Imagining Tomorrow's Grid


For over a century, the electrical grid has been a one-way street. A power company’s operations department estimates the demand for energy, instructs a power plant to produce enough electricity to meet demand, and distributes that power to residences and businesses. Except for incidents of severe weather and mechanical failure, this system is fairly reliable. But new advances in renewable energy, technology, and decentralized power have set the stage for the next generation: the smart grid.

Jianhui Wang, a computational engineer in the Energy Systems division at Argonne National Laboratory, uses advanced modeling and simulation to help pave the way for this major new system. In his talk at the Computation Institute on October 1st, he covered his research on transforming the grid into a two-way street, thereby making it more robust, flexible, and resilient.

These are all desirable goals for the world’s energy system, particularly in the face of diminishing and more expensive natural resources. But because the energy industry is old, massive, and set in its ways, convincing them to take on the great expense needed to update the grid is no easy task. Wang’s models offer a virtual proving ground for how new technologies -- such as wind and solar farms, neighborhood microgrids, smart meters, and electric vehicles -- can reduce costs and emissions when fully integrated into a smarter grid.

For example, Wang’s group created models that test how power companies can integrate wind energy alongside traditional power generation to produce cleaner electricity. One argument against wind power is that it is highly variable -- on days without much wind, windmills obviously don’t produce much energy. So Wang modeled a hybrid generation system that uses wind energy when available, but supplements it with coal or natural gas power when it falls short. By simulating a variety of weather scenarios, power company operators can test out and prepare for the worst case scenario, while using the model to guide the dynamic mixture of wind and traditional power generation on normal days.

Other models created by Wang’s group look at the impact of electric vehicles upon the power grid -- warning that the timing of when owners recharge their vehicles could actually *increase* net emissions -- and how smart buildings and locally generated power can further increase efficiency. As the system grows more and more decentralized, Wang said, the lines between energy generators and consumers will become blurred, accelerating the need for a smart grid that can realize the potential of these changes.

To learn more about Wang’s work, visit his website.

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