A Medium- and Long-Term Orderly Charging Load Planning Method for Electric Vehicles in Residential Areas

Xiao, Zhaoxia; Zhou, Yi; Cao, Jianing; Xu, Rui

doi:10.3390/wevj12040216

Cited by 5 publications

(1 citation statement)

References 11 publications

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“…The forecasting of EV charging demand is vital for intelligent energy management. For optimal control of grid power, medium‐ and long‐term EV charging load estimation schemes have been demonstrated in [37]. Most approaches utilize statistical methods, which are based on past data sets including EV charging load and meteorological data variation with respect to time.…”

Section: Design and Optimization Of Proposed Emsmentioning

confidence: 99%

Intelligent energy management scheme‐based coordinated control for reducing peak load in grid‐connected photovoltaic‐powered electric vehicle charging stations

Amir

Din

Haque

et al. 2023

IET Generation Trans & Dist

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Solar‐based Distributed Generation (DG) powered Electric Vehicles (EVs) charging stations are widely adopted nowadays in the power system networks. In this process, the distribution grid faces various challenges caused by intermittent solar irradiance, peak EVs load, while controlling the state of charge (SoC) of batteries during dis(charging) phenomena. In this paper, an intelligent energy management scheme (IEMS)‐based coordinated control for photovoltaic (PV)‐based EVs charging stations is proposed. The proposed IEMS optimizes the PV generation and grid power utilization for EV charging stations (EVCS) by analysing real‐time meteorological and load demand data. The coordinated control of EMS provides power flow between PV generation, distribution grid, and EVs battery storage in a manner which results in the reduction of peak power demand by a factor of two. Further, the adaptive neuro‐based fuzzy control approach includes forecasting solar‐based electricity generation and EVs loads demand predictions to optimize IEMS according to the Indian power scenario. The proposed IEMS optimally utilizes the buffer batteries system for reducing the peak electricity demand with low system losses and reducing the impact of EVs charging load on distribution grid. The results are analysed using the digital simulation model and validated with real‐time hardware‐in‐loop experimental setup.

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Section: Design and Optimization Of Proposed Emsmentioning

confidence: 99%

Intelligent energy management scheme‐based coordinated control for reducing peak load in grid‐connected photovoltaic‐powered electric vehicle charging stations

Amir

Din

Haque

et al. 2023

IET Generation Trans & Dist

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Communicational aspects in hierarchical real‐time control of electric vehicle charging: Available information and its value

Simolin

Rauma

Rautiainen

et al. 2023

IET Generation Trans & Dist

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Smart electric vehicle (EV) charging is a widely studied topic, and multiple different solutions have been proposed in the scientific literature to execute various demand response objectives. However, most studies use assumptions and simplifications that may not hold in real‐life situations, and thus, the proposed solutions may have a diminished practical value. Here, communicational aspects of hierarchical EV charging control are studied. The study considers the availability, acquisition, and value of certain information in case of real‐time control. The paper illustrates potential pitfalls when using certain assumptions or simplifications in the simulations and proposes a novel algorithm to deal with the lack of preliminary information that exists in real‐life situations. The objective of the proposed algorithm is to allow a lower‐layer controller to track the real‐time controllability of the EVs. This information is necessary in hierarchical control solutions with multiple lower‐layer controllers controlled by an upper‐layer controller to ensure efficient operation. The simulation results shows that a lower layer controller can estimate the controllability of the EV charging in realistic conditions within 1%–4 % accuracy despite the initially unknown characteristics of EVs.

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Control strategy for orderly charging of electric vehicles under a three-phase unbalanced distribution network

Chen,

Zeng,

Yang

et al. 2024

2024 5th International Conference on Computer Engineering and Application (ICCEA)

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A Medium- and Long-Term Orderly Charging Load Planning Method for Electric Vehicles in Residential Areas

Cited by 5 publications

References 11 publications

Intelligent energy management scheme‐based coordinated control for reducing peak load in grid‐connected photovoltaic‐powered electric vehicle charging stations

Intelligent energy management scheme‐based coordinated control for reducing peak load in grid‐connected photovoltaic‐powered electric vehicle charging stations

Communicational aspects in hierarchical real‐time control of electric vehicle charging: Available information and its value

Control strategy for orderly charging of electric vehicles under a three-phase unbalanced distribution network

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