The University of Adelaide researchers have conducted a study on the predictability of solar and wind energy generation and its impact on profits in the electricity market. Their findings suggest that consumers could benefit from lower electricity costs and more reliable clean energy if the energy market is structured to incorporate the predictability of renewable energy sources.
The study’s focus was on the Australian National Electricity Market (NEM), which has been transitioning to incorporate more renewable energy sources. The researchers analyzed data from the NEM and developed a model that takes into account the predictability of solar and wind energy generation. They found that incorporating predictability into the market structure can lead to reduced costs for consumers and increased profits for electricity generators.
The researchers also found that solar and wind energy sources have different predictability patterns. Solar energy generation is more predictable than wind energy, which is affected by weather patterns. The study suggests that incorporating this information into market structures could lead to more efficient use of renewable energy sources.
In their research, Ph.D. candidate Sahand Karimi-Arpanahi and Dr. Ali Pourmousavi Kani, a Senior Lecturer at the University’s School of Electrical and Mechanical Engineering, have explored various methods of achieving more predictable renewable energy. By doing so, they aim to provide significant cost savings in operating expenses, prevent clean energy spillage, and deliver cheaper electricity.
The researchers’ work has focused on developing more accurate forecasting models for renewable energy sources such as wind and solar. They have looked at various factors that affect energy generation, including weather patterns and climate data. Their findings suggest that by improving the accuracy of renewable energy forecasts, it is possible to reduce the amount of energy wasted due to spillage and ensure that clean energy is delivered efficiently.
The researchers’ work has important implications for the wider adoption of renewable energy sources. As the use of wind and solar energy grows, it becomes increasingly important to ensure that these sources are predictable and reliable. By reducing the costs associated with unpredictable energy generation, it is possible to make renewable energy more competitive with traditional energy sources.
“One of the biggest challenges in the renewable energy sector is being able to reliably predict the amount of power generated,” said Mr. Karimi-Arpanahi.
“Owners of solar and wind farms sell their energy to the market ahead of time before it is generated; however, there are sizable penalties if they don’t produce what they promise, which can add up to millions of dollars annually.”
“Peaks and troughs are the reality of this form of power generation, however using predictability of energy generation as part of the decision to locate a solar or wind farm means that we can minimize supply fluctuations and better plan for them.”
A recent study published in Patterns by a team of researchers analyzed six solar farms located in New South Wales, Australia, and compared them with up to nine alternative sites. The analysis parameters considered included factors such as location, climate, and terrain. However, the team also included the predictability factor in their analysis to determine its impact on the optimal location for solar farms.
The research showed that the inclusion of predictability in the analysis parameters led to a change in the optimal location for the solar farms. By choosing the most predictable location, the potential revenue generated by the solar farms increased significantly. This highlights the importance of incorporating predictability into the decision-making process when planning new solar farms.
Dr. Pourmousavi Kani, one of the researchers involved in the study, emphasized the significance of these findings for the energy industry and public policy design. The study’s results could help the industry in planning new solar and wind farms in the most optimal locations, thus increasing their efficiency and profitability. Additionally, the findings could also inform public policy design by emphasizing the importance of predictability in renewable energy production and the benefits of considering this factor in decision-making.
“Researchers and practitioners in the energy sector have often overlooked this aspect, but hopefully our study will lead to change in the industry, better returns for investors, and lower prices for the customer,” he said.
“The predictability of solar energy generation is the lowest in South Australia each year from August to October while it is highest in NSW during the same period.”
“In the event of proper interconnection between the two states, the more predictable power from NSW could be used to manage the higher uncertainties in the SA power grid during that time.”
The researchers’ analysis of the fluctuations in energy output from solar farms may be applied to other applications in the energy industry.
“The average predictability of renewable generation in each state can also inform power system operators and market participants in determining the time frame for the annual maintenance of their assets, ensuring the availability of enough reserve requirements when renewable resources have lower predictability,” said Dr. Pourmousavi Kani.
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