Power & Renewables

Enverus Power Forecasting Solutions: Delivering Precision and Innovation

byDaniel Manfre Jaimes

In the dynamic landscape of energy markets, accurate load forecasting is essential for informed decision-making. Enverus power forecasting solutions have consistently demonstrated exceptional performance, particularly during extreme weather events and critical peak demand periods. Complementing this reliability, our ongoing commitment to innovation has led to significant enhancements in our forecasting models. This blog highlights the accuracy of our load forecasts in recent high-stakes scenarios and introduces a transformative weather algorithm update that further elevates our power forecasting accuracy.

1.21% MAPE: Exceptional Accuracy During Extreme Weather in NYISO

In June 2025, New York City endured a severe heat wave from June 20 to June 25, with temperatures peaking at 99°F in Central Park and 102°F at Kennedy Airport on June 24. This event drove electricity demand to a nine-year high of 31,857 MW in the NYISO system at 6 p.m. on June 24. Our Enverus one-day-ahead forecast demonstrated remarkable accuracy during this extreme event:

  • Hourly MAPE at peak demand (6 p.m.): 1.21%
  • Daily MAPE for June 24: 2.94%

In comparison, the ISO forecast had:

  • Hourly MAPE at peak demand (6 p.m.): 4.58%
  • Daily MAPE for June 24: 5.58%

By leveraging proprietary algorithms within our Mosaic platform, we provided forecasts that significantly outperformed industry benchmarks. This precision enabled our customers to make swift, data-driven decisions during one of the most intense heat waves in recent years, demonstrating that our solutions are reliable not only for routine operations but also under the most challenging conditions.

Precision Call Out: Identifying ERCOT Coincident Peak

Enverus power forecasting solutions also excelled in the ERCOT market during June 2025. On June 19, the Coincident Peak (CP) occurred during Hour Ending 17, and Enverus accurately identified this critical interval one day in advance. This foresight provided customers subscribed to our 4CP alert solution with valuable time to prepare and optimize their operations.

Alert received by Enverus customers who subscribed to the 4CP alert solution. Enverus Mosaic short-term analytics and forecasting solutions are designed to help you explain the past, understand the present and forecast the future.

Our day-ahead load forecast for June 19 achieved a daily MAPE of 1.80% and a MAPE of 1.69% during peak hours (Hour Ending 7 to 22). These metrics highlight the precision and adaptability of our power forecasting tools, which empower customers to stay ahead in dynamic energy markets.

Enhancing Power Forecast Accuracy With a New Weather Algorithm

To further strengthen our power forecasting capabilities, Enverus has introduced a significant enhancement to our weather algorithm. Thorough analyses of cold snaps, heat waves, and shoulder season swings revealed that inaccuracies in temperature forecasts were a primary driver of higher MAPEs. In response, we conducted an extensive review of our temperature forecast data and implemented updates that have yielded substantial improvements across all ISOs.

The backcast analysis for January to April 2025 demonstrates the impact of this new algorithm. Total MAPE accuracy for load forecasts improved by up to 10% in some ISOs, with an average improvement of 4% across the board. Notable enhancements include:

ISOTotal MAPE – BeforeTotal MAPE – AfterImprovement
(percentage points)
ERCOT2.35%2.31%0.04
PJM2.33%2.10%0.23
SPP1.87%1.75%0.12
MISO1.57%1.48%0.09
NYISO2.44%2.38%0.06
ISO-NE3.28%3.18%0.10
CAISO2.94%2.92%0.02

The updated weather algorithm enhances the adaptability of our forecasts, ensuring they remain robust across diverse conditions and seasons.

A Commitment to Excellence in Power Forecasting

Enverus power forecasting solutions combine cutting-edge technology with a relentless focus on improvement. Our ability to deliver highly accurate forecasts during extreme weather events, such as the June 2025 NYISO heat wave, and critical peak periods, like the ERCOT Coincident Peak, demonstrates the reliability of our platform. The recent weather algorithm enhancement further strengthens our models, reducing MAPE across multiple ISOs and reinforcing our commitment to driving superior forecasting outcomes.

By continuously innovating and refining our approach, Enverus ensures that our customers have access to the most accurate and actionable forecasting tools available. Our solutions empower energy market participants to navigate complexity with confidence, delivering measurable value in both routine and extraordinary circumstances.

About Enverus Power and Renewables

With a 15-year head start in renewables and grid intelligence, real-time grid optimization to the node and unparalleled expertise in load forecasting that has outperformed the ISO forecasts, Enverus Power and Renewables is uniquely positioned to support all power insight needs and data-driven decision making. More than 6,000 businesses, including 1,000+ in electric power markets, rely on our solutions daily.  

Picture of Daniel Manfre Jaimes

Daniel Manfre Jaimes

Daniel Manfre Jaimes has been part of the Enverus Power Markets team since 2024 and currently serves as a Power Market Analyst, where he analyzes and provides insights on price, load and power generation forecasting models across North American electricity markets. His work focuses on evaluating model performance, identifying areas for improvement and offering recommendations to enhance forecasting accuracy. Prior to joining Enverus, Daniel developed day-ahead and real-time price forecasting models for the Alberta, ERCOT and PJM electricity markets. He is an electrical engineer who also worked as a Field Electrical Protection Engineer at Siemens, commissioning and implementing protection systems for medium and high voltage substations. Daniel is a registered Professional Engineer (P.Eng.) with APEGA and holds a Master of Science in Electrical Engineering from the University of Calgary.

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