A Genetic Algorithm Driven Linear Programming for Battery Optimal Scheduling in nearly Zero Energy Buildings

Abstract

EU has seen an increasing demand for both nearly zero energy buildings (nZEBs) and building integrated Photovoltaic (BIPV) systems in the last decade. This stems from the energy-driven regulations relating to building efficiency improvements, requiring more realistic and smarter techniques to strengthen their employment and overall performance. Apart from the passive energy-efficiency measures of nZEBs (such as thermal insulation, energy saving appliances, etc.), more advanced and sophisticated energy management mechanisms have to take place in order to accommodate and support their crucial contribution to sustainable development. This paper presents the daily optimum dispatch of a battery, in a building with PV, using Linear Programming (LP) driven by Genetic Algorithm (GA), aiming the minimization of the building's net energy. The obtained results show that there is a high potential of using such approaches for maintaining the net grid energy levels of a building as minimum as possible.