Quantifying the Long-Term Impact of Electric Vehicles on the Generation Portfolio

Shortt, Aonghus; O’Malley, Mark

doi:10.1109/tsg.2013.2286353

Cited by 29 publications

(14 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The FAST algorithm mimics the input-output relationship of a mixed-integer unit commitment model but does so in orders of magnitude faster, which is of practical relevance when simulating many scenarios. The algorithm is described in Lynch et al (2013) and Shortt and O'Malley (2014) and seeks to determine least-cost schedules for generation dispatch, considering start-up and no load costs, as well as variable costs and technical constraints. The FAST solution produces unit-commitment and economic dispatch schedules whose costs are on par with those from the MIP under a relatively tight optimality gap.…”

Section: 4mentioning

confidence: 99%

The impact of the North Atlantic Oscillation on electricity markets: A case study on Ireland

2016

View full text Add to dashboard Cite

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. www.econstor.eu ESRI working papers represent un-refereed work-in-progress by researchers who are solely responsible for the content and any views expressed therein. Any comments on these papers will be welcome and should be sent to the author(s) by email. Papers may be downloaded for personal use only. Terms of use: Documents in The Impact of the North Atlantic Oscillation on Electricity Markets: A Case Study on IrelandJohn Curtis a,b , Muireann Á . Lynch a,b , Laura Zubiate c Abstract: The North Atlantic Oscillation (NAO) is a large-scale circulation pattern driving climate variability in north-western Europe. As the deployment of wind-powered generation expands on electricity networks across Europe the impacts of the NAO on the electricity system will be amplified. This study assesses the impact of NAO, via wind-power generation, on the electricity market considering thermal generation costs, wholesale electricity prices and wind generation subsidies. A Monte Carlo approach is used to model NAO phases and generate hourly wind speed time-series data, electricity demand and fuel input data. A least-cost unit commitment and economic dispatch model is used to simulate an island electricity system, modelled on the all-island Irish electricity system. The impact of NAO obviously depends on the level of wind capacity within an electricity system. Our results indicate that NAO phases can affect thermal generation costs by up to 8%, wholesale electricity prices by as much as €1.5/MWh, and that wind power generators receive on average 12% higher remuneration.

show abstract

Section: 4mentioning

confidence: 99%

The impact of the North Atlantic Oscillation on electricity markets: A case study on Ireland

2016

View full text Add to dashboard Cite

show abstract

“…They show that the intelligent scheduling of EV chargings at off-peak hours increases the utilization of low cost generations, hence lowers the wholesale energy cost. In a similar study, authors of [23] argue that the savings gained due to intelligent charging of EVs could be reflected in charging tariffs and it promotes EV ownership. Furthermore, the work presented in [28] proposes a valley-filling algorithm and models the customer to grid interaction via pricing demand signals.…”

Section: Opportunitiesmentioning

confidence: 97%

“…There are a handful of studies investigating the impact of electric vehicle charging on power generation [19][20][21][22][23]. According to [21], plug-in hybrid electric vehicles (assuming all vehicles are PHEV20 with a battery pack of 7.2 kWh) can increase the total load by 2.7% and the peak load by 2.5% in Colorado.…”

Section: Impact Of the Ev Penetrationmentioning

confidence: 99%

A survey on communication technologies and requirements for internet of electric vehicles

Bayram

Papapanagiotou

2014

J Wireless Com Network

View full text Add to dashboard Cite

Electric vehicles (EVs) are becoming a more attractive transportation option, as they offer great cost savings, decrease foreign oil dependency, and reduce carbon emissions. However, varying temporal and spatial demand patterns of EVs threatens power grid operations and its physical components. Thus, the ability of the power grid to handle the potential extra load has become a major factor in the mainstream success. In order for this integration to occur seamlessly, the power grid and the consumers need to be coordinated in harmony. In this paper, we address the critical challenges introduced by the penetration of EVs, systematically categorize the proposed frameworks for demand management, and the role of information and communication technologies in the solution process. We provide a comprehensive survey on the communication requirements, the standards and the candidate technologies towards the Internet of electric vehicles (IoEV). This survey summarizes the current state of research efforts in electric vehicle demand management and aims to shed light on the continued studies.

show abstract

“…For an electricity dispatch model we use the Flexible Algorithm for Scheduling Technologies (FAST ), which was developed as a response to the problem of providing electricity generation schedules that mimic system-operator decisions in real time, while meeting demand and respecting technical constraints (Shortt and O'Malley, 2014;Lynch et al, 2013). Several approaches are used in the literature to simulate electricity generation schedules depending on the application.…”

Section: 4mentioning

confidence: 99%

Carbon dioxide (CO2) emissions from electricity: The influence of the North Atlantic Oscillation

2016

View full text Add to dashboard Cite

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. In recent years there has been an increasing deployment of wind-powered generation technology, i.e. wind farms, on electricity networks across Europe. As this deployment increases it is important to understand how climate variability will affect both windpowered and non-renewable power generation. This study extends the literature by assessing the impact of NAO, via wind-power generation, on carbon dioxide emissions from the wider electricity system. A Monte Carlo approach is used to model NAO phases, generate hourly wind speed timeseries data, electricity demand and fuel input data. A unit commitment, least-cost economic dispatch model is used to simulate an entire electricity system, modelled on the all-island Irish electricity system. Our results confirm that the NAO has a significant impact on monthly mean wind speeds, wind power output, and carbon dioxide emissions from the entire electricity system. The impact of NAO on emissions obviously depends on the level of wind penetration within an electricity system but our results indicate that emissions intensity within the Irish electricity system could vary by as much as 10% depending on the NAO phase within the next few years. The emissions intensity of the electricity system will vary with the NAO phase. Terms of use: Documents in

show abstract

Quantifying the Long-Term Impact of Electric Vehicles on the Generation Portfolio

Cited by 29 publications

References 10 publications

The impact of the North Atlantic Oscillation on electricity markets: A case study on Ireland

The impact of the North Atlantic Oscillation on electricity markets: A case study on Ireland

A survey on communication technologies and requirements for internet of electric vehicles

Carbon dioxide (CO2) emissions from electricity: The influence of the North Atlantic Oscillation

Contact Info

Product

Resources

About