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:

Using autonomous eVehicles for Renewable Energy Transportation and Distribution: and

Free High Speed Internet to the Home or School Integrated with solar roof top:

High level architecture of Internet Networks to survive Climate Change:

Architecture and routing protocols for Energy Internet:

How to use Green Bond Funds to underwrite costs of new network and energy infrastructure:

Wednesday, August 31, 2011

Modeling the economy in a changing climate

As society adjusts to the knowledge that our climate is changing, policy makers are faced with a difficult question: how can they use policy to help prevent and cope with climate change, while minimizing the damage to their nation or organization’s economic health?

For example, “one policy that has been considered and proposed is carbon taxes and taxes on carbon-emitting industry,” said Ian Foster, director of the Computation Institute at University of Chicago/Argonne National Laboratory. “The question is: will that tend to drive dirty industries offshore in a way that will perhaps increase the total emissions and harm US industry at the same time?”
Two years ago, Foster and several other computer scientists joined forces with economists, climate scientists, and geophysicists to create a computer modeling framework that could help decision makers answer these sorts of questions.
Foster and his colleagues called the first version of their model CIM-EARTH (a Community Integrated Model of Economic And Resource Trajectories for Humankind). Already, several related papers have been published, and in February 2011, a larger group of researchers launched the Center for Robust Decision-Making on Climate and Energy Policy (RDCEP).
Modeling the unpredictable
Computational methods have been used to simulate a variety of complex systems, from black holes to human biology. But all of these have one thing in common: they are all models of physical systems, governed by physical laws.
The same cannot be said of the economy. It’s true that the economy can be constrained by physical limits such as the quantity of a resource that exists on our planet, or the rate at which we can extract it. But with those few exceptions, the economy is governed by collective human behavior – and we can certainly rely on humans engaging in irrational and unpredictable behavior.
“On the other hand, economists do know a lot about how society responds and the economy responds to various pressures,” Foster said.
As an example, he described an approach to economic models called “rational expectations.” The simplest economic models assume that the public will behave as though they knew nothing about the future. But that’s wrong; in reality, we modify our behavior based on what we expect to happen. Rational expectations models attempt to emulate that by assuming that the public has perfect knowledge of the future. The result is a more accurate, effective model – one that will likely only improve as it evolves to assume imperfect knowledge of the future.
Assembling a model
The computational economics community is small, according to Foster, but growing. Historically, they’ve had access to very limited resources. But with the CIM-EARTH model, and other projects launched by RDCEP, economists have the opportunity to work hand-in-hand with experts in optimization, numerical methods, and more.
“Our models have some new features relative to the old ones,” Foster said. “They can run with greater detail, with smaller time steps, they can incorporate factors that are not in the previous models because we have more modern numerical methods.”
For the future
RDCEP, which was launched using a five-year $6 million National Science Foundation grant, has nearly five years remaining to continue to hone, improve, and add to their modeling framework.
“We did one first study that was looking at the sensitivity of the core economic model to some of the input parameters,” Foster said. Next, they plan to do a large study of scenarios in which crop land use changes.
“What we want to do there is actually take an agricultural model and build up a big database characterizing the agricultural output that would result for different land types under different climate scenarios and that would then be used in other studies,” Foster explained.
Another avenue they are exploring is how an increased demand for biofuel might affect land use. For example, will the demand be sufficiently high that forests will be cut down to make room for

Modeling the economy in a changing climate

Green Internet Consultant. Practical solutions to reducing GHG emissions such as free broadband and electric highways.
twitter: BillStArnaud
skype: Pocketpro

Blog Archive