Yes Energy Power Demand Forecasting

Yes Energy Demand Forecasts (formerly TESLA demand forecasts) enable you to make the most informed decisions possible when buying and selling in energy markets worldwide.

Generated with proprietary forecasting engines, Yes Energy Demand Forecasts feed comprehensive weather variables and calendar information to proprietary algorithms. The solution is an advanced regression model that uses detailed demand and weather observation history and incorporates the latest near-term data to respond to changing weather patterns, extreme weather events, and holidays that might impact energy demand.

This is all backed by an expert team of analysts and engineers reviewing and maintaining every model, ensuring the most accurate and reliable forecasting in the industry.

KEY BENEFITS

Manage risk and gain a competitive edge with forecasts for electric load, solar, wind generation, gas consumption, or district heating
Highly accurate power demand forecasting, especially on unpredictable days, using an econometric model that is constantly tuned by a team of data analysts
Access support from the analysts who manage the forecast to understand the why behind it
Global forecasting data for the Americas, Europe, and Asia Pacific

SOLUTIONS THAT SUPPORT END-TO-END MARKET ANALYSIS

Standard or custom solutions provide access to highly accurate and reliable wholesale, grid, and utility-level load forecasts.

Standard Solutions

Temperature Sensitivity
Short-Range Load Forecast
Comparable Day Analysis
Weather Decomposition and Weather Risk

Custom Solutions

Highly accurate power demand forecasting models created using your data, ours, or your preferred vendors, offering more granular detail and updates at least every hour

Award-Winning Innovation

Yes Energy’s Weather Risk Tool has been recognized with the CleanTech Analytics Innovation Award. Selected from thousands of global nominations, this competitive award highlights our commitment to supporting the evolving energy sector.

The Weather Risk Tool focuses on forecasting power demand and providing insights for planning future projects such as solar or wind plants.

Learn more about how you can use Yes Energy Demand Forecasts to make more accurate predictions.

FAQ for Our Power Demand Forecasting Solutions

While load forecasts from Independent System Operators (ISOs) offer valuable insights, combining them with an additional forecast source can enhance accuracy and provide a more comprehensive outlook. Yes Energy Demand Forecasts (formerly TESLA power demand forecasts) offer highly accurate and reliable short-term and long-term forecasts, especially on high-impact days like holidays and extreme weather shifts.

Given the money and risks at stake, many organizations use more than one power demand forecast. We offer additional forecasting tools like weather decomposition, similar-day comparison, and temperature sensitivity (+/- 7 degrees). Our short-term energy demand forecasts are fully integrated into the Yes Energy platform.

This tool is designed to support your in-house team. Maintaining a dedicated full-time staff for load forecasting can be costly and resource-intensive. Also, staff turnover can be a major challenge, and with our solution you gain continuity of service and the reduced risk of knowledge loss, ensuring uninterrupted insights.

You can be confident in our data; our power demand forecasts aren’t a black box with no insight into how the model is built. Our analysts are constantly tuning the models, and you can ask the analysts who built the model questions.

Plus, our accuracy exceeds competitors on high-impact days – giving you a competitive edge. Our linear regression model tracks trends and shows how variables affect demand, offering transparency that machine-learning models can’t provide.

We license by company, not by seat, so there’s no additional cost for adding extra users within your organization.

Our accuracy beats competitors on “big potential loss” days, such as holidays or days with extreme weather conditions. We provide additional tools, such as weather decomposition, similar-day comparison, and temperature sensitivity (+/- 7 degrees) that help you “customize” your energy demand forecast.