Australia’s rapidly increasing number of large scale wind and solar farms are being encouraged to invest in technology such as cloud-cams and “nose-cone lidars” that will improve the accuracy of the output from these wether-dependent and variable energy sources.
The Australian Renewable Energy Agency is providing $10 million to help trial technologies that can deliver the forecasting services, and importantly encore individual wind and solar farms to “self-forecast” output 5-minutes ahead and provide that input to the Australian Energy Market Operator.
Current forecasting measures are more accurate than most people realise. Even on a day ahead basis, the forecasts are more than 90 per cent accurate, and are about as accurate as load forecasts. On short term forecasts such as 5 minute intervals essential for AEMO’s dispatch decisions, the accuracy is usually more than 99 per cent.
But there are still issues. These forecasts are system-wide, not on individual installations. And on those occasions when individual wind and solar farms produce more than the AEMO dispatch allocation, they miss out on revenue.
When they fall short, due to a lull in wind or a cloud passing overhead, they are subject to what are known as “causer pay” penalties. This refers broadly to the cost of making up the shortfall or correcting frequency variations that occur as a result.
These “causer-pay” penalties have amounted to several hundred million dollars in recent years, although it should be noted that wind and solar are not the only culprits here.
Fossil fuel generators also miss their output targets due to sudden trips (and there have been more than 50 of those since the start of summer) or simple errors like pushing the wrong button.
Wind and solar farm operators, however, are keen for the “self-forecasting” because it means that they can manage their own output – and AEMO’s expectations – more accurately and be less subject to either revenue shortfalls or penalties.
Some of the technologies include “cloud-cams” that have been trialled at some solar farms in Australia such as Fulcrum3D’s technology at Uterne in Alice Springs and Karratha Airport. Put simply, it is a camera that monitors approaching clouds and can predict when and by how much the output of solar farms can be affected.
Lidar technology – which stands for light detection and ranging, and is also known as laser scanning – can be placed in the nose-cones of wind turbines to more accurately predict short term wind speeds, protecting wind farm operators from the impact of unexpected short-term lulls or gusts.
Other technologies that will be encouraged under the program may include software and the use of satellite data.
ARENA says that the program is seeking to demonstrate wind and solar farms can provide more accurate forecasts of their output into AEMO’s central dispatch system.
The projects it will fund will deliver ‘5-minute ahead’ forecasts, and also explore the commercial benefits to wind and solar farms of investing in forecasting technology and examine factors that affect the accuracy of forecasts in different weather, operational conditions and geographies.
ARENA CEO Ivor Frischknecht said this initiative originated in ARENA’s A-Lab innovation workshop last year, and could allow wind and solar farms to be better integrated into the grid while simultaneously improving grid security and reducing energy costs.
“As more variable renewables enter the market, we need to improve the accuracy of our short-term forecasts so we can anticipate what will happen as a cloud passes over a solar farm or if the winds change,” he said.
“At present, wind and solar farms can be disadvantaged if their available output doesn’t match the central forecast. If the forecasts are too low, wind and solar farms are restricted in how much electricity they can paid to produce.
“If forecasts are too high, the wind or solar farm may be obliged to pay for the cost of stabilising, which increases the price of electricity and is ultimately passed on.”
AEMO CEO Audrey Zibelman said if successful, the initiative would be another step forward in strategically integrating renewable generation into the National Electricity Market (NEM).
“Accurate short-term forecasts are essential for balancing supply and demand, and avoiding grid instability,” Ms Zibelman said.
“If we can more accurately predict demand and the output of all types of generation, we expect this will reduce the need for additional frequency control services in the future, which the market pays for,” she said.
Expressions of Interest open today and close on May 9, 2018. Successful applicants will be notified in June 2018 and invited to submit full applications.