scholarly journals Possibilities and Challenges for the Inclusion of the Electric Vehicle (EV) to Reduce the Carbon Footprint in the Transport Sector: A Review

Energies ◽  
2020 ◽  
Vol 13 (10) ◽  
pp. 2602 ◽  
Author(s):  
Aritra Ghosh
Keyword(s):  
Greenhouse Gas Emission ◽  
Global Climate ◽  
Storage System ◽  
Photovoltaic System ◽  
Transport Sector ◽  
Sustainable Mobility ◽  
Charging Station ◽  
Essential Components ◽  
The Government ◽  
Solar Photovoltaic System

To combat global climate change moving towards sustainable, mobility is one of the most holistic approaches. Hence, decarbonization of the transport sector by employing electric vehicles (EVs) is currently an environmentally benign and efficient solution. The EV includes the hybrid EV (HEV), the plug-in hybrid EV (PHEV), and the battery EV (BEV). A storage system, a charging station, and power electronics are the essential components of EVs. The EV charging station is primarily powered from the grid which can be replaced by a solar photovoltaic system. Wide uptake of EVs is possible by improving the technologies, and also with support from the government. However, greenhouse gas emission (GHG) saving potential of the EV is debatable when the required power to charge the EV comes from traditional fossil fuel sources.

scholarly journals Micro grid for All India Institute of Medical Sciences, Madurai

Clean Energy ◽  
2021 ◽  
Vol 5 (2) ◽  
pp. 254-272
Author(s):  
C Palanichamy ◽  
P Naveen
Keyword(s):  
Tamil Nadu ◽  
Storage System ◽  
Healthcare Facility ◽  
Photovoltaic System ◽  
India Institute ◽  
Diesel Generator ◽  
Medical Sciences ◽  
System A ◽  
Utility Grid ◽  
The Government

Abstract In 2018, the Government of India approved the establishment of the New All India Institute of Medical Sciences (AIIMS) in Thoppur, Madurai, Tamil Nadu, India. As the most important amenity for continuing primary care and rescue response is a healthcare facility, a secure electricity supply becomes an imperative necessity. Hence, as the energy supplier for the new AIIMS, Madurai, this paper proposes a microgrid combined with the utility grid. The microgrid consists of a 4-MW photovoltaic system, a 1.8-MW wind-turbine energy-conversion system, a backup diesel generator capable of meeting the forecasted maximum demand and a 1-MW battery energy-storage system. The AIIMS Microgrid will have a service providing a capacity of 20 MVA following integration with the utility grid. The proposed microgrid would be the first attempt at healthcare facilities in India since its first day of work to ensure the availability of electricity. It would have a 9.8% return on investment, a 13.6% internal rate of return and a payback period of 6.75 years once it is operational, as well as an attractive levelized cost of energy (LCOE) of USD 0.07547/kWh. It would provide an environmentally friendly atmosphere by avoiding an annual emission of 6 261 132 kg of carbon dioxide, 27 362 kg of sulphur dioxide and 12 838 kg of nitrogen oxides as compared to power supplied entirely from the utility grid.

scholarly journals A Robust Optimization for Designing a Charging Station Based on Solar and Wind Energy for Electric Vehicles of a Smart Home in Small Villages

2018 ◽  
Author(s):  
Amir Ahadi ◽  
Shrutidhara Sarma ◽  
Jae Sang Moon ◽  
Jang Ho Lee
Keyword(s):  
Renewable Energy ◽  
Electric Vehicles ◽  
Storage System ◽  
Real Life ◽  
Energy Systems ◽  
Energy Storage System ◽  
Photovoltaic System ◽  
Design Stage ◽  
Renewable Energy Systems ◽  
Charging Station

In recent years, integration of electric vehicles (EVs) has increased dramatically due to their lower carbon emissions and reduced fossil fuel dependency. However, charging EVs could have significant impacts on the electrical grid. One promising method for mitigating these impacts is the use of renewable energy systems. Renewable energy systems can also be useful for charging EVs where there is no local grid. This paper proposes a new strategy for designing a renewable energy charging station consisting of wind turbines, a photovoltaic system, and an energy storage system to avoid the use of diesel generators in remote communities. The objective function is considered to be the minimization of the total net present cost, including energy production, components setup, and financial viability. The proposed approach, using stochastic modeling, can also guarantee profitable operation of EVs and reasonable effects on renewable energy sizing, narrowing the gap between real-life daily operation patterns and the design stage. The proposed strategy should enhance the efficiency of conventional EV charging stations. The key point of this study is the efficient use of excess electricity. The infrastructure of the charging station is optimized and modeled.

scholarly journals Reinforcement Learning-Based Energy Management of Smart Home with Rooftop Solar Photovoltaic System, Energy Storage System, and Home Appliances

Sensors ◽  
2019 ◽  
Vol 19 (18) ◽  
pp. 3937 ◽  
Author(s):  
Sangyoon Lee ◽  
Dae-Hyun Choi
Keyword(s):  
Energy Storage ◽  
Smart Home ◽  
Storage System ◽  
Energy Storage System ◽  
Photovoltaic System ◽  
Solar Photovoltaic ◽  
Air Conditioner ◽  
Indoor Temperature ◽  
Q Learning ◽  
Solar Photovoltaic System

This paper presents a data-driven approach that leverages reinforcement learning to manage the optimal energy consumption of a smart home with a rooftop solar photovoltaic system, energy storage system, and smart home appliances. Compared to existing model-based optimization methods for home energy management systems, the novelty of the proposed approach is as follows: (1) a model-free Q-learning method is applied to energy consumption scheduling for an individual controllable home appliance (air conditioner or washing machine), as well as the energy storage system charging and discharging, and (2) the prediction of the indoor temperature using an artificial neural network assists the proposed Q-learning algorithm in learning the relationship between the indoor temperature and energy consumption of the air conditioner accurately. The proposed Q-learning home energy management algorithm, integrated with the artificial neural network model, reduces the consumer electricity bill within the preferred comfort level (such as the indoor temperature) and the appliance operation characteristics. The simulations illustrate a single home with a solar photovoltaic system, an air conditioner, a washing machine, and an energy storage system with the time-of-use pricing. The results show that the relative electricity bill reduction of the proposed algorithm over the existing optimization approach is 14%.

scholarly journals New algorithm for energy dispatch scheduling of grid-connected solar photovoltaic system with battery storage system

2021 ◽  
pp. 27-34
Author(s):  
F. Slama ◽  
H. Radjeai ◽  
S. Mouassa ◽  
A. Chouder
Keyword(s):  
Energy Demand ◽  
Power Flow ◽  
Storage System ◽  
Threshold Energy ◽  
Energy Storage System ◽  
Photovoltaic System ◽  
Pv System ◽  
The Stability ◽  
Solar Photovoltaic System ◽  
Grid Based

Purpose. In last decade the problem of energy management system (EMS) for electric network has received special attention from academic researchers and electricity companies. In this paper, a new algorithm for EMS of a photovoltaic (PV) grid connected system, combined to an storage system is proposed for reducing the character of intermittence of PVs power which infect the stability of electric grid. In simulation model, the PV system and the energy storage system are connected to the same DC bus, whereas EMS controls the power flow from the PV generator to the grid based on the predetermined level of PV power. In the case where the PV power is less than the predefined threshold, energy is stored in the batteries banc which will be employed in the peak energy demand (PED) times. Otherwise, it continues to feed the principal grid. The novelty of the proposed work lies in a new algorithm (smart algorithm) able to determine the most suitable (optimal) hours to switching between battery, Solar PVs, and principal grid based on historical consumption data and also determine the optimal amount of storage energy that be injected during the peak demand. Methods. The solution of the problem was implemented in the Matlab R2010a Platform and the simulation conducted on Laptop with a 2.5 GHz processor and 4 GB RAM. Results. Simulation results show that the proposed model schedules the time ON/OFF of the switch in the most optimal way, resulting in absolute control of power electric path, i.e. precise adaptation at the peak without compromising consumers comfort. In addition, other useful results can be directly obtained from the developed scheme. Thus, the results confirm the superiority of the proposed strategy compared to other improved techniques.

Operation of a Hydrogen Storage-Based Smart DC Microgrid

2022 ◽  
pp. 145-172
Author(s):  
Mahesh Kumar
Keyword(s):  
Hydrogen Storage ◽  
Low Voltage ◽  
Storage System ◽  
Energy Storage System ◽  
Photovoltaic System ◽  
Control Technique ◽  
Dc Microgrid ◽  
Hydrogen Storage System ◽  
Solar Photovoltaic System ◽  
Battery Energy

In this chapter, the author presents the operation and power management of the hydrogen storage-based smart DC microgrid (DCMG). In this microgrid, several renewable distributed generations (DGs) such as wind turbine, solar photovoltaic system, solid oxide fuel cell (SOFC), and battery energy storage system are interconnected together and to the various DC and AC loads to form a ring-type low voltage distribution network. An additional storage as Hydrogen storage system has been connected to the dc microgrid for balancing the power at all times in the DCMG, under islanded mode operation, for all practical cases. An architecture of the hydrogen storage-based DC microgrid is suggested mainly for the remote rural area. For the regeneration of the electricity from the stored hydrogen, a SOFC DG system is also used in the proposed DCMG. A control technique is also developed for the operation of the hydrogen storage-based DCMG. The proposed DCMG system provides a reliable and high-quality power supply and will supply the power to all loads (both DC and AC) simultaneously.

scholarly journals Design of Battery Storage System for Malaysia Low Voltage Distribution Network with the Presence of Residential Solar Photovoltaic System

Energies ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4887
Author(s):  
Meysam Shamshiri ◽  
Chin Kim Gan ◽  
Junainah Sardi ◽  
Mau Teng Au ◽  
Wei Hown Tee
Keyword(s):  
Low Voltage ◽  
Reverse Flow ◽  
Control Strategies ◽  
Storage System ◽  
Distribution Networks ◽  
Photovoltaic System ◽  
Solar Photovoltaic ◽  
Network Losses ◽  
Solar Photovoltaic System ◽  
Solar Generation

The recent proliferation of residential solar photovoltaic systems has prompted several technical challenges to the operation of low voltage (LV) distribution networks. More specifically, the mismatch of the solar generation and demand profiles, particularly during the midday when the demand is low and solar generation is high, can lead to network overvoltages and increased network losses. In addition, the solar photovoltaic system is not able to reduce the system’s maximum demand, given the residential LV network would normally have an evening peak when the sun goes down. In this regard, this paper examines two different control strategies in designing the battery energy storage system. One aims to eliminate reverse flow caused by the surplus solar energy and the other aims for peak demand reduction.

scholarly journals Design and Simulation of Romanian Solar Energy Charging Station for Electric Vehicles

Energies ◽  
2018 ◽  
Vol 12 (1) ◽  
pp. 74 ◽  
Author(s):  
Gheorghe Badea ◽  
Raluca-Andreea Felseghi ◽  
Mihai Varlam ◽  
Constantin Filote ◽  
Mihai Culcer ◽  
...  
Keyword(s):  
Solar Energy ◽  
Electric Vehicles ◽  
Renewable Resources ◽  
Clean Energy ◽  
Energy System ◽  
Photovoltaic System ◽  
Transport Sector ◽  
Charging Station ◽  
One Year ◽  
Main Components

Since mid 2010, petrol consumption in the transport sector has increased at a higher rate than in other sectors. The transport sector generates 35% of the total CO2 emissions. In this context, strategies have been adopted to use clean energy, with electromobility being the main directive. This paper examines the possibility of charging electric vehicle batteries with clean energy using solar autochthonous renewable resources. An isolated system was designed, dimensioned, and simulated in operation for a charging station for electric vehicles with photovoltaic panels and batteries as their main components. The optimal configuration of the photovoltaic system was complete with improved Hybrid Optimization by Genetic Algorithms (iHOGA) software version 2.4 and we simulated its operation. The solar energy system has to be designed to ensure that the charging station always has enough electricity to supply several electric vehicles throughout all 24 h of the day. The main results were related to the energy, environmental, and economic performance achieved by the system during one year of operation.

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