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Forecasting Solar Power and Uncontrollable Loads

One of the key features of the Pleevi optimizer engine is its integration with our advanced solar power and uncontrollable load forecasting services. By leveraging state-of-the-art forecasting models, our system can predict future energy generation and consumption with high accuracy. When enabled, this feature allows the optimizer to construct optimal energy schedules based on forecasted data, ensuring better energy management and improved efficiency.

PV (Photovoltaic) Forecasting​

Photovoltaic (PV) forecasting involves predicting the power output of solar energy systems based on various factors such as weather conditions, solar irradiance, temperature, and historical production data.

How PV Forecasting Improves Optimization​

By incorporating PV forecasts, the Pleevi optimizer can:

  • Anticipate energy production: Predicting solar power output helps in planning energy usage efficiently.
  • Enhance energy storage management: Forecasts enable better scheduling of battery charging and discharging.
  • Reduce reliance on the grid: By forecasting solar availability, the optimizer can minimize grid dependency and costs.
  • Optimize charging schedules: Ensures that energy-intensive processes, such as EV charging, are scheduled when solar energy is abundant.

Our PV forecasting models are continuously improved using real-time data and machine learning, ensuring highly accurate predictions that enhance overall system efficiency.

UL (Uncontrollable Load) Forecasting​

Uncontrollable Load (UL) forecasting refers to predicting the energy consumption of assets that are not directly controlled by the Pleevi optimizer. These loads typically include non-steerable energy-consuming devices such as:

  • Building electricity usage (lighting, appliances, office equipment, etc.)
  • Peripheral devices (printers, networking equipment, etc.)
  • Carports and HVAC systems (air conditioning, heating, ventilation)
  • Unregistered or unmanaged chargers (EV chargers that are outside the optimizer's control)

How UL Forecasting Enhances Optimization​

By understanding future energy consumption patterns of uncontrollable loads, the Pleevi optimizer can:

  • Improve energy distribution: Ensures that controlled assets receive energy at the right times while accommodating known background consumption.
  • Enhance demand response: Helps prevent unexpected energy shortages by accounting for passive consumption trends.
  • Support grid balancing: Avoids unnecessary grid stress by predicting peak load times and adjusting controlled assets accordingly.

With UL forecasting, Pleevi creates a more comprehensive and efficient energy scheduling strategy, ensuring optimal balance between generation, consumption, and cost-effectiveness.

By integrating both PV and UL forecasting, the Pleevi optimizer provides a smarter, data-driven approach to energy management. These forecasts enable businesses to reduce costs, optimize their energy usage, and move towards a more sustainable and autonomous energy system.