Approach for prediction of cold loads considering electric vehicles during power system restoration

Hashemian, Seyed Mehran; Khodabakhshian, Amin; Gholipour, Mehdi; Esmaili, Mohammad Reza; Malekpour, Mostafa

doi:10.1049/iet-gtd.2020.0046

Cited by 5 publications

(5 citation statements)

References 41 publications

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“…The research studies on resilience enhancement strategies for EVs are mainly divided into three phases according to the disaster timeline (1) pre-disaster recovery planning: an opportunity for communities to respond to disasters and manage vital recovery issues rapidly, for example, keeping the essential services up and running. There are several predisaster strategies such as on-site energy storage in charging stations [286] and deployment of off-grid charging stations integrated with RESs [287,288], (2) on-disaster strategies: the immediate execution of the emergency operations during a disaster to save lives, protect property, and satisfy basic human requirements through charging network during shortnotice mass evacuations [289,290] and resource allocation approaches with different priorities to supply the power for EVs and emergency services [291], (3) post-disaster strategies: designing effective strategies for restoration process (including three steps of start-up generation, reconfiguration, and load restorations) to restore the power system as fast as possible considering the Cold Load Pick-up (CLPU) phenomenon and EVs recharging demand [292]. CLPU phenomenon, more likely occurring after a disaster, is called when the load demand is greater than the regular system operation and is predicted by model-driven methods (challenge: information should be gathered from whole loads/ equipment) [293] and stochastic methods (limitations to collect the load performance such as EV loads) [294].…”

Section: Resilience Power Supply For Evsmentioning

confidence: 99%

“…To model the CLPU at the load restoration stage, the effect of power outage duration should be considered since the attribute of CLPU is influenced by the ambient temperature and thermal loss over the power outage duration [346]. EVs can contribute to the CLPU after a power outage since CLPU is usual for any load interacting with the energy storage component [292]. The study [347] proposed a Monte Carlo simulation method to anticipate the CLPU derived from EV recharging on the distribution transformers.…”

Section: Ev Cold Load Pickup After Outagesmentioning

confidence: 99%

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Power System Resilience: The Role of Electric Vehicles and Social Disparities in Mitigating the US Power Outages

Loni,

Asadi

2024

Smart Grids and Energy

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Electrical power systems with their components such as generation, network, control and transmission equipment, management systems, and electrical loads are the backbone of modern life. Historical power outages caused by natural disasters or human failures show huge losses to the economy, environment, healthcare, and people’s lives. This paper presents a systematic review on three interconnected dimensions of (1) electric power system resilience (2) the electricity supply for/through Electric Vehicles (EVs), and (3) social vulnerability to power outages. This paper contributes to the existing literature and research by highlighting the importance of considering social vulnerability in the context of power system resilience and EVs, providing insights into addressing inequities in access to backup power resources during power outages. This paper first reviews power system resilience focusing on qualitative and quantitative metrics, evaluation methods, and planning and operation-based enhancement strategies for electric power systems during prolonged outages through microgrids, energy storage systems (e.g., battery, power-to-gas, and hydrogen energy storage systems), renewable energy sources, and demand response schemes. In addition, this study contributes to in-depth examination of the evolving role of EVs, as a backup power supply, in enhancing power system resilience by exploring the EV applications such as vehicle-to-home/building, grid-to-vehicle, and vehicle-to-vehicle or the utilization of second life of EV batteries. Transportation electrification has escalated the interdependency of power and transportation sectors, posing challenges during prolonged power outages. Therefore, in the next part, the resilient strategies for providing electricity supply and charging services for EVs are discussed such as deployments of battery swapping technology and mobile battery trucks (MBTs), as well as designing sustainable off-grid charging stations. It offers insights into innovative solutions for ensuring continuous electricity supply for EVs during outages. In the section on social vulnerability to power outages, this paper first reviews the most socioeconomic and demographic indicators involved in the quantification of social vulnerability to power outages. Afterward, the association between energy equity on social vulnerability to power outages is discussed such as inequity in backup power resources and power recovery and restoration. The study examines the existing challenges and research gaps related to the power system resilience, the electric power supply for/through EVs, social vulnerability, and inequity access to resources during extended power outages and proposes potential research directions to address these gaps and build upon future studies.

