Ways in Which Big Data and Analytics Can Help Utilities

Data collection, processing, and analytics are not new to the utility industry.

The utility sector has been collecting various data for a long time. Data like machine reading, transmission recordings have been logged almost since the very beginning. Now, with the advent of IoT technologies, real-time data collection has become possible.

With the rise of computing power and storage capacity, it is easier to collate and analyse the data points and draw business inferences from them. Even though the adoption has been slow, the industry is waking up to the benefits of data analytics.

Let us take a look at how the energy and utility sector benefit with the use of data analytics–

1. Power Generation Planning and Outage Prevention: By their very nature, they go hand in hand. The power and utility companies generally have all the historical consumption data based on which one can predict the capacity that needs to be generated. Hence, it goes a long way in planning for future workloads and reducing outages. With effective capacity planning, companies are in a better position to foresee bad weather conditions or a surge in demand and be better prepared to deal with the outages.
2. Forecasting and Dynamic Pricing: It is extremely important for utility companies to understand future demand and plan accordingly. To understand the demand, they need to analyse various data points and elements.
   For example, there is a carnival in Rio and the authorities need to plan for a load. In this case, various factors such as the number of people coming into town and the number of hotel bookings play a role in load planning. Big data analytics can help companies analyse all such data elements and draw actionable insights.
   Another facet to the same becomes handy when it comes to renewable energy. Imagine the increased efficacy companies can achieve if they know the wind speed and the best time to capture the solar energy to effectively use it later.
   Dynamic pricing comes into picture when companies want to charge a premium. Based on the loads and time of the day, when it is costly to generate and transmit energy, increased pricing can be employed.
3. Site Selection: Selecting the right site for the plant set up has always been an area of great importance for the utility companies. Even for the traditional ones, the location needs to apt to ensure that the transmission losses are minimal. On top of that, companies also need to be mindful of natural calamities and weather conditions like inclement weather, earthquakes, etc. For renewable sources of energy, there are additional complexities – which location gets the maximum sunlight or wind? Where can we maximise the hydropower? All these things can be simplified with the help of data and analytics, which can help in identifying the right locations.
4. Asset Maintenance: Every utility site looks like a playground for heavy machinery, including power generating electrical equipment, cranes or earthmovers. Ensuring that these assets are working in their full capacity all the time is extremely important. At the same time, companies also want to know if any assets are lying idle so that those can be leased out for extra revenue generation. Predictive health monitoring and maintenance helps in reducing downtime and ensuring the health of the assets.
5. Energy Efficiency: The society as a whole has started moving towards efficient usage of energy. The increasing awareness about climate change has further augmented the move. The customer awareness and the rush to reduce carbon footprint by efficiently using fuels have brushed off on the utility sector too. The proliferation of IoT devices and smart grids along with smart metering has made it extremely user easy for companies to monitor energy usage. Companies can monitor data and do the optimal capacity management. Based on historical records, they can predict how the capacity may increase and how it can be optimised to reduce wastage. Based on the insights, utility companies can incentivise households for optimal energy utilisation.
6. Customer Insights: Big data and analytics help utility companies get a 360-degree view of their customers. Data points and analysis of energy utilisation in various households and trends can make it easy for the utility companies to spot anomalies. Similarly, every household can be given a customised incentive model to use its utilities in a certain pattern. This level of granular reporting can help in efficient load management.
7. Theft Detection: Several areas are prone to power theft. This is extremely rampant in rural areas or developing economies. With the proliferation of IoT, the power profligacy has reduced considerably. Smart Grids and Smart metering have enabled the detection of an anomaly. With that data, the exact source of theft and the location of theft can be zeroed down upon, and the necessary steps can be taken.

Earlier utilities used to be managed by government organisations. Today, in almost all the countries, private players are also coming into the picture, and there is a competition between them. Customer satisfaction and cost-benefit have become important factors in winning market share. All the above use cases provide utility organisations with the speed, agility in tandem with the cost benefits. Using data and analytics, they can reduce wastage and unearth new revenue generation routes to increase the bottom-line and generate sustainable profitability.