The modern power system is becoming more complicated due to the ever increasing penetration of power electronics, which is referred to as a power electronics-dominated system (PEDS). In this case, the analysis, control, and operation of the entire power system should tone with the energy-paradigm transition pace, where the challenges should be properly tackled. After the brief introduction of grid-connected converters, this paper explores stability challenges of PEDSs, especially on the low inertia issue and the multi-timescale characteristics, as well as the dynamics when connected to weak grids. The low inertia issue is considered as one of great challenges that power electronics introduce to the conventional power grids. On this basis, the stability issues of PEDSs are discussed. The exploration reveals that the multi-timescale coupling among various control loops and the mutual effects of multiple converters demand much more attention than ever before. Also, the coordinated control of converters for the global stability of PEDSs is summarized, part of which offers the possibility to solve the inertia problem. This paper serves as inspiration on potential solutions to these issues. In order to provide a more intuitive impression of the inertia problem in PEDSs, a case study is exemplified to further highlight the analysis and discussion.

In power electronics-dominant systems (PEDSs), the declining-inertia issue is one of the most significant challenges to tackle. The inertia emulation from DC-link capacitors is one cost-effective and application-friendly solution to enhance the system inertia. Although the virtual inertia control of the DC-link capacitor supports the grid frequency with a relatively long-term effect, it affects the dynamic of the power converter at multiple timescales. In turn, the maximum effective virtual inertia from the DC-link capacitor is limited by the operation condition of the converter. Thus, to properly design the virtual inertia control, the dynamics of the faster timescale than the inertia emulation should be addressed. With the above, this article analyzes the maximum virtual inertia of DC-link capacitors based on a multi-timescale model of power converters. First, the system stability considering virtual inertia control of DC-link capacitors is analyzed in the submodel at the voltage control timescale (VCT), where the virtual inertia control parameters are accordingly tuned on a pre-designed converter. Then, the maximum effective virtual inertia is identified in the submodel at the rotor motion timescale (RMT). The exploration and findings in this article are beneficial to the power converter design and future inertia placement optimization in PEDSs. Case studies on a hardware-in-the-loop platform are conducted to validate the proposed model and the analysis method.

Frequency security is one of the challenges for the power grid penetrated by renewable energy systems (RESs). Virtual inertia provision from the RESs is considered to be efficient support for frequency security enhancement. How to estimate the frequency nadir rapidly and accurately is crucial for the online inertia allocation for the RESs. This paper develops a generic average system frequency (G-ASF) model for the power grid to estimate the frequency nadir at first. The low-order generic model of the speed governing system of the SG is proposed to enhance the accuracy and flexibility of the G-ASF model. Then, based on the G-ASF model, an online inertia allocation strategy for the grid-connected RESs under frequency nadir constraint is proposed. With the pre-identified generic models of the speed governing systems, the G-ASF model of the entire power grid is periodically updated according to the grid operation state. Next to the model updating, the critical inertia of the power grid is periodically calculated under the pre-defined contingencies for frequency security verification. Then, the virtual inertia provision tasks are determined and allocated to the RESs periodically, and the grid frequency security is effectively ensured. The simulation results validate the proposed model and strategy.

Grid frequency support, e.g., by the virtual inertia control (VIC), of photovoltaic (PV) systems, is more demanded than ever before. To achieve the full-range frequency support (i.e., to tackle the under- or overfrequency issues), the power reserve is necessary for PV systems. Accordingly, a power reserve control (PRC) method based on the maximum power point tracking (MPPT) is adopted in this article, referring to as MPPT-PRC. It measures the real-time maximum available power (MAP) periodically, being independent of physical sensors and burdensome computation. However, the MAP measurement loop inevitably couples with the power reserve loop, which makes the realization of the VIC challenging. Aiming at this issue, an event-triggering strategy is elaborately designed to switch the PV system in-between different operating modes. The strategy is realized by a set of control signals. They are responsible for the detection of frequency incidents, the activation of MPPT, the measurement of MAP, respectively. Consequently, the VIC can be achieved based on the MPPT-PRC without any conflicts or instability. Experimental tests are performed on StarSim real-time hardware-in-the-loop system to validate the proposed MPPT-PRC-based VIC, as well as the coordination of the control loops.

State-of-charge (SOC) estimation of lithium-ion (Li-ion) batteries with good accuracy is of critical importance for battery management systems. For the model-based methods, the electrochemical model has been widely used due to its accuracy and ability to describe the internal behaviors of the battery. However, the uncertainty of parameters and the lack of correction from voltage also induce errors during long-time calculation. This paper proposes a particle filter (PF) based method to estimate Li-ion batteries’ SOC using electrochemical model, with sensitive parameter identification achieved using the particle swarm optimization (PSO) algorithm. First, a single particle model with electrolyte dynamics (SPME) is used in this work to reduce the computational burden of the battery electrochemical model, whose sensitive parameters are selected through the elementary effect test. Then, the representative sensitive parameters, which are difficult to measure directly, are adjusted by PSO for a high efficiency. Finally, a model-based SOC estimation framework is constructed with PF to achieve accurate Li-ion battery SOC. Compared with extended Kalman filter and equivalent circuit model, the proposed method shows high accuracy under three different driving cycles.