Germany has an interesting history of controversy surrounding energy sources. For Germans, Wyhl, Waldsterben, and Chernobyl, call to mind past controversy about energy supply (especially nuclear) and the option of renewability. Along with the first and second oil crises the nation faced, these incidents gave Germany the push it needed to begin to seriously look into renewable energy resources. Since, Germany has been making growing efforts towards finding and implementing more sustainable forms of energy focusing largely on electricity.
In 1974 the German federal government launched a plan to research alternate sources of energy. This begun with the failed GROWIAN project through which a single, 3MW wind turbine was attempted to be built. As I stated before this was a failed effort that lead the government to develop the turbine on a smaller scale, a decision which produced successful results. Some of the most recent turbines are over 1500kW and that number is growing.
In 1991 the government introduced a 250MW incentive for generators of wind energy. Accoring to Wüstenhagen and Bilharz, generators were required to take part in a new program which was to create a new database on how wind turbines in Germany were to operate called the Scientific Measurement and Evaluation Programme (WMEP). Subsidies, loans, and tax incentives also became available for investment support.
But what is at the root of Germany green energy policy is the Erneuerbare-Energien-Gesetz (EEG) or, for English speakers, the renewable energy law of 2000 and amended law of 2004. The act had three main functions or principles:
1. Each generated kW/H from renewable energy gets a feed-in tariff. A guaranteed 20 yr payment is given to renewable plant operators. Anyone producing renewable energy can sell it for a 20 yr fixed price
2. German consumers who use renewable energy pay for it through their electricity bill; Germany’s “public purse” is not charged
3. Rates of payment for the new plants decrease periodically; over time technology will be more efficient and less costly
As a result of all of Germany’s effort to development more renewable energy, there have been over 13,000 MW of new wind capacity between the years 1991 and 2003. Because of its overall success in this, Germany can serve as a model to nations who resist making the change.
UPDATE:
Germany’s phase-out of nuclear energy has proven to be too effective and German consumers taking the biggest hits. Germany currently has the second highest power prices in Europe.
The cost of electricity has shot up and now the average German pays what is $181 a year and that number is set to increase 38% by 2013.
However, Germany remains a leader in renewable energy research and implementation. The country continues to make strides, and despite setbacks and current obstacles is reaping the benefits of its renewable energy policy.
For a more in-depth look into Germany’s green energy policy and the strides and losses made, please refer to the following sources which were used to obtain the information presented in this blog post:
Wüstenhagen, Rolf, and Michael Bilharz. “Green Energy Market Development In Germany: Effective Public Policy And Emerging Customer Demand.” Energy Policy 34.13 (2006): 1681-1696. GreenFILE. Web. 30 Sept. 2012.
And good ole WikiPedia
http://en.wikipedia.org/wiki/Renewable_energy_in_Germany
http://en.wikipedia.org/wiki/German_Renewable_Energy_Act
UPDATE information from:
Schultz , S. (2012, August 29). Power failures: Germany rethinks path to green future. Spiegel Online International. Retrieved from http://www.spiegel.de/international/germany/problems-prompt-germany-to-rethink-energy-revolution-a-852815.html
nixandra
September 30, 2012
After watching each installment of Michael Bay’s box office hit, I found the true origins of America’s favorite robots. No the Transformers aren’t from Cybertron but from the bottom of a box of Legos and constructed by students like me and my classmates. Well not really, but the drama of that is so much more exciting.
Anyhow, this is the first of our activities and in it we set out to study the motion of our newly constructed robots as well as the measurements of distance and power. We calculated our results using a few key formulas. The set of formulas we used formed a Jenga tower. Each piece supported another and if you miscalculated one thing the whole came crashing down and you had to start all over.
First we started with measuring diameter of the robot’s tires in order to calculate circumference. We measured using a standard and converted from inches to centimeters to meters.
Here’s the conversion equations:
cm = in • 2.54
m = cm/100
The diameter of the tires equaled 0.0508 m. From this we calculated circumference using this equation: circumference = π • diameter or C = πd. From this we calculated that C=0.1596. This is the number we input into the computer program for Lego Mindstorm.
