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JP Elektroprivreda Srbije (EPS) Serbian leading energy provider boosts trading profits with predictive artificial intelligence Accurate energy demand evaluation is vital for Serbia’s leading utility supplier, Elektroprivreda Srbije (EPS). Wanting to improve and optimize the process of consumption forecasting, the company‘s stakeholders resolved to use a new solution combining Microsoft Azure Machine Learning with Power Apps and Power BI. In addition to extending the company’s forecast period and simplifying data entry and visualization, EPS saw both its prediction time and margin of error drop beyond expectations. Customer Customer profile Software and services JP Elektroprivreda Srbije Public Enterprise Electric Azure (EPS) Power Industry of Serbia is a Azure Machine Learning Website: eps.rs/eng state-owned public utility and Power Apps Country: Serbia one of the largest companies Power BI Industry: Energy in Serbia, operating in Customer size: Corporate electricity generation, supply, (10,000+ employees) distribution, and trading. Serbian energy provider boosts trading profits with predictive AI “We worked closely Demand forecasting in the energy industry is crucial since energy overconsumption and underutilization generate substantial losses. Serbia’s leading electricity provider, Elektroprivreda with Microsoft so that Srbije (EPS), faced such inefficiencies. Dispatchers used to manually input large volumes of historical we could transfer data, consumption and meteorological data into spreadsheets to predict supply trends—an error-prone years of experience, process that affected the company’s bottom line. “We play balancing markets on an hourly basis. Each deviation is an extra cost,” explains Dragan Vlaisavljević, Executive Director at EPS. and thought process To optimize electricity trading and accelerate decision-making, EPS turned to Microsoft and local into code. Now we just partner Informatika AD. “The team suggested machine learning technology. As far as we know, this need to provide data, had never been done before, so we started with a proof of concept,” says Danilo Komatina, Principal and the system does Engineer at EPS. The company's new solution combines Microsoft Azure Machine Learning, Power Apps, and Power BI. the rest.” Faster, more accurate forecasting Twenty years’ worth of data was digested by the Azure-based solution, and it applies continual machine learning, which gives EPS the agility to accommodate fluctuations. Thanks to real-time data analysis and automation, forecasting electricity consumption now takes 15 minutes instead of two hours, and the time saved is used for trading optimization. EPS has streamlined data collection Dragan Vlaisavljević, using Power Apps, and replaced manual reporting with Power BI dashboard visualization to improve Executive Director, real-time decision making, “My team prepares the data and puts reports on Power BI. I immediately Elektroprivreda Srbije (EPS) see what’s happening just using the mobile app,” says Vlaisavljević. The error margin that hovered between 5 percent to 15 percent shrunk to 1.7 percent. “Reduced error deviation means reduced costs to cover it. We save up to EUR600,000 per year for the “Ultimately, we now balancing market alone,” explains Komatina. “As we also trade better; we predict we’ll be making another EUR300,000 of profits per year,” adds Vlaisavljević. “We don’t have to start and stop our produce more generators as often, so there are fewer malfunctions, reducing repair costs and downtime periods. electricity, sell more, Ultimately, we now produce more electricity, sell more, and buy less,” summarizes Komatina. and buy less.” AI—from spark to flame The project boosted the company's confidence to embrace emerging technologies. “You don’t need a lot of IT experience, or know how to code, or have to invest too much time. We worked closely with Microsoft so that we could transfer data, years of experience, and thought process into code. Now we just need to provide data, and the system does the rest,” says Vlaisavljević. “We are currently exploring how Azure can help tackle challenges like price prediction, trading data Danilo Komatina, Principal Engineer, collection, and integration with existing processes. And we look forward to expanding our energy Elektroprivreda Srbije (EPS) demand forecasting to the whole Central and Eastern Europe trading zone,” he concludes. To find more stories like Partner Digital transformation to: Informatika AD (informatika.com/en) • Empower employees this, visit the global Informatika AD provides services in the • Engage customers development, implementation and • Optimize operations evidence website: maintenance of IT and business • Transform products customers.microsoft.com solutions. This case study is for informational purposes only. MICROSOFT MAKES NO WARRANTIES, EXPRESS OR IMPLIED, IN THIS SUMMARY. Document published April 2020 .
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