Integration of Electric Vehicles into the Electric Power System Based on Results of Road Traffic Census

Iwafune, Yumiko; Ogimoto, Kazuhiko; Azuma, Hitoshi

doi:10.3390/en12101849

Cited by 16 publications

(12 citation statements)

References 13 publications

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“…Equations (5) and (6) describe the SOC condition of the EV battery, and (7)-(9) define that EV charge and discharge do not occur at the same time. Equation (10) describes the input and output balance of the whole household.…”

Section: B Ev Battery Optimization Model (Planning Model)mentioning

confidence: 99%

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Driving Simulator for Electric Vehicles Using the Markov Chain Monte Carlo Method and Evaluation of the Demand Response Effect in Residential Houses

Iwafune¹,

Ogimoto²,

Kobayashi³

et al. 2020

IEEE Access

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It is essential to secure flexible resources in power systems to increase the proportion of variable renewable energy generation systems. One flexible resource is demand response (DR) of the batteries of electric vehicles (EVs). In this study, we propose an electric vehicle driving simulator using the Markov chain Monte Carlo (MCMC) method and an EV demand response evaluation model. The former is a highly versatile EV driving simulator that can produce a random driving pattern based on actual EV fleet data, taking into account various features. The latter is a residential DR evaluation model that minimizes a household electricity bill based on the simulated fleet data and enables realistic DR operation using three processes: forecasting, planning, and operation. The contribution of this paper is to enable evaluation of realistic EV battery value in various housing and EV utilization combinations. We found that the EV battery control provides an economic benefit of US$62 (5% of the night-charging case cost) with only charge control and US$370 (31%) with charge and discharge control, as the average expected value based on our assumption of evaluation. Because 40-kWh EV batteries have a sufficiently large capacity to store surplus power from a rooftop PV, they can be operated by determining the operation schedule based on a fixed-fee structure without forecasting or planning.

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Section: B Ev Battery Optimization Model (Planning Model)mentioning

confidence: 99%

“…We have proposed evaluation models of DR resources for housing construction [3], [4] and for power systems [5]. In this paper, we quantitatively evaluate the value of EV batteries in a house.…”

Section: Introductionmentioning

confidence: 99%

Driving Simulator for Electric Vehicles Using the Markov Chain Monte Carlo Method and Evaluation of the Demand Response Effect in Residential Houses

Iwafune¹,

Ogimoto²,

Kobayashi³

et al. 2020

IEEE Access

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“…The annual mileage of the commuter EV is estimated to be 9390 km. According to the analysis based on a nationwide survey in Japan [13], the average mileage of private cars is approximately 9300 km/year, and the mileage of only short-range cars including most non-commuter cars is below approximately 5475 km/year. Therefore, the EV mileage estimated in this case study is considered to be adequate.…”

Section: Case Ev Driving Patternmentioning

confidence: 99%

Comparison of the Economic and Environmental Performance of V2H and Residential Stationary Battery: Development of a Multi-Objective Optimization Method for Homes of EV Owners

Kataoka

Shichi

Yamada

et al. 2019

WEVJ

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The use of batteries of electric vehicles (EVs) for home electricity applications using a bidirectional charger, a process called vehicle-to-home (V2H), is attracting the attention of EV owners as a valuable additional benefit of EVs. To motivate owners to invest in V2H, a quantitative evaluation to compare the performance of EV batteries with that of residential stationary batteries (SBs) is required. In this study, we developed a multi-objective optimization method for the household of EV owners using energy costs including investment and CO2 emissions as indices and compared the performances of V2H and SB. As a case study, a typical detached house in Japan was assumed, and we evaluated the economic and environmental aspects of solar power self-consumption using V2H or SB. The results showed that non-commuting EV owners should invest in V2H if the investment cost of a bidirectional charger is one third of the current cost as compared with inexpensive SB, in 2030. In contrast, our results showed that there were no advantages for commuting EV owners. The results of this study contribute to the rational setting of investment costs to increase the use of V2H by EV owners.

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“…The LFC timescale is an ancillary service that corresponds to a secondary frequency-control reserve [24]. We analyzed the electricity supply and demand using a production-cost model [25] that endogenously optimizes the operation of the power system, including generators, hydropumped storage, interconnection lines, and the balancing capacity provided by V2G power control on the LFC timescale (V2G LFC). The operational cost savings of the power system attributable to the V2G LFC were determined considering VRE penetration and EV fleet availability in each interconnected area.…”

Section: Introductionmentioning

confidence: 99%

“…We assume that the aggregated EV fleet for V2G consists of private EVs on daily work-home commutes. An analysis of Japanese vehicle driving patterns [25] showed that private commuter cars had high switching potential from conventional vehicles to EVs, due to small driving distances, and the fleet behavior was predictable because most activities were between the home and office before and after working hours.…”

Section: Introductionmentioning

confidence: 99%

Marginal Value of Vehicle-to-Grid Ancillary Service in a Power System with Variable Renewable Energy Penetration and Grid Side Flexibility

2021

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Regulating the frequencies of power grids by controlling electric vehicle charging and discharging, known as vehicle-to-grid (V2G) ancillary services, is a promising and profitable means of providing flexibility that integrates variable renewable energy (VRE) into traditional power systems. However, the ancillary services market is a niche, and the scale, saturation, and time-dependency are unclear when assuming future changes in the power system structure. We studied the marginal value of V2G ancillary services as a balancing capacity of the power system operation on the load-frequency control (LFC) timescale and evaluated the reasonable maximum capacity of the LFC provided by V2G. As a case study, we assumed that the Japanese power system would be used under various VRE penetration scenarios and considered the limited availability time of V2G, based on the daily commuter cycle. The power system operation was modeled by considering pumped storage, interconnection lines, and thermal power–partial load operations. The results show that the marginal value of V2G was greater during the daytime than overnight, and the maximum cost saving (USD 705.6/EV/year) occurred during the daytime under the high-VRE scenario. Improving the value and size of V2G ancillary services required coordination with energy storage and excess VRE generation.

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Integration of Electric Vehicles into the Electric Power System Based on Results of Road Traffic Census

Cited by 16 publications

References 13 publications

Driving Simulator for Electric Vehicles Using the Markov Chain Monte Carlo Method and Evaluation of the Demand Response Effect in Residential Houses

Driving Simulator for Electric Vehicles Using the Markov Chain Monte Carlo Method and Evaluation of the Demand Response Effect in Residential Houses

Comparison of the Economic and Environmental Performance of V2H and Residential Stationary Battery: Development of a Multi-Objective Optimization Method for Homes of EV Owners

Marginal Value of Vehicle-to-Grid Ancillary Service in a Power System with Variable Renewable Energy Penetration and Grid Side Flexibility

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