Improving household's efficiency via scheduling of water and energy appliances

In this work we monitor and study electrical and water consumptions in a home environment in order to reduce its energy costs. To this end, we apply a population-based optimisation algorithm to determine optimal operation schedules for certain appliances in a domestic environment. We propose a criteria function that assesses the performance of an operation schedule for controllable appliances in the household. An optimisation problem is, then, formulated and solved in order to compute the desired operation schedule that minimises this criteria. Particle Swarm Optimisation (PSO) was the algorithm chosen to solve this problem, mainly because of its simple implementation and relatively low computational burden, allowing it to generate (near-optimal) solutions in a feasible time. A fine-tuning of its parameters was promoted. The best computed solutions for a time horizon of one day revealed not only the ability to take advantage of night periods (when energy is cheaper) but also that a positive balance in the electrical bill can be obtained, benefiting from excess photovoltaic energy being sold to the public grid.