Adapted Stochastic PV Hosting Capacity Approach for Electric Vehicle Charging Considering Undervoltage

Mulenga, Enock; Bollen, M.H.J.; Etherden, Nicholas

doi:10.3390/electricity2030023

Cited by 15 publications

(15 citation statements)

References 26 publications

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“…In the United States, EV electricity usage climbed from 0.1 terawatt-hours to 1.9 terawatt-hours between 2012 and 2017. The excessive increase in EVs integrated into the DN has some technical issues that should be considered [3,187,188].…”

Section: Hosting Capacity Of Electric Vehiclesmentioning

confidence: 99%

A Comprehensive Review of Renewables and Electric Vehicles Hosting Capacity in Active Distribution Networks

Zenhom,

Aleem,

Zobaa

et al. 2024

IEEE Access

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The excessive integration of renewable distributed generation (RDG) and electric vehicles (EVs) could be considered the two most problematic elements representing the greatest threat to the distribution network (DN) technical operation. In order to avoid going beyond technical limitations, the term hosting capacity (HC) was proposed to define the highest permitted amount of distributed generation (DG) or EVs that can be integrated safely into the DN. The connection of RDGs was first brought to the attention of researchers and DN operators since it accounts for the most notable portion of these technical issues. Hence, the phrase 'DG-HC' was initially proposed and evolved significantly over the last few years. Currently, EV integration in most DNs worldwide is still low, but given the worldwide support for clean transportation options, expectations are raised for a significant increase. As a result, it is anticipated that over the next years, the effect of EV integration on the DN will be highly noticeable, requiring greater attention from researchers and DN operators to define the accepted limits of EV penetration levels, 'EV-HC,' which is expected to pass along the same line of DG-HC. This article provides an in-depth review of both DG-HC and EV-HC. It first analyses how the DG-HC research has grown over the years and then studies the published EV-HC papers, illustrating to what extent there is a similarity between them and, finally, employs these analyses to expect future development in the EV-HC research area. This article includes the different uses of the term HC, the most common performance indices of DG-HC, the various methods for assessing DG-HC, the different techniques for DG-HC enhancement, the effects of integrating EVs on the DG-HC, and finally, calculating and enhancing methods for EV-HC.

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Section: Hosting Capacity Of Electric Vehiclesmentioning

confidence: 99%

A Comprehensive Review of Renewables and Electric Vehicles Hosting Capacity in Active Distribution Networks

Zenhom,

Aleem,

Zobaa

et al. 2024

IEEE Access

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“…To identify and search for solutions to PQ problems, the literature proposes the analysis of the hosting capacity (HC) of electric vehicles (EVs). HC is generally defined as the amount of new load or generation that can be connected on a feeder without jeopardizing the reliability or PQ of the power system [11]. The research conducted in [12,13] presents a comprehensive review of the various methods for analyzing EV hosting capacity.…”

Section: Introductionmentioning

confidence: 99%

An Overview of Electric Vehicle Load Modeling Strategies for Grid Integration Studies

Huaman-Rivera,

Calloquispe-Huallpa,

Luna Hernandez

et al. 2024

Electronics

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The adoption of electric vehicles (EVs) has emerged as a solution to reduce greenhouse gas emissions in the transportation sector, which has motivated the implementation of public policies to promote their use in several countries. However, the high adoption of EVs poses challenges for the electricity sector, as it would imply an increase in energy demand and possible impacts on the power quality (PQ) of the power grid. Therefore, it is important to conduct EV integration studies in the power grid to determine the amount that can be incorporated without causing problems and identify the areas of the power sector that will require reinforcements. Accurate EV load patterns are required for this type of study that, through mathematical modeling, reflect both the dynamic behavior and the factors that influence the decision to recharge EVs. This article aims to present an overview of EVs, examine the different factors considered in the literature for modeling EV load patterns, and review modeling methods. EV load modeling methods are classified into deterministic, statistical, and machine learning. The article shows that each modeling method has its advantages, disadvantages, and data requirements, ranging from simple load modeling to more accurate models requiring large datasets.

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“…Therefore, defining DER production and location information is necessary before starting the HC calculation. Despite the possibility that the stochastic methods described in [8], [9], [10] could be applied to represent real-life scenarios, it is important to recognize that the stochastic results might not be the most appropriate solution for HC.…”

Section: Introductionmentioning

confidence: 99%

An Enhanced Approach for Solar PV Hosting Capacity Analysis in Distribution Networks

Abideen

Ellabban²,

Ahmad

et al. 2022

IEEE Access

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With the falling cost of Distributed Energy Resources (DERs) and the shift from fossil fuel to renewable energy in many countries, the integration of DERs is expected to grow. This can lead to a wide range of problems in the power system, such as voltage violations, overloading of distribution lines, reverse power flow, etc. Therefore, it is imperative to account for these adverse effects of the integration of DERs on the distribution network and minimize their impact when calculating the Hosting Capacity (HC). Two algorithms are presented in this study derived from a novel modified iterative method and a novel Repeated Particle Swarm Optimization (RPSO) method for determining the HC for multiple DER units simultaneously or a single DER unit integrating into radial or mesh networks. These algorithms calculate the optimal HC based on six scenarios of annual load and DER generation profiles. The developed algorithms were tested on the IEEE 123 bus network, and their results were compared. For a large-scale DER case, the modified iterative method significantly outperforms both the PSO and the normal iterative method in terms of computation time (30 minutes versus 3 hours versus 6 hours, respectively). In the case of multiple DERs, the RPSO method is the only option, as the other two methods cannot simultaneously optimize multiple DERs. As a result, it has been concluded that it is necessary to select HC calculation methods carefully and in accordance with the application, as each method has its own strengths and weaknesses.

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Adapted Stochastic PV Hosting Capacity Approach for Electric Vehicle Charging Considering Undervoltage

Cited by 15 publications

References 26 publications

A Comprehensive Review of Renewables and Electric Vehicles Hosting Capacity in Active Distribution Networks

A Comprehensive Review of Renewables and Electric Vehicles Hosting Capacity in Active Distribution Networks

An Overview of Electric Vehicle Load Modeling Strategies for Grid Integration Studies

An Enhanced Approach for Solar PV Hosting Capacity Analysis in Distribution Networks

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