Optimal charging/discharging of grid-enabled electric vehicles for predictability enhancement of PV generation

Ghofrani, M.; Arabali, A.; Ghayekhloo, M.

doi:10.1016/j.epsr.2014.08.007

Cited by 50 publications

(39 citation statements)

References 22 publications

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“…Uncertainties like price or tariff developments or weather effects are addressed either by a sensitivity analysis (Komiyama and Fujii, 2014), by integrating probabilistic approaches (ElNozahy et al, 2015) or by approaches to minimize forecast uncertainties (Ghofrani et al, 2014;Moshövel et al, 2015). Not in all cases are the uncertainties of relevance to the results (Cai et al, 2013).…”

Section: Literature Reviewmentioning

confidence: 99%

Solar energy storage in German households: profitability, load changes and flexibility

2016

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Highlights• Domestic photovoltaics (PV) and storage systems are techno-economically analyzed.• PV & storage are profitable in the medium term due to high self-consumption rates.• Controlled electric vehicle charging improves load flexibility and self-generation.• External procurement of electricity drastically changes and decreases to 48-58 %.• Dynamic tariffs e. g. with load limits or demand charges incentivize load shifting. AbstractThe developments of battery storage technology together with photovoltaic (PV) roof-top systems might lead to far-reaching changes in the electricity demand structures and flexibility of households. The implications are supposed to affect the generation mix of utilities, distribution grid utilization, and electricity price. Using a techno-economic optimization model of a household system, we endogenously dimension PV system and stationary battery storage (SBS). The results of the reference scenario show positive net present values (NPV) for PV systems of approx. 500-1,800 EUR/kW p and NPV for SBS of approx. 150-500 EUR/kWh. Main influences are the demand of the households, selfconsumption rates, investment costs, and electricity prices. We integrate electric vehicles (EV) with different charging strategies and find increasing NPV of the PV system and self-consumption of approx. 70 %. With further declining system prices for solar energy storage and increasing electricity prices, PV systems and SBS can be profitable in Germany from 2018 on even without a guaranteed feed-in tariff or subsidies. Grid utilization substantially changes by households with EV and PV-SBS. We discuss effects of different incentives and electricity tariff options (e. g. load limits or additional demand charges). Concluding, solar energy storage systems will bring substantial changes to electricity sales. Keywordsdemand flexibility; optimization model; tariff design; electric vehicles; controlled charging; battery storage profitability Abbreviations CHP -combined heat and power; EEG -(Erneuerbare Energien Gesetz) Renewable Energy Act; EVelectric vehicle; EV2H -electric vehicle to home; NPV -net present value; PV -photovoltaics; RMSD -root-mean-square deviation; SBS -stationary batteries system; SoC -state of charge; ToU -time of use; UoSC -use of system charge

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Section: Literature Reviewmentioning

confidence: 99%

Solar energy storage in German households: profitability, load changes and flexibility

2016

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“…However, the intermittent nature of the RE sources creates uncertainties that require sophisticated scheduling strategies. This is particularly true for photovoltaic (PV) system, where its output power fluctuations and availability exhibit major challenges for such integration . A possible solution to compensate for the intermittency is to incorporate energy storage unit (ESU) into the PV grid‐connected charging system (simply known as a PV‐ESU grid system) .…”

Section: Introductionmentioning

confidence: 99%

Optimized sizing of photovoltaic grid‐connected electric vehicle charging system using particle swarm optimization

et al. 2018

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Summary In this paper, the particle swarm optimization (PSO) is used to find optimum size of the photovoltaic (PV) array and energy storage unit (ESU) for PV grid‐connected charging system (in office workplace) for electric vehicles (EV). It is designed in such a way that the EVs are charged at a fixed price (rather than time‐of‐use price) without incurring economic losses to the station owner. The simulation is modeled using the single diode model (for PV) and the state of charge of Li‐ion battery (for ESU and EV). The objective function of the PSO is formulated based on a financial model that comprises of the grid tariff, EV demand, and the purchasing as well as selling prices of the energy from PV and ESU. By integrating the financial model with energy management algorithm (EMA), the PSO computes the minimum number of PV modules (Npv) and ESU batteries (Nbat) for a various number of vehicles and office holidays. The resiliency of the proposed system is validated under different weather conditions, EV fleet, parity levels, energy prices, and operating period. Furthermore, the performance of the proposed system is compared with the standard grid charging system. The results suggest that with the computed Npv and Nbat, the charging price is decreased by approximately 16%, while the EV charging burden on the grid is reduced by 94% to 99%. It is envisaged that this work provides the guidance for the installers to precisely determine the optimum size of the components prior to the physical construction of the charging station.

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“…Reference [26] does not consider cloudy days. References [24,25] do not consider the fact that each vehicle has individual state of charge (SOC), departure time and intended minimum SOC level on departure. Reference [23] requires investment to local energy storage in addition to the EV batteries, but this cost is not discussed.…”

Section: Related Research In Electric Vehicle Battery Exploitationmentioning

confidence: 99%

“…Reference [23] ignores battery degradations costs, and [20] has an unrealistically small and unjustified figure of 1 ¢/kWh. References [24,25] only use EV batteries to cover the difference between forecasted and actual PV generation, without exploiting the batteries for storing the surplus generation and thus underusing the capacities of the batteries. Reference [26] does not consider cloudy days.…”

Section: Related Research In Electric Vehicle Battery Exploitationmentioning

confidence: 99%

Internet of Energy Approach for Sustainable Use of Electric Vehicles as Energy Storage of Prosumer Buildings

2018

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Vehicle-to-building (V2B) technology permits bypassing the power grid in order to supply power to a building from electric vehicle (EV) batteries in the parking lot. This paper investigates the hypothesis stating that the increasing number of EVs on our roads can be also beneficial for making buildings sustainably greener on account of using V2B technology in conjunction with local photovoltaic (PV) generation. It is assumed that there is no local battery storage other than EVs and that the EV batteries are fully available for driving, so that the EVs batteries must be at the intended state of charge at the departure time announced by the EV driver. Our goal is to exploit the potential of the EV batteries capacity as much as possible in order to permit a large area of solar panels, so that even on sunny days all PV power can be used to supply the building needs or the EV charging at the parking lot. A system architecture and collaboration protocols that account for uncertainties in EV behaviour are proposed. The proposed approach is proven in simulation covering one year period for three locations in different climatic regions of the US, resulting in the electricity bill reductions of 15.8%, 9.1% and 4.9% for California, New Jersey and Alaska, respectively. These results are compared to state-of-the-art research in combining V2B with PV or wind power generation. It is concluded that the achieved electricity bill reductions are superior to the state-of-the-art, because previous work is based on problem formulations that exploit only a part of the potential EV battery capacity.

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Optimal charging/discharging of grid-enabled electric vehicles for predictability enhancement of PV generation

Cited by 50 publications

References 22 publications

Solar energy storage in German households: profitability, load changes and flexibility

Solar energy storage in German households: profitability, load changes and flexibility

Optimized sizing of photovoltaic grid‐connected electric vehicle charging system using particle swarm optimization

Internet of Energy Approach for Sustainable Use of Electric Vehicles as Energy Storage of Prosumer Buildings

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