2 resultados para Microelectrical mechanical systems (MEMS)
em Coffee Science - Universidade Federal de Lavras
Resumo:
Solar heating of potable water has traditionally been accomplished through the use of solar thermal (ST) collectors. With the recent increases in availability and lower cost of photovoltaic (PV) panels, the potential of coupling PV solar arrays to electrically heated domestic hot water (DHW) tanks has been considered. Additionally, innovations in the SDHW industry have led to the creation of photovoltaic/thermal (PV/T) collectors, which heat water using both electrical and thermal energy. The current work compared the performance and cost-effectiveness of a traditional solar thermal (ST) DHW system to PV-solar-electric DHW systems and a PV/T DHW system. To accomplish this, a detailed TRNSYS model of the solar hot water systems was created and annual simulations were performed for 250 L/day and 325 L/day loads in Toronto, Vancouver, Montreal, Halifax, and Calgary. It was shown that when considering thermal performance, PV-DHW systems were not competitive when compared to ST-DHW and PVT-DHW systems. As an example, for Toronto the simulated annual solar fractions of PV-DHW systems were approximately 30%, while the ST-DHW and PVT-DHW systems achieved 65% and 71% respectively. With current manufacturing and system costs, the PV-DHW system was the most cost-effective system for domestic purposes. The capital cost of the PV-DHW systems were approximately $1,923-$2,178 depending on the system configuration, and the ST-DHW and PVT system were estimated to have a capital cost of $2,288 and $2,373 respectively. Although the capital cost of the PVT-DHW system was higher than the other systems, a Present Worth analysis for a 20-year period showed that for a 250 L/day load in Toronto the Present Worth of the PV/T system was approximately $4,597, with PV-DHW systems costing approximately $7,683-$7,816 and the ST-DHW system costing $5,238.
Resumo:
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.