We powered on our robots to begin and the math still wasn’t over. With the circumference we needed to figure out number the of wheel turns. For this we had another equation:
Number of Wheel Turns = (rotation°) / (360°/1 Turn)
Then both wheel turns and circumference were used to calculate the distance our robot travelled:
Distance (meters) = Number of Wheel Turns • Circumference
Distance was entered into yet another equation to find velocity:
Velocity = Distance (meters) / Time (seconds)
It all seems very mathematical, and it is, but most of the information could be inputted into the program and was automatically calculated; we recorded the given information.
To begin the actual experiment, we cleared a pathway for the robot to travel without any obstructions (like its power cord which kept getting in the way) and adjusted the power so that the distance would not exceed the measurement of our ruler, 12 inches or 30.48 centimeters or 0.3048 meters.
We conducted a trial of one power level (75) and three sets of testing for increased accuracy. We found that our measurements of distance we never the same and always greater than those measured by the computer. This could be due to eyeballing exact distances when they fell between the marked lines of the ruler. I’ll list our measurements or distance (D) and velocity*(V) compared to those of the computer in addition to number of wheel turns (WT).
*Because in our tests we set time (seconds) = 1, velocity and distance are equivalent in number
Test 1
Students Computer
D = 0.27305 D = 0.227873
V = 0.27305 V = 0.227873
WT = 1.42778
Test 2
Students Computer
D = 0.2795 D = 0.24605
V = 0.2795 V = 0.24605
WT = 1.54167
Test 3
Students Computer
D = 0.27432 D = 0.246493
V = 0.27432 V = 0.246493
WT = 1.54444
At the end of our trial set we were to calculate our margin of error in order to measure how applicable our results would be on the grand scale. A high margin of error means results are less accurate/applicable and a low margin of error means results are more accurate/applicable. To measure this we used this equation:
% Error = ( (Distance measured – Distance calculated by computer) / ((Distance measured + Distance calculated by computer) / (2) ) •100%
The margin of error for each test is detailed below.
Test 1
% Error = ( (0.27305 – 0.227873) / ( (0.27305 + 0.227873) / 2) ) •100%
% Error = ( (0.045177) / ( (0.0500923 / 2) ) • 100%
% Error = ( (0.045177) / (0.2504615) ) • 100%
% Error = 0.18037503 • 100% = 18.04%
Test 2
% Error = ( (0.2795 – 0.24605) / ( (0.2795 + 0.24605) / 2) ) • 100%
% Error = ( (0.03345) / ( (0.52555 / 2) ) • 100%
% Error = ( (0.03345) / (0.262775) ) •100%
% Error = 0.12729521 •100% = 12.73%
Test 3
% Error = ( (0.27432 – 0.246493) / ( (0.27432 + 0.246493) / 2) ) •100%
% Error = ( (0.027827) / ( (0.520813) / 2) ) • 100%
% Error = ( (0.027827) / (0.2604065) ) • 100%
% Error = 0.10685985 •100% = 10.69%
The average for the % error for all three tests is as follows:
Average % Error = (% Error Test 1 + % Error Test 2 + % Error Test 3) / (Total Number of Tests)
Average % Error = (18.04% + 12.73% + 10.69%) / 3
Average % Error = (41.46%) / 3 = 13.82%
Given the small sample size of our testing, I think our margin of error is reasonable though next time we can do more to improve our measuring accuracy.
That’s all for this Lego Mindstorm experiment. Until next time!
Welcome every and anyone! In this blog I’ll be posting on experiments and sustainability topics from my Contemporary Science and Innovation course. With all of the drama surrounding climate change and sustainable energy resources, I decided to take this class as a way to see through the agendas and become more informed and try to find some sort of truth to the matter.
Feel free to look around the blog and check back for updates if you find anything you’re interested in.
Thanks for Visiting!
Nixandra
