Wireless sensor network (WSN) technology has been successfully applied to energy saving applications in many places, and plays a significant role in achieving power conservation. However, previous studies do not discuss WSN costs and cost-recovery. The application of WSNs is currently limited to research and laboratory experiments, and not mass industrial production, largely because business owners are unfamiliar with the possible favorable return and cost-recovery on WSN investments. Therefore, this paper focuses on the cost-recovery of WSNs and how to reduce air conditioning energy consumption in convenience stores. The WSN used in this study provides feedback to the gateway and adopts the predicted mean vote (PMV) and computational fluid dynamics (CFD) methods to allow customers to shop in a comfortable yet energy-saving environment. Four convenience stores in Taipei have used the proposed WSN since 2008. In 2008, the experiment was initially designed to optimize air-conditioning for energy saving, but additions to the set-up continued beyond 2008, adding the thermal comfort and crowds peak, off-peak features in 2009 to achieve human-friendly energy savings. Comparison with 2007 data, under the same comfort conditions, shows that the power savings increased by 40% (2008) and 53% (2009), respectively. The cost of the WSN equipment was 500 US dollars. Experimental results, including three years of analysis and calculations, show that the marginal energy conservation benefit of the four convenience stores achieved energy savings of up to 53%, recovering all costs in approximately 5 months. The convenience store group participating in this study was satisfied with the efficiency of energy conservation because of the short cost-recovery period.
Keywords: CFD; PMV; WSN; marginal energy conservation benefit.