The electric grid all across the world is an engineering marvel that is distributing more than 1 million megawatts of energy across 300,000 miles of transmission lines. Even with such enormous capacities, many countries are facing issues of power shortage, which is caused by an insufficient power supply or an inefficient grid system. The emergence of digital technologies has enabled power companies and power authorities to manage the electrical network far more efficiently. With the help of a powerful computer, automation technologies, and data a smart grid can efficiently transmit electricity. The smart grid allows companies to quickly restore electricity after a power disturbance, reduce operations and management costs, reduce peak demand, integrate large-scale renewable energy systems, and provide improved security. So how can data analytics revolutionize the smart grid market space?
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Power companies use data analytics to predict transformer failures so that the load can be efficiently allocated and distributed. Data can also help power companies to fully utilize transformer assets by using transformer monitoring programs, which compares the loading of the transformer over a period with standard operational parameters. Because of such constant monitoring, power companies can procure replacements before incurring power outages. With the efficient utilization of transformer assets, a smart grid can significantly reduce infrastructure costs.
Conservation Voltage Reduction (CVR)
A smart grid ensures that line voltage meets the operational targets, allowing utilities to manage demand and energy consumptions better. Additionally, usage of CVR along with smart grid results in peak shaving, lowered emissions, and mitigation of distributed generation (DG) voltage impacts.
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Theft and Leak Detection
Data analytics can analyze and identify patterns associated with tamper events during power usage and compare it with usage among similar residences to identify potential energy theft. Advanced analytics in the smart grid system can detect anomalies in the usage pattern and notify the concerned authority of possible power thefts or power leaks.
Advanced metering infrastructure (AMI) in a smart grid can capture interval data across broad consumer demographics to generate usage patterns. Analyzing this information along with historical data, weather, and other demographics information allows utility companies to accurately predict future demand and adjust their energy supply as per the forecasts.
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All implemented smart grids are continually gathering customer data, which can later be used to improve customer satisfaction. As energy companies are facing increased price and demand pressure, they are always willing to experiment with new programs. Data analytics can help identify which customer cohort are more likely to adopt the new program by merging meter data with demographic and financial data of the customer.