Trading optimization made simple.

The AMS Trading Platform helps asset owners and managers in Australia’s National Electricity Market increase revenues, avoid costs, reduce risks, and maintain compliance with an AI-powered bidding platform.

How the Platform Works in the NEM

Forecasting

To predict future market prices for energy and FCAS, the platform uses artificial intelligence (AI) machine learning to continuously analyze thousands of variables, including system loads, transmission headroom, generator activity, and weather.

Optimization

The platform calculates the optimal bids across all markets for the next dispatch interval through to the next day, considering price forecasts, operational constraints, and business objectives.

Bidding

The platform creates market-compliant bid files, which are submitted directly to AEMO or routed to the customer’s trading desk for submission. The AMS Trading Platform automatically generates rebid reasons which are clear, transparent, and compliant.

Solutions for Renewable Energy Generators

Powerful Trading Tools for Semi-Scheduled Generators

AVOID NEGATIVE PRICES

Forecast market prices and bid proactively to avoid financial losses

MINIMIZE CURTAILMENT

Anticipate and detect network constraints, bid to maximize generation

MINIMIZE FCAS COSTS

Optimize bidding to minimize Contingency FCAS cost allocations

EXECUTE TRADING STRATEGIES

Support for merchant strategies, PPAs, and hybrid arrangements

PARTICIPATE IN FCAS MARKETS

Co-optimized bidding of energy and FCAS for eligible generators

STREAMLINE OPERATIONS

Reduce operational costs with 24/7 bidding coverage

 

Solutions for Grid-Scale Energy Storage

Maximize Revenues and Minimize Opportunity Cost

ANTICIPATE MARKET PRICES

Proprietary AI-powered price forecasts for energy and FCAS drive trading strategy

CUSTOM TRADING STRATEGIES

Configure and update asset trading strategies in real-time based on commercial priorities

CO-OPTIMIZED BIDDING

Continuously optimize bids across the energy market and all eight FCAS markets

CONTINUOUS REBIDDING

Rebid automatically and compliantly each time asset or market conditions change

TECHNOLOGY AGNOSTIC

Integrate and optimize hardware from any OEM or systems integration vendor

SUPPORT FOR ALL ASSET TYPES

Supports scheduled, non-scheduled, network, and hybrid BESS configurations

ASSESS REVENUE POTENTIAL

Forecast project revenues, test impacts of a range of project and market scenarios

OPTIMIZE ASSET WARRANTY

Maximize project revenues while respecting the asset’s warranty

A Technology-Agnostic Platform

Designed to optimize the trading of wind, solar, and energy storage from any provider.

The AMS Trading Platform supports energy storage and renewable technologies from any provider, and is configured to meet the unique warranty constraints and operating parameters of each asset.

Avoid the pitfalls of closed systems and vendor lock-in with a trading platform designed to work across your entire portfolio, including wind and solar.

Powerful Tools to Complement Trading Desk Operations

BETTER
FORECASTING

Leverage the power of AI to make better decisions, instead of relying solely on AEMO pre-dispatch.

REMAIN
IN CONTROL

Submit manual bids or pause algorithmic bidding and override manually at any time.

SIMULATION
ENVIRONMENT

Experiment with simulated assets to make better business decisions.

ADJUSTABLE
STRATEGIES

Instantly tailor bidding preferences to fit your business objectives and portfolio goals.

PORTFOLIO
OPTIMIZATION

Smart bids for all asset types in your portfolio, including wind, solar, and energy storage.

“We couldn’t be more excited with AMS' performance at Snowtown. AI software gives us an edge to manage risk and improve margins in energy markets that are becoming more challenging with high penetrations of renewable generation.”

Deion Campbell Chief Executive, Tilt Renewables

Take the AMS Trading Platform for a test drive.

Schedule a demo and platform simulation to discover how much revenue our platform can unlock from your assets in the NEM.

Request a Demo

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