Incentives for rescheduling residential electricity consumption to promote renewable energy usage

Managing energy consumption and production is a challenging problem and proactive balancing between the amount of electricity produced and consumed is needed. In this work, we examine mechanisms that give incentives to consumers to efficiently reschedule their demand, thus balancing the overall energy production and consumption. Viewing the smart grid as a MAS, each agent represents a consumer; this agent takes into account its user's preferences and proposes an optimal energy consumption plan via a gamified GUI. To implement this we propose a distributed architecture through which we give the incentives (either economic, or social); we test a number of pricing mechanisms and we develop a very fast agent optimization strategy. We also present experiments both from software simulations on real data and pilot tests with human participants: the simulations allow to evaluate the mechanisms and agents, whilst the gamified tests are useful to assess the usability of the GUI and the usefulness of the agent suggestions. With human subjects, we evaluated which type of incentives is more compelling: economic or social. Results validate that by using our agent optimization approach the performance of the smart grid can be improved, and that specific mechanisms allow better utilization of renewable sources.