Renewable Energy optimization with Big Data, Machine Learning, and Artificial Intelligence

Energy plays a key role in the economy and environment. Renewable energies are sources of clean, inexhaustible and increasingly competitive energy. They differ from fossil fuels principally in their diversity, abundance and potential for use anywhere on the planet, but above all in that, they produce neither greenhouse gases – which cause climate change – nor polluting emissions. Their costs are also falling and at a sustainable rate, whereas the general cost trend for fossil fuels is in the opposite direction in spite of their present volatility.

The energy industry produces massive amounts of data. To turn this data into insights to improve productivity and cut costs, major energy players are turning to process automation.

Big Data, Machine Learning, and artificial intelligence (AI) are used to interpret the past, optimize the present and predict the future. The energy sector heavily depends on optimization and predictions for energy production, energy grid balancing, and energy demand pattern analysis.

Below are the key benefits can be availed with Big Data, Machine Learning & Artificial Intelligence utilization:

•  Grid & Demand management: Electricity generated by Renewable Energy sources will be delivered to end customers through a complex network or power grid. Power generation and power demand must match at all the time. Otherwise, such issues may lead to failure of the power grid network. To avoid such incidents power grid companies need to have accurate power forecasting from all the generators and demand/supply analysis. 
•  Predictive maintenance: Apart from the assurance on reliability and robustness of the power grid, we need to avoid the break down of machinery, power lines etc. With modern technology each machinery, power lines and generating stations are equipped with a lot of sensors for collecting the data and real-time status. With the help of machine learning, data can be analyzed for predicting future, machinery remaining useful life etc. 
• Spare parts management: It is very difficult to optimize the required spare parts with less amount of inventory to avoid stoppage of machinery due to non-availability of parts. Machine learning and artificial intelligence can handle those issues based on historical data.
•  Predicting weather conditions with historical data : With the advancement of Big Data, Machine learning & Artificial Intelligence historical data can now combine with weather and satellite data to predict the weather conditions. Based on the weather condition energy generation can be estimated, which will help to optimize the utilization of power grid availability and generation. 

Apart from the above listed a few benefits, we can take n-number of benefits to manage the power grids and better utilization of generations. 

#Energy Optimization, #RenewableEnergy, #Datascience,#Machinelearning #Big Data #Artificial Intelligence #Angad Gupta #Wind Energy #Grid Management #ML #AI #Forecasting