Fuzzy logic controller and game theory based distributed energy resources allocation

publishedVersio

Non-cooperative game theory based stepwise power tariff model using Monte-Carle simulation for agricultural consumers

In the present study the concept of non-cooperative game theory is proposed in the retail electricity market for introducing stepwise power tariff model (SPT) for agricultural consumers. The objective of the paper is to increase the energy generation through green energy generation sources (GEGS), introduction of plug-in hybrid electric vehicles, education of families, standard wiring and appliance efficiency in tariffs for agricultural consumers with non-cooperative game theory. Agricultural consumers are able to generate a huge amount of electricity through GEGS and are able to control the consumption in their own way, and the non-cooperative game theory is introduced. Energy consumption pattern varies with respect to time during off-peak load period to peak load period; during the peak load period the demand is high as compared to off peak load hour duration energy consumption for the consumers and policy makers interrupting the energy supply during peak hours for agricultural consumers. To maintain the balance between generation and consumption, energy saving is essentially required and needs to maintain the consumption patterns and increase the penetration level of distributed generation at the agricultural consumer end due to availability of land. This paper proposes an algorithm for a demand response methodology using SPT with non-cooperative game theory model based on monthly energy consumption to maintain the balance. The uncertainty about energy generation through GEGS taken in consideration using Monte-Carlo simulation (MCS). Simulation results obtained by the proposed methodology are compared with the conventional methodology of energy tariff used in India and provide better results for active consumers and generate a considerable amount of electricity through GEGS

Non-cooperative game theory based stepwise power tariff model using Monte-Carle simulation for agricultural consumers

publishedVersio

Fuzzy logic controller and game theory based distributed energy resources allocation

publishedVersio

A Fuzzy-Genetic-Based Integration of Renewable Energy Sources and E-Vehicles

E-Vehicles are used for transportation and, with a vehicle-to-grid optimization approach, they may be used for supplying a backup source of energy for renewable energy sources. Renewable energy sources are integrated to maintain the demand of consumers, mitigate the active and reactive power losses, and maintain the voltage profile. Renewable energy sources are not supplied all day and, to meet the peak demand, extra electricity may be supplied through e-Vehicles. E-Vehicles with random integration may cause system unbalancing problems and need a solution. The objective of this paper is to integrate e-Vehicles with the grid as a backup source of energy through the grid-to-vehicle optimization approach by reducing active and reactive power losses and maintaining voltage profile. In this paper, three case studies are discussed: (i) integration of renewable energy sources alone; (ii) integration of e-Vehicles alone; (iii) integration of renewable energy sources and e-Vehicles in hybrid mode. The simulation results show the effectiveness of the integration and the active and reactive power losses are minimum when we used the third case

A Fuzzy-Genetic-Based Integration of Renewable Energy Sources and E-Vehicles

E-Vehicles are used for transportation and, with a vehicle-to-grid optimization approach, they may be used for supplying a backup source of energy for renewable energy sources. Renewable energy sources are integrated to maintain the demand of consumers, mitigate the active and reactive power losses, and maintain the voltage profile. Renewable energy sources are not supplied all day and, to meet the peak demand, extra electricity may be supplied through e-Vehicles. E-Vehicles with random integration may cause system unbalancing problems and need a solution. The objective of this paper is to integrate e-Vehicles with the grid as a backup source of energy through the grid-to-vehicle optimization approach by reducing active and reactive power losses and maintaining voltage profile. In this paper, three case studies are discussed: (i) integration of renewable energy sources alone; (ii) integration of e-Vehicles alone; (iii) integration of renewable energy sources and e-Vehicles in hybrid mode. The simulation results show the effectiveness of the integration and the active and reactive power losses are minimum when we used the third case