Summary
The project looked at new techniques of applying known models to the forecasting challenge, and ways to understand how solar and wind can smoothly integrate into the electricity grid.
Key results
- Significant benefit came from the collaboration, with knowledge sharing occurring at yearly meetings
- The key collaborators covered a range of expertise in forecasting, weather models, statistics, integration of renewables and market mechanisms. This ensured a clear link of development between the weather and solar and wind resource, citing and implications to large scale and distributed technology, as well as the network and market mechanisms associated with integration of solar technologies. These set up the basis for determining a forecasting system for solar PV. The expertise allowed good progress to be made and knowledge development in the solar resource and forecasting area
- Collaborative projects involving researchers with different skill bases allows a greater scope to be covered, giving a more holistic view of the area of research. Planning is key for the success of a project.
Need
Solar energy is highly variable across daily and seasonal cycles and is also influenced by factors such as absorption and scattering by clouds, water vapour, dust and pollutants. This is one of the limitations preventing the increased use of solar energy to generate electricity.
The problem can be reduced by connecting sources of solar-generated electricity to the main electricity grid in a way that takes into account the intermittent nature of sunlight and other forms of renewable energy.
Weather monitoring and forecasting can play an important role in managing the community’s demand for energy as well as the amount of renewable energy that can be generated.
This makes accurate forecasts central to economically viable use of renewable energy technologies.
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Project innovation
The project developed tools identifying the relationship between predictable weather patterns and the performance of key intermittent solar energy technologies, including weather patterns that reduce solar energy. This information can be used to identify the best locations for solar technologies to be installed as well as to design a system that can forecast solar electricity generation in real time.
Different computer modelling techniques were used to predict future weather patterns over a range of timescales, and the results used to develop forecasts. Other computer models were analysed that can forecast and measure the effect of large amounts of renewable energy in electricity grids.
Benefit
The project helps increase the understanding of the amount of solar energy used in the Australian electricity network by providing tools to manage large amounts of intermittent solar power generation and other forms of renewable energy.