Demand Response with Communicating Rational Consumers
For system operators designing real-time pricing mechanisms, this work offers analytical comparisons of information models and behavioral assumptions, though the results are incremental and domain-specific.
The paper analyzes how different consumer behaviors (selfish, altruistic, welfare-maximizing) and information models (private, local communication, broadcast) affect demand response under real-time pricing. It shows that communication reduces demand uncertainty with negligible impact on aggregate utility and welfare, and provides policy insights on price parameter effects.
The performance of an energy system under a real-time pricing mechanism depends on the consumption behavior of its customers, which involves uncertainties. In this paper, we consider a system operator that charges its customers with a real-time price that depends on the total realized consumption. Customers have unknown and heterogeneous consumption preferences. We propose behavior models in which customers act selfishly, altruistically or as welfare-maximizers. In addition, we consider information models where customers keep their consumption levels private, communicate with a neighboring set of customers, or receive broadcasted demand from the operator. Our analysis focuses on the dispersion of the system performance under different consumption models. To this end, for each pair of behavior and information model we define and characterize optimal rational behavior, and provide a local algorithm that can be implemented by the consumption scheduler devices. Analytical comparisons of the two extreme information models, namely, private and complete information models, show that communication model reduces demand uncertainty while having negligible effect on aggregate consumer utility and welfare. In addition, we show the impact of real-time price policy parameters have on the expected welfare loss due to selfish behavior affording critical policy insights.