Asian solar stocks on Thursday echoed a rally by their U.S. peers, with some surging as much as 20 percent on signs that prices for solar energy components are stabilizing.

Most solar stocks retreated by more than 60 percent last year as prices for panels that convert sunlight into electricity fell sharply, erasing profit margins for manufacturers.

The global rally came as investors cheered figures showing a dramatic rise in new solar installations in Germany in the fourth quarter and higher prices for polysilicon, a key raw material.

For more information please visit CNBC’s website at http://www.cnbc.com/id/45967909 to read the article and see stock quotes on specific solar energy companies.

This hands-on book explains the myths and solves the mysteries about energy and moisture in the home. How to build airtight shells and detect hidden air leaks. The pros and cons of popular insulation materials. The uses (and misuses) of air and vapor barriers. Details for high-R wall systems.

Plus:

Here is an interesting report from The New York Times. Follow the link to read the whole story.  Halfway between Los Angeles and San Francisco, on a former cattle ranch and gypsum mine, NRG Energy is building an engineering marvel: a compound of nearly a million solar panels that will produce enough electricity to power about 100,000 homes.

The project is also a marvel in another, less obvious way: Taxpayers and ratepayers are providing subsidies worth almost as much as the entire $1.6 billion cost of the project. Similar subsidy packages have been given to 15 other solar- and wind-power electric plants since 2009.

The government support — which includes loan guarantees, cash grants and contracts that require electric customers to pay higher rates — largely eliminated the risk to the private investors and almost guaranteed them large profits for years to come. The beneficiaries include financial firms like Goldman Sachs and Morgan Stanley, conglomerates like General Electric, utilities like Exelon and NRG — even Google.

A great deal of attention has been focused on Solyndra, a start-up that received $528 million in federal loans to develop cutting-edge solar technology before it went bankrupt, but nearly 90 percent of the $16 billion in clean-energy loans guaranteed by the federal government since 2009 went to subsidize these lower-risk power plants, which in many cases were backed by big companies with vast resources.

When the Obama administration and Congress expanded the clean-energy incentives in 2009, a gold-rush mentality took over.

As NRG’s chief executive, David W. Crane, put it to Wall Street analysts early this year, the government’s largess was a once-in-a-generation opportunity, and “we intend to do as much of this business as we can get our hands on.” NRG, along with partners, ultimately secured $5.2 billion in federal loan guarantees plus hundreds of millions in other subsidies for four large solar projects.

“I have never seen anything that I have had to do in my 20 years in the power industry that involved less risk than these projects,” he said in a recent interview. “It is just filling the desert with panels.”

From 2007 to 2010, federal subsidies jumped to $14.7 billion from $5.1 billion, according to a recent study.

Most of the surge came from the economic stimulus bill, which was passed in 2009 and financed an Energy Department loan guarantee program and a separate Treasury Department grant program that were promoted as important in creating green jobs.

States like California sweetened the pot by offering their own tax breaks and by approving long-term power-purchase contracts that, while promoting clean energy, will also require ratepayers to pay billions of dollars more for electricity for as long as two decades. The federal loan guarantee program expired on Sept. 30. The Treasury grant program is scheduled to expire at the end of December, although the energy industry is lobbying Congress to extend it. But other subsidies will remain.

The windfall for the industry over the last three years raises questions of whether the Obama administration and state governments went too far in their support of solar and wind power projects, some of which would have been built anyway, according to the companies involved.

Obama administration officials argue that the incentives, which began on a large scale late in the Bush administration but were expanded by the stimulus legislation, make economic and environmental sense. Beyond the short-term increase in construction hiring, they say, the cleaner air and lower carbon emissions will benefit the country for decades.

“Subsidies and government support have been part of many key industries in U.S. history — railroads, oil, gas and coal, aviation,” said Damien LaVera, an Energy Department spokesman.

Nov 11, 2011 – Forecasting software from Siemens is being used to predict how much electricity wind farms will generate. These predictions are important for the effort to compensate for fluctuations in available wind energy in the power supply system because of changes in the weather. Based on weather forecasts for the next 72 hours, the software calculates as precisely as possible the expected amount of electricity from wind power for that period. On average, the predictions for the daily output of a wind farm turn out to be more than 90 percent accurate. The software was successfully tested in one offshore and two onshore wind farms and is currently being used in Denmark.
The more wind or solar energy contributes to the power supply, the bigger the challenges become for those who operate electrical grids. If the weather is calm or the sky is overcast, gas-fired power plants have to be brought on line at short notice. If the wind picks up or the sun comes out, there is suddenly too much electricity in the grid. To regulate the supply of electricity and keep the grid stable, the operators need good forecasts of the amount of power that wind or solar farms will contribute. With these forecasts, it also becomes possible to sell excess amounts of energy on the electricity market. In addition, they can be used to schedule maintenance work during periods in which lower yields are expected. 
The forecasting method used by Siemens is based on a neural network. A neural network is a software algorithm that operates in a way similar to the human brain. The global Siemens research department Corporate Technology (CT) develops neural networks in order to calculate the behavior of highly complex systems — these might include wind farms, gas turbines, or even stock markets. The CT researchers have created a neural network that uses the forecast temperature, wind speed, and air humidity at the site of the wind farm to calculate the amount of power the wind farm will generate. Based on historical data, the software learns to make the most accurate predictions possible. At first it doesn’t know how strongly the various factors impact the output of the wind farm, and its predictions are random guesses. But it aims to minimize the discrepancies between the predictions and the actual values by changing the weightings of individual parameters, which allows it to become increasingly accurate over the course of thousands of iterations. At present, the average error rate of the prediction is no more than seven percent. Siemens is currently developing similar systems for photovoltaic plants. (IN 2011.11.2)