The Big Data and the Renewable Energy

  1. Some motivation/background why it fits to the topic of Big Data.

Since the fossil fuels are not the limitless resource and cause a lot environmental problems such as global warming and air pollution, it is important to develop the renewable energy technologies that do not affect the environment. There are many renewable energy technologies such as solar, wind, and tidal energy and many companies try to develop this technology. The Vestas is one of these companies that has business on wind power. The wind power is clean and one of major renewable energy technologies. However it has also the disadvantages; the wind power facilities take too many spaces, it also causes the noise pollution while the turbine rotates and the wind power is useless when the place has high wind which is often occurred in Mexico. Therefore, this company tries to find the most efficient place to construct the wind power facilities so that the disadvantage is minimized. The tool to solve this problem is big data processing and the supercomputer. They collect the huge amount of data on the climate and weather of the particular location so that they can find the most ideal place for the wind power. This is important because the efficient power generation is possible as well as decreasing the effect of the disadvantages of the wind power. This is one of the examples of using big data to solve the environmental problems as well as the problem occurred by the limited fossil fuel.

  1. Short summary description of the business/service

(1) Business with Big Data

Not only construct the wind turbine for the wind power, Vestas uses ClearSight.™ to offer the data on the service about the renewable energy that is suit to the people. The huge amount of data is collected so that the ideal situation for the different cases can be applicable. For this purposes, the Vestas uses supercomputer to store this vast amount of data as well as to process this data. The computer is connected with 50+miilion sensors and these will enable the Vestas to collect the data from turbine and to simulate on the ideal situation. Also the Vestas uses SmartData which transformed the data into more efficient and applicable data for the best location of construction of the wind power. The wind turbine is one of the core items for the wind power so from the data from the SmartData can be used to find the suitable turbine for the specific location. Using the data will reduce the cost and make the better business.

(2) Other Services

Only installation of the wind power plant isn’t the job of Vestas. The real job starts once the Wind plant is installed and in operation. The philosophy of the company isn’t just about engineering and logistics but to create the solutions for the problems that may arise later. It provides service based on AOM( Active Output Management). Due to harsh weather, breakage, etc , different parts of wind plant may get damaged. It provides maintenance service mainly in three approach i.e. Blade care, Generator care and Gear box care. Big data resources can be used by these companies to forecast and find the predictability of speed and direction of wind, so to run the power plant accordingly.

 

  1. First Obvious Opportunities/threads

(1) Opportunities

Vestas, being the energy industry’s global partner on wind power solutions, has been designing, manufacturing, installing and servicing wind turbines across the globe, with more than 76GW of wind turbines in 75 countries. Using smart big data sources, the company has been able to interpret, forecast and exploit wind resources and deliver best class wind power solutions. In this modern era, where the demand of energy is increasing more than ever, the opportunities and field of Vestas are also increasing. Recently, Vestas has received 40 MW energy production order from Brazil. Vestas received order from long term global partner of Brazil i.e. Gestamp Eolica Brazil to install 20 MW turbines at the wind parks located in Rio Grande do Norte, Brazil. This contract and strong partnership with Gestamp Wind has made Vestas stronger and increased the opportunities for Vestas to expand its market. Similarly, it has received an order to generate 100 MW(Watt) from China. Also, it has received order from Mongolia for the first time.

(2) Threats

Vestas has the potential to encounter distinct threats, which must be accounted for in order to maintain their strong market share. A pronounced threat to Vestas business is the potential for oil prices to fluctuate. In the case that oil prices decrease, Vestas, along with the renewable energy sector, would likely experience negative effects. The volatility of stock markets is also a viable threat to Vestas. An economic depression in a major market such as the United States of America or China could lead to a direct decrease in business dealings within the country and has the potential for a global recession. Government policies regarding subsidies of renewable energy and the regulation of renewable energy are feasible threats to Vestas as well. Subsidies provide incentive to invest in a nation’s renewable energy projects. A reduction in these allocations would likely reduce new investment prospects and would negatively affect the renewable energy industry within the nation negatively. The implementation of new government regulations on renewable energy could affect Vestas because they have the potential to fundamentally change the prospect of further investment in the sector within a nation.

  1. Bibliography

(1) https://www.vestas.com/#

(2) https://www.navigantresearch.com/blog/august-presents-prospects-and-threats-for-renewable-energy

(3) http://www.utilitydive.com/news/utilities-what-are-renewables-strengths-weaknesses-opportunities-and-4. th/261478/

(4) http://www.awea.org/Advocacy/Content.aspx?ItemNumber=797

(5) http://smartdata.vestas.com/Vestas%20Smart%20Data%20And%20Consultancy%20Services

  1. Group Memebr

Lee Ilseok, Manish Baral, David Duvall, Franklin Shiyi Gao

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One thought on “The Big Data and the Renewable Energy

  1. Not only can big data help to determine the perfect location for wind turbines (and other sources of renewable energy, like solar panels), but also to construct a forecasting system that will be able to predict the amount of energy that will be collected, and then decide whether it is to be stored or redirected into a power grid.

    This innovation will contribute to tackle one of the main problems of renewable energy: its intermittent and unpredictable character.

    Refer to the following articles about IBM and their new Hybrid Renewable Energy Forecasting (HyRef) solution for more information on this new method:
    http://www.ibmbigdatahub.com/infographic/big-data-analytics-adds-power-renewable-energy
    http://www.eweek.com/database/ibm-big-data-analytics-powers-renewable-energy-forecasting-system

    Like

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