Parameter Optimization Method of Grid-Forming Energy Storage Considering System Frequency Stability and Small Signal Stability

doi:10.12204/j.issn.1000-7229.2023.12.011

Abstract

Abstract:

To deal with the problem of insufficient inertia of new energy, the control technology of virtual synchronous generators (VSG) in grid-forming energy storage has been continuously developed, which provides inertia support for the system while causing power oscillation and reducing the power angle stability of the system. To solve this problem, the mechanism of the influence of the virtual inertia and virtual damping parameters of the virtual synchronous generator on the system stability is explained, and a parameter optimization strategy is proposed for the virtual synchronous generator. This strategy simultaneously considers the frequency stability and small-signal stability of the system to establish an objective function optimization model. The objective function minimizes the maximum frequency deviation and the maximum sum of the damping ratio of the system oscillation mode. The stability interval of each control parameter is considered the constraint condition. The strategy was solved using a fast non-dominated sequencing genetic algorithm (NSGA-II) with an elite strategy. Finally, the effectiveness of this method is verified through a simulation.

This work is supported by National Natural Science Foundation of China(No. 52277096).

Key words: grid-forming energy storage, virtual synchronous generator (VSG), inertia, damping

CLC Number:

TM712

LI Li, WANG Jiaming, ZHANG Qinglei, LI Jun, WANG Tong. Parameter Optimization Method of Grid-Forming Energy Storage Considering System Frequency Stability and Small Signal Stability[J]. ELECTRIC POWER CONSTRUCTION, 2023, 44(12): 125-135.

Figures/Tables 11

Fig.1 Structure diagram of PMSG-VSG-k system

Fig.2 Control block diagram of the converter of VSG

Fig.3 Equivalent circuit diagram of wind turbine grid-connected

Fig.4 NSGA-Ⅱ algorithm flow diagram

Table 1 Parameter optimization results

Fig.5 Topological structure diagram of a four-machine two-zone system with two PMSG-VSGs

Fig.6 Non-linear simulation results

Table 2 Optimal parameters of the first PMSG-VSG under different output

Table 3 Optimal parameters of the second PMSG-VSG under different output

Fig.7 Non-linear simulation results

Fig.B1 Specific application process of control parameter optimization method in practical engineering

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