The ecological awareness is on the rise, and so is the revenue stemming from renewable power sources. According to Allied Market Research, the global renewable energy market was valued at $928.0 Billion in 2017, and is expected to reach $1,512.3 Billion by 2025, registering a compound annual growth rate of 6.1% from 2018 to 2025.
Like any business, the renewable energy business needs efficiency software to fully utilize the power of data in order to boost production efficiency. The best solution for the task is the Artificial Intelligence subgroup - Machine Learning, because:
a) Machine learning predicts future power production, and
b) it gives better predictions as time goes by (more time = more data = improved prediction), also
c) it improves production efficiency (improved prediction = better process optimization = improved efficiency).
The AI machine learning algorithm applied in Solar energy production uses these sets of input data:
1) The weather report and weather history of a region (along with sun intensity, angle, etc.) that creates improved weather forecasting.
2) Historic data of the Solar Power Plant (along with its characteristics).
The input data goes through a so-called Training process of the machine learning algorithms within asw:maximus which provides the output data, in this case - the prediction of power in either a single solar power plant or a variety of them.
The asw:maximus machine learning uses data it has on solar energy plants, the predictions of their production and comes up with a final prediction. This final prediction is the best power-producing location according to its potential for solar power production. The great thing about asw:maximus is that it can offer numeric predictions so you can choose your power plant precisely according to your plans about budget, needed power amount, or any other plan upon your request.
Alongside giving predictions for potential power plants and their locations, asw:maximus keeps an eye on the existing power plants as well. By monitoring the electricity usage of every individual user, it gives predictions of the exact amount of energy needed for a particular day, thus taking care of your current as well as future business simultaneously.
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