Post by simranratry20244 on Feb 12, 2024 3:24:17 GMT -6
How do we make renewable energy a reliable, less variable and intermittent resource? Renewable energy depends on meteorological phenomena, such as wind or sunlight, which we cannot change, but which we can know and predict with the help of Big Data analysis and Artificial Intelligence . Technology has already greatly facilitated the development of renewable energy, but there is still room for improvement in terms of precision, optimization, efficiency and innovation. For Pedro Tejedor, director of the Energy and Environment area of the IIC, “the development of renewable energies reaches its maximum potential thanks to the application of new technologies to its operation.” Specifically, today predictive analytics can be used in all phases of the life cycle of renewable plants: their installation, energy generation and distribution, and network maintenance.
In this post, we review how technology and Artificial Intelligence can help, from many points of view, in the optimal use of renewable sources . Predictive analytics in renewable energy generation Prediction of renewable energy Colombia Telemarketing Data generation depends largely on good analysis of meteorological data . Already in its design, to choose the place where a new plant is going to be installed, whether wind or solar, the historical meteorological data in the candidate locations are one of the determining factors for its selection. Energy and AI In many cases, this first analysis requires terabytes of information to process , to estimate how much that plant would have produced in each of the possible locations and thus be able to choose the most profitable one. Later, with the parks already installed and operating, it is necessary to know in advance how much energy is going to be produced.
This allows us to go to the offer in the electricity markets, which are increasingly demanding in terms of precision, with the best of energy predictions,” explains Pedro Tejedor. In this case, weather forecasts adapted to the evolution of the park are used. Most of these parks choose to outsource this predictive activity to companies that are experts in technology and data analysis , such as the Institute of Knowledge Engineering (IIC). The IIC has its own renewable energy production prediction system (EA3) for parks of all sizes and technologies. This allows forecasts to be prepared with different time horizons and with the update frequency needed to bid on the markets. Smart electrical energy networks Renewable energies also pose a challenge for the electrical energy transportation and distribution network . Being able to pour energy into practically any point of the network, it is necessary to know in advance what that production will be, to prevent local saturations that could lead to blackouts. Distribution companies also need high precision for their operation here.