Smart grid and BPM make perfect match
Smart grid infrastructure has the potential to revolutionize how utility companies operate. It allows them to track real-time data from consumers, power generation sites, transformer units and any sensor-equipped part of the utility grid. Essentially, the smart grid creates a deluge of data that utility companies have to not only store, but analyze in real time to identify grid conditions, decide how much power is needed from generation sources and troubleshoot any problems that may be developing within the infrastructure.
It is almost impossible to keep up with the amount of data created by the smart grid manually. Instead, utility companies depend heavily on tools that automate core data collection tasks. However, this does not always provide enough context and automation to truly streamline operations. Instead of using only basic tools, utility companies are increasingly turning to business process management software and similar solutions to automate elements of data analysis.
By using BPM solutions alongside smart grid systems, utility workers can have data that is relevant to their role or pertaining to an emergency condition delivered to them in a streamlined way, dramatically improving operational efficiency.
To understand the full implications that BPM can have on power delivery and environmental efficiency, consider how utility companies have to deal with solar, wind and other forms of intermittent renewable energy. Because these forms of power are generated through sources that can be difficult to predict and are not constantly available, they cannot easily be relied upon as a primary source of electricity within a utility grid.
The smart grid overcomes this, to some extent, by providing so much data about delivery and use requirements that utility providers can better predict how much energy will be needed at any time and adjust delivery plans accordingly. As a result, a utility company can use wind and solar energy in a more dependable way and use traditional power generation sources when they know, based on data delivered through the smart grid, that the energy delivery capabilities of the intermittent renewable sources will not match demand.
However, depending on wind or solar power in this way hinges on not only having the data available to predict power use, but to constantly analyze power consumption models, power generation trends based on environmental conditions and other forms of information that contribute to delivery. The automated analysis enabled by BPM can enable this functionality and provide an easier avenue into renewable energy.