Photovoltaics (PV) and electric vehicle-to-grid (V2G) strategies for peak demand reduction in urban regions in Brazil in a smart grid environment

Drude, Lukas; Pereira, Luiz Carlos; Rüther, Ricardo

doi:10.1016/j.renene.2014.01.049

Cited by 138 publications

(72 citation statements)

References 24 publications

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“…Charging can only be controlled and regulated based on a good knowledge of future electric mobility pattern. This knowledge will enable the full potential of possible grid services (Habib et al, 2015) and market supporting measures (Drude et al, 2014). These measures are highly relevant in the context of energy transition and concomitant increase in renewable electricity generation (REG) as well as decentralized generation in general.…”

Section: Introductionmentioning

confidence: 99%

Generating electric vehicle load profiles from empirical data of three EV fleets in Southwest Germany

Schäuble

Kaschub

Ensslen

et al. 2017

Journal of Cleaner Production

105

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The increasing demand for electricity caused by a growing number of electric vehicles (EV) is a major challenge for future energy systems. For an integration of the electricity demand from EV, a comprehensive knowledge of its characteristics is essential. The analysis of charging behavior patterns of EV and resulting load profiles become important premises for this crucial task. Three electric mobility studies in Germany's southwestern region (Get eReady, iZEUS, and CROME) deliver comprehensive data of EV use for this purpose. In this paper we analyze and discuss the mobility and charging characteristics of this data in detail. We derive empirical EV load profiles and show how they are affected by charging management as well as charg- representation of EV demand in analyses of future energy systems.

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Section: Introductionmentioning

confidence: 99%

Generating electric vehicle load profiles from empirical data of three EV fleets in Southwest Germany

Schäuble

Kaschub

Ensslen

et al. 2017

Journal of Cleaner Production

105

View full text Add to dashboard Cite

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“…So far, there are 25 cities included in this plan. PHEV can be utilized as an electricity consumer or electricity supplier [4,5]. One of the promising integration mechanisms is the implementation of interaction between renewable energy sources and EVs (including PHEVs).…”

Section: Introductionmentioning

confidence: 99%

Microgrid economic operation considering plug-in hybrid electric vehicles integration

Chen

Duan

2015

J. Mod. Power Syst. Clean Energy

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In this paper, the microgrid economic scheduling mathematical model considering the integration of plug-in hybrid electric vehicles (PHEVs) is presented and the influence of different charging and discharging modes on microgrid economic operation is analyzed. The generic algorithm is used to find an economically optimal solution for the microgrid and PHEV owners. The scheduling of PHEVs and the microgrid are optimized to reduce daily electricity cost and the potential benefits of controlled charging/discharging are explored systematically. Constraints caused by vehicle utilization as well as technical limitations of distributed generation and energy storage system are taken into account. The proposed economic scheduling is evaluated through a simulation by using a typical grid-connected microgrid model.

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“…Deploy BES [124,[127][128][129] Reduce losses [36,128] Deploy both [30,36,[125][126][127] Reduce unbalance [36,119] Reduce loading [36] Reduce costs [36,86,118,123,126] Reduce GHG emissions [86,117] Reduce transformer, feeder capacities required [36,129] Improve voltages [36,75,116,127] Improve QoS [36] Even though these papers form a comprehensive realm of studies regarding whether to augment grid or deploy PV and BES, the following limitations can be pointed out,  The papers above have assumed that either augmenting/reconfiguring the grid/phase or deploying onsite PV and BES is the best solution for reducing the impact, costs, GHG and increasing QoS. However, in practice, their various combinations (e.g., grid augmentation and PV; grid augmentation, PV, and BES; etc.)…”

Section: 34mentioning

confidence: 99%

“…Therefore, the probabilistic charging strategies are incompatible with the charging facilities where frequent real-time control of charging is required. From historical solar irradiation [97,98,115,145] From historical data [125,167] By prediction [142,168] PV panel's tilt, azimuth, and seven other relevant weight coefficients [169] Estimated from a supplied solar intensity [56,98,123,125,145,168,170] Directly obtained from the historical data [97,118,167] Probabilistic PV output…”

Section: Real-time Ev Load Dispatching Addressing Pv Output Variabilimentioning

confidence: 99%

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PV-based EV charging station with vehicle-to-grid services for business premises

Islam¹

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The transportation sector is the second major contributor to the global greenhouse gas (GHG) emissions, next to electricity generation sector. GHG emissions are projected to grow in the future due to the over-reliance on fossil fuels for both electricity generation and transportation sectors.However, the growth can be stalled by gradually introducing electric vehicles (EVs) as they produce less GHG compared to their conventional counterparts. Despite that, their proliferation has been stunted by a completely new set of challenges in addition to a very high capital cost. These challenges include low driving ranges, scarcity of electric vehicle charging stations (EVCS), long charging time and inability to provide charging service readily. Nevertheless, some of these challenges can be addressed by installing EVCS at business premises (i.e., offices, universities, etc.) and augmenting EVCS with onsite PV and battery energy storage (BES). In that case, the impacts of EV charging on the grid will be less significant; charging services will be available readily, and GHG emissions growth can be reduced significantly. Moreover, EVCS, under suitable conditions, would be able to provide vehicle-to-grid (V2G) services, which makes EVCS more attractive.Despite such prospective opportunities, offhand planning and operational planning of EVCS would deem them unachievable. In addition, the inherent intermittency of PV, and EV and grids loads will pose considerable hindrance on availing those benefits.Hence, this research focusses on an EVCS with onsite PV and BES, in the perspective of planning and operational planning including V2G services. The cornerstone of the planning and operational planning is an appropriate EV load model that captures the uncertainties of EV charging. In addition, the EV load model reflects the grid voltage and EV battery's state of charge (SOC)-dependency of EV charging. Moreover, it accounts for the diversity of the EV population embodied by market shares, battery sizes, charging levels, and charging voltages, currents, and power factors. Furthermore, it is scalable to facilitate seamless assimilation of a large EV population. Therefore, a new EV load model is first proposed with MATLAB/Simulink validation reflecting the factors above along with the recommendations by the standard BS EN 61851-23:2014. This EV model is then incorporated into the planning activities, which include four chronological exercises. Firstly, the impact (i.e., grid voltage, current, losses, etc.) of the EV charging on the grid at different locations, namely home, office, public charging, is investigated considering the uncertainties. Secondly, the optimal location of the PV and BES based EVCS is divulged regarding the reduction of the impact and costs involved while enhancing the charging quality of service (QoS). Thirdly, a suitability analysis is performed for the obtained optimal location to find the most suitable combination of the grid upgrading, PV deployment, and BES iii deployment to satisfy the QoS, ...

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Photovoltaics (PV) and electric vehicle-to-grid (V2G) strategies for peak demand reduction in urban regions in Brazil in a smart grid environment

Cited by 138 publications

References 24 publications

Generating electric vehicle load profiles from empirical data of three EV fleets in Southwest Germany

Generating electric vehicle load profiles from empirical data of three EV fleets in Southwest Germany

Microgrid economic operation considering plug-in hybrid electric vehicles integration

PV-based EV charging station with vehicle-to-grid services for business premises

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