Rapid growth of renewable energy generation and DC loads as electric vehicles and consumer electronics results in the proliferation of DC microgrids. DC microgrids are small electrical grids where energy sources and loads are connected to a main energy distribution power line using power converters.
Two High Voltage DC (HVDC) transmission technologies, the mature Line Commutated Converter (LCC) and newer Voltage Source Converter (VSC) technologies have their own pros and cons. For a HVDC transmission system carrying power from a single generation center to multiple load centers, by using a multi-terminal LCC-VSC type hybrid HVDC configuration, advantages of both technologies can be exploited. There is also the possibility of tapping into existing point-to-point LCC transmission lines using this hybrid configuration to supply intermediate locations.
The field of plastic waste management is essential for sustainable society that utilizes plastic waste for energy production. Land filing and incineration of plastic waste has large environmental impacts due to GHG emissions. Thus, pyrolysis is considered a low environmental impact process with high value end products. RF thermal plasma technology will help reduce operating cost, cleaner thermal source, shorten reaction time and provide high quality hydrocarbon gasoline and diesel.
In the wake of the Paris meeting on global climate change in December of 2015 (COP21), commitments to drive down greenhouse gas emissions have escalated around the world. Man-made carbon dioxide (CO2) emissions are accepted as the largest contributor to climate change. Promising next-generation technologies for decreasing CO2 emissions are being investigated at the lab scale. Unfortunately, the technology developers often lack next-step projects and connections with industrial end-users to allow the technology to advance and become commercialized.
Yukon Energy Corporation (YEC) began generating hydro-electricity at the Aishihik Hydro Facility, situated within Champagne and Aishihik First Nations (CAFN) Traditional Territory, Yukon, in 1975. Their continuing water use license will expire in 2019. Notwithstanding the Aishihik facilitys 41 years of energy production, CAFN has repeatedly expressed social and environmental concerns associated with the facility's operation.
During the proposed internships, smart-grid integrated adaptive corrosion protection system (ACPS) will be developed as a stand-alone unit to provide optimum corrosion protection along with the nanostructured local data storage and off-grid powering. This will allow the continuous monitoring of the corrosion status of the metal infrastructures (e.g. transmission towers) along with the power-grid monitoring data. The proposed system can be directly monitored from the centralized control-room.
Lithium ion batteries (LIBs) are considered the top candidates among electrochemical energy storage systems (ESS) due to their high energy density which has triggered the growth market of popular devices such as cell phones, computers, electric vehicles (EV) etc. As ESS, LIBs are continuously charged and discharged during their utility. The charge/discharge cycle is known to contribute towards their degradation depending on the charging protocol and operating conditions.
Degradation assessment for critical assets in power generation has great significance for power industry. Existing degradation assessment models failed either in combining the multimodal condition monitoring data or in removing time-varying working condition influences, resulting in inaccurate and/or unreliable degradation assessment results. In order to achieve robust and accurate degradation assessment for power generation critical assets, this project aims at developing new models based on both maintenance data and condition monitoring data from ENMAX.
Heating and cooling in residential and commercial buildings account for 20% of total energy consumption in Canada. Conditioning indoor air using less energy is closely associated with minimizing production of greenhouse gases and making a sustainable global environment. In this study, we apply a nanocomposite fibrous membrane for an energy recovery ventilator (ERV). Heat and moisture from an exhaust contaminated indoor air are captured via ERV and recycled for conditioning entering outdoor air, ultimately resulting in energy savings and improving the indoor air quality of buildings.
The aim of this project is to predict building energy consumption for next days. Firstly, we will collect several data such as weather data, time data, and historical energy consumption of the building. We will analyze the collected data to recognize the usage patterns of the building, for instance, the low and the high electricity consumption of building. After data analysis, we will apply several machine learning models to predict energy consumption of building, and finally all models will be compared to choose the outperform method.