Sunshine Duration Recorders TRIZ Cases
- System and method for seasonal energy consumption determination using verified energy loads with the aid of a digital computer
See how verified seasonal energy loads and meteorological data enable accurate photovoltaic fle
- "solar power forecasting"
See how distributed sky cameras and 3D cloud reconstruction predict solar irradiance occlusion,
- System and method for HVAC modification based on virtual audit result with the aid of a digital computer
See how expressing energy load as a function of outdoor temperature enables remote HVAC auditin
- Power generation prediction system and method thereof
See how segmented neural networks reduce retraining time when pyranometers change, providing ma
- System and method for determining seasonal energy consumption with the aid of a digital computer
See how expressing energy load as a function of outdoor temperature in point-intercept form ena
- Solar power forecasting
See how distributed digital cameras generate 3D sky models to predict solar irradiance from clo
- Photovoltaic energy system with solar intensity prediction
See how solar intensity sensors detect approaching clouds to preemptively adjust photovoltaic p
- Weather and satellite model for estimating solar irradiance
See how qualitative weather descriptions are converted to quantitative coefficients and combine
- Remote Energy Auditing Using Utility Data and Weather Integration
See how digital analysis of utility load and weather data enables remote building energy audits
- Solar Irradiance Estimation Using Weather and Satellite Data
Qualitative weather reports are converted into irradiance inputs and combined with satellite imagery to improve local solar estimates without dense sensors.
- 3D Rooftop Solar Potential Mapping Without Site Visits
3D aerial data, GIS, and shadow simulation assess rooftop solar potential accurately without repeated site visits, cutting evaluation time and cost.
- Solar Radiation Estimation Using PV Output and Terrain Data
Machine learning combines PV generation, weather, and terrain data to estimate solar radiation more accurately under cloud and mountain effects.
- PV Power Forecasting Using Sky Images and Weather Data
Combining sky-image analysis with weather data improves solar radiation and PV output prediction for better plant planning and operation.
- Solar Power Plant Valuation Using Sunlight and PV Yield Modeling
By combining sunshine simulation, PV loss modeling, and discounted cash flows, this case improves solar power plant valuation under weather and market uncertainty.
- PV Configuration Inference From Production Data for Fleet Forecasting
Measured PV output and solar data are used to infer tilt, azimuth, shading, and inverter parameters for faster, more accurate fleet forecasting.
- Vehicle Data Reward Control for Solar Energy Participation
Mileage rewards for transmitting sunlight, temperature, location, and time data help increase vehicle solar energy participation.
- PV Energy Forecasting via Empirical Normalized Irradiation
Empirical weighting of irradiance and clear-sky data estimates normalized irradiation for more reliable photovoltaic fleet energy forecasts.
- Optical Sensor Lens Layout for Wider Rain Detection
Equalizing lens portions spread light from multiple emitters to widen rain sensing range while preserving solar radiation detection accuracy.
- Solar Power Forecasting Using Clear-Sky and Cloud Cover Data
Clear-sky output and local cloud cover data are combined to forecast photovoltaic generation more accurately for grid production scaling.
- Photovoltaic Configuration Inference for Obstruction-Aware Forecasting
Historical output and solar data are used to infer PV tilt, azimuth, shading, and inverter parameters for more accurate energy forecasting.
- Behind-the-Meter Solar Forecasting from Panel Mapping and Weather Data
Aerial panel mapping plus meteorological data estimates behind-the-meter solar output to guide grid upgrades and reduce blackout risk.
- Solar Power Forecasting With Bellwether Meter Clustering
Bellwether meters in solar clusters enable real-time generation forecasts without third-party weather services, cutting latency and meter deployment.
- Disease Severity Modeling from Leaf Wetness and Temperature
A leaf wetness and temperature model predicts disease severity quickly from hourly weather data, reducing computation for targeted treatment.
- Solar Irradiance Mapping From 2D Aerial Images
A trained model estimates surface irradiance from 2D aerial images, avoiding costly 3D data for fast solar potential mapping.
- Aerial Image Irradiance Mapping Without 3D Reconstruction
Deep learning estimates surface irradiance from 2D aerial images, avoiding costly 3D data for faster solar planning.