Synauta is a startup bringing the world's best Internet of Things solutions to water utilities. Our deep industry knowledge prepares utilities for true connectivity to realize energy savings. We provide cyber security, sensors and software. In this project we will create a temperature prediction algorithm to save energy for water treatment plants. More energy can be saved if operators can plan to make more treated water when temperatures are high and less treated water when temperatures are lower. Over a week, the amount of water produced would be the same, but less energy would be used.
EPCOR Distribution and Transmission Inc., an electric utility based in Edmonton is carrying out inspections on a fixed time interval for all of its distribution assets. In the case of pad-mounted distribution transformers, many of the time-based inspections resulted in the decision of “no action required”. This project aims to investigate the inspection data and develop a simple mathematical model to define the optimal inspection schedule for pad-mounted distribution transformers. This project will reduce the inspection costs of EPCOR Distribution and Transmission Inc.
Municipal wastewater contains excessive nutrients, which when discharged without sufficient treatment can cause eutrophication in the receiving water bodies. Digested sludge liquor, the produce water generated from the treatment of sludge that is produced from municipal wastewater treatment plant contains high concentrations of ammonia that is toxic to aquatic biota and requires further treatment.
Recent studies have called into question the Linear No Threshold (LNT) model of radiation protection, which predicts a linear increase in cancer risk with low-dose radiation exposure. However, current experimental evidence suggests that low-dose radiation (LDR,
The current project will focus on understanding the behavior of one of the most important CANDU reactor components when it is subjected to the reactor environment. This study will develop a fundamental understanding of the X-750 material’s behavior resulting in innovative technologies that benefit the nuclear industry in Canada.
The smart grid represents a marriage between power systems and information technology to provide increased and reliable access to power. The greater dependence on information systems however makes it more vulnerable to cyberattack. Modeling these systems accurately is a significant challenge due to their complexity and connected nature. In this work, we focus on the open research problem of developing a modeling platform that combines co-simulation, real equipment and data analytics.
The problem considered in this work is how to produce highly accurate and consistent land-use/land-cover (LULC) maps significantly faster than current semi?automated methods for use by Manitoba Hydro. The goal is to improve the ability to produce maps quickly and efficiently as priority needs arise. This project will use an approach for automated LULC mapping from satellite images using deep learning methods pioneered by the applicants. By classifying each pixel in a satellite image into LULC categories using neural networks, rapid and accurate LULC maps can be successfully produced.
Energy consumers and prosumers are currently dealing with each other via utility companies, which is a slow, costly and indirect mechanism. With the aim of moving toward a free market, the goal of this project is to provide a suitable platform for automatic development and evolution of smart contracts in distributed transactive energy markets. This platform will make the blockchain technology, underlying smart contracts, applicable to direct transactions between energy consumers and prosumers, enabling additional steps towards a free market.
Wastewater is an abundant and an underutilized thermal energy source that experiences relatively constant temperature year-round with predicted flow rates. These features serve as a heat source/sink for heat pump-based HVAC systems to provide combined heating, cooling and domestic hot water to large-scale commercial, residential, and institutional buildings. There is a substantial potential in extracting enough thermal energy from sewer with relatively low carbon footprint.
This project will explore the non-invasive ways to find potential leaks in buried gas distribution pipelines using sound propagation. When there is a sound source at one point of the pipeline, the nature of the sound coming to another point of the pipeline will depend on the properties of the surrounding soil, properties of the pipe and its integrity. We will study the mechanics of sound propagation in a buried pipeline surrounded by soil, using methods of modern mechanics. We will also use similar methods to formulate best practices of data analysis.