Why Wind Farms need Analytics?

Now, that you have a big wind farm, which is connected to the grid and is adding a few MWH at the end of every day to it. However, one of the challenges that the wind power company’s face is that it is not consistent; but intermittent. To generate power consistently, the power company needs to depend on a few external factors like analytics.

Wind farms across the world are productive as long as there is wind to rotate the turbine. By default, the SCADA system that is supplied along with the wind turbine helps to get more information about the functioning of the turbine, wind blade angle, etc., but does not provide information about under which weather conditions the wind is working. 

Along with knowing about the functioning of the equipment, if the company could also get information about weather and wind predictions, turbine and overall wind farm performance, and predictive maintenance data simultaneously, then it gets the big picture of what is happening, what factors are critical to maintain the consistency of the wind power generation, which wind turbines are beating the benchmark, which wind turbines are not functioning and need maintenance, etc.

Countries, where wind power is not that much great, companies make sure that they are one-step ahead in knowing about the wind movements so that they can align all their turbines in that direction beforehand to make advantage out of the wind flow. 

From power grid point of view, all the captive power generating units should make commitment to their respective grids regarding how much power they add to the grid at the end of the day or by a particular period. Now, if the wind is not consistent and the company could not generate enough power, then they are bound to pay penalties to the grid. In this case, analytics help companies to calculate correctly how much they could commit based on the real-time and historical sensor data that they gathered, so far.

Analytics data not only provides power generation [ex: based on weather and wind movements] inputs, but also avails asset maintenance [ex: turbine fitness] data.  In the current scenario, where renewable energy like wind is favored by all the public, governments, and corporates at all levels and purposes, analytics play a bigger role in achieving the benchmarks set by the wind power generation industry.

Indian Judges Beat Sentiment Analytics! Hands Down!

The new trend in Indian court judgments involving ‘high profile’ personalities is baffling! These cases have been running since so many years and not only the case stakeholders but also the ‘aam aadmi’ [common man] knows what the issue behind these cases was. In other words, it is a public secret and everyone knows who did what, who committed the crime, and finally, what happened!

There is a saying since olden days that the ‘law of the land’ is nothing but what ‘citizens of the land feel right’! Earlier days, kings used to follow the same rule; public perception matters a lot! One can read this kind of instances in our holy scriptures. For example, Lord Sri Rama vs. Sita [his wife!] episode in Ramayana! However, nowadays, public perception has become a gimmick! 

Nowadays, Indian judges are giving mind boggling, earth shattering, and jaw dropping judgments that are creating ‘helpless’ tsunamis in the hearts of a common man. These judgments are taking the ‘belief’ wind out of his ‘life’ sail!  When the whole gamut of a country is thinking and expecting that a case’s judgment would be in a particular way [punishment for the alleged criminal!], the final judgment was delivered in a different way [criminal acquitted!].  

However, this blog is not about finding the nuances of the above said judgment but about what would have happened if someone uses ‘sentiment analytics’ engine to find out the pulse of the people regarding the ‘so called’ alleged criminals and their committed crimes [before the final judgment!] to guess how many years of punishment would have been awarded to them by the ‘so called’ case processing judge! 

As you know, any sentiment analytics engine plugs in to so many social feeds to gather and analyze so many discussions, statements, etc., to understand and derive a score [positive/negative] about a particular search keyword.  

Now, sentiment analytics helps us to perceive the public perception; what they have been thinking and discussing about a particular event or cause? In this case, what sort of results does the common man get? Are they in sync with what has been happening as per the recent judgments? If not, then there is a problem with the sentiment analytics functioning [but not the judge’s judgment!]; something is missing somewhere which the engine builders have not factored in!  

This blog begs the answer for following question: Can’t we predict the exact judgment polarity before the judgment using sentiment analytics in Indian law context?

Oil Frackers become Power Crackers!

Oil fracking companies across the world are known for polluting the environment. Whole world tagged them as polluters so far. However, it seems now that polluters tag has to be removed from them. They have added one more last step to their chain of activities to make more money by using the scalding-hot water, which is a byproduct of fracking business, to generate geo-thermal power. 

Yes! What you read is true and in fact happening! Frackers are not polluters now; instead, they are become helpers of the world by generating the most wanted resource, power. As you know, to produce one-barrel of oil, they need seven times more water. On an average, they use lot of water annually than they produce oil. Now, they brainstormed and have come up with a new thought about using this planet’s most precious commodity, water, in a profitable way.

Once the hot byproduct gets pumped out, they are diverting it to in to off-the-shelf geo-thermal power stations, which then convert that heat in to power. Once the power generates, they are free to use either for their own purpose or push it to the grid to get a few more dollars. 

And you know what, once the water comes out of the geo-thermal station, they are again pumping it back in to the ground to continue with the next cycle of fracking!

Way to go Frackers! You rock!

Asset Management – Oil & Gas Industry

Being known for capital- & asset-intensive assets, lengthening the lifespan of an asset is one of the prime goals of oil & gas industry.  However, the irony of the situation is that as per OEE [Overall Equipment Effectiveness] index, oil and gas industry lags behind others when it comes to maintaining assets effectively. 

Now, across the globe, oil & gas industries are employing predictive analytics to overcome the challenges of critical asset equipment performance, life cycle, integrity, security, and utilization.  Based on the insights provided by predictive analytics, companies are not only predicting the equipment failure in advance but also are overcoming the challenges of diminishing and limited personnel expertise in maintaining assets effectively. Besides, they also attained the capability to intelligently operate multiple assets from a centralized location, which helps them maintain their assets in a cost-effective manner.

Lately, companies started employing predictive analytics at 3 different levels when it comes to maintaining assets. 

• At the production unit level, they are deploying analytics to understand how equipment is performing. Automated analytics could be used to improve uptime, efficiency, and throughput.
• At the facilities level, they are deploying analytics to understand about procurement, production scheduling, and shipping goods.
• At the enterprise level, they are deploying analytics to understand the larger business context. For example, to understand the impact of fluctuating costs, changing market conditions, asset performance, etc.

As you already know, Predictive Modeling draws from statistics and optimization techniques to extract accurate information from large volumes of data. From preventive maintenance to alert management, predictive analytics helps to do asset management system aimed at minimizing production costs and extending the life of assets.

Following are the advantages of using predictive analytics to maintain assets in oil & gas industry:

• Increases asset availability
• Reduces resource non-productive time
• Helps to resolve defect rates, speedily
• Reduces spares inventory holding costs
• Reduces maintenance costs

In summary, by helping to manage, measure and track the life cycle of every capital-intensive asset in oil & gas industry, predictive analytics is helping companies to resolve asset management issues by sharing automated and collaborative data across the extended enterprise.