Access to accurate variable renewable energy (VRE) supply forecasts allows grid operators to reduce the spare capacity generation to back up intermittent renewables, reducing grid balancing costs. Moata Solar Yield Forecaster is an AI based tool specifically designed to forecast the performance of large, complex or multi-site portfolios.
With more accurate forecasting from solar photovoltaic (PV) plants, project owners can sell their output ‘subsidy free’ or via Power Purchase to balance their output. Grid operators are able to balance the grid and asset managers can optimise the dispatch of their assets and determine reasons for underperformance - all in real-time.
- Energy yield modelling of complex PV plants, including irregular layouts and novel technologies such as bifacial or floating solar.
- Model architecture able to cover historical and current performance, and full range of forecast time horizons.
- Can be combined with demand forecasting modelling to produce whole system supply or demand balance forecasts.
- Fully automated platform, aggregating data to deliver a single source of truth.
State-of-the-art forecasting analytics, with commercial grade weather forecasts at different horizons (up to 10 days ahead) and granularities, for multiple applications and global coverage.
- Forecasting accuracy reporting for continual improvement.
- Customisable solution that can evolve with client requirements.
- Combination of AI models with physical performance models to optimise performance.
- Cost-efficient grid balancing from improved forecasting accuracy.
- Reduced data handling requirements and likelihood of human error with implementation of systematic and best practice data management.
- An end to manual processes with insights available instantly enabling information to be acted on in a timely fashion.
- Accelerated operational reporting and quicker decision making with instant access to data and real-time updates.