Smart charging of electric vehicles with photovoltaic power and vehicle-to-grid technology in a microgrid; a case study

Kam, Mart van der; Sark, W.G.J.H.M. van

doi:10.1016/j.apenergy.2015.04.092

Cited by 278 publications

(145 citation statements)

References 39 publications

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“…The stochastic variable of the PV generation is only present in the objective function (11). Hence, the existing constraints remain the same but the values of the variables are now depending on the scenarios and the SMILP follows the constraints (4)e (10).…”

Section: Two Stage Stochastic Optimization With Sample Average Approxmentioning

confidence: 99%

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Integrating renewable energy sources by electric vehicle fleets under uncertainty

Seddig

Jochem

Fïchtner

2017

Energy

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a b s t r a c tElectric vehicles are one of the concepts towards green and sustainable transportation systems. However, several uncertainties with respect to electricity demand and availability of electric vehicles as well as electricity supply by renewable energy sources influence an optimal scheduling through smart charging strategies. This paper investigates the possibilities to integrate additionally loads of uncertain renewable energy sources by smart charging strategies of three different electric vehicle fleets namely, com mercial customers, commuters, and opportunity parkers. Therefore, data from an empiric field test with a public charging infrastructure in a parking garage with a photovoltaic system is taken. Various stra tegies are analyzed, considering the changing individual electricity demand, restrictions and parking times of electric vehicle fleets by combining a Monte Carlo simulation approach with different meth odologies like a heuristic algorithm, an optimization model and stochastic programming. The numerical results indicate that the domestic photovoltaic generation of the car park can be fully used by the electric vehicle fleets for charging and the utilization of photovoltaic can be doubled when comparing uncon trolled and optimized charging strategies. The commuter fleet has the highest CO 2 emission reduction potential of all three electric vehicle fleets. Moreover, load management decreases costs, even when uncertainties are considered.

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Section: Two Stage Stochastic Optimization With Sample Average Approxmentioning

confidence: 99%

“…Refs. [9], [10]. Not only opti mized scheduling strategies are applied, but also different algo rithm can be used to determine optimized schedules, e. g. Ref.…”

Section: Related Workmentioning

confidence: 99%

Integrating renewable energy sources by electric vehicle fleets under uncertainty

Seddig

Jochem

Fïchtner

2017

Energy

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“…N (20, 1), [19,21] N (8, 1), [5,10] U {2, 4} U {3, 4}, U {1, 2} 0 HP (day) N (13, 1), [12,14] Table I.…”

Section: A Experimental Setupmentioning

confidence: 99%

“…Our experiments are based on power characteristics from real loads (e.g., [13], [14]) that show similar use behavior and are complemented with potential flexibility, e.g., [15]. One amount unit corresponds to 0.5kW.…”

Section: A Experimental Setupmentioning

confidence: 99%

Aggregating energy flexibilities under constraints

Valsomatzis

Pedersen

Abelló

et al. 2016

2016 IEEE International Conference on Smart Grid Communications (SmartGridComm)

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Abstract-The flexibility of individual energy prosumers (producers and/or consumers) has drawn a lot of attention in recent years. Aggregation of such flexibilities provides prosumers with the opportunity to directly participate in the energy market and at the same time reduces the complexity of scheduling the energy units. However, aggregated flexibility should support normal grid operation. In this paper, we build on the flex-offer (FO) concept to model the inherent flexibility of a prosumer (e.g., a single flexible consumption device such as a clothes washer). An FO captures flexibility in both time and amount dimensions. We define the problem of aggregating FOs taking into account grid power constraints. We also propose two constraintbased aggregation techniques that efficiently aggregate FOs while retaining flexibility. We show through a comprehensive evaluation that our techniques, in contrast to state-of-the-art techniques, respect the constraints imposed by the electrical grid. Moreover, our techniques also reduce the scheduling input size significantly and improve the quality of scheduling results.

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“…Most of the scholarships on EV charging and renewable energy generation have focused on design, operation, and optimal charging strategies [12][13][14][15][16]. A conceptual architecture and an assessment framework were proposed to explore integration scenarios of EVs and renewable energy generation in distribution networks [17].…”

Section: Introductionmentioning

confidence: 99%

An Optimal Charging Strategy for PV-Based Battery Swapping Stations in a DC Distribution System

Li³

et al. 2017

International Journal of Photoenergy

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Photovoltaic-(PV-) based battery swapping stations (BSSs) utilize a typical integration of consumable renewable resources to supply power for electric vehicles (EVs). The charging strategy of PV-based BSSs directly influences the availability, cost, and carbon emissions of the swapping service. This paper proposes an optimal charging strategy to improve the self-consumption of PV-generated power and service availability while considering forecast errors. First, we introduce the typical structure and operation model of PV-based BSSs. Second, three indexes are presented to evaluate operational performance. Then, a particle swarm optimization (PSO) algorithm is developed to calculate the optimal charging power and to minimize the charging cost for each time slot. The proposed charging strategy helps decrease the impact of forecast uncertainties on the availability of the battery swapping service. Finally, a day-ahead operation schedule, a real-time decision-making strategy, and the proposed PSO charging strategy for PV-based BSSs are simulated in a case study. The simulation results show that the proposed strategy can effectively improve the self-consumption of PV-generated power and reduce charging cost.

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Smart charging of electric vehicles with photovoltaic power and vehicle-to-grid technology in a microgrid; a case study

Cited by 278 publications

References 39 publications

Integrating renewable energy sources by electric vehicle fleets under uncertainty

Integrating renewable energy sources by electric vehicle fleets under uncertainty

Aggregating energy flexibilities under constraints

An Optimal Charging Strategy for PV-Based Battery Swapping Stations in a DC Distribution System

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