NewcastleNew South Wales, Australia Research facility, publicly-owned Synengco was approached by CSIRO to be a part of their study on Fault Detection & Diagnosis (FDD) in the commercial building industry. Their study engaged several vendors with FDD solutions and compared their offerings over a 12-month paid trial. Objectives ✓ Monitor Read more…
South Brisbane,Queensland, Australia Energy plant, Queensland Children’s Hospital The Queensland Children’s Hospital energy plant has a lot of flexibility to provide the various services that the hospital requires. However, this makes it difficult for managers to know how the plant should be operated for the lowest life cycle cost. Synengco’s Read more…
Central Coast, NSW, Australia Coal-fired power station, privately-owned SentientSystem has been deployed as a platform for Real-time Optimisation (RTO) on power stations around the world. Our customers use the platform to capture and operationalise plant knowledge and operations experience as RTO Modules that take control actions that optimise the plant’s Read more…
Various stations across Queensland, Australia Coal-fired power station portfolio, publicly-owned Objectives ✓ Reduce the risk of equipment failure✓ Increase system performance Key Outcomes ✓ Reduced operating costs and greenhouse gas emissions through real-time optimisation of soot blowing activity✓ Avoided loss of availability through early warning of equipment faults✓ Real-time decision Read more…
Eastern and Southern States, Australia Participants in the Eastern National Electricity Market (NEM) Synengco is collaborating with the energy analytics team within the Queensland Government, aiming to make informed, data-driven recommendations to policy makers. Leveraging on best practice concepts from ISO 55001 and US EPA NESCS, a systematic framework for Read more…
Darling Downs Region,Queensland, Australia Combined cycle gas-fired power station, privately-owned By using SentientSystem, one performance engineer can proactively monitor a portfolio of assets that would typically take a team of five. This is achieved by automating routine data cleaning and analysis tasks and applying advanced decision support algorithms to focus Read more…