Power Evaluator Machine-Learning Powered Nodal Forecasting

Power markets are dynamic. The acceleration of the energy transition injects significant variability and uncertainty. Renewable energy sources such as solar and wind can be volatile in the short term but highly predictable as they strongly correlate with the weather. Non-homogeneous electricity prices due to different operating locations, market rules, operating models, climate change, and demand increase price volatility and can affect the accuracy of power plant valuations.

Understand how Power Evaluator delivers unique and advanced forecasting capabilities to mitigate the risk of power price fluctuations in power plant valuations.

Key Features

Consistent LMP basis forecasts across an entire power market

Unlike typical nodal engineering dispatch models that lack the data to produce a consistent LMP basis forecast, Power Evaluator is deeply rooted in historical relationships and a set of key drivers to produce reliable forecasts across the entire US power market.

Bringing all nodal prices to customers’ fingertips

Avoid costly fees on disparate nodal datasets or consultancy services. Gain full access to our nodal forecasts for the entire US power market to value projects and power plants alongside zonal fundamentals, and asset data within the Power Evaluator.

LMP basis forecasts are aligned with S&P Global comprehensive power market outlook

LMP basis forecasts are aligned with S&P Global comprehensive power market outlook.

Stochastic modeling is the future of power price forecasting

Randomness and chaos will always be present in markets. Our modeling simulates spikes predicated on the historical probability of freezes, heat waves, and outages to provide more accurate energy forecast prices and mitigate price volatility.

See Power Evaluator in Action

Capabilities of our machine-learning-powered nodal forecasts

Mixed model approach

Power Evaluator selects the best forecast from four models that layer machine learning and advanced statistics on top of S&P Global fundamentals forecasts.

Dynamic model selection

Our algorithm chooses the most accurate forecasting tool using a twelve-month validation period which is then used to retrain the best model.

Training period optimization

Our data accuracy is optimized by intelligently scrapping outdated or unrepresentative historical data for training.

Stochastic outlier generation

We accurately replicate and generate outage behaviors and unusual pricing events using five layers of stochastic draws.

Forecasting Analytics for Nodal and Energy Storage

How you can use our nodal forecasts

Battery Storage Developerective

A battery storage developer needs to assess to profitability of prospective project sites. Power Evaluator can source for the battery arbitrage margins at many sites in North America. By applying the temporal arbitrage and storage value forecasts, the optimal value locations can be screened instantly and help the developer understand the historical pricing relationships at each site, to evaluate profitability.

Wind Developer

A wind developer is looking for a suitable site to build a series of turbines in West Texas. As part of the early scoping process, the developer needs to rank the potential land lease agreements. The Power Evaluator provides evaluations of nodes and interconnection points for numerous potential sites and assesses the LMP basis risk relative to the traded hubs where the contracts would settle for each site, to pinpoint the best spot for new turbines.

Private Equity Analyst

A senior analyst at a private equity firm wants to acquire assets in the power industry that are likely to be the most profitable. Power Evaluator can perform evaluations on multiple power plants using our proprietary power plant data, LMP basis forecast, and basis variation statistics for the node quickly.

Renewable Portfolio Owner

A renewables portfolio owner identifies an opportunity to acquire a power project acquisition and needs to assess its risk. The Power Evaluator can assess the merchant tail risk of the target and provide a quick view of both zonal and nodal price movements in the distant future.

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