An evolutionary game approach to predict demand response from real-time pricing

Abstract

Real-time pricing is an incentive-based demand response, which makes it challenging to predict the outcome of the implementation. This paper focuses on the prediction of consumer behaviour from real-time pricing based on a population game model. The participation in demand response and the rescheduling of consumption are studied to predict change in demand. Moreover, we looked at different types of consumers and used their characteristics to study dynamics among them. The dynamic behaviour of the consumers from pricing is modeled with the replicator dynamic equation. Simulation results show how consumers schedule their consumption during peak and non-peak hours. Based on this model, the demand response from real-time pricing is predicted over time, and the effect in peak reduction is studied. An evolutionary game approach enables the interpretation of dynamic consumer behaviour and the design of adaptable pricing for consumers.