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Sökning: id:"swepub:oai:DiVA.org:kth-312043" > LSTM-based Energy M...

LSTM-based Energy Management for Electric Vehicle Charging in Commercial-building Prosumers

Zhou, H. (författare)
Zhou, Y. (författare)
Hu, J. (författare)
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Yang, G. (författare)
Xie, D. (författare)
Xue, Y. (författare)
Nordström, Lars, 1969- (författare)
KTH,Elkraftteknik
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 (creator_code:org_t)
Journal of Modern Power Systems and Clean Energy, 2021
2021
Engelska.
Ingår i: Journal of Modern Power Systems and Clean Energy. - : Journal of Modern Power Systems and Clean Energy. - 2196-5625 .- 2196-5420. ; 9:5, s. 1205-1216
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
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  • As typical prosumers, commercial buildings equipped with electric vehicle (EV) charging piles and solar photovoltaic panels require an effective energy management method. However, the conventional optimization-model-based building energy management system faces significant challenges regarding prediction and calculation in online execution. To address this issue, a long short-term memory (LSTM) recurrent neural network (RNN) based machine learning algorithm is proposed in this paper to schedule the charging and discharging of numerous EVs in commercial-building prosumers. Under the proposed system control structure, the LSTM algorithm can be separated into offline and online stages. At the offline stage, the LSTM is used to map states (inputs) to decisions (outputs) based on the network training. At the online stage, once the current state is input, the LSTM can quickly generate a solution without any additional prediction. A preliminary data processing rule and an additional output filtering procedure are designed to improve the decision performance of LSTM network. The simulation results demonstrate that the LSTM algorithm can generate near-optimal solutions in milliseconds and significantly reduce the prediction and calculation pressures compared with the conventional optimization algorithm. 

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Annan elektroteknik och elektronik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Other Electrical Engineering, Electronic Engineering, Information Engineering (hsv//eng)
TEKNIK OCH TEKNOLOGIER  -- Naturresursteknik -- Energisystem (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Environmental Engineering -- Energy Systems (hsv//eng)
TEKNIK OCH TEKNOLOGIER  -- Maskinteknik -- Farkostteknik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Mechanical Engineering -- Vehicle Engineering (hsv//eng)

Nyckelord

Building energy management system (BEMS)
electric vehicle (EV)
long short-term memory (LSTM)
machine learning
prosumer
recurrent neural network
Electric vehicles
Energy management
Energy management systems
Forecasting
Learning algorithms
Long short-term memory
Office buildings
Optimization
Photovoltaic cells
Solar power generation
Building energy management system
Building energy management systems
Commercial building
Conventional optimization
Electric vehicle
Electric vehicle charging
Memory algorithms
Offline
Data handling

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