THE DESIGN OF A POWER SYSTEM FOR A WIRELESS SENSOR NETWORK FOR LONG-TERM OPERATION

Wireless sensor networks (WSNs) have shown wide applicability to many fields including monitoring of environmental, civil, and industrial settings. WSNs however are resource constrained by many competing factors that span their hardware, software, and networking. One of the central resource constrains is the charge consumption of WSN nodes. With finite energy supplies, low charge consumption is needed to ensure long lifetimes and success of WSNs. This thesis details the design of a power system to support long-term operation of WSNs. The power system’s development occurs in parallel with a custom WSN from the Queen’s MEMS Lab (QML-WSN), with the goal of supporting a 1+ year lifetime without sacrificing functionality. The final power system design utilizes a TPS62740 DC-DC converter with AA alkaline batteries to efficiently supply the nodes while providing battery monitoring functionality and an expansion slot for future development. Testing tools for measuring current draw and charge consumption were created along with analysis and processing software. Through their use charge consumption of the power system was drastically lowered and issues in QML-WSN were identified and resolved including the proper shutdown of accelerometers, and incorrect microcontroller unit (MCU) power pin connection. Controlled current profiling revealed unexpected behaviour of nodes and detailed current-voltage relationships. These relationships were utilized with a lifetime projection model to estimate a lifetime between 521-551 days, depending on the mode of operation. The power system and QML-WSN were tested over a long term trial lasting 272+ days in an industrial testbed to monitor an air compressor pump. Environmental factors were found to influence the behaviour of nodes leading to increased charge consumption, while a node in an office setting was still operating at the conclusion of the trail. This agrees with the lifetime projection and gives a strong indication that a 1+ year lifetime is achievable. Additionally, a light-weight charge consumption model was developed which allows charge consumption information of nodes in a distributed WSN to be monitored. This model was tested in a laboratory setting demonstrating +95% accuracy for high packet reception rate WSNs across varying data rates, battery supply capacities, and runtimes up to full battery depletion.

Study of Liquid Desiccant Air-Conditioning for High Performance Greenhouses

Greenhouses have become an invaluable source of year-round food production. Further development of viable and efficient high performance greenhouses is important for future food security. Closing the greenhouse envelope from the environment can provide benefits in space heating energy savings, pest control, and CO2 enrichment. This requires the application of a novel air conditioning system to handle the high cooling loads experienced by a greenhouse. Liquid desiccant air-conditioning (LDAC) have been found to provide high latent cooling capacities, which is perfect for the application of a humid greenhouse microclimate. TRNSYS simulations were undertaken to study the feasibility of two liquid desiccant dehumidification systems based on their capacity to control the greenhouse microclimate, and their cooling performance. The base model (B-LDAC) included a natural gas boiler, and two cooling systems for seasonal operation. The second model (HP-LDAC) was a hybrid liquid desiccant-heat pump dehumidification system. The average tCOPdehum and tCOPtotal of the B-LDAC system increased from 0.40 and 0.56 in January to 0.94 and 1.09 in June. Increased load and performance during a sample summer day improved these values to 3.5 and 3.0, respectively. The average eCOPdehum and eCOPtotal values were 1.0 and 1.8 in winter, and 1.7 and 2.1 in summer. The HP-LDAC system produced similar daily performance trends where the annual average eCOPdehum and eCOPtotal values were 1.3 and 1.2, but the sample day saw peaks of 2.4 and 3.2, respectively. The B-LDAC and HP-LDAC results predicted greenhouse temperatures exceeding 30°C for 34% and 17% of the month of July, respectively. Similarly, humidity levels increased in summer months, with a maximum of 14% of the time spent over 80% in May for both models. The percentage of annual savings in space heating energy associated with closing the greenhouse to ventilation was 34%. The additional annual regeneration energy input was reduced by 26% to 526 kWhm-2, with the implementation of a heat recovery ventilator on the regeneration exhaust air. The models also predicted an electrical energy input of 245 kWhm-2 and 305 kWhm-2 for the B-LDAC and HP-LDAC simulations, respectively.