The need for more and more energy and the growth of both energy related infrastructures and the number of users/customers are putting pressure on utility companies to exploit their operational and customer information. This information is most of the times located on disparate, non-integrated and under-utilized IT systems when the same the time Utilities face increasing needs of analysis & risk management and also forecasting ones on various areas like collections, electric load and maintenance, leading them to effective decision making across the enterprise.

Analytical View, through SAS' experience in working with hundreds of utilities worldwide, provides solutions offering a broad degree of automation, scalability, statistical sophistication and transparency that enable utilities to operate more efficiently and effectively at all levels of decision making.

Basic areas of interest in the Utility sector depending also on the market (e.g. because smart-meters are not installed worldwide) is collections optimization and electric load forecasting. In areas where large-scale smart meter implementation projects run, floods of data are generated that must be harnessed, converted into information and used to build more efficient operations. Utility forecasters can then seize this opportunity to optimize resource allocations, predict future growth, the volume, magnitude and location of demand and deepen insight for the planning process.

An area that should interest all Utilities all over the world regardless of how much ‘intelligent’ the grid is, is Predictive Asset Maintenance (rather than just Predictive Maintenance) which can improve uptimes, performance and availability of crucial assets while reducing unscheduled maintenance by helping organizations accurately predict events enabling them to run assets at peak performance.

Utilizing SAS tailored solutions, which use a combination of data integration, automation, analysis and predictive analytics, provides insight into asset performance on a large scale. The basic benefits of applying a Preventive Maintenance policy based on these insights are:

Reduced downtime. Near-real-time monitoring and predictive alerts and models help Utilities avoid major defects, prevent long downtimes and address potential performance issues before they escalate.

Optimized maintenance cycles. Leading-edge optimization algorithms and solvers let Utilities expand the maintenance cycle without jeopardizing asset uptimes or risking degradations or failures.

Reduced unscheduled maintenance. Predictive and near-real-time performance alerts allow maintenance teams to fix issues during scheduled outages in a planned, cost-effective way – and choose the optimal time to replace assets.

Improved root-cause analysis. Award-winning analytics and predictive data mining capabilities drive continuously improved reliability, efficiency and quality – identifying root causes and enabling engineers to troubleshoot and correct performance issues faster and more effectively.

Enhanced data visibility. After capturing large volumes of all types of data – from legacy to modern MES, ERP, CMMS and other systems – the solution transforms, standardizes and cleanses the data to make it accessible to a wide range of users.

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