The last roll of Kodachrome

 

Research explores future energy security of China

 

July 30, 2015 China needs to reduce its dependence on coal and improve the range of fuels it uses if it is to have long term energy security, according to new research from the University of East Anglia (UEA). The study, published in the journal Technological Forecasting and Social Change, looks at the future of electricity supply in China and the issues it faces in reducing its carbon emissions -- nationally China's electricity sector accounts for more than half its total greenhouse gas emissions. The country's electricity sector is the largest in the world and energy security concerns mean that China meets its electricity needs with domestic resources, resulting in a system heavily reliant on coal. However, increasing demand for electricity and direct coal consumption, and gradual depletion of its own supply, have led to it becoming the world's largest coal importer. Lead researcher Dr Konstantinos Chalvatzis, of UEA's Norwich Business School and the Tyndall Centre for Climate Change Research, said: "China's energy sector is under pressure to achieve a secure and affordable supply while at the same time reducing its carbon emissions. There has been this long argument about whether China can give up coal because that would harm their supply security. "We recommend that the Chinese Government continues to work towards two main objectives. First, increase the share of renewable energy sources, such as wind and hydro-power, in the fuel mix and as a result maintain high energy independence. Secondly, improve diversity in the fuel mix. If imports are necessary, prioritise non-coal fuels, such as nuclear fuels and natural gas. These two objectives will improve electricity supply security while allowing China to decarbonise its economy." While acknowledging that China appears to be leading its electricity sector away from the dominance of coal, the researchers say that at this stage this is only a gradual, incremental change that will not deliver a radically different fuel mix in less than a decade. "We argue that long-term aggressive deployment of renewable energy will unblock China's coal-biased technological dependence and increase supply security in all fronts," said Dr Chalvatzis, a Senior Lecturer in Business and Climate Change. "However, reduced supply diversity in China during the 1990s will not recover until after 2020s due to the long-term coal lock-in that can threaten to hold China's back from realising its full potential. "China's rapid growth rate presents a challenge as well as an opportunity for the country's energy future. The challenge is to secure increasing energy supplies while maintaining a decarbonisation path. In contrast, the opportunity lies in transforming the historical coal lock-in into a diversified and secure energy supply system that will fuel the Chinese economy for the years to come." China is the world's largest consumer of coal and its electricity sector is the largest single source of coal demand, consuming approximately half of the country's coal. Electricity consumption continues to grow rapidly, reaching a growth rate of 7.2% in the first three quarters of 2013, while electricity production for the same period grew at 6.8%. Dr Chalvatzis said: "Policy makers must design a path that will be influenced by the international energy prices and the role of technological 'dumping' caused by China or other countries. In this process climate policy, its effect on energy prices and their subsequent consequences for the well-being of the global economy will also need to be considered. "The success of China's decarbonisation path is keenly observed by the international community. The capacity of the Chinese Government to commit to international emission targets is linked to its capacity to achieve these targets without compromising its energy supply security and development prospects." Source:  University of East Anglia

Machine Learning’s Impact on Solar Energy

 

