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Renewable energy -- the data is blowing in the wind

Better weather and power forecasting has many benefits. Among the most financially significant is improving the economics of renewable from wind and solar energy as well as fostering integration with conventional sources such as hydro and fossil. 

If utilities can forecast, hour by hour, or better yet minute by minute, how much wind is blowing through a wind farm, or what the cloud cover will be at a solar plant, they can manage the supply and grid much more efficiently. 

By knowing that the exact behavior of wind, they can reduce the need for natural gas-fired backup gas turbines and minimize costly ramp up and down events.

Boosting renewables is one of the most economic ways to reduce carbon emissions, increase energy output and thereby improve standards of living. 

Although building wind and solar facilities is a significant investment, the fuel is free, unlike fossil fuel generation which costs money for every kilowatt generated. 

However, to get the full benefit, it requires making the system of renewables and their back up generating capacity as efficient as possible in order to be more economically competitive with coal and natural-gas fired generating plants.

It’s no easy task when a natural gas glut has caused energy prices to plunge.

Technology will be the key factor to improving renewable system efficiency – in particular energy output forecasting. With the right conditions for investment renewable energy can be generated at enormous scale.

For example, some days, Germany gets up to 50 percent of its electricity generation from renewables. However, at the same time, many countries are planning to reduce the taxpayer-funded subsidies that helps renewable energy to be competitive with traditional energy sources.

The International Energy Agency (IEA) forecasts that renewables can surpass gas by 2016 in the global power mix, in part because of subsidies from governments, but the industry must not be complacent lest it wants to face a decline, the report has warned. 

After a long legislative back and forth, Congress gave the production tax credit a one year reprieve in January, and its expiration deadline has once again started to loom and cast a shadow on the U.S. renewable industry. 

Meanwhile in Europe, after the election in September, Germany—one of the top wind energy producing countries—may become the latest European country to curb financial support for renewable energy investments.

Public sector funding encourages additional capital investment, which has helped the industry grow, but the unwanted uncertainty has been a nagging hurdle for the renewable energy industry.

However, the results so far are impressive. 

In the U.S., wind power topped the list of new generation sources that came on line. Last year, some 13.1 gigawatts (GW) were installed, comprising 42 percent of all new capacity, while around the world the trend is echoed, with global capacity growing by a record amount, too—44.7 GW—increasing the total installed base by 19 percent to 282.4 GW.

In most jurisdictions, utilities are required to purchase and resell any renewable energy that producers generate, but they face the challenge of integrating it into their supply portfolio and transmission system. 

The roadblock for the grid operator is that they must pay the renewable producer for every watt-hour delivered. But, they must also pay a gas-turbine owner to keep some generators in standby mode in case the wind fails to blow consistently. 

If the grid operator knows the exact supply coming from wind and the demand from the consumers, it can tell the stand-by turbine operator to idle down for a period of time.

Widely deployed sensors and sophisticated analytics are opening the way to much more accurate weather and energy forecasting. 

For example, a new big data analytics system called the Hybrid Renewable Energy Forecasting solution(HyRef) is designed to help the energy industry monitor and predict wind and solar output and use renewable energy to maximum benefit. 

Advanced techniques can produce accurate forecasts covering a single square kilometer and across different lead times (from 15 min to 72 hours). This technology will provide utilities with a clearer view of just what kind of power production they can get from wind and solar facilities. This, in turn, will allow energy companies to manage the grid to minimize of the expense of backup gas turbines.

In China, where capital investment from the public sector is not in question, State Grid Jibei Electricity Power Company is planning on using HyRef, to integrate renewable energy into the grid. Making analytics the cornerstone of Zhangbei, a 670 MW demonstration project, which is the world’s largest renewable energy initiative combining wind and solar power, energy storage and transmission. 

The weather and energy output forecasting accuracy and precise grid management is projected to increase renewable power from the project by 10 percent-- enough to power 14,000 homes.

The renewable industry can’t win by over-relying on subsidies to make itself viable in the long term. The industry focus should be on relentless innovation. And no longer is innovation just about the scale of wind turbines or length of their blades, nor is it just about solar cell efficiency. It is about big data analytics, like weather modeling and energy output forecasting.

By addressing the challenges of long-term integration costs into the system for large scale generation and reducing the need for subsidized capital investment, renewables can once and for all stake their claim in the broader mix of power generation around the world. 

Ultimately, that is good for the planet as much as it is to the consumer.

Stephen J. Callahan is a Partner within the Energy & Utilities industry of IBM Global Business Services. Over his 30 year career in industry and consulting he has led the development and implementation of a wide range of business and technical systems including utility operational, financial, networking, RTO, AMI and Smart Grid systems.