Energy optimization for a smart prosumer

Abstract

This paper outlines the optimization of cost of electrical energy consumption for a small microgrid typical of a residential area where each household has renewable generation capability and the daily load is portioned into essential none-interruptible and schedulable or interruptible loads. Dual tariffs exist, for buying and the other for in-feed into the utility grid. The optimization makes appliances scheduling decisions to suit prevailing power availability as well amount of power to sell or procure from the utility depending on availability and prevailing real time pricing. We assume availability of time-variant energy parameters, then formulate a global optimization problem whose solutions leads to quantification of the optimal amount of energy purchased and sold for each of the individual households. When the unrealistic assumption of availability of information is removed from the implementation of the global optimization, an online algorithm that only requires the current values of the time varying supply and demand processes shows by simulation that the distributed algorithm can realise credible scheduling of prosumer household electricity usage. This is imperative as the very requirement of involving the consumer for appliances scheduling defeats the optimization cause as humans are not suitable for such repetitive and mundane tasks.