Portfolio Optimization of Photovoltaic/Battery Energy Storage/Electric Vehicle Charging Stations with Sustainability Perspective Based on Cumulative Prospect Theory and MOPSO

Recently, an increasing number of photovoltaic/battery energy storage/electric vehicle charging stations (PBES) have been established in many cities around the world. This paper proposes a PBES portfolio optimization model with a sustainability perspective. First, various decision-making criteria are identified from perspectives of economy, society, and environment. Secondly, the performance of alternatives with respect to each criterion is evaluated in the form of trapezoidal intuitionistic fuzzy numbers (TrIFN). Thirdly, the alternatives are ranked based on cumulative prospect theory. Then, a multi-objective optimization model is built and solved by multi-objective particle swarm optimization (MOPSO) algorithm to determine the optimal PBES portfolio. Finally, a case in South China is studied and a scenario analysis is conducted to verify the effectiveness of the proposed model.

[1]  Samer Madanat,et al.  Optimal design of electric vehicle public charging system in an urban network for Greenhouse Gas Emission and cost minimization , 2017 .

[2]  A. Tversky,et al.  Advances in prospect theory: Cumulative representation of uncertainty , 1992 .

[3]  Huiru Zhao,et al.  Optimal Siting of Charging Stations for Electric Vehicles Based on Fuzzy Delphi and Hybrid Multi-Criteria Decision Making Approaches from an Extended Sustainability Perspective , 2016 .

[4]  Hu-Chen Liu,et al.  Optimal Siting of Electric Vehicle Charging Stations Using Pythagorean Fuzzy VIKOR Approach , 2018, Mathematical Problems in Engineering.

[5]  Brian Norton,et al.  Performance of a campus photovoltaic electric vehicle charging station in a temperate climate , 2019, Solar Energy.

[6]  Pavol Bauer,et al.  System design for a solar powered electric vehicle charging station for workplaces , 2016 .

[7]  Sungjoo Lee,et al.  Managing uncertainty to improve decision-making in NPD portfolio management with a fuzzy expert system , 2012, Expert Syst. Appl..

[8]  M. Sheikhalishahi,et al.  Unique NSGA-II and MOPSO algorithms for improved dynamic cellular manufacturing systems considering human factors , 2017 .

[9]  Zhibin Wu,et al.  An interval type-2 fuzzy analysis towards electric vehicle charging station allocation from a sustainable perspective , 2017, Sustainable Cities and Society.

[10]  Yanbing Ju,et al.  Study of site selection of electric vehicle charging station based on extended GRP method under picture fuzzy environment , 2019, Comput. Ind. Eng..

[11]  Pin-Yu Chu,et al.  A fuzzy AHP application in government-sponsored R&D project selection☆ , 2008 .

[12]  Lixin Miao,et al.  Feasibility Study of a Solar-Powered Electric Vehicle Charging Station Model , 2015 .

[13]  Carlo Cecati,et al.  Modeling of a Photovoltaic-Powered Electric Vehicle Charging Station with Vehicle-to-Grid Implementation , 2016 .

[14]  A. Hashemizadeh,et al.  Project portfolio selection for construction contractors by MCDM–GIS approach , 2019, International Journal of Environmental Science and Technology.

[15]  Madjid Tavana,et al.  A fuzzy hybrid project portfolio selection method using Data Envelopment Analysis, TOPSIS and Integer Programming , 2015, Expert Syst. Appl..

[16]  Md. Raju Ahmed,et al.  Feasibility assessment & design of hybrid renewable energy based electric vehicle charging station in Bangladesh , 2018 .

[17]  Sanjeevikumar Padmanaban,et al.  Photovoltaic Integrated Hybrid Microgrid Structured Electric Vehicle Charging Station and Its Energy Management Approach , 2019, Energies.

[18]  Seyedmohsen Hosseini,et al.  Development of a Bayesian network model for optimal site selection of electric vehicle charging station , 2019, International Journal of Electrical Power & Energy Systems.

[19]  Minghe Sun,et al.  Robust optimization for interactive multiobjective programming with imprecise information applied to R&D project portfolio selection , 2014, Eur. J. Oper. Res..

[20]  Fangqiu Xu,et al.  Site selection of photovoltaic power plants in a value chain based on grey cumulative prospect theory for sustainability: A case study in Northwest China , 2017 .

[21]  Hu-Chen Liu,et al.  An Integrated Multi-Criteria Decision Making Approach to Location Planning of Electric Vehicle Charging Stations , 2019, IEEE Transactions on Intelligent Transportation Systems.

[22]  Luis M. Fernández-Ramírez,et al.  Control and operation of power sources in a medium-voltage direct-current microgrid for an electric vehicle fast charging station with a photovoltaic and a battery energy storage system , 2016 .

[23]  Xinying Li,et al.  Portfolio optimization of renewable energy projects under type-2 fuzzy environment with sustainability perspective , 2019, Comput. Ind. Eng..

[24]  Juan M. Corchado,et al.  Strategic Particle Swarm Inertia Selection for Electricity Markets Participation Portfolio Optimization , 2018, Appl. Artif. Intell..

[25]  Ali Karaşan,et al.  Location selection of electric vehicles charging stations by using a fuzzy MCDM method: a case study in Turkey , 2018, Neural Computing and Applications.

[26]  Madjid Tavana,et al.  A hybrid fuzzy rule-based multi-criteria framework for sustainable project portfolio selection , 2013, Inf. Sci..

[27]  Pankaj Gupta,et al.  Intuitionistic fuzzy multi-attribute group decision-making with an application to plant location selection based on a new extended VIKOR method , 2016, Inf. Sci..

[28]  Robert Ries,et al.  A multiple objective decision making model for energy generation portfolio under fuzzy uncertainty: Case study of large scale investor-owned utilities in Florida , 2015 .