This paper proposes a novel inertia-enhanced distributed control method to complement the inertia of microgrids. The rate of change of frequency (RoCoF) and the rate of change of voltage (RoCoV) are employed in this paper to quantify the frequency inertia and voltage inertia, respectively. Then, a fully distributed algorithm with constrained changing rates is proposed. By bounding the changing rates of frequency and voltage during the consensus control, the algorithm can address the consensus problem while enhancing the inertia of microgrids. Compared with most inertia control methods, the proposed method can utilize the reserve power of scattered DGs to supply inertia. Besides, it performs better under disturbances and delays than conventional distributed control methods. The effectiveness of the proposed method is validated by several cases in MATLAB/Simulation and a hardware experiment.

In island microgrids, to tap the voltage control potential of different DGs, this paper presents a unified distributed cooperative voltage control approach for grid-following (GFL) and grid-forming (GFM) DGs. The proposed approach consists of a unified modeling method and a novel range-consensus-based distributed control algorithm. The modeling method employs power coupling and extended state observer (ESO) to unify different inner dynamics and control structures of DGs, making the voltage regulation of different DGs can be addressed by designing the same distributed controller. The proposed distributed algorithm introduces deviation-based states to converge the voltages to an expected range instead of a consensus state, making the algorithm is more in line with the voltage control standard of the grid code than the common state consensus ones. Besides, the local feedback designed in the algorithm improves the anti-interference ability of the system. The Lyapunov technique verifies the stability of the proposed method. Finally, the effectiveness of the proposed scheme is validated by several simulation results and a hardware-in-the-loop (HIL) test.

An enormous challenge for state estimation (SE) in power distribution networks with high penetration of photovoltaic generators lies in how to deal with measurement uncertainty. Driven by this motivation, an interval arithmetic (IA) based SE is proposed in this paper, which considers interval modeling for measurement uncertainty. The proposed SE is formulated as two interval optimization models based on the unknown-but-bounded theory, and solution bounds of state variables are obtained using a two-stage linear programming approach. In particular, the proposed SE is extended to realistic power distribution networks with mixed microphasor measurement units (μPMU), voltage magnitude, smart meters and feeder terminal units. Case studies and results are illustrated and discussed to demonstrate the performance of the proposed IA-based SE. It could provide the operators intuitive and effective bounds of system states for advanced power industrial applications under consideration of uncertainty.

This paper presents a novel distributed voltage control strategy to maintain the voltage of active distribution networks containing multiple microgrids. Local voltage regulation characteristics, such as power reserve, adjustment cost and regulating speed, are identified first. According to a neighbors’ voltage regulation characteristics, the microgrid coordinates neighborhood resources and asks them for coordination as soon as voltage problems occur. Microgrids schedule local resources based on a cooperative distributed model predictive control algorithm scheme with neighbor-to-neighbor communication. Tests are performed in an active distribution network with three microgrids. The numerical studies have shown that the proposed strategy mitigates the voltage fluctuation rapidly and efficiently with minimum operating cost.

Advanced digital filter is important for grid voltage synchronization, harmonic information extraction and converter control. The complex variable filter (CVF) such as the reduced order generalized integrator (ROGI) is one of the most prevalent filters. However, it is proven in this paper that the real coefficient CVF achieves performance identical to the real variable filter (RVF) such as the second-order generalized integrator (SOGI). It implies that the advantages of CVF are not fully utilized. Therefore, in this paper, the real coefficient is extended to a complex one leading to a complex coefficient CVF (CC-CVF), and the filter performance of CVF for extracting the harmonics is significantly improved. Furthermore, linear quadratic regulation (LQR) is employed to design the complex coefficients to achieve a better dynamic performance. Finally, the CC-CVF is enhanced with frequency estimation capability. The proposed CC-CVF is verified by extensive simulations and experiments.