A simple control strategy and dynamic energy management for the operation of combined grid-connected and standalone solar photovoltaic applications

Rakesh, Namani; Subramaniam, Sreeramanan; Samikannu, SarojiniMary; Madhusudanan, G.

doi:10.1016/j.jksues.2021.12.009

Cited by 5 publications

(2 citation statements)

References 26 publications

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“…Here, the microgrids and nano grids work with the entity that manages small-scale utility network area units, which can be seamlessly isolated from the electrical grid. 1 Each supply a way to incorporate distributed energy resources (DER) and renewable energy-based electric vehicles into a broad area network, 2 and the area unit plays a significant role during this effort. The relationship among transport electrification as well as renewable energy resources (RESs) includes great possible to counter fuel dependence, greenhouse gas (GHG) emissions, 3 solving the total edges of electrical quality.…”

Section: Introductionmentioning

confidence: 99%

Review of electric vehicle (EV) charging using renewable solar photovoltaic (PV) nano grid

Satheesh Kumar,

Ashok Kumar,

Senthilrani

2023

Energy & Environment

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This review article gives a comprehensive review of existing research on renewable solar photovoltaic (PV) nanogrid, which is described from small-scale power system with a single domain for reliability, control, and power quality (PQ) for electric vehicle (EV) charging. A primary feeder on the Microgrid is connected to a nanogrid test bed that includes PV as power source, a battery energy storage system (BESS), smart-inverter multiple and EV charging stations (EVCS). The control algorithms are graded on four metrics: (1) voltage profiles, (2) renewable penetration, (3) PV curtailed and (4) net power flows. To investigate the local power quality, a steady-state power flow model of the nano-grid is created. The control algorithms successfully employ the battery to shift the nano-grid peak load while limiting the nano-grid demand to set level. Furthermore, an increasing emphasis is being placed on commonly used strategies for addressing the characteristics of each renewable system. This review paper characterizes the dynamic operation of 4 distinct BESS control algorithms for solar EV charging nanogrid: (1) peak load shifting, (2) reduce peak period impact, (3) cap demand, and (4) photovoltaic capture. These control modes are executed and analyzed on real-world nano-grid site, and optimal BESS control modes are assessed in terms of (1) solar electric vehicle charging, (2) power quality, (3) grid net demand, (4) photovoltaic curtailment, and (5) solar penetration. Finally, the problems highlight research gaps, and discussions on future trends are critical for enhancing the general technology of the renewable solar photovoltaic nano-grid for EV charging.

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Section: Introductionmentioning

confidence: 99%

Review of electric vehicle (EV) charging using renewable solar photovoltaic (PV) nano grid

Satheesh Kumar,

Ashok Kumar,

Senthilrani

2023

Energy & Environment

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“…Looking ahead to 2060, the International Energy Agency predicts a significant increase in power demand, particularly in the transportation sector, where electricity will replace gasoline as the primary fuel. [2,3] Renewable energy sources (RES) are expected to play a vital role in meeting emission reduction goals, emphasizing the need for electrical service quality in the smart grid era. [4] The integration of renewable distributed generation (DG) units and the unpredictable charging loads of EVs introduce uncertainty into smart grid operation, challenging conventional reliability assessment methods.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Technique for Optimal Placement of Fast‐Charging Stations of Electric Vehicles for the Reliability of Distribution Network

Ranjith Kumar,

Vallimurugan

2023

Energy Tech

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Proper planning for electric vehicle (EV) charging stations, as well as the necessary network development, is critical for the continued growth of EVs and conventional loads. This article proposes a hybrid method for the allocation of fast‐charging stations (FCSs) and photovoltaic (PV) with battery energy storage (BES) and scheduling. The proposed hybrid technique is the wrapper of golden jackal optimization (GJO) and random forest algorithms (RFA), commonly named the GJO–RFA technique. Using the GJO approach, the allocation and EV assignment problems are resolved. RFA is used to address EV, traffic flow, and PV‐related uncertainties. The objective of the proposed approach is to minimize the loss of energy, investments, index of voltage deviation, and operation and maintenance costs of FCS, PV, and BES. The associated important factors are also assessed, including the number of charging ports, FCS capacity, and EV flow caught using a FCS. As a test example, a 33‐node radial distribution network with the appropriate traffic network is used. For the final problem, the proposed approach to minimal energy loss is 2622.7270 kWh. By then, the performance of the proposed approach is executed in MATLAB, and it is contrasted with other existing techniques. The result shows that the proposed method‐related energy loss is less than existing approaches.

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Optimal battery-swapping mechanism for electric vehicles using hybrid approach

Madhanakkumar,

Vijayaragavan,

Krishnakumar

et al. 2023

Clean Techn Environ Policy

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A simple control strategy and dynamic energy management for the operation of combined grid-connected and standalone solar photovoltaic applications

Cited by 5 publications

References 26 publications

Review of electric vehicle (EV) charging using renewable solar photovoltaic (PV) nano grid

Review of electric vehicle (EV) charging using renewable solar photovoltaic (PV) nano grid

A Hybrid Technique for Optimal Placement of Fast‐Charging Stations of Electric Vehicles for the Reliability of Distribution Network

Optimal battery-swapping mechanism for electric vehicles using hybrid approach

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