An Agent-based Modeling for Price-responsive Demand Simulation

With the ongoing deployment of smart grids, price-responsive demand is playing an increasingly important role in the paradigm shifting of electricity markets. Taking a multi-agent system modeling approach, this paper presents a conceptual platform for discovering dynamic pricing solutions that reflect the varying cost of electricity in the wholesale market as well as the level of demand participation, especially regarding household customers and small and medium sized businesses. At first, an agent-based meta-model representing various concepts, relations, and structure of agents is constructed. Then a domain model can be instantiated based upon the meta-model. Finally, a simulation experiment is developed for use case demonstration and model validation. The simulation is for the supplier to obtain the profit-maximizing demand curve which has such a shape that it follows the spot price curve in inverse ratio. The result suggests that this multi-agent-based construct could contribute to 1) estimating the impacts of various time-varying tariff options on peak-period energy use through simulation, before any experimental pilots can be carried out; 2) modeling the electricity retail market evolving interactions in a systematic manner; 3) inducing innovative simulation configurations.