Energy Internet and eVehicles Overview
Governments around the world are wrestling with the challenge of how to prepare society for inevitable climate change. To date most people have been focused on how to reduce Green House Gas emissions, but now there is growing recognition that regardless of what we do to mitigate against climate change the planet is going to be significantly warmer in the coming years with all the attendant problems of more frequent droughts, flooding, sever storms, etc. As such we need to invest in solutions that provide a more robust and resilient infrastructure to withstand this environmental onslaught especially for our electrical and telecommunications systems and at the same time reduce our carbon footprint.
Linking renewable energy with high speed Internet using fiber to the home combined with autonomous eVehicles and dynamic charging where vehicle's batteries are charged as it travels along the road, may provide for a whole new "energy Internet" infrastructure for linking small distributed renewable energy sources to users that is far more robust and resilient to survive climate change than today's centralized command and control infrastructure. These new energy architectures will also significantly reduce our carbon footprint. For more details please see:
Free High Speed Internet to the Home or School Integrated with solar roof top: http://goo.gl/wGjVG
High level architecture of Internet Networks to survive Climate Change: https://goo.gl/24SiUP
Architecture and routing protocols for Energy Internet: http://goo.gl/niWy1g
How to use Green Bond Funds to underwrite costs of new network and energy infrastructure: https://goo.gl/74Bptd
Saturday, May 5, 2012
Rutgers to deploy follow the sun solar center using GreenHadoop and GreenNebula
[Here is a very cool project at Rutgers that demonstrates how we can build “adaptable” ICT green solutions that will be needed for a much warmer planet and yet at the same are also excellent solutions for mitigation.
It is this type of ingenuity that we will need in the coming decades, rather than silliness of energy efficiency, to address the challenges of severe weather caused by climate change and the shut down of coal trains and plants by protestors once the public starts to realize the real implications of climate change -- BSA
We are building a solar-powered micro-datacenter called Parasol. It comprises a small container, a set of solar panels, and batteries. The container lies on a steel structure placed on the roof of our building. The solar panels are mounted on top of the steel structure and shade the container from the sun. The container hosts two racks of energy-efficient servers (up to 160 of them) and networking equipment. The container uses free cooling whenever possible, and direct-exchange air conditioning otherwise.
Besides the solar panels, Parasol can draw energy from its batteries and/or the electrical grid. Three manual switches enable different configurations for the supply of energy. For example, we can configure Parasol to operate completely off the electrical grid. Parasol also includes extensive power monitoring infrastructure to quantify how much energy is drawn from each available source.
We are also building software for maximizing the use of green energy in Parasol. Our two first systems, GreenSlot and GreenHadoop, have been described in the literature. Both systems assume that there are no batteries and that brown energy should only be consumed when green energy is not available. We are currently working on GreenNebula, our extension of the OpenNebula cloud manager. GreenNebula will be aware of the green energy available at the datacenter. In addition, it will maximize the green energy use by migrating virtual machines across green datacenters. Finally, it will enable us to share Parasol with researchers from other institutions.
Interest has been growing in powering datacenters (at least partially) with renewable or “green” sources of energy, such as solar or wind. However, it is challenging to use these sources because, unlike the “brown” (carbon-intensive) energy drawn from the electrical grid, they are not always available. This means that energy demand and supply must be matched, if we are to take full advantage of the green energy to minimize brown energy consumption. In this paper, we investigate how to manage a datacenter’s computational workload to match the green energy supply. In particular, we consider data-processing frameworks, in which many background computations can be delayed by a bounded amount of time. We propose GreenHadoop, a MapReduce framework for a datacenter powered by a photovoltaic solar array and the electrical grid (as a backup). GreenHadoop predicts the amount of solar energy that will be available in the near future, and schedules the MapReduce jobs to maximize the green energy consumption within the jobs’ time bounds. If brown energy must be used to avoid time bound violations, GreenHadoop selects times when brown energy is cheap, while also managing the cost of peak brown power consumption. Our experimental results demonstrate that GreenHadoop can signiﬁcantly increase green energy consumption and decrease electricity cost, compared to Hadoop.
Activists block coal trains
R&E Network and Green Internet Consultant.
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