Applications of probability model to analyze the effects of electric vehicle chargers on distribution transformers

Sexauer, Jason M.; McBee, Kerry D.; Bloch, Kelly A.

doi:10.1109/epec.2011.6070213

Cited by 13 publications

(10 citation statements)

References 6 publications

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“…Numerous studies have been done on EMS, but most of the research contributions are focused on economic objectives. Technical objectives of EMS include power quality, 33 equipment performance, 34 and degradation of transformers, 35,36 and its consideration provides better performance of the system, better power quality, improve life expectancy, and reduce maintenance and downtime. Integration of PEVs, ESS, and RES without proper coordination may cause the system to deviate from its intended performance, for example, PEV charging and discharging in uncoordinated manger may lead to thermal stress on the distribution network and transformer, 37 and uncoordinated integration of RES may create reactive power problem that causes deviation in voltage and other issues.…”

Section: Objectives Of Emsmentioning

confidence: 99%

Energy management system for smart grid: An overview and key issues

2020

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Summary Energy crisis and the global impetus to “go green” have encouraged the integration of renewable energy resources, plug‐in electric vehicles, and energy storage systems to the grid. The presence of more than one energy source in the grid necessitates the need for an efficient energy management system to guide the flow of energy. Moreover, the variability and volatile nature of renewable energy sources, uncertainties associated with plug‐in electric vehicles, the electricity price, and the time‐varying load bring new challenges to the power engineers to achieve demand‐supply balance for stable operation of the power system. The energy management system can effectively coordinate the energy sharing/trading among all available energy resources, and supply loads economically in all the conditions for the reliable, secure, and efficient operation of the power system. This paper reviews the framework, objectives, architecture, benefits, and challenges of the energy management system with a comprehensive analysis of different stakeholders and participants involved in it. The review paper gives a critical analysis of the distributed energy resources behavior and different programs such as demand response, demand‐side management, and power quality management implemented in the energy management system. Different uncertainty quantification methods are also summarized. This review paper also presents a comparative and critical analysis of the main optimization techniques used to achieve different energy management system objectives while satisfying multiple constraints. Thus, the review offers numerous recommendations for research and development of the cutting‐edge optimized energy management system applicable for homes, buildings, industries, electric vehicles, and the whole community.

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Section: Objectives Of Emsmentioning

confidence: 99%

Energy management system for smart grid: An overview and key issues

2020

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“…The load behavior of EV charging units is problematic for power systems and the components associated with them [19]- [21]. While there have been various attempts to model these chargers, each charger design is different from the next and usually contains some sort of proprietary design, making the modeling task more than trivial [22]- [24].…”

Section: Harmonic Distortionmentioning

confidence: 99%

Modeling Harmonic Impacts of Electric Vehicle Chargers on Distribution Networks

Woodman

Bass

Donnelly

2018

2018 IEEE Energy Conversion Congress and Exposition (ECCE)

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As the proliferation of electric vehicles continues to grow, it is becoming important to understand the impacts that electric vehicle charging will have on distribution assets. EV chargers are non-linear, multi-state loads. This manuscript presents a design method for the modeling of EV charging units using a VHDL-AMS simulation environment, per IEEE Standard 1076.1. Voltage and current data collected from in-service EV charging stations were used to create harmonic profiles of the EV charging units. From these profiles, generalized models for both Level 2 and Level 3 EV chargers were created. These models were validated within a larger system context using the IEEE 13 node test feeder. A VHDL-AMS tool has been created so distribution engineers may assess the impacts that EV chargers have on distribution assets. The tool may also be used to assist with the selection of transformers, conductors, and protection equipment.

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“…With considerations in cost, reliability, power losses and voltage profile, synchronised scheduling of charging stations and DGs is studied in [19]. Furthermore, the capacity‐boosting with DGs is proposed to compensate for the increasing PEVs penetration in [20]. The design of charging stations integrated with wind generation and storage is explored in [21].…”

Section: Introductionmentioning

confidence: 99%