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Scientists at a major Chinese grid operator have proposed using an improved version of the particle swarm optimization algorithm to tune the inertia and damping coefficients in batteries linked to photovoltaic systems. Their approach was validated through a series of simulations and found to improve transient performance.
Researchers at Chinese grid operator State Grid Handan Electric Power Supply have outlined a new grid-forming control scheme for PV storage systems that aims to overcome typical problems of conventional control strategies such as excess power and long response times.
The new strategy uses particle swarm optimization (PSO), which is a social model that mimics real-life foraging rules of bird flocks and is often used in heuristics and metaheuristics, to determine the steady-state inertia coefficient for controlling grid formation within storage systems.
The scientists proposed an improved version of the PSO algorithm with elimination and replacement features. In particular, they optimized the evolutionary step size of the algorithm in response to perturbations of virtual synchronous generators (VSGs) through an adaptation of the inertia factor and a boundary transition strategy.
“This study uses the PSO algorithm that develops step sizes that are larger in the initial phase and progressively decrease as the iterations progress,” they explained, noting that the inertia factor should not be too small in the early stages or too large later on. “The evolution rate can be increased in the early stages while maintaining convergence effects in the later stages.”
The algorithm is said to control the size of the inertia factor based on the number of iterations and the relevant particle distance values ??during the iterative process. It is also reported that it can set upper and lower thresholds to avoid calculation failures caused by an inertia factor that is too large or too small.
Validation
The algorithm was validated in a simulation performed through Matlab/Simulink software. They assume that the algorithm will be applied in a five-port PV microgrid system equipped with a battery, a voltage and frequency regulation unit, a constant power output unit, and a load end. The battery is considered as a voltage-type DC voltage source after being converted through a converter and gathered on the DC bus.
In the simulation, the group considered three different scenarios: sudden load increase; sudden load decrease; and load fluctuation. The performance of the proposed improved PSO algorithm was compared with that of a conventional PSO algorithm and the former was found to exhibit “faster convergence speed and better convergence performance.” Reduced frequency fluctuations and response times were also observed, as well as improved boosting and reduced manpower demand.
The academics presented their findings in the paper “ Adaptive grid- forming strategy for a photovoltaic storage system based on edge transfer PSO algorithm,” published in Energy Reports . They said their new strategy has significant potential for engineering applications. |
