Optimal selection of energy storage nodes based on improved cumulative prospect theory in China

2020 ◽  
Vol 12 (6) ◽  
pp. 064101
Author(s):  
Jicheng Liu ◽  
Zhenzhen Wang ◽  
Yu Yin ◽  
Yinghuan Li ◽  
Yunyuan Lu
Keyword(s):  
Energy Storage ◽  
Prospect Theory ◽  
Cumulative Prospect Theory ◽  
Optimal Selection ◽  
Selection Of

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

2020 ◽  
Vol 12 (3) ◽  
pp. 985 ◽  
Author(s):  
Jicheng Liu ◽  
Qiongjie Dai
Keyword(s):  
Energy Storage ◽  
Portfolio Optimization ◽  
Prospect Theory ◽  
Electric Vehicle ◽  
Optimization Model ◽  
Cumulative Prospect Theory ◽  
Battery Energy Storage ◽  
Electric Vehicle Charging ◽  
Battery Energy ◽  
Charging Stations

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.

scholarly journals Extended GRA Method Based on Cumulative Prospect Theory with Probabilistic Hesitant Fuzzy Information for MAGDM and its Application to Green Supplier Selection

2021 ◽  
Author(s):  
Ningna Liao ◽  
Guiwu Wei ◽  
Xudong Chen
Keyword(s):  
Prospect Theory ◽  
Simulation Analysis ◽  
Cumulative Prospect Theory ◽  
Decision Makers ◽  
Risk Appetite ◽  
Probabilistic Values ◽  
Grey Relational ◽  
Decision Elements ◽  
Different Levels ◽  
Selection Of

Abstract An extended grey relational analysis (GRA) method is introduced in this article to reduce the limitations of the classical GRA method using the cumulative prospect theory (CPT) which takes into account psychological factors such as the risk appetite of decision makers. Moreover, the circumstance of probabilistic hesitant fuzzy (PHF) which assigns probabilistic values to DMs’ different levels of hesitation shows its superiority when making decisions in a complex environment. Meanwhile the weighting vector of each attribute is calculated according to the entropy which is calculated by the different prospect decision elements. Thus, in this paper, we proposed an extended GRA method based on cumulative prospect theory in the probabilistic hesitant fuzzy circumstance and applying the model in the selection of the green supplier. At last, the comparative analysis and the simulation analysis are made to show the practicability of this newly proposed method.

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