Optimal coordinated operation scheduling for electric vehicle aggregator and charging stations in an integrated electricity-transportation system

Ding, Zhaohao; Ying, Lü; Lai, Kexing; Yang, Ming; Lee, Wei-Jen

doi:10.1016/j.ijepes.2020.106040

Cited by 69 publications

(28 citation statements)

References 31 publications

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“…Because the private EV is becoming increasingly prevalent as a means of transportation accounting for 85% of the civilian cars [35]. Considering that the individual consumer is more sensitive to the price of EV charging, this paper takes the private EV as an analysis object and proposes a novel pricing method of EV charging considering the consumer differences.…”

Section: Introductionmentioning

confidence: 99%

Comprehensive Pricing Scheme of the EV Charging Station considering Consumer Differences Based on Integrated AHP/DEA Methodology

Yin

Zhang

et al. 2020

Mathematical Problems in Engineering

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Scientific pricing of the electric vehicle charging station is closely related to consumer behavior inevitably. Existing studies have not considered the impacts of consumer differences on the charging price, which will fail to meet the interests of various types of consumers. This paper proposes a novel pricing method based on consumer classification and comprehensive evaluation strategies. First, the basis for consumer classification is established according to a single factor sensitivity analysis of the consumer benefit model; then, the nonlinear expression of the basis is piecewise linearized. Additionally, with the principle of least fitting error to determine consumers’ classification, the initial charging price schemes for various types of consumers are formulated. Second, this paper defines evaluation indices and establishes the hierarchy model for comprehensive evaluation schemes. Finally, the integrated analytic hierarchy process and data envelopment analysis are adopted for comprehensive evaluation of schemes. Simulations results illustrate that the proposed method can formulate the comprehensive optimal charging price considering consumer differences, and the method can reflect the impacts of both subjective and objective factors conveniently and accurately.

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Section: Introductionmentioning

confidence: 99%

Comprehensive Pricing Scheme of the EV Charging Station considering Consumer Differences Based on Integrated AHP/DEA Methodology

Yin

Zhang

et al. 2020

Mathematical Problems in Engineering

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“…The two common algorithms (Genetic Algorithm and Particle Swarm Optimisation) are being used to develop priority based service. The use of these algorithms especially at the distribution section level enhances the performance efficiency of the grid network [7,27,29].…”

Section: Prevention Of Cyberattacksmentioning

confidence: 99%

A comprehensive review on IoT‐based infrastructure for smart grid applications

Pal

Chavhan

Gupta

et al. 2021

IET Renewable Power Gen

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Currently, there is a huge production in the automotive industries and energy consumption resulted into spike in the cost and emissions of greenhouse gases. Hence, an efficient energy utilisation mechanism has become a prime most important factor. Energy and its conservation problem also have raised and become one of the prominent critical factors needed to address. Therefore, the development of smart grid infrastructure is one of the solutions to address the above issue.This article discusses different methods and mechanisms require to manage energy efficiently within the smart grid network using communication technologies and protocols and proposed an integration method of electric vehicles and smart grid using communication networks for charging or discharging electricity and exchanging relevant information. In addition, this paper discusses different integration strategies and multi-agent system implementation in the smart grid network. The proposed multi-agent system shows the efficient method for monitoring power flow and maintaining the stability of the grid. The paper also presents the optimal scheduling of charging of electric vehicles in the smart grid network. Finally, the authors investigated and presented many standard communication protocols and their comparisons with respect to different scenarios. This paper discuss different methods and concepts which would require to manage energy efficiently by using recent communication technologies, communication protocols, and sensor technologies. INTRODUCTIONDue to the growth of industries and population density, energy demand has been increasing exponentially. Hence, the energy consumption is under focus in order to reduce the energy crisis in the future. In this 21st century, conventional electrical energy and network will not meet up with the industries due to the lack of reliability, efficiency, security, seamless connectivity, etc. Therefore, a lot of new technologies (communication and sensor) have evolved to provide above features. The evolved communication and sensor technologies applied to the power grid to make smarter, that is, Smart Grid (SG) [1,2]. The SG infrastructure is the backbone of the future smart cities and the connected electric mobility. The connected infrastructureThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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“…Distributed optimization is also used to coordinate DC power networks with fixed electric loads and generation plants using natural gas, 37 electric vehicle charging stations and electric vehicle aggregators, 38 different regions in large‐scale conventional AC OPF problems, 39 and AC microgrids and battery swapping stations 40 . These approaches use Lagrangian‐relaxation‐based techniques such as subgradient methods or alternating direction method of multipliers 41 because they model the participants under coordination using mixed‐integer models or other formulations that induce a duality gap.…”

Section: Literature Reviewmentioning

confidence: 99%

A decoupling strategy for protecting sensitive process information in cooperative optimization of power flow

et al. 2021

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Optimal power flow (OPF) with close cooperation between the power grid and flexible electricity‐intensive chemical processes can reduce costs for the grid and for electricity users. However, this would require sharing detailed chemical process models, which may reveal confidential information and potentially jeopardize competitive advantages for a chemical process operator. We propose an algorithm that enables economically advantageous cooperation without the need to exchange sensitive information. Low‐order linear models are used to represent the dynamic behavior of electricity‐intensive processes. We integrate these models into the OPF problem and solve the problem using a decoupling strategy based on Benders‐type cuts. The cuts introduce limited communication between the chemical processes and the grid without exchanging explicit information pertaining to the process dynamics and performance. Our results reproduce solutions obtained by sharing detailed process models up to a user‐defined optimality gap for several test cases that reflect both normal and congested grid states. We also investigate the trade‐off between the value of the optimality gap and computational effort. Finally, we study the scaling behavior of the iterative procedure with respect to flexible loads at multiple grid locations.

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Optimal coordinated operation scheduling for electric vehicle aggregator and charging stations in an integrated electricity-transportation system

Cited by 69 publications

References 31 publications

Comprehensive Pricing Scheme of the EV Charging Station considering Consumer Differences Based on Integrated AHP/DEA Methodology

Comprehensive Pricing Scheme of the EV Charging Station considering Consumer Differences Based on Integrated AHP/DEA Methodology

A comprehensive review on IoT‐based infrastructure for smart grid applications

A decoupling strategy for protecting sensitive process information in cooperative optimization of power flow

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