A stepwise power tariff model with game theory based on Monte-Carlo simulation and its applications for household, agricultural, commercial and industrial consumers

The concept of game theory has been adapted in the regulation of retail electricity market within the constraints of stepwise power tariff (SPT) for economic energy consumption. The objective is to increase the penetration level of renewable energy sources (RES) and electric vehicles with implementation of Bayesian game model for categorized (i.e. household, agricultural, commercial & industrial) consumers. Bayesian game model is based on degree of information shared by consumers due to their selfish nature. The main goal is to create an algorithm using constraints RES, storage through electric vehicles, electric wiring, number of consumer, efficient equipment, social status of family etc. within the distributed network. However managing large number of consumers from different categories and different degree of information shared with defined constraints is a challenging task. This paper proposed an algorithm of demand response using stepwise power tariff with game theory (SPTGT) to achieve the objectives in different equilibrium states on the basis of degree of information shared by categorized consumers. The uncertainty of consumption and generation through RES are taken into account using Monte-Carlo simulation (MCS). A comprehensive simulation study is carried out to reveal the effectiveness of the proposed method and find the nash equilibrium between consumers and utilities. The results obtained with proposed SPT-GT approach has been compared with conventional tariff approach shows the effectiveness of proposed model and encourage consumers to share maximum information to increase the payoffs.