Wed, 07/29/2015 - 1:00pm Lindsay Hock, Editor IBM's solar forecasting technology. Image: IBM Research In 2013, solar was the second-largest source of new electricity generating capacity in the U.S., exceeded only by natural gas. A USA SunShot Vision Study suggests solar power could provide as much as 14% of U.S. electricity demand by 2030, and 27% by 2050. There are currently two main customers for renewable energy forecasting technologies: utility companies and independent system operators (ISOs). However, the difficulty in producing accurate solar and wind forecasts has required electric utilities to hold higher amounts of energy reserves as compared to conventional energy sources. Yet, solar power installations grow each day, and future solar penetration levels require increased attention to the value of more accurate solar forecasting. With better solar and wind forecasts, it’s possible that solar energy’s contribution to the U.S.’s energy will reach up to 50%. Until now, due to intermittency, solar energy won’t supply more than 20 to 30% of the U.S.’s energy. However, a collaboration between IBM and the U.S. Dept. of Energy (DOE) could double the accuracy of solar and wind forecasts within the next year with the help of IBM Research’s machine learning technology. “This collaboration could have a huge impact on the energy industry, as well as local businesses, the economy and the natural environment,” says Hendrik Hamann, Physical Analytics Manager, IBM Research. “Part of our goal is to help a wide range of industries and professions better understand how the world works so we can all make better decisions.” Announced on July 16, 2015, IBM Research revealed that solar and wind forecasts it’s producing using machine learning and other cognitive computing technologies proved 30% more accurate than ones created using convention approaches. The research program was funded by the DOE’s SunShot Initiative, and the results suggest new ways to optimize solar resources as they are increasingly integrated into the nation’s energy system. Machine learning for solar improvements So how does machine learning compare to conventional approaches for solar and wind forecasts? Think of it as big data meets science, says Hamann. While other solar forecasting systems take more narrow location and timeframe views, IBM’s approach incorporates a great number of weather and solar energy prediction models. “We use machine learning techniques to blend those using historical data as a function of weather situation, forecast horizon and location to create what we call a supermodel,” says Hamann. These advances are valuable for the future of alternative energy, and the machine learning model can generate accurate forecasts of solar energy from minutes ahead to several days. IBM Research worked with academic, government and industry partners for about three years to develop this self-learning weather model renewable forecasting technology, otherwise known as SMT. This technology uses a combination of machine learning, big data analytics and mathematical modeling of complex weather systems to continuously analyze, learn from and improve solar forecasts derived from a large number of weather models, including satellite observations, sensor networks and local weather stations and sky cameras. The system analyzes the data to forecast how much solar energy will be available at different locations and times. IBM’s approach provides a general platform for renewable energy forecasting, including wind and hydro. The SunShot Initiative “IBM’s goal is to help produce a more sustainable energy future by integrating solar power into the energy pipeline,” says Hamann. “Our collaboration with the DOE’s SunShot Initiative now makes this possible as the collaborative effort seeks to make solar energy fully cost-competitive with traditional energy sources before the end of 2020.” Through the DOE SunShot Initiative, IBM Research is working with a number of collaborators in academia, government and industry to grain various perspectives. “For example, National Renewable Energy Laboratory (NREL) and ISO-New England are two main partners who are helping evaluate the important metrics to determine accuracy of solar forecasting,” says Hamann. IBM Research is also providing foundational solar forecasts covering all 48 contiguous states at 5-km spatial resolution. This is primarily for government agencies, utilities and grid operators to evaluate how solar forecasting can impact the supply and demand, in addition to operations. source: http://www.rdmag.com/articles/2015/07/machine-learnings-impact-solar-energy

3 Exercises You Need To Do To Counteract Sitting All Day

 

Fitness Lifestyle by Joel Runyon Are you a desk jockey? Do you spend most of your day sitting or hunched over a computer or laptop? According to a report from CNN, sitting all day may actually be killing you, or at the very least, could be taking years off of your life. When you sit, especially for long periods of time, your body slowly becomes more hunched over. Your internal organs get compacted and are forced to operate in less than ample space. Over time, the spine begins to weaken because of the unnatural stress placed on the joints. Hip muscles and joints begin to shorten and become tight, making standing up straight less comfortable. Ultimately, the body’s blood circulation decreases due to lack of movement. This is partially why legs and ankles will also swell during long stationary periods. The point is alarmingly clear: if you sit for long periods of time during the day, you could actually be doing your body some real harm. The great news is that there are simple foam rolling exercises that you can do in the comfort of your own home that can help your body heal, which all take less less than 15 minutes total. Grab a foam roller or a mobility ball (like a lacrosse ball) and try out these three exercises.   Glute Smash If you’re sitting on your butt all day, you need to give it some love. Most people don’t realize that rolling out your glutes will help you loosen more than just your butt muscles. You’ll also loosen your upper hamstrings and help remove some pressure from your lower back. How to do it: Place a mobility ball, or a lacrosse ball under your glute muscle on one side. Rotate the ball until you find a tight spot or “trigger point”. Contract and release the muscle (basically squeeze your butt cheek and release it) for two minutes. Keep your legs bent with the knees out to the side. Hip Flexor Like I mentioned earlier, when you sit for long periods of time, the hip muscles (including the quad and hip flexors) slowly shorten and become tighter. Tight hips make it really uncomfortable to stand up straight, and the tight joint puts a lot of unnecessary pressure on the lower back. Stretch out and open up the hips by focusing on the hip flexors. How to do it: Laying on your side, put the foam roller on the upper outside of your leg – near your hip. Roll the foam roller and knead it into the muscle tissue, fascia and tendon between your knee all the way up to your hip. Continue back and forth. T-Spine Smash This simple movement is one of my favorites because it helps counteract the “dreaded hunchback syndrome” so many people get from hunching over their computers every day. A great added benefit: part of this movement passes over the shoulders so you are able to help release tension that has built up throughout the week. How to do it: Lay on your back with your knees bent and your heels close to your butt. Position the foam roller just above your shoulder blades. Look straight up and give yourself a hug. Feel the stretch in your back as you hold the position and roll the foam roller down to your lower back and back to between your shoulder blades. Repeat for the duration of the movement. If you’re still not sure about each of these movements, find an app like MoveWell that will guide you through each movement in the mobility workout, step-by-step, or head over to these tutorials on YouTube: Glute Stretches Hip Stretches Thoracic Spine Stretches