Economic and technical aspects of plug-in electric vehicles in electricity markets

Shafie‐khah, Miadreza; Neyestani, Nilufar; Damavandi, Maziar Yazdani; Gil, Fabio A. S.; Catalão, João P.S.

doi:10.1016/j.rser.2015.09.079

Cited by 44 publications

(14 citation statements)

References 69 publications

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“…These studies have analyzed the interaction mechanism between consumers and supply chain operation decisions by portraying how consumers' preferences for low carbon lead to a market reaction for low carbon, and they have further proposed a low-carbon supply-chain decision model and method [9][10][11]. In response to the rise of the NEV market, the relationship between consumers' preferences for low carbon and NEV market acceptance, government subsidies for NEVs, and the impact of low carbon preferences on NEV supply chain decisions, have attracted the interest of some scholars [8,[12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Supply-Chain Pricing and Coordination for New Energy Vehicles Considering Heterogeneity in Consumers’ Low Carbon Preference

2020

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Given consumers' willingness to pay different prices for new energy vehicles (NEVs) and traditional vehicles, we construct a utility model of ordinary and green consumers. We establish pricing game models for centralized and decentralized decisions in an NEV's supply chain in order to study the impact of changes in consumers' low carbon preference heterogeneity on supply chain pricing and member profit. The results show that consumers' low carbon preferences and the ratio of green consumers increases with the ex-factory and selling prices of NEVs. An increase in the percentage of green consumers under centralized decision-making will reduce the total profit of the supply chain. Manufacturers' profits under decentralized decision-making are greater than the dealers' profits, and the sum of the two members' profits under decentralized decision-making is less than the total profit of the supply chain under centralized decision-making. We design a revenue-sharing contract to eliminate the double marginal effect.

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Section: Introductionmentioning

confidence: 99%

Supply-Chain Pricing and Coordination for New Energy Vehicles Considering Heterogeneity in Consumers’ Low Carbon Preference

2020

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“…At the next step, positive and negative distances from AV are calculated for each alternative and each criterion as follows, separately for maximizing Labels (13) and (14) and minimizing criteria Labels (15) and (16):…”

Section: Evaluation By the Edas Methodsmentioning

confidence: 99%

Decision-Aiding Evaluation of Public Infrastructure for Electric Vehicles in Cities and Resorts of Lithuania

et al. 2018

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Abstract:In the National Communication Development of [2014][2015][2016][2017][2018][2019][2020][2021][2022] Program and Guidelines of the Development of the Public Electric Vehicle Charging Infrastructure confirmed by the Government of the Republic of Lithuania, it is planned that, until the year of 2025, among newly registered vehicles, electric ones should make at least 10%. Analysis of the trend of electric vehicles makes evident that the target does not have a real chance to be achieved without targeted efforts. In order to improve the infrastructure of electric vehicles in major cities and resorts of Lithuania, we have carried out a comparative analysis of public infrastructure for electric vehicles in 18 Lithuanian cities and resorts. For the quantitative analysis, we proposed eight criteria describing such an infrastructure. As perception of the infrastructure by owners of electric cars depends on complex factors, we used multiple criteria evaluation methods (MCDM) for evaluation of the current state of its development by four such methods: EDAS, SAW, TOPSIS, and PROMETHEE II. Based on the evaluation results, prominent and lagging factors were understood, and proposals for effective development of public infrastructure of electric vehicles were proposed for improvement of the infrastructure.

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“…Information gap decision theory (IGDT) is applied to handle the uncertainties of microgrid and solved by MILP framework. Many other type of uncertainty handling method such as robust, fuzzy, scenario based, linearization based, unscented transform, probabilistic, possibilistic Monte Carlo, Gaussian mixture model, estimation distribution, and stochastic inventory theory are also proposed by researchers to model uncertainties in an EMS. Selection of appropriate method to handle uncertainty is required in the power system to avoid a large gap between supply and demand.…”

Section: Factors To Be Considered For Ems Implementationmentioning

confidence: 99%

Energy management system for smart grid: An overview and key issues

2020

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Summary Energy crisis and the global impetus to “go green” have encouraged the integration of renewable energy resources, plug‐in electric vehicles, and energy storage systems to the grid. The presence of more than one energy source in the grid necessitates the need for an efficient energy management system to guide the flow of energy. Moreover, the variability and volatile nature of renewable energy sources, uncertainties associated with plug‐in electric vehicles, the electricity price, and the time‐varying load bring new challenges to the power engineers to achieve demand‐supply balance for stable operation of the power system. The energy management system can effectively coordinate the energy sharing/trading among all available energy resources, and supply loads economically in all the conditions for the reliable, secure, and efficient operation of the power system. This paper reviews the framework, objectives, architecture, benefits, and challenges of the energy management system with a comprehensive analysis of different stakeholders and participants involved in it. The review paper gives a critical analysis of the distributed energy resources behavior and different programs such as demand response, demand‐side management, and power quality management implemented in the energy management system. Different uncertainty quantification methods are also summarized. This review paper also presents a comparative and critical analysis of the main optimization techniques used to achieve different energy management system objectives while satisfying multiple constraints. Thus, the review offers numerous recommendations for research and development of the cutting‐edge optimized energy management system applicable for homes, buildings, industries, electric vehicles, and the whole community.

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Economic and technical aspects of plug-in electric vehicles in electricity markets

Cited by 44 publications

References 69 publications

Supply-Chain Pricing and Coordination for New Energy Vehicles Considering Heterogeneity in Consumers’ Low Carbon Preference

Supply-Chain Pricing and Coordination for New Energy Vehicles Considering Heterogeneity in Consumers’ Low Carbon Preference

Decision-Aiding Evaluation of Public Infrastructure for Electric Vehicles in Cities and Resorts of Lithuania

Energy management system for smart grid: An overview and key issues

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