Energy Management System With PV Power Forecast to Optimally Charge EVs at the Workplace

Meer, Dennis van der; Mouli, Gautham Ram Chandra; Ramírez-Elizondo, Laura; Bauer, Pavol

doi:10.1109/tii.2016.2634624

Cited by 190 publications

(103 citation statements)

References 29 publications

(45 reference statements)

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“…Smart charging of EVs can provide several benefits to the EV owner and to the providers of the EV charging infrastructure: 1. Reduce the cost of EV charging based on energy prices [17] 2. Provide new revenue streams like vehicle-to-grid [18] 3.…”

Section: Smart Charging Of Evsmentioning

confidence: 99%

“…Implementing multiplexing of EV chargers and using a single charger for several EVs. This will drastically reduce cost of EV charging infrastructure [17][25]…”

Section: Smart Charging Of Evsmentioning

confidence: 99%

“…In the future, integration of several smart charging applications in a single framework will be the key. The benefits will then add up and the net gain will become economically attractive for large-scale implementation [17].…”

Section: Smart Charging Of Evsmentioning

confidence: 99%

“…3, DC disconnectors can be used to connect different EVs to the same EV fast charger. Based on the EV user energy demand and departure time, the EV charging can be scheduled for the multiplexed EVs [17], [25].…”

Section: Multiplexing Of Ev Charger To Several Evsmentioning

confidence: 99%

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Future of electric vehicle charging

Mouli

Venugopal

Bauer

2017

2017 International Symposium on Power Electronics (Ee)

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Abstract-Charging infrastructure for electric vehicles (EV) will be the key factor for ensuring a smooth transition to emobility. This paper focuses on five technologies that will play a fundamental role in this regard: smart charging, vehicle-to-grid (V2G), charging of EVs from photovoltaic panels (PV), contactless charging and on-road charging of EVs. Smart charging of EVs is expected to enable larger penetration of EVs and renewable energy, lower the charging cost and offer better utilization of the grid infrastructure. Bidirectional EV chargers will pave the way for V2G technology where the EV can be used for energy arbitrage and demand-side management. Solar charging of EV will result in sustainable transportation and use of the EV battery as PV storage. On the other hand, stationary contactless charging and on-road inductive charging of EV will remove the necessity for any cables, eliminate range anxiety issues and pave the way for automated driving. The electromagnetic and power converter design for contactless power transfer systems for future highways is reviewed in this paper.

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Section: Smart Charging Of Evsmentioning

confidence: 99%

“…Implementing multiplexing of EV chargers and using a single charger for several EVs. This will drastically reduce cost of EV charging infrastructure [17][25]…”

Section: Smart Charging Of Evsmentioning

confidence: 99%

Section: Smart Charging Of Evsmentioning

confidence: 99%

Section: Multiplexing Of Ev Charger To Several Evsmentioning

confidence: 99%

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Future of electric vehicle charging

Mouli

Venugopal

Bauer

2017

2017 International Symposium on Power Electronics (Ee)

Self Cite

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“…Where p is an autoregressive parameter, d is differencing parameter and q is moving average parameter. Typically, Box-Jenkins method is followed to find p, d and q parameters [2]. This method is usually difficult to understand and find the correct parameters.…”

Section: Introductionmentioning

confidence: 99%

Solar and Wind Power Forecasting with Optimal ARIMA Parameters

Swaroop¹,

Reddy²

2018

IJET

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The solar and wind renewable energy sources are gaining popularity to encourage green energy into the power system. The cost of generation of solar and wind energy sources are decreasing and competing with conventional coal-based generation. Therefore, it is very important to integrate these renewable sources into the power system. Integrating Solar and wind energy sources require to solve the uncertainty problem. Both the solar and wind energy generation is uncertain and not controllable. In this paper, sliding window optimal ARIMA forecasting algorithm is proposed to solve the uncertainty associated with solar and wind sources. The proposed forecasting method is used on the data collected from National Renewable Energy Laboratory website.

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Residential virtual power plant with photovoltaic output forecasting and demand response

Cui

Wang

Lin

et al. 2019

Asian Journal of Control

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Decreasing conventional power supply is promoting the development of the distributed renewable energy sources, such as solar power and wind power.Recently rooftop photovoltaic has been widely applied, and accordingly efficient energy management is getting increasingly important for fully use of renewable energy and the peak shaving of the main grid. This paper investigates the residential energy management as a small-scale virtual power plant (VPP) connected to the main grid includes distributed energy resources, energy storages and residential loads. The self-organizing map (SOM) and the radical basis function (RBF) networks are adopted to classify the weather types and predict hourly photovoltaic output precisely. In a time-of-use electricity market, price-based demand response is applied to adjust the demand. The residential VPP has two goals: maximum profit by selling surplus power to grid and minimum power purchased from grid. The two goals are integrated as an optimization object by introducing a weight parameter. The algorithm combining receding horizon optimization and linear programming is proposed to solve the optimization problem in residential VPP. Numerical simulation tests can help to find the most suitable value of the weight parameter. Different scenarios are simulated and discussed to demonstrate the performance of the VPP and the proposed algorithm.

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Energy Management System With PV Power Forecast to Optimally Charge EVs at the Workplace

Cited by 190 publications

References 29 publications

Future of electric vehicle charging

Future of electric vehicle charging

Solar and Wind Power Forecasting with Optimal ARIMA Parameters

Residential virtual power plant with photovoltaic output forecasting and demand response

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