Home energy management system incorporating heat pump

With the further development of the world economy and society, the demand for electricity is rising significantly. To account for this growing electricity demand, smart grid technology development has ensued. Furthermore, Energy Management Systems (EMSs), especially Home Energy Management System (HEMS) are critical for a smart grid to function effectively. Understanding the energy demand of the loads and the available energy, either from the national grid or from renewable energy technologies, is fundamental to a HEMS. Heat Pumps (HP), as a result, are becoming increasingly popular for heating and cooling in residential houses as they offer high efficiency power output and low CO
₂
emissions which significantly supports Demand Side Management (DSM). This paper presents a program for a HEMS using a variant of Particle Swarm Optimisation (PSO) algorithm, i.e. Binary Particle Swarm Optimisation (BPSO). A HP is used as the load and the optimisation program sets about minimising the operational cost, i.e. the cost of electricity, while maintaining end-user comfort levels. This paper also details an indoor thermal model for temperature update in the heat pump control program. The results show that the electricity cost is reduced by 9.2% while keeping the temperature in the preset end-user comfort range. Additionally, the influence of a number of important parameters in the program are investigated.