilistic load flow simulation shows that the highest peak charging loads do not directly correspond to the highest loaded transformers, stressing the necessity to perform power grid simulations when examining grid capacity impact.

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Publication Details

Published
2025-06-29
DOI
https://doi.org/10.1109/powertech59965.2025.11180247
Primary Topic
Bacterial Identification and Susceptibility Testing
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article
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Charging Requirement and Grid Impact from Electric Heavy Construction Equipment

Bacterial Identification and Susceptibility Testing
article

Charging Requirement and Grid Impact from Electric Heavy Construction Equipment

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Abstract

The construction sector contributes around 37 % of global CO2 emissions, highlighting the need for de-carbonization. Part of the emissions originate in the use of diesel-driven heavy equipment. Considering the fast pace of transitioning from fossil fuels to electricity in other vehicle sectors, this may be a possible path for heavy equipment, considering the introduction of electric heavy equipment on the market. This study presents a model to calculate the charging requirements of a fully electrified heavy equipment fleet, applied in the study area of Skåne in Sweden. The charging loads are created through a Monte Carlo simulation, enabling probabilistic load flow simulations. Using the actual power grid model in the study area, provided by the local grid owners, allows for the exploration of how the charging loads are correlated to other loads and generators in the system. This study shows that the charging behavior largely affects the size of the peak charging powers, reaching peaks of up to 20 MW on primary substation transformer level (135/22 kV or 135/11 kV). The aggregated heavy equipment charging loads are shown to cause overloads in 18 out of 86 substations. Furthermore, the probabilistic load flow simulation shows that the highest peak charging loads do not directly correspond to the highest loaded transformers, stressing the necessity to perform power grid simulations when examining grid capacity impact.

Lund University (SE)
Industry, innovation and infrastructure
Openalex Percentile: Top 37%
Bacterial Identification and Susceptibility Testing
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