Fulcrum3D CloudCAM Solar Forecasting
Sector: Power Generation (CCGT) • Location: Australia
Source: Australian Renewable Energy Agency (ARENA)
The Fulcrum3D CloudCAM solar forecasting project aims to provide high accuracy short-term power forecasts utilising all-sky cameras and state-of-the-art software. The project will forecast power generated at Genex Power’s 50 MW Kidston Solar Farm in Queensland (including reduction in output from cloud cover) to reduce uncertainty in solar power generation.Fulcrum3D CloudCAM Solar Forecasting proje
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Status
Original status | closed |
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Description
Description | The Fulcrum3D CloudCAM solar forecasting project aims to provide high accuracy short-term power forecasts utilising all-sky cameras and state-of-the-art software. The project will forecast power generated at Genex Power’s 50 MW Kidston Solar Farm in Queensland (including reduction in output from cloud cover) to reduce uncertainty in solar power generation.Fulcrum3D CloudCAM Solar Forecasting project aimsto reduce causer pays charges which can be enacted when a semi-scheduled generator is unable to meet the generation target set by the Australian Energy Market Operator (AEMO) dispatch system. AEMO is now allowing semi-scheduled generators to submit their own five-minute forecasts. If these are more accurate than AEMO’s current forecasts then this should lower the causer pays penalties payable by the solar farm.Short term forecasts are also expected to increase robustness of electricity supply and reduce costs. The project will:Optimise storage dispatch, demand response and other grid support technologies,Spin reserve management,Provide Frequency Control Ancillary Service (FCAS) support,Assist with grid connection requirements.Key resultsFulcrum3D installed 9 CloudCAMs (cameras) with their associated data loggers and NBN connection at Kidston Solar Farm in Queensland. These were incorporated with the existing Kidston SCADA system in conjunction with a new, highly detailed power model. The model uses data inputs from power station equipment (including inverters, dataloggers, and met stations) and models the current unconstrained generation capability. These systems work together to produce five-minute forecasts of Kidston Solar Farm output and submit them to AEMO’s MP5F API. This forecast is now being used in dispatch and is consistently outperforming ASEFS and reducing Causer Pays charges. The project has met its contracted outcomes. The project’s core achievement was demonstrating that it is possible to satisfy AEMO’s accuracy requirements and achieve zero Causer Pays charges at solar farms via MP5F with generators operating under normal conditions. |
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Original Currency | USD |
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Source
Source reliability | High |
Data quality score | 100% |
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