Economic benchmark of charging strategies for battery electric vehicles

Dietz, Benjamin; Ahlert, Klaus-Henning; Schuller, Alexander; Weinhardt, Christof

doi:10.1109/ptc.2011.6019241

Cited by 18 publications

(11 citation statements)

References 15 publications

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“…Heydt (1983) proposes to increase daily load factor by shifting loads into off-peak hours. Sioshansi, Fagiani, and Marano (2010) and Dietz et al (2011) minimize the charging cost for EV drivers. Bashash, Moura, and Fathy (2011) estimate the load imposed on the grid by battery-healthconscious charging of plug-in hybrid electric vehicles at distinct locations.…”

Section: Ev Charging Coordinationmentioning

confidence: 99%

“…Another important aspect is the amount of information required for decision making. Prior research (Lopes, Soares, and Almeida 2009;Sioshansi, Fagiani, and Marano 2010;Dietz et al 2011) has established two polar charging strategies: uncoordinated ("naïve") and coordinated ("smart") charging. Following Flath, Ilg, and Weinhardt (2012), we complement these strategies with a heuristic smart charging strategy based on very limited information on future trips and prices.…”

Section: Electric Vehicle Charging Strategiesmentioning

confidence: 99%

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Improving Electric Vehicle Charging Coordination Through Area Pricing

Flath

Ilg

Gottwalt

et al. 2014

Transportation Science

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M eeting charging demands of large electric vehicle fleets will raise electrical load significantly and may pose challenges for today's power system. Appropriate coordination of electric vehicle charging can reduce these threats. Acknowledging the interdependency between the transportation and the power system created by electric vehicles, we develop a charging coordination model based on German mobility data. We extend the prior work by explicitly accounting for both the temporal and the spatial dimension. We are thus able to analyze the loads from price-based EV fleet charging while at the same time accounting for distribution grid constraints. Furthermore, we propose a heuristic charging strategy based on limited trip and price information. Our results show that the sole use of time-based electricity prices for the coordination of electric vehicle charging produces high load spikes independent of the charging strategies and power levels. These peaks are induced by simultaneous charging activity and may cause stability problems within distribution grids in residential areas. To mitigate these load spikes, we introduce a spatial price component that reflects local capacity utilization. These local prices induce both a temporal and spatial shift of charging activity that mitigates the load spikes.

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Section: Ev Charging Coordinationmentioning

confidence: 99%

Section: Electric Vehicle Charging Strategiesmentioning

confidence: 99%

Improving Electric Vehicle Charging Coordination Through Area Pricing

Flath

Ilg

Gottwalt

et al. 2014

Transportation Science

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“…The different disciplines focus on various aspects of the charging coordination problem. Whereas electrical engineers tend to minimize power losses [11], maximize EV integration [12], or optimize system parameters [13], [14], economists are more likely minimizing cost for power suppliers or minimizing cost for EV drivers [15], [16].…”

Section: Ev Charging Coordinationmentioning

confidence: 99%

A Revenue Management Approach for Efficient Electric Vehicle Charging Coordination

Flath

Gottwalt

Ilg

2012

2012 45th Hawaii International Conference on System Sciences

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Ambitious goals of electric vehicle (EV) penetration may conflict with the capabilities of today's power system. Especially simultaneous charging at home may lead to significant load spikes or grid stability issues. Prior research has identified the need for appropriate coordination approaches. This research focuses mostly on coordinating system loads ignoring local grid constraints. The suggested mechanisms either are centralized control approaches ignoring user preferences or based on the electrical energy cost. We propose to complement these approaches by using mechanisms from revenue management for perishable assets. First, we formalize charging coordination as a minimal revenue management problem and then derive an appropriate advance sale mechanism. By accounting for heterogeneous customer segments, this approach can achieve a socially efficient allocation of available charging capacity. Using a local neighborhood scenario, we evaluate the impact of such an approach.

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“…The work in [15] and [16] describes novel business opportunities for EV aggregation agents between EV owners and the Iberian Electric Market. A more detailed economic analysis is shown in [17] for different combinations of EV models, mobility patterns, and charging strategies at the German case.…”

Section: Introductionmentioning

confidence: 99%

Direct Load Control Decision Model for Aggregated EV Charging Points

Sánchez-Martin

Sanchez

Morales-España

2012

IEEE Trans. Power Syst.

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This paper details a decision model to implement direct load control (DLC) on battery charging processes at electric vehicle charging points located at parking areas. The programming model combines optimally three types of energy management decisions: grid-to-vehicle charges, vehicle-to-grid discharges, and novel vehicle-to-vehicle energy exchanges. The objective function maximizes the net energy supplied to batteries minimizing simultaneously the global energy cost. A 50-plug-in vehicle park case is analyzed for three possible mobility patterns: household, commercial and mixed. Outputs from the DLC model are compared with the ones using a dumb charging policy from the service quality and economic points of view. Finally, a sensitivity analysis has been done to evaluate the economic impact of the Depth of Discharge condition to preserve battery lifecycle of electric vehicles. Index Terms-Charging points, direct load control (DLC), electric vehicle batteries, grid to vehicle, vehicle to grid, vehicle to vehicle. NOMENCLATUREHere, we provide the main nomenclature used for quick reference of acronyms and elements of the programming model. Lower-case symbols denote indexes and parameters, and uppercase symbols denote variables. A. Main Acronyms[1] EV/EVB Electric vehicle/electric vehicle battery. PHEV Plug-in hybrid electric vehicle. EVCP Electric vehicle charging point. DLC Direct load control. AU/CAU Aggregation unit/central aggregation unit. G2VGrid-to-vehicle charging process. V2GVehicle-to-grid discharging process. V2VVehicle-to-vehicle energy exchange. B. IndexesType of plug-in vehicles {EV, PHEV}.

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Economic benchmark of charging strategies for battery electric vehicles

Cited by 18 publications

References 15 publications

Improving Electric Vehicle Charging Coordination Through Area Pricing

Improving Electric Vehicle Charging Coordination Through Area Pricing

A Revenue Management Approach for Efficient Electric Vehicle Charging Coordination

Direct Load Control Decision Model for Aggregated EV Charging Points

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