Application of new multi-objective optimization algorithm for EV scheduling in smart grid through the uncertainties

Yin, Wenjun; Mavaluru, Dinesh; Ahmed, Munir; Abbas, Mazhar; Darvishan, Aida

doi:10.1007/s12652-019-01233-1

Cited by 18 publications

(18 citation statements)

References 42 publications

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“…The cost of the total distribution of the grid exploitation in the presence of EVs, dispersed outputs and demand response is calculated through the following planned method [15]:…”

Section: E Objective Functionsmentioning

confidence: 99%

“…The coefficient of the dispersed output power is assumed to be 1, so only the dynamic energy will be noticed in the relations. In this matter, the function involves only the cost of unsustainable resources exploitation [15]:…”

Section: E Objective Functionsmentioning

confidence: 99%

“…The first constraint in the issue of intelligent distribution network programming is the equilibrium balance. This constraint represents the equality of production with utilization in an energy system whose relationship is as follows [15]:…”

Section: ) Equality and Inequality Constraints Of Netweorkmentioning

confidence: 99%

“…Considering the initial state of battery balance V2G, P Stored(V ,1) is set as entering data before performing the optimization. The extreme discharge limit per car is defined by equation 27, in order not to exceed the permitted amount of electric car charging energy [15]:…”

Section: ) Equality and Inequality Constraints Of Netweorkmentioning

confidence: 99%

“…To model the technical constraints of the dispersed resources and prevent this parameter from exceeding the specified value, relations (30) and (31) are expressed [15]:…”

Section: ) Equality and Inequality Constraints Of The Dispersed Prodmentioning

confidence: 99%

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An Improved Multicriteria Optimization Method for Solving the Electric Vehicles Planning Issue in Smart Grids via Green Energy Sources

Abedinia

Bagheri

2020

IEEE Access

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In the given research, a new multicriterion (multiobjective) optimization algorithm has been considered to solve the problem of electric vehicles (EV) scheduling in a smart network in view of sustainable energy sources based on the cost and pollution minimization. By considering the environmental and economic problems, the application of EVs as a proper charging/discharging scheduling model and green energy sources plays an important role in the power system. This study focuses on multicriteria scheduling through uncertainty factors via inexhaustible assets and EVs, presenting a battery storing framework and reducing both the operation costs and the amount of the framework's pollution while improving the procedures. For this purpose, a new optimization algorithm has been considered to address the mentioned problem taking into account some clean energy sources and emission. The proposed model is examined in smart grid environment based on real-life model by Demand Response Program (DRP) evaluation and the uncertainties in sustainable energies. The proposed optimization algorithm shows more desirable results in comparison with other models, while the efficiency of the suggested approach is studied and evaluated in two power systems, i.e., a 33-bus standard power system and a 94-bus Portugal network. The obtained results

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“…The cost of the total distribution of the grid exploitation in the presence of EVs, dispersed outputs and demand response is calculated through the following planned method [15]:…”

Section: E Objective Functionsmentioning

confidence: 99%

Section: E Objective Functionsmentioning

confidence: 99%

Section: ) Equality and Inequality Constraints Of Netweorkmentioning

confidence: 99%

Section: ) Equality and Inequality Constraints Of Netweorkmentioning

confidence: 99%

“…To model the technical constraints of the dispersed resources and prevent this parameter from exceeding the specified value, relations (30) and (31) are expressed [15]:…”

Section: ) Equality and Inequality Constraints Of The Dispersed Prodmentioning

confidence: 99%

See 3 more Smart Citations

An Improved Multicriteria Optimization Method for Solving the Electric Vehicles Planning Issue in Smart Grids via Green Energy Sources

Abedinia

Bagheri

2020

IEEE Access

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Study on optimal scheduling strategy of electric vehicles clusters in distribution power grid

Yin

Ming

2022

Optim Control Appl Methods

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In order to reduce the negative impact of disorderly charging of electric vehicles on the power grid, this article uses an improved particle swarm optimization algorithm to optimize the electric vehicle charging model. With full consideration of various constraints, load variance, load peak‐valley difference, and the charging cost of electric vehicle users are taken as optimization targets. The simulation results show that the orderly charging control strategy proposed in this article realizes the peak‐shaving and valley‐filling of the grid, reduces load fluctuations, improves the performance of the grid, and improves the safety and reliability of grid operation. The method proposed in this article provides a reference for electric vehicle charging scheduling.

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Dynamic Electric Vehicle Charging Optimization Model Based on PSO and GA Algorithms

Wang,

Yin,

et al. 2024

Lecture Notes in Electrical Engineering

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Application of new multi-objective optimization algorithm for EV scheduling in smart grid through the uncertainties

Cited by 18 publications

References 42 publications

An Improved Multicriteria Optimization Method for Solving the Electric Vehicles Planning Issue in Smart Grids via Green Energy Sources

An Improved Multicriteria Optimization Method for Solving the Electric Vehicles Planning Issue in Smart Grids via Green Energy Sources

Study on optimal scheduling strategy of electric vehicles clusters in distribution power grid

Dynamic Electric Vehicle Charging Optimization Model Based on PSO and GA Algorithms

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