A group of scientists from a major Chinese grid operator have proposed to use an enhanced version of the particle swarm optimization algorithm to adjust inertia and damping coefficients in batteries linked to PV systems. Their approach was validated through a series of simulation and was found to enhance transient performance.
Image: Ephramac, Wikimedia Commons
From ESS News
Researchers from Chinese grid operator State Grid Handan Electric Power Supply have outlined a new grid-forming control scheme for photovoltaic storage systems that is intended to overcome the typical issues of conventional control strategies such as power overshoot and prolonged response times.
The new strategy uses particle swarm optimization (PSO), which is a social model that mimics the real rules of the bird flock’s foraging and is often used in heuristics and metaheuristics, to determine the steady-state inertia coefficient for grid-forming control within storage systems.
The scientists proposed an enhanced version of the PSO algorithm with elimination and replacement features. They optimized, in particular, the algorithm’s evolutionary step size in response to virtual synchronous generators (VSG) disturbances through an adaptation of the inertia factor and a boundary transition strategy.
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