6 days ago

An Elastacloud Energy Solution: The BSUoS Forecast.

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Today, energy companies are at the forefront of cutting-edge technology, with an onus on supplying energy in the most sustainable way. The diversification of the UK energy supply mix incorporates low-carbon renewable energy sources such as wind, hydro and solar. Today more than 20 percent of energy in the United Kingdom comes from renewable sources. In summer, it’s often closer to 100 percent. Many energy companies have diversified their supply sources to incorporate these low-carbon and sustainable energy sources, but this has led to complications in balancing demand and supply.

 

The Balancing Services Use of System Charge (BSUoS), charged by National Grid to help recoup the costs of balancing the grid from energy production, is a tariff which energy generators are liable to pay. The fee is paid to the system operator in half-hour periods for balancing the supply to meet demand, ensuring providers are generating energy efficiently. But if generation is not tightly monitored, the charge accumulates, severely damaging profitability.

 

Difficulty predicting charges

 

The charge is also difficult to predict. The price is volatile with external factors, such as weather conditions, which reflects the energy mix of the UK. The intermittent power generation and intermittency of weather conditions make calculating predictions complicated. With the ability to predict the charge, generation companies can better respond to the inherent intermittency of renewable energy generation and pricing. Equally, they will learn more about the drivers of the BSUoS charge and how to avoid over or under producing energy.

 

The Elastacloud team were approached by a large UK energy generation company to discover if this could be possible with their data, and so, in a recent project we built the BSUoS Forecast.

 

The solution: the BSUoS Forecast

 

The forecast was built using Microsoft Azure machine learning services. Our Data Scientists used historical BSUoS, demand, and generation data to build the machine learning model for the forecast that generates automated reports for the user. These reports provide a prediction of the BSUoS charge for the customer with significantly greater accuracy than other industry standard models.

 

The service enables energy companies to reduce costs by avoiding generation during the high price periods, and a reduced error risk. The proficiency and accuracy of the model not only provides advanced, industry-leading predictive reports, but makes it understandable and intuitive. As for the wider energy sector, the Forecast is a market-leading data science service, allowing generation companies to more profitably diversify their energy mix through improved optimisation of their own generation profile.

 

Our unparalleled experience using Azure machine learning cloud services, combined with our energy sector expertise has enabled us to provide our clients in the industry with cutting-edge business solutions. The BSUoS forecast is just one example of how we boost our customers’ value through the optimisation of data.

 

Get in touch today to find out more about the BSUoS forecast. The tool is available for energy companies who want to predict their BSUoS charge.

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