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Section: Resilience Power Supply For Evsmentioning

confidence: 99%

Section: Ev Cold Load Pickup After Outagesmentioning

confidence: 99%

Power System Resilience: The Role of Electric Vehicles and Social Disparities in Mitigating the US Power Outages

Loni,

Asadi

2024

Smart Grids and Energy

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“…Poor performance outside the sample and low calculation efficiency Conditional value at risk (CVaR) [27,30] Better subadditivity, which can reflect the VaR beyond the confidence interval…”

Section: Handling Of Uncertain Factorsmentioning

confidence: 99%

“…The authors of [29] described the uncertainty of load and scenery through conditional value at risk (CVaR), constructing a two-stage load recovery optimization model, and effectively solved the uncertainty in load recovery by solving linear programming and mixed-integer quadratic programming. The authors of [30] proposed a prediction method considering the increase in cooling load demand during load recovery, and took electric vehicle load as an example for explaining the impact process of the increase in cooling load demand on system recovery. The authors of [31], established a mixed-integer programming model to reduce the phase angle difference at both ends of the line to be paralleled, and part of the load was restored simultaneously; this approach was proposed to solve the problem of the closing angle exceeding the limit in the process of subnetwork paralleling.…”

Section: Introductionmentioning

confidence: 99%

Optimal Regulation of Parallel Closing Angle of Power System Loop Network Considering Wind–Wave Dynamics

et al. 2022

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The shortage of fossil fuels has led to increasing attention on new energy technologies, such as wind power and photovoltaic energy technologies, and the volatility of new energy has become the biggest obstacle for its participation in the process of power-system restoration. This paper presents an optimal control method of the parallel closing angle of the loop network in the process of power system recovery considering the uncertainty of wind-power output. Firstly, based on solving the uncertainty of wind-power output, a probability-prediction model of wind-power output based on the quantile regression of long-term and short-term memory networks (LSTMs) is established. Based on predicting the future wind-power output interval, the probability density function of the output at each time point in the future is obtained by a kernel density estimation. Secondly, by adjusting the output of conventional units and restoring the feeder load, a multiobjective optimal-control model is established to minimize the output change of conventional units and restore the most important feeder load. Based on considering the output probability of new energy, the optimal control of the phase angle difference at both ends of the line to be paralleled is realized, and the multiobjective optimization algorithm is used to solve the established model. Finally, the effectiveness of the proposed method and model is verified by IEEE 39-bus system simulation.

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“…How the side wind affects the vehicle and how to apply it to identify existing weaknesses and errors will be investigated by studying books and articles written about calculating the radius of horizontal arcs in combination with longitudinal slopes, and then, the behavior of vehicles in the face of arcs combined with longitudinal slope and wind is investigated using vehicle dynamic simulator software [5]. Cars, trucks, and buses are the most widely used vehicles on the roads.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of the Crosswind Effect on the Horizontal Curve Safety on Rural Highways Using Vehicle Dynamic Simulation

Yazdipour

Kordani

2022

Shock and Vibration

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Horizontal curves, as one of the most accident-prone parts of the road, have always attracted special attention. When a vehicle is moving on a road, the driver has to be constantly on the lookout for small deviations from the main route, possibly due to disturbances such as wind, road roughness, and unwanted entrances by the driver. These types of deviations have a corrosive effect on the driver and will eventually lead to the overturning and slipping of vehicles, so they should be minimized. AASHTO standard procedures, as the most valid road design bylaw, do not consider the effect of lateral wind, in which the effect of lateral wind in arcs has been investigated in this research. The work conducted in this research is to increase knowledge about the directional stability of vehicles that are affected by strong winds and to investigate the parameters of the study using accurate models of dynamic simulation of vehicles that are subject to winds. This study aimed to increase the understanding of vehicle sensitivity to wind due to strong lateral winds. For this purpose, the process of passing different types of vehicles through horizontal arcs in different longitudinal slopes with different velocities of the vehicle under lateral wind is simulated and the mechanical properties of vehicles under such conditions are calculated to compare with the results obtained from the passage of vehicles through a smooth horizontal arc (without longitudinal slope) and without lateral wind. Overturning angle, slip angle, lateral acceleration, and lateral coefficient of friction of vehicles in this study were calculated through software outputs, and the effect of lateral wind on the safety of arcs has been investigated.

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Approach for prediction of cold loads considering electric vehicles during power system restoration

Cited by 5 publications

References 41 publications

Power System Resilience: The Role of Electric Vehicles and Social Disparities in Mitigating the US Power Outages

Power System Resilience: The Role of Electric Vehicles and Social Disparities in Mitigating the US Power Outages

Optimal Regulation of Parallel Closing Angle of Power System Loop Network Considering Wind–Wave Dynamics

Evaluation of the Crosswind Effect on the Horizontal Curve Safety on Rural Highways Using Vehicle Dynamic Simulation

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