Solar energy is an important source of renewable energy and its market has been exploding in recent years. The global solar energy market was valued at $52.5 billion last year and is projected to reach $223.3 billion by 2026. Part of the reason for this explosive growth is the possibilities machine learning techniques are unlocking in the industry. Machine learning technology uses mathematical algorithms to help to make predictions about the future, which companies can then use to create better strategies. By transforming their business strategy from the traditional approach to new data-driven competencies, solar energy companies have the potential to improve their bottom line immensely.
1. Improve the accuracy of solar forecasting
Accurately forecasting the weather is crucial to the operation of solar farms. Just last year, the Department of Energy pledged $12 million to projects aiming to advance solar forecasting technology. One of these projects- IBM’s Watt Sun- successfully used machine learning technology to improve the accuracy of solar forecasting by 30%.
2. Predictive Maintenance
The goal of predictive maintenance in solar energy is to predict when and where equipment is likely to fail, so that the maintenance team can fix it before a blackout occurs. Blackouts are costly, and millions of dollars can be saved if potential failures are predicted with greater accuracy. These savings come in two forms: minimization of downtime and optimization of the periodic maintenance operations.
3. Optimize energy management
Through the machine learning method, we can effectively model and plan the habits of users (like the distribution of the users, hours when electricity demand is the highest, etc.) to create customized pricing strategies. At the same time, we can use the predictions to adjust the energy supply and thereby improve efficiency.
Cresco International helps clients in the solar energy industry to accelerate their digital transformation with the most advanced technology.
IBM Watson Studio
Watson Studio provides you with the environment and tools to solve your business problems by collaboratively working with data. You can choose the tools you need to analyze and visualize data, to cleanse and shape data, to ingest streaming data, or to create and train machine learning models.
IBM and The Weather Company
The Weather Company, an IBM Business, delivers personalized, actionable insights to consumers and businesses across the globe by combining the world’s most accurate weather data with industry-leading AI, Internet of Things (IoT) and analytics technologies.
The solution provides newscasters, pilots, energy traders, insurance agents, state employees, retail managers and more with insight into weather’s impact on their businesses, helping them make smarter decisions to improve safety, reduce costs and drive revenue.
In Conclusion Generally speaking, Watson Studio provides the platform for data scientists and machine learning engineers to collaborate and build the analytics project. The Weather Company provides qualified data and prediction based on IBM Global High-Resolution Atmospheric Forecasting System (IBM GRAF). Contact us today at 1-866-4-CRESCO or info@crescointl.com to learn more
