Following the completion of the Methane Emission Reduction and GHG Facility Abatement projects in 2016 and 2017 respectively, Union Gas established the Facility GHG Emission Reduction Program in September 2017. The purpose of this program is to ensure Union Gas meets its annual compliance plan obligations under Ontario’s cap-and-trade program and prepares effectively for federal methane reduction regulations that are anticipated to be implemented by 2020. Specifically, Union Gas’s program will:
Union Gas will annually review identified GHG emission reduction opportunities using criteria that effectively balance compliance obligations, anticipated future regulations, customer preferences and other noteworthy benefits such as safety and operational reliability.
Enbridge’s Liquids Pipelines business segment implements a variety of techniques to optimize its’ operations and reduce power consumption across our network of oil pipelines. In 2017, these techniques included:
As part of our strategy to support the transition to a low carbon future, Enbridge is working to vertically integrate its platforms for renewable energy and natural gas. We are engaging with the expansion of renewable natural gas (RNG) – energy produced from the decomposition of organic waste – as well as the introduction of power-to-gas (P2G) technology that produces hydrogen by developing the first utility scale P2G pilot facility in North America, in partnership with the Canadian tech firm Hydrogenics. The integration of renewable fuel supplies like RNG and hydrogen into existing pipeline distribution systems for natural gas could make a significant contribution to meeting emission reduction targets by reducing the carbon content of energy used to heat homes and buildings and to fuel transportation.
Enbridge, a Canadian leader in green energy investment, is using big data, machine learning and predictive analytics to help optimize our wind power performance across North America. Enbridge’s one-of-a-kind Performance Analytics and Situational Awareness (PASA) solution could be a game changer in a sector grappling with increasing maintenance costs. PASA helps optimize turbine servicing, avoid downtime, and predict mechanical issues—and could one day help ensure the viability of the wind energy industry as a whole.
To create the PASA solution, which has been fully operational since early 2017, Enbridge’s advanced analytics team developed machine-learning models to identify wind turbine blade defects, and estimate time-to-failure and remaining useful life for any given turbine blade. To date, this solution has:
Enbridge researchers have been sharing their findings with industry and academic peers to help the industry improve the commercial viability of green energy projects.