Predictive Analytics For Reliable Utilities

The world today relies on the critical services of electricity, gas, water, wastewater, and waste removal.  These services are plagued with ageing assets and higher expectations from customers, making it necessary to tap into new technologies to improve operational efficiencies and reliability. 
 
The ability to predict outages and failures, better optimise field crew and maintenance efforts can be achieved through Predictive AI. Utilising IoT sensors, historical and live data, AI analytical models provide real-time monitoring of whole networks and can predict the majority of problems, identifying the root cause in advance. What may have taken weeks or months for a dedicated data science team, can now be achieved in a timely manner providing real-time actionable insights. 
 
AI Predictive Analytics not only assists with operational risk management and asset management, it can help with load forecasting and process optimisation. Identifying inefficiencies and boosting reliability all through the power of latent data and artificial intelligence. 
 
Benefits of AI Predictive Analytics to Utility Services:

  • Improved customer satisfaction through accurate forecasting and supply
  • Reduced asset maintenance costs and increased asset life-span
  • Improved safety
  • Improved decision making with AI analytics, used by SCADA engineers, asset managers and operators
  • Reduction in unexpected outages and failures and improved service reliability
  • Fuel cost savings through the prevention of excessive energy consumption, ideal for water desalination plants and power stations

 
If you're looking for an innovative way to optimise your plant, get in touch today.

 

Request Demo

Power plants use a mere 20-30% of their collected data to inform decision making. With companies either lacking the data infrastructure, management or analytics capabilities. McKinsey

VROC Detects Generator Fault and optimizes energy production 

VROC's AI platform was used to analyse the performance of two identical air supply units to identify the cause of a loss of energy production and excessive energy consumption as well as reliability issues. 

VROC successfully identified the root cause of the issue which lead to a heat retention for our client and fuel savings which have been estimated at $280,000 USD per annum.

Read the full case study

generator