Intelligent energy system refers to the use of intelligent control strategies with the energy system, which can help minimise energy waste and loss, optimise load control, increase and improve energy efficiency and/or maximise the benefits of renewable energy. Renewable energy and intelligent controls are interlinked and correlated with each other. Without intelligent controls, the full benefits of renewable energy technologies may not be achievable, specifically the ground source heat pump (GSHP) technologies. This was observed, especially by the University of Central Lancashire (UCLan) that had incorporated a GSHP to one of its building. The GSHP is under performing due to the inefficient controls implemented with the GSHP. This paper proposes an intelligent multi-agent building management system (MAS BMS) that aims to tackle this issue. Intelligence is provided by an ARTMAP, a type of artificial neural network that provides incremental learning inspired by how human process memory. Simulation results show the proposed intelligent MAS BMS is able to maximise the use of the GSHP effectively by profiling, predicting and coordinating its usage with other energy resources. The proposed method has performed better than the existing control strategies for the GSHP. (C) 2013 Elsevier B.V. All rights reserved.