TY - JOUR
T1 - Risk and Resilience Based Residential Electric Vehicle Integration Framework for Restoration of Modern Power Distribution Networks
AU - Alghamdi, Abdullah
AU - Jayaweera, Dilan
N1 - Not yet published as of 25/04/2025
PY - 2025/4/17
Y1 - 2025/4/17
N2 - The restoration of power distribution networks following extreme events is a critical challenge, particularly when traditional utility-owned mobile power sources (MPSs) are limited in number, capacity, and deployment flexibility. Residential electric vehicles (EVs) present a scalable and decentralized alternative due to their widespread availability and bidirectional charging capabilities. However, the large-scale integration of nonpredetermined residential EVs into power restoration remains under-explored. This paper proposes the Individually-Owned EV Integration Innovative Framework (IIIF) to optimize residential EV participation in grid restoration. The IIIF introduces a novel EV user behaviour model, suggesting a 24% likely improvement in participation prediction accuracy used in the restoration process and leading to more effective EV mobilization. Additionally, a dynamic clustering framework is integrated to enhance EV allocation to public EV charging points (EVCPs), increasing EVCP utilization and optimizing EV distribution to reduce congestion and waiting times. The IIIF also incorporates an advanced EV dispatch model, which optimizes routing decisions to minimize power consumption and enhance discharging efficiency, leading to improved power delivery compared to conventional strategies. To ensure resilience, the IIIF integrates a risk assessment and backup strategy, activating MPSs when EVs alone are insufficient to meet restoration demand. Performance evaluation on the IEEE 123-bus system demonstrates that the IIIF reduces power restoration time by 27% and decreases total operational costs by 19% compared to conventional EV-based and MPS-only restoration approaches. These findings establish the IIIF as a benchmark framework for resilient, cost-effective, and large
AB - The restoration of power distribution networks following extreme events is a critical challenge, particularly when traditional utility-owned mobile power sources (MPSs) are limited in number, capacity, and deployment flexibility. Residential electric vehicles (EVs) present a scalable and decentralized alternative due to their widespread availability and bidirectional charging capabilities. However, the large-scale integration of nonpredetermined residential EVs into power restoration remains under-explored. This paper proposes the Individually-Owned EV Integration Innovative Framework (IIIF) to optimize residential EV participation in grid restoration. The IIIF introduces a novel EV user behaviour model, suggesting a 24% likely improvement in participation prediction accuracy used in the restoration process and leading to more effective EV mobilization. Additionally, a dynamic clustering framework is integrated to enhance EV allocation to public EV charging points (EVCPs), increasing EVCP utilization and optimizing EV distribution to reduce congestion and waiting times. The IIIF also incorporates an advanced EV dispatch model, which optimizes routing decisions to minimize power consumption and enhance discharging efficiency, leading to improved power delivery compared to conventional strategies. To ensure resilience, the IIIF integrates a risk assessment and backup strategy, activating MPSs when EVs alone are insufficient to meet restoration demand. Performance evaluation on the IEEE 123-bus system demonstrates that the IIIF reduces power restoration time by 27% and decreases total operational costs by 19% compared to conventional EV-based and MPS-only restoration approaches. These findings establish the IIIF as a benchmark framework for resilient, cost-effective, and large
UR - https://www.sciencedirect.com/journal/international-journal-of-electrical-power-and-energy-systems
M3 - Article
SN - 0142-0615
JO - International Journal of Electrical Power and Energy Systems
JF - International Journal of Electrical Power and Energy Systems
ER -