Fuzzy robust flexible programming with [formula omitted] measure for electric sustainable supply chain

Abstract

Electricity as a source of energy, is one of the most essential part in our life. In recent time, it is noted that the temperature of earth increases in compare to the previous years. It is caused due to burning of the conventional energy sources such as gas, oil, and coal from thermal power plant and other sources, which brings about global warming. Bases on this fact, we propose a multi-objective mixed-integer programming model to design an electric sustainable supply chain network by considering resiliency and responsiveness. In order to formulate the environmental issues, a power-to-gas (P2G) technology is considered as an environment-friendly system. The presence of P2G can reduce the carbon level and it has some major advantages, i.e., it collects carbon dioxide (CO2) from thermal power plant and then converts CO2 to hydrogen (H2) with the help of water (H2O) and methane (CH4) gas. The drawbacks in addressing the uncertainty of the parameters are overcome by proposing a novel fuzzy robust flexible programming approach based on Me measure. Thereafter, a new approach namely, multi-choice conic goal programming with utility function is introduced to solve the proposed multi-objective model. Damodar Valley Corporation (DVC) in India is considered as a case study about electric network that envisages the sustainable issues of an electric supply chain. Finally, experimental results show that one bio-fuel plant, one photovoltaic plant, one air turbine plant, and two mixed-cycle power plants are build at the end of the scheduled period.