Aggregated impacts of electric vehicles on electricity distribution in New South Wales, Australia

This paper proposes two electric energy management systems (EMSs) in the context of a gridconnected residential neighbourhood with electric vehicles (EVs), battery storage, and solar photovoltaic (PV) generation. The EMSs were developed to minimize the cost of electricity whilst having no impact on routine individual energy needs and travel patterns. The EMSs were evaluated using common sets of real data with the aim to compare the effectiveness of a centralized EMS with decentralized EMS. The models also accounted for the battery capacity degradation and the associated costs. Simulation studies and numerical analyses were presented to validate the effectiveness of the proposed EMSs considering a high-density residential building in Sydney, Australia. The simulation results indicate that the centralized EMS is more effective compared to the decentralized EMS in terms of cost savings. It is also observed that the energy management strategies significantly reduce the energy drawn from the grid compared to un-optimized energy management schemes.

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“…The time of use tariff (TOU) and the cumulative household load are taken from [36] and presented in fig. 6.…”

Section: ) Energy Tariffmentioning

confidence: 99%

“…For simplicity, a mid-range V2G capable EV is considered with a rated battery capacity of 24 kWh and a usable battery capacity of 19.2 kWh (i.e., 80% depth of discharge), as in [36]. The initial and final SOC of stationary battery and the EVs are considered the same to model the continuity.…”

Section: ) Ev Specifications and Travel Patternsmentioning

confidence: 99%

Energy Management Systems for Residential Buildings With Electric Vehicles and Distributed Energy Resources

et al. 2021

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“…On average, vehicles in NSW travel approximately 11650 kilometres per annum. It was reported in [12] that about 88% of those vehicles drive less than 30 km per day, and approximately 95% of vehicles travel less than 45 km per day.…”

Section: A Ev Load Modellingmentioning

confidence: 99%

Novel Sizing Method of Energy Storage System Considering Intermittent Usage of EVs in a Constrained Grid

Irshad

Rafique

Hossain

et al. 2020

2020 2nd International Conference on Smart Power &Amp; Internet Energy Systems (SPIES)

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Charging of electric vehicles (EVs) significantly impact the reliability of the power system. A constrained power grid is a feasible solution to maintain the reliability of the power system. However, in a constrained power grid, it is challenging for the system operator to balance the additional load. Fast and high-power density of batteries makes them a conceivable option for this task, if properly sized. Charging profile of EVs is constructed by considering travel pattern, charging need and driver's behaviour of EVs. Moreover, a sizing algorithm is proposed to compute the battery capacity for parking lots equipped with EV chargers in a constrained grid. The proposed sizing algorithm ensures 1) balance the EV load, 2) avoid over/under-sizing of the system. The accuracy of the proposed battery sizing algorithm is shown by simulation results, characterised by using real data of household travel survey and parking occupancy data.

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“…The building consists of five floors with four individual apartments on each floor and a ground floor with parking space. It is assumed that each apartment has its own designated parking space and a Level-1, bidirectional EV charger at 220 V, 15 A, 3 kW charging/discharging power with 10% losses, as used by [15], [18]. Each apartment has a floor surface of 92 m2.…”

Section: Datasetsmentioning

confidence: 99%

“…3) Electric vehicles & travel data: Our simulations assumed that each household had one EV with a rated battery capacity of 24 kWh and a useful battery capacity of 19.2 kWh (i.e. 80% depth of discharge) as used by [15], [18]. Data for vehicle travel/usage pattern was extracted from The Victorian Integrated Survey of Travel and Activity (VISTA) [20].…”

Section: Datasetsmentioning

confidence: 99%

An aggregator-based-strategy to minimize the cost of energy consumption by optimal utilization of energy resources in an apartment building

Rafique

Nizami

Irshad

et al. 2019

2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Syst

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Buildings and transport consume two thirds of the total global energy. It is desirable to maximize the use of renewable generation in these sectors, and to optimize the use of that energy by managing diverse sources and loads. This is particularly challenging in high-density residential premises where the space for such infrastructure is limited, and storage can have significant impact on energy utilization and demand. In this paper, we have proposed an aggregator-based-strategy (ABS) to optimally utilize the available energy resources and storage in an apartment building with twenty households, each having an electric vehicle (EV), and an aggregated solar photovoltaic (PV) energy and stationary battery storage (BS) system. The strategy is flexible and can be applied to any building with EVs, solar PV and BS to minimize the cost of energy consumption without compromising the flexibility of energy usage or travel requirements. The model also accounts for the battery capacity degradation and its associated cost to make it more realistic. The model is evaluated using real data and the results show that the strategy not only reduces the cost of energy consumption but also reduces the amount of energy drawn from the grid significantly.

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Aggregated impacts of electric vehicles on electricity distribution in New South Wales, Australia

Cited by 8 publications

References 20 publications

Energy Management Systems for Residential Buildings With Electric Vehicles and Distributed Energy Resources

Energy Management Systems for Residential Buildings With Electric Vehicles and Distributed Energy Resources

Novel Sizing Method of Energy Storage System Considering Intermittent Usage of EVs in a Constrained Grid

An aggregator-based-strategy to minimize the cost of energy consumption by optimal utilization of energy resources in an apartment building

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