Executive Summary

CPV Retail Energy partnered with Tigo Energy to deploy Predict+, an AI-powered forecasting and analytics platform designed to improve electricity demand forecasting and support more informed market decisions.

Using Predict+, CPV Retail Energy can analyze large volumes of energy consumption data and generate accurate forecasts that help guide operational planning and market participation. The platform combines smart meter data, weather signals, and machine learning models to provide insights into demand patterns and energy consumption behavior.

Today, Predict+ helps CPV Retail Energy forecast energy demand across its portfolio while delivering deeper insights into electricity market dynamics and consumption trends.

The Challenge

Retail electricity providers operate in complex and highly dynamic energy markets. Accurately forecasting customer demand is essential for managing procurement, reducing market exposure, and maintaining profitability.

CPV Retail Energy needed a solution capable of:

• Forecasting electricity demand across a large customer base
• Processing high volumes of energy consumption data
• Improving visibility into demand trends and consumption behavior
• Supporting market participation decisions
• Enhancing operational planning in volatile electricity markets

Traditional forecasting approaches often rely on static models or limited data inputs, making it difficult to adapt to rapidly changing demand patterns.

The Solution

CPV Retail Energy deployed Predict+, Tigo Energy’s AI-driven forecasting platform designed specifically for energy markets.

Predict+ integrates multiple data sources to generate accurate energy demand forecasts, including:

• Smart meter consumption data
• Historical demand profiles
• Weather forecasts and weather history
• Behavioral and economic signals
• Market data

Machine learning models analyze these data streams to generate high-resolution electricity demand forecasts that can support operational planning and market strategies.

Predict+ also delivers analytics that help CPV Retail Energy better understand demand drivers and consumption patterns across its customer base.

Implementation

Predict+ integrates directly with existing energy data infrastructure and smart meter systems.

Once connected, the platform continuously processes incoming data and updates forecasting models to reflect changing consumption patterns and market conditions.

This adaptive learning approach allows CPV Retail Energy to maintain accurate demand forecasts even as weather patterns, customer behavior, and market dynamics evolve.

The platform also enables CPV Retail Energy to visualize demand forecasts and consumption insights through analytics dashboards designed for energy market operators.

Results

With Predict+, CPV Retail Energy gained a powerful platform for forecasting electricity demand and analyzing consumption behavior.

Key outcomes include:

Large-Scale Demand Forecasting

Predict+ forecasts more than 300 GWh of electricity consumption daily across global deployments.

Improved Demand Visibility

Advanced analytics provide deeper insight into consumption trends and behavioral drivers of electricity demand.

Better Market Intelligence

Forecasting insights help CPV Retail Energy make more informed procurement and trading decisions.

Data-Driven Operations

Machine learning models continuously update forecasts as new data becomes available, enabling more adaptive planning.

Why Predict+

Predict+ enables retail electricity providers to move beyond traditional forecasting methods by leveraging advanced machine learning and energy analytics.

The platform delivers:

• High-resolution demand forecasting
• Real-time data integration
• Advanced consumption analytics
• Scalable forecasting across large customer bases

These capabilities allow energy retailers to better anticipate demand, manage risk, and operate more efficiently in competitive electricity markets.

About CPV Retail Energy

CPV Retail Energy is a retail electricity provider that supplies energy to residential and commercial customers. The company operates in competitive electricity markets where accurate demand forecasting and market intelligence are critical to managing procurement and pricing strategies.

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