Environmental sustainability policy on plug-in hybrid electric vehicle penetration utilizing fuzzy TOPSIS and game theory

Abstract In this paper, environmental policymaking based on sustainable development was evaluated in Tehran to increase the penetration of plug-in hybrid electric vehicles. First, different aspects of sustainable development, including the environmental, economic, social, and technical aspects of Tehran’s vehicles from 2002 to 2018, were examined through the extended sustainable development model. The model documented the unsustainability of the development of vehicles in Tehran, the main reason for which could be the current air pollution in this city. Following this, based on the principle of sustainable development, some policy indices for the development of plug-in hybrid electric vehicle penetration were introduced and ranked using the fuzzy TOPSIS method, which ranked in the point of view of two players, namely buyers of vehicles and the state. Finally, to find the appropriate policy index, using the game theory method and taking the vehicle buyer and the state as the players, the Nash equilibrium point was defined as an appropriate policy for the development of plug-in hybrid electric vehicles. Thus, using the data obtained, the number of these vehicles for the year 2032 was estimated. Graphic abstract

[1]  Marina Bosch,et al.  Fuzzy Multiple Attribute Decision Making Methods And Applications , 2016 .

[2]  Miriam Borchardt,et al.  Tool for environmental performance assessment of city bus transit operations: case studies , 2014, Clean Technologies and Environmental Policy.

[3]  Andreas Poullikkas,et al.  Sustainable options for electric vehicle technologies , 2015 .

[4]  Neil Strachan,et al.  An integrated systematic analysis of uncertainties in UK energy transition pathways , 2015 .

[5]  Sreten Davidov,et al.  Planning of electric vehicle infrastructure based on charging reliability and quality of service , 2017 .

[6]  Chris Silvia,et al.  Assessing the impact of policy interventions on the adoption of plug-in electric vehicles: An agent-based model , 2016 .

[7]  Seyed Reza Hejazi,et al.  Sustainable development by waste recycling under a three-echelon supply chain: A game-theoretic approach , 2017 .

[8]  Joongha Ahn,et al.  Optimal allocation of energy sources for sustainable development in South Korea: Focus on the electric power generation industry , 2015 .

[9]  Ali Nejat,et al.  A comprehensive model of regional electric vehicle adoption and penetration , 2017 .

[10]  Azah Mohamed,et al.  A review of the stage-of-the-art charging technologies, placement methodologies, and impacts of electric vehicles , 2016 .

[11]  Payam Sadeghi-Barzani,et al.  Optimal fast charging station placing and sizing , 2014 .

[12]  Robert C. Green,et al.  The impact of plug-in hybrid electric vehicles on distribution networks: a review and outlook , 2010, IEEE PES General Meeting.

[13]  Yusak O. Susilo,et al.  The effect of policy incentives on electric vehicle adoption , 2016 .

[14]  Kaveh Madani,et al.  A game theory-reinforcement learning (GT-RL) method to develop optimal operation policies for multi-operator reservoir systems , 2014 .

[15]  L. Proskuryakova,et al.  Updating energy security and environmental policy: Energy security theories revisited. , 2018, Journal of environmental management.

[16]  J. Xie,et al.  Policy Incentives for the Adoption of Electric Vehicles across Countries , 2014 .

[17]  Ching-Lai Hwang,et al.  Fuzzy Multiple Attribute Decision Making - Methods and Applications , 1992, Lecture Notes in Economics and Mathematical Systems.

[18]  Mohamed F. El-Santawy A VIKOR Method for Solving Personnel Training Selection Problem , 2012 .

[19]  Juneseuk Shin,et al.  A hybrid electric vehicle market penetration model to identify the best policy mix: A consumer ownership cycle approach , 2016 .

[20]  Sadegh Vaez-Zadeh,et al.  Developing a DSR-HNS policy making framework for electric energy systems , 2012 .

[21]  Ning Wang,et al.  A global comparison and assessment of incentive policy on electric vehicle promotion , 2019, Sustainable Cities and Society.

[22]  Manouchehr Vaziri,et al.  Evaluation of sustainable policy in urban transportation using system dynamics and world cities data: A case study in Isfahan , 2015 .

[23]  Pantelis Capros,et al.  Factors Influencing Electric Vehicle Penetration in the EU by 2030: A Model-Based Policy Assessment , 2019, Energies.

[24]  Insoon Yang,et al.  A dynamic game approach to distributionally robust safety specifications for stochastic systems , 2017, Autom..

[25]  J. Kasprzak,et al.  Eco-efficiency analysis of an innovative packaging production: case study , 2018, Clean Technologies and Environmental Policy.

[26]  Jonn Axsen,et al.  Anticipating plug-in hybrid vehicle energy impacts in California: Constructing consumer-informed recharge profiles , 2010 .

[27]  Sidi-Mohammed Senouci,et al.  Game model to optimally combine electric vehicles with green and non-green sources into an end-to-end smart grid architecture , 2016, J. Netw. Comput. Appl..

[28]  Yan Li,et al.  Study on crowdfunding’s promoting effect on the expansion of electric vehicle charging piles based on game theory analysis , 2017 .

[29]  Joeri Wesseling,et al.  Explaining variance in national electric vehicle policies , 2016 .

[30]  L. R. Johnson,et al.  Plug-in electric vehicle market penetration and incentives: a global review , 2015, Mitigation and Adaptation Strategies for Global Change.

[31]  Soleiman Mohammadi Limaei,et al.  Multi-objective game theory model and fuzzy programing approach for sustainable watershed management , 2018 .

[32]  Huiru Zhao,et al.  Optimal site selection of electric vehicle charging station by using fuzzy TOPSIS based on sustainability perspective , 2015 .

[33]  R. Neck Dynamic game theory and models of international macroeconomic policy , 2010 .

[34]  Henrik Ny,et al.  A Strategic Sustainability Analysis of Electric Vehicles in EU Today and Towards 2050 , 2016 .

[35]  Kenneth S Kurani,et al.  Anticipating PHEV Energy Impacts in California , 2009 .

[36]  Apostolos Malatras,et al.  Renewable energy production management with a new harmony search optimization toolkit , 2016, Clean Technologies and Environmental Policy.

[37]  Farhad Samaie,et al.  Comparison of sustainability models in development of electric vehicles in Tehran using fuzzy TOPSIS method , 2020 .

[38]  Chris Davis,et al.  Electric vehicle charging in China's power system: Energy, economic and environmental trade-offs and policy implications , 2016 .

[39]  Goran Krajačić,et al.  Long-term energy planning of Croatian power system using multi-objective optimization with focus on renewable energy and integration of electric vehicles , 2016 .