The global consensus has emerged to replace traditional fossil fuel-based power generation with renewable energy sources such as photovoltaic and wind power, leading to the formation of renewable energy delivery systems (REDSs). Within these systems, a trend towards the integration of grid-following (GFL) and grid-forming (GFM) devices has emerged. The REDS incorporating GFL and GFM devices exhibit high dynamic order, with complex dynamic interactions between heterogeneous equipment clusters and between equipment clusters and the network, posing challenges for the mechanism analysis and quantitative computation of small-signal stability. This paper proposes an eigen-subsystem computation method for the small-signal stability analysis of REDSs. It defines the double-infeed eigen-subsystem (DIES), which includes a GFL device and a GFM device. By equivalently reducing the complex, high-dimensional REDS to several low-dimensional DIES, the method preserves the dynamic interactions both between devices and between devices and the network. This approach enables efficient and accurate small-signal stability analysis of REDSs.
Firstly, for a REDS incorporating GFL and GFM devices, a full-order small-signal model of the system is constructed. The general approach for deriving the eigen-subsystem is briefly outlined, which involves reducing the complex high-dimensional system to several simple low-dimensional eigen-subsystems through decoupling. Subsequently, for a REDS with an equal number of n GFL devices and n GFM devices, based on the full-order model of the system, a matrix block diagonalization method is proposed on top of the matrix diagonalization method. A fast algorithm based on the Givens method is presented to solve for P⊗I4 (P∈Rn×n), thus decoupling the REDS into n DIESs. Stability criteria for the DIES are also provided. When the device parameters are given, the stability operating region Ω of the DIES can be determined. The DIES remains stable if its network impedance falls within Ω. Thirdly, for more generalized scenarios, a node-splitting method is introduced to increase the number of less abundant devices, addressing the imbalance in the number of GFL and GFM devices. An eigen-subsystem-based method for small-signal stability analysis of REDSs is proposed. The REDS is stable if the set of network impedances Ω1, formed by all decoupled DIESs, lies within the stability region Ω. Otherwise, the REDS becomes unstable and exhibits the same stability issues as the unstable DIES. Finally, time-domain simulations are conducted, and a 3-machines 9-nodes system as well as a 54-machines system are used to validate the effectiveness and correctness of the proposed method in the small-signal stability analysis of REDSs incorporating GFL and GFM devices. Experimental comparisons show that, compared to traditional eigenvalue analysis methods, the proposed method significantly improves computational efficiency.
The following conclusions can be drawn: (1) The REDS is mode-equivalent to its DIESs, and the stability characteristics of the original system can be traced back through DIESs. (2) For general REDS with n GFL devices and m GFM devices, the system can be decoupled and reduced in order by constructing a mode-equivalent system through node-splitting. This results in m DIESs, and (n-m) eigen-subsystems of single GFL devices (where n>m, or vice versa). (3)When the device parameters are given, the stability operating region Ω of the device-side characteristics can be determined. The network-side information of the eigen-subsystems obtained from the decoupling of the REDS forms a set of network impedances Ω1. By checking whether Ω1 belongs to Ω, the stability of the original system can be quickly assessed. Currently, small-signal synchrony stability has primarily been analyzed for the DIES. A future challenge is how to comprehensively analyze system stability under interactions among different components and quantify the stability margin of hybrid delivery systems.
| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |