The parametric analysis of the electric vehicles and vehicle to grid system’s role in flattening the power demand

Electric vehicles are getting popularity as these are eco-friendly and could be a part of power sector in the future. Electric Vehicles are the smart hybrid vehicles, which stores electric power during their operation, which could be stored in storage cells. These electric vehicles may be plug-in electric vehicles or battery operated electric vehicles. The concept of aggregators may be utilized, wherein the stored energy in vehicles could be supplied to grid during parking hours .This also facilitate the consumers to sale power during the high power demand and purchase power during low power demand. Thus, a bi-directional flow of power could be possible either from vehicle to grid or vice-versa. A large penetration of electric vehicles could result in increase in power demand which could be compensated by proper coordinated unit commitment and optimization techniques. The increasing load on grid by the impact of demand and trends in small generating units which require proper selection of number of generating units to put in line and other units in off condition calls for the concept of unit commitment. It is the selection of more efficient units to be in service and shutting down the other unit while maintaining all the other constraint constant. This would result in effective power flow in an economic manner, simultaneously maintaining the adequacy and reliability of the system. The proposed research represents the scope of intelligence algorithm for unit commitment problem with effective solution of vehicle to grid operations along with sustainable energy for realistic power system.

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Housing peak shaving algorithm (HPSA) with plug-in hybrid electric vehicles (PHEVs): Vehicle-to-Home (V2H) and Vehicle-to-Grid (V2G) concepts

4th International Conference on Power Engineering, Energy and Electrical Drives ◽

10.1109/powereng.2013.6635704 ◽

2013 ◽

Cited By ~ 7

Author(s):

Harun Turker ◽

Ahmad Hably ◽

Seddik Bacha

Keyword(s):

Electric Vehicles ◽

Hybrid Electric Vehicles ◽

Peak Shaving ◽

Vehicle To Grid ◽

Hybrid Electric

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Eco-Driving for Different Electric Powertrain Topologies Considering Motor Efficiency

World Electric Vehicle Journal ◽

10.3390/wevj12010006 ◽

2021 ◽

Vol 12 (1) ◽

pp. 6

Author(s):

Alexander Koch ◽

Tim Bürchner ◽

Thomas Herrmann ◽

Markus Lienkamp

Keyword(s):

Dynamic Programming ◽

Electric Vehicles ◽

Quadratic Functions ◽

Simultaneous Optimization ◽

Speed Profile ◽

Power Demand ◽

Electric Motors ◽

Car Following ◽

Motor Efficiency ◽

Computationally Expensive

Electrification and automatization may change the environmental impact of vehicles. Current eco-driving approaches for electric vehicles fit the electric power of the motor by quadratic functions and are limited to powertrains with one motor and single-speed transmission or use computationally expensive algorithms. This paper proposes an online nonlinear algorithm, which handles the non-convex power demand of electric motors. Therefore, this algorithm allows the simultaneous optimization of speed profile and powertrain operation for electric vehicles with multiple motors and multiple gears. We compare different powertrain topologies in a free-flow scenario and a car-following scenario. Dynamic Programming validates the proposed algorithm. Optimal speed profiles alter for different powertrain topologies. Powertrains with multiple gears and motors require less energy during eco-driving. Furthermore, the powertrain-dependent correlations between jerk restriction and energy consumption are shown.

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Analysis of EV Cost-Based Charging Load Profiles

Proceedings ◽

10.3390/proceedings2020065002 ◽

2020 ◽

Vol 65 (1) ◽

pp. 2

Author(s):

Elisavet Koutsi ◽

Sotirios Deligiannis ◽

Georgia Athanasiadou ◽

Dimitra Zarbouti ◽

George Tsoulos

Keyword(s):

Electric Vehicles ◽

User Preferences ◽

Reference Scenario ◽

Electricity Prices ◽

Horizon 2020 ◽

Vehicle To Grid ◽

Electrical Grid ◽

Incentive Strategies ◽

Grid Load ◽

The Impact

During the last few decades, electric vehicles (EVs) have emerged as a promising sustainable alternative to traditional fuel cars. The work presented here is carried out in the context of the Horizon 2020 project MERLON and targets the impact of EVs on electrical grid load profiles, while considering both grid-to-vehicle (G2V) and vehicle-to-grid (V2G) operation modes. Three different charging policies are considered: the uncontrolled charging, which acts as a reference scenario, and two strategies that fall under the umbrella of individual charging policies based on price incentive strategies. Electricity prices along with the EV user preferences are taken into account for both charging (G2V) and discharging (V2G) operations, allowing for more realistic scenarios to be considered.

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To Represent Electric Vehicles in Electricity Systems Modelling—Aggregated Vehicle Representation vs. Individual Driving Profiles

Energies ◽

10.3390/en14030539 ◽

2021 ◽

Vol 14 (3) ◽

pp. 539

Author(s):

Maria Taljegard ◽

Lisa Göransson ◽

Mikael Odenberger ◽

Filip Johnsson

Keyword(s):

Electric Vehicles ◽

Investment Model ◽

Research Issues ◽

Charging Infrastructure ◽

Vehicle To Grid ◽

Long Term Storage ◽

Electricity System ◽

Home Location ◽

The Individual ◽

Storage Technologies

This study describes, applies, and compares three different approaches to integrate electric vehicles (EVs) in a cost-minimising electricity system investment model and a dispatch model. The approaches include both an aggregated vehicle representation and individual driving profiles of passenger EVs. The driving patterns of 426 randomly selected vehicles in Sweden were recorded between 30 and 73 days each and used as input to the electricity system model for the individual driving profiles. The main conclusion is that an aggregated vehicle representation gives similar results as when including individual driving profiles for most scenarios modelled. However, this study also concludes that it is important to represent the heterogeneity of individual driving profiles in electricity system optimisation models when: (i) charging infrastructure is limited to only the home location in regions with a high share of solar and wind power in the electricity system, and (ii) when addressing special research issues such as impact of vehicle-to-grid (V2G) on battery health status. An aggregated vehicle representation will, if the charging infrastructure is limited to only home location, over-estimate the V2G potential resulting in a higher share (up to 10 percentage points) of variable renewable electricity generation and an under-estimation of investments in both short- and long-term storage technologies.

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Optimal Pricing of Vehicle-to-Grid Services Using Disaggregate Demand Models

Energies ◽

10.3390/en14041090 ◽

2021 ◽

Vol 14 (4) ◽

pp. 1090

Author(s):

Charilaos Latinopoulos ◽

Aruna Sivakumar ◽

John W. Polak

Keyword(s):

Power Systems ◽

Electric Vehicles ◽

Power Grids ◽

Local Distribution ◽

Technical Problems ◽

Vehicle To Grid ◽

Distribution Transformers ◽

Demand Models ◽

Multiple Vehicles ◽

Infrastructure Investments

The recent revolution in electric mobility is both crucial and promising in the coordinated effort to reduce global emissions and tackle climate change. However, mass electrification brings up new technical problems that need to be solved. The increasing penetration rates of electric vehicles will add an unprecedented energy load to existing power grids. The stability and the quality of power systems, especially on a local distribution level, will be compromised by multiple vehicles that are simultaneously connected to the grid. In this paper, the authors propose a choice-based pricing algorithm to indirectly control the charging and V2G activities of electric vehicles in non-residential facilities. Two metaheuristic approaches were applied to solve the optimization problem, and a comparative analysis was performed to evaluate their performance. The proposed algorithm would result in a significant revenue increase for the parking operator, and at the same time, it could alleviate the overloading of local distribution transformers and postpone heavy infrastructure investments.

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