Helping Microgrids Meet The Demand

Scientists have developed a computer algorithm that improves microgrid stability and reliability by making it mimic the inertia of a large power grid.

AsianScientist (Sep. 7, 2017) – Scientists in Korea and the US have developed a computer algorithm that better manages the power reserves of microgrids. They report their findings in the IEEE/CAA Journal of Automatica Sinica.

The power it takes to bring a Boeing 747 from a resting state on the airport tarmac to speeding across the sky is enormous. The plane can continue in its active state for as long as its fuel lasts. A frisbee, in contrast, takes far less energy to become airborne, but with no energy supply, it falls almost immediately. This scenario is analogous to the traditional power system and decentralized microgrids. The power grid has a large reserve of energy to continue in an active state, while a microgrid quickly spends its reserve.

If the power supply rate is too low, the microgrid will fall short of demand as the system’s inertia depletes. This problem is made more complicated in microgrids powered by renewable energy resources, such as solar panels or wind turbines. Storage systems are costly, but sunshine and wind strength are largely unreliable for consistent use.

In this study, researchers propose a way to better control easily-spent microgrids. They created a computer-based algorithm that can mirror the microgrid’s inertia by alternating the system’s direct current over specific ranges.

“The microgrid concept is a big step towards solving the controllability problems of distributed resources,” said Dr. Im Won-Sang of Lehigh University, the first author of the study. “For a microgrid to work autonomously, it must maintain its own supply-demand balance.”

“In traditional power systems, supply-demand imbalance changes the system frequency at a rate determined by the total system inertia. Our algorithm tries to make [the] microgrid work like a large power grid with large inertia,” he added.

Based on simulations performed by the scientists, the algorithm improves the efficiency of microgrid management. However, Im noted that the larger inertia imposed by the algorithm limits the flexibility and fast response times of the microgrid. Their future work will focus on making microgrid controllers that are quicker and more accurate.

The article can be found at: Im et al. (2017) Distributed Virtual Inertia Based Control of Multiple Photovoltaic Systems in Autonomous Microgrid.


Source: Chinese Association of Automation; Photo: Shutterstock.
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