Project leader Joakim Munkhammar of the Department of Civil and Industrial Engineering at Uppsala University says, "Our MCM model, as it's called, serves to predict what will happen in the next minute, hour or day, based on what usually follows a particular solar irradiance level. This model has a simple design, is easy to train and use, and provides surprisingly accurate solar irradiance forecasts." The model, presented to the scientific community last year, is based on a hidden Markov model, a statistical model for recognition and probabilistic forecasting of processes and patterns. The MCM (Markov chain mixture) distribution model divides solar irradiance into levels and calculates the probabilities of sunlight in the next and subsequent time periods being at the various levels. On this basis, it is possible to forecast when and between which levels sunlight will vary, and to compare the forecasts with actual observations to see how well the former match reality.
Renewable energy sources provided nearly 10% of both domestic energy production and U.S. electrical generation in 2008 with non-hydro renewable electricity expanding by 17.6% over the previous year; renewable energy will account for about a third of new electricity capacity added to the U.S. grid over the next three years.
The model has now been tested by both scientists. This included test runs to compare the model with several other models. In one study, in which the researchers tested the model and five established benchmark models (used for comparison to evaluate the relative performance of new models), the new MCM model yielded the most reliable forecasts, especially for the near future.The Uppsala researchers now hope it will be feasible to use their model to control technical systems.
"We look forward to working with other scientists and companies on testing the model with real physical systems, such as those for battery energy storage. We're going to try and boost the cost effectiveness of storage systems by adjusting the charge based on forecasts of local solar power generation," Munkhammar says.
Explore furtherKate Doubleday et al, Benchmark probabilistic solar forecasts: Characteristics and recommendations, Solar Energy (2020). DOI: 10.1016/j.solener.2020.05.051 Journal information: Solar Energy
The Itaipu Dam in Paraguay provides 76% of the country’s electricity and 17% of the electricity consumed in Brazil (displacing 67.5 million tonnes of CO2 every year). In Iceland, 100% of the energy is supplied by geothermal and hydropower sources!
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