Though utility companies have always employed analytics to a certain degree, the data they gather from power plants, transformers, generators and other equipment only reflect those that have already happened. Industry experts agree that making operational decisions based on historical data is ineffective and may lead to false conclusions.
By relying on historical data, the decision-making process of utility companies becomes more reactive than proactive. Let’s take the health of power plants as an example. Many of the power plants operating in developing countries are well beyond their lifespans, and the constant increase in demand for electricity puts more pressure on these dated facilities. As a result of the overwhelming requirement, these power plants often break down, forcing utility companies to perform unplanned maintenance activities. However, because the unexpected breakdown is outside the maintenance cycle in vigor, utility companies usually choose to delay the operation and “sweat” the facilities even more. Professionals knowledgeable in power systems will agree that “sweating” assets will only increase the chances of breakage, higher maintenance costs and sub-par performance.
The latest technologies in advanced analytics allow utility providers to plug the gathered data into a statistical model, which is capable of scientifically predicting future scenarios based on operational events that have already occurred. This will, then, enable utility providers to make proactive decisions that will help regulate the electricity supply and plan maintenance schedules. Using the forecast, utility companies will be able to estimate the electricity demand and supply per area and per season. When, for example, they ascertain a potential gap in demand, they can take the proactive step of introducing other sources of electricity, like temporary power plants, into the energy mix.
If load shedding is really unavoidable, having advanced analytical tools will allow utilities to effectively manage and communicate planned outages. From the statistical information available, utility providers can determine critical operation times for industrial and commercial companies, so that they can work around the schedule in such a way that the planned power outage will have the least impact on these entities’ business operations. For instance, they can collaborate with rental power providers that will provide the necessary power to industrial and commercial zones during the hours when the permanent facilities aren't able to generate enough electricity.
Today’s advanced analytics systems are more accessible, because the latest technologies provide for plug-and-play operations, even for non-specialists. They use a considerable degree of artificial intelligence to meet the requirements of modern-day businesses and utilities. This allows them to make proactive decisions that will ultimately save them time and money, and optimise processes and resource allocation.
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