IBM Unveils New Wind and Solar Prediction System

IBM introduced an improved technology for predicting energy consumption and modeling weather scenarios that will help municipal enterprises around the world improve the reliability of their power supply systems using renewable energy sources. The solution combines weather forecasting technology and analytical tools to accurately calculate wind and solar energy. Due to this, municipal enterprises will be able to integrate renewable energy sources into a single power grid, which will allow reducing carbon dioxide emissions, as well as significantly increasing the amount of produced clean energy for consumers and legal entities.



The solution, called the Hybrid Renewable Energy Forecasting (HyRef) Hybrid Renewable Energy Prediction System, uses the capabilities of weather scenarios simulation, advanced cloud-based image processing technology, and a near-real-time cloud monitoring camera. At the same time, sensors installed on wind turbines monitor air temperature, wind speed and direction. In combination with analytics, a data collection and processing solution can provide accurate local weather forecasts for a specific wind farm a month in advance, as well as every 15 minutes.
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In addition, HyRef allows you to predict the performance of a single wind turbine and count the amount of generated renewable energy using local weather forecast data. This level of accessibility of information will provide municipal enterprises with improved management capabilities for ever-changing wind and sun energy, as well as forecasting energy availability for subsequent storage or use in a single power grid. Moreover, such data will help energy companies integrate other sources of traditional fuels, for example, coal and natural gas.

" Municipal enterprises around the world are choosing a strategy to integrate renewable energy into their power grids. The ultimate goal is to generate 25% of global energy from renewable sources by 2025 ," said Dennis McGinn, President and Head of the United States renewable energy (American Council on Renewable Energy, ACORE). —The data coming from HyRef’s weather modeling and forecasting tools will significantly speed up this process and also provide us with the ability to get closer to unlocking the full potential of renewable energy . "

Jibei State Grid Company (State Grid Jibei Electricity Power Company Limited, SG-JBEPC), a subsidiary of the State Grid Corporation of China (State Grid Corporation of China, SGCC), is already using the HyRef solution to integrate renewable energy into a common grid. This initiative was the first stage of the most ambitious project to introduce renewable energy sources. The project, called Zhangbei 670MW, is part of the five-year PRC program to reduce the use of traditional fuels and involves the extraction, transmission and storage of wind and solar energy.

Through the use of IBM's wind forecasting technology, the first phase of the Zhangbei project will accelerate the integration of renewable energy sources by 10%. The amount of additional energy received will help supply electricity to more than 14,000 homes. Moreover, the efficient use of generated energy allows municipal enterprises to intelligently distribute energy capacity, while analytical solutions provide the necessary tools to increase the performance of the power grid.



“ Using analytics and big data technology will allow municipal enterprises to adapt to the intermittent nature of renewable energy sources. They will also be able to predict the amount of solar and wind energy generated using completely new opportunities, ” said Brad Gammons, CEO of IBM Global Energy. and Utilities Industry -. We have created an intelligent system that combines weather forecasting, and energy in order to increase system availability and op imizatsii performance power. "

Hybrid Renewable Energy Forecaster is an advanced weather modeling technology based on other innovative IBM projects, such as Deep Thunder . The IBM-created Deep Thunder solution provides high-resolution local micro-forecasts per square kilometer, covering areas of various sizes, from municipalities to entire states. Combined with data analytics, the solution helps commercial organizations and government agencies to improve service levels, more efficiently manage logistics and plan equipment deployment to reduce the likelihood of adverse weather effects, while also reducing costs, improving customer service, and even saving lives. people.

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