4.5 Article

Adaptive virtual synchronous generator control using optimized bang-bang for Islanded microgrid stability improvement

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SPRINGER SINGAPORE PTE LTD
DOI: 10.1186/s41601-023-00333-7

关键词

Virtual synchronous generator (VSG); Microgrid; Hybrid energy storage system (HESS); Particle swarm optimization (PSO); Frequency nadir; ROCOF; Bang-bang; Virtual inertia

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This paper applies a virtual synchronous generator (VSG) controller to a hybrid energy storage system (HESS) in an isolated microgrid to maintain frequency stability. It investigates the use of adaptive virtual inertia constant and constant virtual damping coefficient for frequency stability enhancement and compares them with the constant parameter VSG. The paper also proposes modifications to the control technique and evaluates the VSG parameters through different methods. The superiority of the proposed technique in enhancing frequency stability, accelerating steady-state frequency restoration, and reducing energy requirement is examined.
In this paper, a virtual synchronous generator (VSG) controller is applied to a hybrid energy storage system (HESS) containing a battery energy storage system and supercapacitor storage system for maintaining the frequency stability of an isolated microgrid. The microgrid contains a photovoltaic generation system and a diesel generator in addition to the HESS and two constant impedance loads that are fed through a medium voltage radial feeding system. The adaptive virtual inertia constant (H) with constant virtual damping coefficient (D) based on ' bang-bang' control for the microgrid's frequency stability enhancement is investigated and compared with the constant parameter VSG. In addition, the bang-bang control is modified to adapt the D beside the adaptive H, and the system response is investigated and compared with the conventional adaptive H technique. The VSG parameters are evaluated based on two different methods. The first is a computational method based on the simplified small signal stability analysis, while the other is based on an optimization method using two different objective functions and the particle swarm optimization technique. This paper also investigates the superiority of the proposed technique compared to other techniques in enhancing frequency stability, accelerating steady-state frequency restoration, and reducing the energy requirement of the HESS. The required power from the HESS is shared between the two energy storages using the low pass filter technique so as to reduce battery peak current.

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