Analytics, Data Science & AI Service Provider for Energy & Utilities Industry

Utility

Utility and energy sectors are working under strict regulatory compliance and also being bombarded with ever increasing data sources from digital, machine and IOT sensors. Intelligent use of various data sources can improve the productivity of energy generation and distribution infrastructure thus help in saving costs and improving profit.

One of the most profitable generation and distribution companies in utility sector in India engaged with Business Brio to identify duplicate utility meters to reduce revenue leakage. A predictive model was developed using power consumption trend, enhancement requests, proximity location, text mining to predict possible duplicate meters and enable the revenue collection team to reduce the redundant meters.

Forecasting

At Business Brio, we have used Single Exponential Smooth, Double Exponential Smooth, ARIMA and back-propagation neural network. We did find Neural network to have better forecasting performance than the classical forecasting algorithms in case of wind energy forecasting for a particular project and won the NASSCOM Analytics Innovation award in 2015 for effectively using the same for business.

Optimization

Methods like Goal Node, Integer Linear Program, Simplex Method and Interior Point Method are used depending on the context and relevance. At Business Brio we use Lindo as a tool for optimization.

Machine Learning

Unsupervised and supervised learning methods like regression, support vector machines (SVM),KNN, K-means, PCA are used to recognize patterns and make data-driven predictions or decision outputs. We extensively use Python and R for applying the algorithms.

Decision Trees

CART, CHAID, Random Forests, mathematical and computational techniques are used to aid the categorization and classification of a given data information. Apart from programming tools, we also use WEKA for decision trees.

Sentiment Analysis

Opinion mining or emotion AI refers to the use of natural language processing, text analysis, and computational linguistics to systematically identify, extract, quantify, and study affective states and subjective information. In past projects, we have heavily used LSE, HSA, text mining for semantic algorithms.

Business Brio works with utility companies to reduce revenue leakage and predict supply using AI and predictive models

Plug Revenue leakage

Identify duplicate utility meters to reduce revenue leakage by analyzing power consumption trend, proximity location, power line enhancement requests, new meter requests in recent past and develop a predictive model to predict duplicate meters for individual consumers

Applications

Energy Forecasting

Predict wind energy supply in a power grid for understanding the need of conventional energy as controlled input using Artificial Neural Network and its ensemble with OLS for shorter (<=3 hours) and medium time horizon (<24 hrs) and plan production from conventional energy sources with greater accuracy

Predictive maintenance of distribution infrastructure

Minimize production downtime and save costs by predicting when components of power distribution infrastructure like transformers or utility machines like HVAC, water chillers, air compressors etc. needs maintenance by monitoring data from sensors, usage metrics, power or fuel consumption, machine parameters etc. Track and predict overloading and carry out load distribution of critical transformers in your power distribution infrastructure

Customer Analytics

Leverage data to provide customer usage statistics, monitor trend and also plan your future infrastructure for providing better customer satisfaction by data visualization and dashboard

Ask For a Consultation

Leverage analytics to improve productivity of utility infrastructure and plug revenue leakage.

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Advantages

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