Ai-MicroCloud for Utilities
Energy Consumption, Active Power Loss Forecasting,
Heat Consumption, Building Energy Optimization
From electricity generation to storage, transport, distribution, and consumption, the energy industry value chain is extremely volatile and is being rapidly transformed by global market trends such as deregulation, renewable energy, carbon footprint reduction, energy exchanges and smart meter/grid technologies. Modeling for the energy industry supports key decision making that can affect short-term supply and demand planning, energy efficiency, spot market futures, energy production, and long-term capacity management.
Build Domain-Specific Utilities Applications:
Ai-MicroCloud™ enables you to develop, deploy and manage bespoke real-time domain-specific Ai applications in energy optimization, energy consumption and active power loss forecasting.
Ai will become a key enabler of the new, complex, and data-reliant energy system, offering a key tool to improving operational efficiency in an increasingly cut throat environment
Time Series Data Analytics in Utilities
Accurate energy forecasting is a crucial factor underlying utility company financial performance. They need accurate energy forecasts since extreme wholesale price volatility requires hedging against volume and price risk. It is important to determine which input variable have the highest relevance in calculating forecast. Examples of explanatory data variables can be historical load data in different levels of aggregation, as well as real-time measurement, weather data, calendar information, day/night etc.
Active Power Losses Forecasting
Electricity distribution is impacted by line resistance, outside temperature and switching states in the grid, potentially resulting in energy grid losses. Transmission system operators (TSO) must compensate for losses and manage them as it influences balance on the grid. Examples of explanatory variables include historical actual values for losses and technical information such as relevant points on the power grid, load and weather data.
Domestic heat consumption for water heating (cooking, bathing) and space heating. Continuous monitoring and detection of anomalous values can indicate issues such as ruptured pipes, loss of system pressure, water diversion or issues with radiators or boilers.
Building Energy Optimization
Buildings produce, store, and consume power, interacting with multiple suppliers – Stable (nuclear, hydro), controlled variables (coal, gas) and variable (Solar, wind). Building managers can harness AI to enable decision-making on power optimization alternatives, including drawing power, producing and uploading energy; producing and consuming energy; and producing and storing energy.
Edge Video Analytics Use Cases for Utilities
Safety Gear Detection
Detect number of objects such as safety vests, hardhats, bunny suits, safety glasses
Detect multiclass objects and alert when someone enters a restricted area
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For Time Series Data
Automated predictive model-building that creates human-readable explainable forecasts and anomaly detection models from historical time series data
Ai-MicroCloud™ for Utilities