The time has come for domestic solar power producers to more accurately forecast energy output by utilising recent scientific innovations such as Sun4Cast and Solar Times Series Tool
Although the Indian solar power sector is growing at a fast pace and distribution utilities are increasingly relying on them, the industry is more focussed on monitoring rather than forecasting output, which in coming years may prove costly.
Utilities and grid operators typically plan their energy unit commitment for a day or more ahead. For variable generation units like solar farms, it means that they require a forecast of how much solar power will be available. This helps them to optimise their energy mix. However, such forecasting systems are still not in use among the country’s solar operators.
In fact, the nascent industry initially lacked data to even site their plants, as a result of which some of them missed targets by almost 10 per cent. Almost 80 per cent of proposed projects failed to take off due to incorrect Direct Normal Irradiance data. However, the scenario has since changed, with a few commercial organizations providing more stability and accuracy to the industry, according to Ritesh Pothan, a renewable energy consultant and Director, Natural Group.
Forecasting is necessary for power distribution companies to plan their load as well for organizations to meet their debt commitments. “Missing generation by even five to 10 per cent will result in discoms needing to keep polluting plants operating as well as the developer losing profitability and going bankrupt,” Pothan told indiaclimatedialogue.net. “Moreover, it (forecasting) allows bankability for financial institutions without which more than 70 per cent of the plants wouldn’t be possible and generation targets will be missed.”
Most industry players in India say that there should be an emphasis on promoting multiple data sets. Pothan says that that rather than relying only one set of data, an open database using the monitoring stations installed at most plants as well as other locally available resources would help a great deal.
It is in this context that the latest developments in solar forecasting assume their importance. For instance, a team of US scientists launched a new solar forecasting system in September called Sun4Cast, according to the National Center for Atmospheric Research (NCAR). The innovation “offers the potential to save the solar energy industry hundreds of millions of dollars through improved forecasts of the atmosphere,” NCAR said in a statement.
“We have found that the Sun4Cast system can lower the error in solar forecasts by 50%,” Sue Ellen Haupt, director of NCAR’s Weather Systems and Assessment Program who led the research team, told indiaclimatedialogue.net. “One of our utility partners calculated that this error reduction would save them USD 820,000 in 2024 (larger solar deployment expected by then). Our economist calculated that if all utilities in the US deployed Sun4Cast and saw the 50% decrease in error, it could save USD 455 million over a 26-year period as more solar power is deployed in the US.”
This kind of research and development is important because it not only contributes to the reduction in costs for solar and wind energy, but also makes it easier for utilities to integrate renewables into the electrical grid, said William Mahoney, deputy director of NCAR’s Research Applications Laboratory. “When it comes to balancing demand for power with supply, it’s vital to be able to predict sources of energy as accurately as possible.”
Using a combination of advanced computer models, atmospheric observations, and artificial intelligence techniques, Sun4Cast provides zero to 6-hour predictions of solar irradiance and the resulting power production for specific solar facilities at 15-minute intervals. This enables utilities to continuously anticipate the amount of available solar energy. In addition, forecasts extend out to 72 hours, allowing utility officials to make decisions in advance for balancing solar with other sources of energy.
Solar irradiance is notoriously difficult to predict. It is affected not just by the location and types of clouds, but also a myriad of other atmospheric conditions, such as the amount of dust and other particles in the air, relative humidity, and air pollution. Further complicating the forecast, even passing cumulus clouds can reflect sunlight in a way that can increase the amount of energy produced by solar panels.
In order to design a system to forecast solar energy output, NCAR and its partners drew on an array of observing instruments, including satellites, radars and sky imagers, specialized software, mathematical and artificial intelligence techniques. Central to Sun4Cast is a new computer model of the atmosphere that simulates solar irradiance based on meteorological conditions. Called WRF-SolarTM, it is derived from the NCAR-based Weather Research and Forecasting model, which is widely used by meteorological agencies worldwide.
This innovation is a positive step ahead and one that is sure to help countries such as India, which have ambitious plans for the solar sector. Haupt says such a system could also help countries like India to more economically integrate solar energy into their power mix.
Time Series Tool
Vaisala, a global leader in environmental and industrial measurement, also launched an innovative Solar Time Series Tool a few months ago. This enables solar project developers, operators and engineering teams to minimize long-term resource risk and improve energy estimates. The new subscription-based service removes the barriers of cost and time in accessing multiple high quality solar resource datasets.
Solar resources vary significantly from year-to-year and month-to-month, says Gwendalyn Bender, Energy Assessment Product Manager at Vaisala. “Before investing and building a project, it is important to understand these variations so that you have an accurate estimate of how much power your project is likely to produce on an average as well as during extreme highs and lows,” Bender told indiaclimatedialogue.net. “This helps ensure that during periods of low resource, you will still be able to produce enough power to service the debt the project acquired during the financing phase.”
The Solar Time Series Tool provides up to 20 years of hourly, investment grade solar resource data at any location around the globe, Bender said. Having this detailed of information helps create a much more complete and accurate picture of what energy fluctuation will be across years and even hours. It also provides high quality, bankable solar resource data through a cost-effective subscription for more accurate project design decisions and energy calculations. Additionally, it provides solar resource data produced through five different models so developers and engineering firms can compare them to find the best-suited data source for the specific project location.
Since the tool is global, Bender says it should be a big advantage for developers and financiers in India where there is obviously a very strong solar resource as well as strong government support to rapidly grow solar capacity. “In India, it is also particularly important to understand year-to-year variability in solar resources due to the significant impact of the monsoon. Some years the monsoon arrives early or late or is stronger or weaker,” Bender said. “This has a direct impact on solar power production and understanding these historical extremes in advance is very critical.”
However, forecasting is currently more of an afterthought in India and most developers install products to monitor rather than to forecast the generation of solar plants. There also seems to be a lack of effort in trying to create a shared database among producers.
The Ministry of New and Renewable Energy is collating data, but it needs to be more transparent and the industry needs to work together to create this universal database, said Pothan, the energy consultant. “The thinking of everyone for themselves needs to go away for the solar arena to bloom,” Pothan said.