Renewable Energy Company Enhances Asset Valuation with Price Modelling

A global renewable energy company has transitioned to a new market modelling framework using Lacima Trader > Sim, to improve the valuation of its solar assets in the Australian market.

The Project

This renewable energy producer, with a significant portfolio of solar contracts, sought to address limitations in its existing modelling framework. The previous approach, based on fundamental intrinsic value, did not capture the volatility and price behaviours, especially at intra-day and sub-hourly intervals, driven by complex market bidding dynamics.

To value assets more accurately and simulate extrinsic value, the company required a new modelling framework capable of high-resolution simulation. Lacima was selected for its best-in-class analytics, offering fast deployment, high accuracy, and ease of use.

The Client

The client is a global leader in solar energy development, with operations across six continents. The company manages both manufacturing and solar project development, maintaining a substantial operating portfolio and utility-scale pipeline of solar power projects. With thousands of megawatts of solar energy capacity installed and a strong global footprint, the business is focused on accelerating the clean energy transition through innovation and analytics-led decision-making.

The Solution

The company implemented Lacima Trader > Sim, featuring single-factor modelling, to accurately simulate price dynamics down to five-minute intervals. This solution captures extreme price events, from negative prices to sharp spikes, enabling detailed forecasting across multiple scenarios.

Using Lacima Trader > Sim, the company produced generation-weighted energy and ancillary service price curves with sub-hourly granularity for up to 35 years ahead. Due to the familiar Excel interface, the deployment required minimal training and system integration.

The Outcome

The implementation has enabled significantly more accurate asset valuations, giving the business deeper insights into both intrinsic and extrinsic asset value, as well as future investment decisions. The ability to generate ancillary service price curves with high temporal granularity is also supporting more robust energy storage valuations, strengthening the company’s position during commercial negotiations.