Electric Vehicle Charging in an Office Building Microgrid With Distributed Energy Resources

Roy, Juan Van; Leemput, Niels; Geth, Frederik; Büscher, J.; Salenbien, Robbe; Driesen, Johan

doi:10.1109/tste.2014.2314754

Cited by 149 publications

(87 citation statements)

References 21 publications

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“…For the objective function (14), whether cost is paid or revenue is received is determined by buying or selling electricity, which is influenced by the charging/discharing decision of battery and the power scheduling. For each time stage t, introduce another two variables z t and t , with z t being the total cost (revenue) at t and t being (19).…”

Section: Linearization Of the Cost And Constraintsmentioning

confidence: 99%

“…For the demand side, Amin Khodaei and Mohammad Shahidehpour [13] investigated the optimal energy management in a community-based microgrid with mixed-integer programming and Lagrangian relaxation considering various kinds of residential loads. Roy et al [14] evaluated different charging strategies for hybrid electric vehicles in an office building microgrid with a PV system and evaluated their performance in different scenarios. Liu et al [15] proposed a heuristic operation strategy for electric vehicle charging activities based on dynamical event triggering for real-time power allocation.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Operational Optimization for Microgrid of Buildings with Distributed Solar Power and Battery

Zhang

Jia

2016

Asian Journal of Control

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Improving building energy efficiency is significant for energy conservation and environmental protection. When there are multiple buildings with solar power generation and batteries connected in a microgrid, coordinating the distributed energy supply and consumption may substantially improve the energy efficiency. We consider this important problem in this paper and make the following three major contributions. First, we formulate the operation optimization of a microgrid of buildings as a two-stage stochastic programming problem. Second, the problem is transformed into a stochastic mixed-integer linear programming. Then the scenario method is used to solve the problem. Third, case studies of a university campus is presented. The numerical results show that coordinating the distributed solar power and battery can reduce the operational cost of the microgrid.

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Section: Linearization Of the Cost And Constraintsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Operational Optimization for Microgrid of Buildings with Distributed Solar Power and Battery

Zhang

Jia

2016

Asian Journal of Control

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“…EVs and HEVs not only save fossil fuel, but also achieve low gas emissions for environmental protection [3]. Emerging renewable energy techniques have been introduced in EVs [4]. In EVs and HEVs, the bidirectional DC/DC converter is a prominent option to exchange power between the low-voltage energy storage device and the high-voltage DC bus of the traction motor [5].…”

Section: Introductionmentioning

confidence: 99%

The Chaotic-Based Control of Three-Port Isolated Bidirectional DC/DC Converters for Electric and Hybrid Vehicles

et al. 2016

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Three-port isolated (TPI) bidirectional DC/DC converters have three energy ports and offer advantages of large voltage gain, galvanic isolation ability and high power density. For this reason this kind of converters are suitable to connect different energy sources and loads in electric and hybrid vehicles. The purpose of this paper is to propose chaotic modulation and the related control scheme for TPI bidirectional DC/DC converters, in such a way that the switching harmonic peaks can be suppressed in spectrum and the conducted electromagnetic interference (EMI) is reduced. Two chaotic modulation strategies, namely the continuously chaotic modulation and the discretely chaotic modulation are presented. These two chaotic modulation strategies are applied for TPI bidirectional DC/DC converters with shifted-phase angle based control and phase-shifted PWM control. Both simulation and experiments are given to verify the validity of the proposed chaotic modulation-based control schemes.

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“…Therefore, though the EVs have been primarily advocated to be charged at HC [46] and BC [47], a considerable amount of energy may need to be replenished at CC [48], depending on the driving ranges. The authors in [47] in this regards have found that when EVs are fully charged at HC, the energy consumption at BC amounts to about 21.5% of the total charge energy at home and work combined. If EVs are only partly charged at HC, the average charge energy at BC is more than doubled.…”

Section: Classification Of Ev Charging Locationsmentioning

confidence: 99%

“…However, neither PV nor BES has been considered in these papers. Deterministic grid load or grid load ignored [16,17,47,53,57,75,[80][81][82][83][84][85][86][87] Recorded grid load data; probabilistic EV load [88] Constructed worst case scenario with deterministic EV load [89] Probabilistic EV and grid loads [32,90,91] Deterministic PV output [17,83,84] Probabilistic PV output [47,75,86] For probabilistic modelling, the combined EV load is a function of the number of EVs [82,85], their charging characteristics with respect to SOC as discussed in Section 2.2 and various other parameters. Referred to Table 2.7, among these parameters, daily travel distance, arrival time and departure time are frequently used.…”

Section: Step 2: Analyzing the Impact Of Ev Charging On The Gridmentioning

confidence: 99%

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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Electric Vehicle Charging in an Office Building Microgrid With Distributed Energy Resources

Cited by 149 publications

References 21 publications

Operational Optimization for Microgrid of Buildings with Distributed Solar Power and Battery

Operational Optimization for Microgrid of Buildings with Distributed Solar Power and Battery

The Chaotic-Based Control of Three-Port Isolated Bidirectional DC/DC Converters for Electric and Hybrid Vehicles

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

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