Demand for Power Supply Manufacturers Has Added New Ways to Improve Energy Gathering

Power Supply Manufacturers Demand Improved Solar Variability Software

In 2010, researchers at Sandia National Laboratories developed a system to monitor the exact way in which clouds affect large solar power plants. The system was developed to provide valuable data to power companies that utilize solar power in their electrical power systems. There was data collected on cloud shape, size, and movement to provide information to utility companies so they have a way to predict and prepare for power fluctuations caused by changes in the weather. This information is useful and will allow utility companies to make better decisions on where to place potential power plants. It will also allow them to better predict power output from photovoltaic power plants.

The Sandia researchers focused on the La Ola Solar Farm that is located on the Hawaiian island of Lana’i. It is the largest solar power plant in the state and can supply up to 30 percent of Hawaii’s electricity demand. Hawaii has one of the highest solar photovoltaic power penetration rates in the world. Predicting and understanding solar variability in a plant of that size is crucial to maintaining reliable solar output.

Researchers have long known what happens when an entire photovoltaic power plant is under cloud cover, but what had been unknown prior to research is what happens when just part of a solar power plant is under the shadow of a cloud, while the rest of it stays in direct sunlight. This is where the data researchers obtained from La Ola Solar Farm became so valuable.

To get this data, the Sandia engineers connected 24 small sensors to the plant’s photovoltaic panels and used radio signals to send the data. Every second, the sensors took readings and provided the researchers with detail about cloud direction and activity that had never before been available. The environment of Lana’i was perfect because of the high concentration of photovoltaic power, and also because the large 10-acre plant often had times when it was partially covered with cloud shadow, and partially in direct sunlight. The work that was done at the La Ola plant led to new methods that will answer questions about plant output and variability at a possible future photovoltaic power plant site.

The Study of Solar Variability Continues to Develop in 2012

In 2012, researchers at University of California in San Diego discovered ways in which to improve software that can do the calculations to determine the fluctuation in the solar grid that is caused by changes in cloud cover. The UC San Diego engineers just released a newer and more accurate version of the software program that gives grid managers and photovoltaic power plant developers the ability to predict the fluctuations in solar output.

The basis of the software program is the Solar Variability Law which was discovered by Matthew Lave, a current student in the Department of Mechanical and Aerospace Engineering who is seeking his Ph.D.. Matthew Lave conducted his research in the lab of Jan Kleissl, a professor at UC San Diego in the Jacobs School of Engineering. Lave used data collected from the California power grid to come up with the Solar Variability Law. Basically, Mathew Lave discovered that there is a direct correlation between the amount of radiation and the amount of power produced by the solar panels. This was determined by measuring the distance between weather stations and dividing that distance by the time frame for change in the power output. This is the basis for the Solar Variability Law.

The advantages of the new version of the solar variability software are numerous. For one thing, the new version of the software utilizes all of the newest research and information discovered by Matthew Lave. Also, the new software version only needs data from a singular sensor on the ground. There is no longer a need for a network of sensors. This cuts down on inaccurate data due to sensor failure. The ability to use only one sensor was made possible by using cloud speed data provided by the National Oceanic and Atmospheric Administration model.

The new improvements make the software more useful to photovoltaic power plant developers and power supply manufacturers who are not likely to have access to a network of sensors, but can probably get access to one ground sensor. Due to these improvements, the new software developed by UC San Diego is in high demand. Many solar power plant developers and power supply manufacturers can use the software to create more efficient and predictable power output.

At the moment, the largest demand for the new software is from developers working to meet new solar requirements set by the Power and Electric Power Authority in Puerto Rico. The Puerto Rican agency wants any new power plant operator to limit changes in power output to 10 percent per minute. Since it is common for photovoltaic power plants to have their power output fluctuate by more than 70 percent per second, it will be quite a task to get the change in power output under 10 percent per minute.

Jan Kleissl’s team has begun to work with the University of Puerto Rico professor, Eric Harmsen, to help them discover ways in which to comply with the new requirements. Together they set up a pyranometer – a sensor used to collect solar data. To estimate what the conditions are like in Puerto Rico, the group from UC San Diego has been using information that was gathered from Oahu.

UC San Diego is now offering to run their new model for free to developers. To receive the free modeling, the developers must provide data on plant layout and solar radiation to the UC San Diego Team. They are currently working on obtaining the required licensing agreements to move the software to the commercial sector.

Every year solar power continues to develop and make up a larger percentage of nationwide power grids. As this growth continues it is going to become increasingly critical that photovoltaic power plant operators are able to forecast power production. The ongoing research and development at UC San Diego is making solar power a more reliable and appealing option around the world.