Lack of charging facilities is still a significant barrier for electrification of the logistic system. How to effectively schedule the electric vehicle (EV) charging power to reduce the charging station operating cost when the number of chargers was limited becomes an important issue. To tackle this issue, an optimal charging scheduling method by responding to the time-of-used (TOU) electricity price is proposed. First, the uncontrolled charging model to fully charge EVs as fast as possible is established. Then, an optimal charging scheduling model by considering the limited number of chargers is proposed to both reduce the charging cost and guarantee the charging demand of each EVs. The proposed model is formulated as a bilevel programming (BP) model. The charger index and available charging duration for each EV are determined at upper level, while the charging power of each EV at each time slot is determined at the lower level. After that, a solving approach is introduced for the proposed BP model. The efficacy and performance of the proposed charging scheduling method is verified by simulation results.

The increasing of electric vehicles (EVs) alleviates the faced environmental problems but brings challenges to the optimal operation of transportation network (TN) and distribution network (DN). However, the most of existing research works consider EV charging station assignment and navigation services in the TN separately from charging station power scheduling services in the DN. To overcome this research gap, this paper proposes a collaborative optimal routing and scheduling (CORS) method, providing optimal route to charging stations and designing optimized charging scheduling schemes for each EV. In the order of reporting, whenever an EV reports its charging demand, a CORS optimization model is built and solved so that a specific charging scheme is designed for that EV. Then, the TN and DN status is updated to guide the subsequent EVs operating. The proposed CORS integrates the real-time state of the TN and DN, and effects positive benefits in helping EVs to avoid traffic congestion, improving the utilization level of charging facilities and enhancing charging economy. The combined distributed biased min consensus algorithm and generalized benders decomposition algorithm are adopted to solve the complex nonlinear optimization problem. Through comparing with the existing methods, better effectiveness is verified by simulation results.

In this paper, a virtual inertia and damping control (VIDC) strategy is proposed to enable bidirectional DC (bi-DC) converter to damp the voltage oscillation, using the energy stored in energy storage system (ESS) to emulate the inertia of DC microgrid (DC-MG) without modifications of system hardware. Both inertia part and damping part are modelled in the VIDC regulator, by analogizing with DC machine. Droop control is introduced to achieve multi-parallel operation of ESS. Further, its small signal model is established and the dynamic characteristic of the DC bus voltage during power fluctuation is analyzed. A 2nd-order equivalent model is introduced to simplify the parameters design. By analyzing the control performance indices, the VIDC parameters are optimized. At last, based on the principle of equivalent machine, an inertia matching method of the multi-parallel bi-DC converters is proposed. The simulation results verify that ESS, by acting as a synthetic inertia, can improve the voltage dynamic characteristics and stability in islanded DC-MG. Compared with other control methods, it has better control effect.

The frequency and voltage restoration along with power sharing is imperative for the safe, reliable and stable operation of the islanded AC microgrids (MGs). In this paper, a novel distributed fractional-order predefined-time sliding mode controller (DFOPTSMC) is proposed as a secondary controller for the islanded AC MGs. The proposed DFOPTSMC can ensure that frequency and estimated average voltage (EAV) converge to reference value along with accurate power sharing within a setting predefined time. The fractional calculus algorithm is implemented to design the DFOPTSMC, which increases the degree of freedom of parameter adjustment and greatly enhances the flexibility of the DFOPTSMC. In addition, a distributed predefined-time observer is presented to achieve the EAV within a setting predefined time. The upper bound convergence time of the islanded AC MGs under the proposed DFOPTSMC is directly equal to a tunable parameter, thus overcoming the disadvantages of finite-time control and fixed-time control. The Lyapunov function is applied to present rigorous proof to analyze the stability of the islanded AC MGs under the proposed DFOPTSMC. An islanded AC MG is taken into simulation on the Matlab/Simulink 2021a platform and the experimental platform to test and verify the effectiveness and superior performance of the proposed DFOPTSMC. The results indicate that the proposed DFOPTSMC can significantly enhance the dynamic performances of the islanded AC MGs.

Virtual inertia and damping control (VIDC) improves the stability of DC microgrid (DC-MG). However, the potential positive feedback aggravates low-frequency oscillation induced by the interaction insides control loops, which is explained and solved in this paper. The multi-timescale impedance modelling framework is established to clarify stability mechanism of VIDC and the low-frequency oscillation of VIDC controlled DC-MG. Control loops of different timescales are visualized as independent loop virtual impedance (LVI) elements to form an impedance circuit considering the constant power load (CPL), rather than an all-in-one impedance as the external dynamic representation of power converters. Concrete impedance analysis is performed on LVI to reveal the impedance-shaping effect of control loops intuitively, the physical impedance nature of control parameters and the interaction among different timescale, which illustrates the stability mechanism of VIDC. The low-frequency oscillation ( LC impedance interaction) in voltage- and inertia-loop is elaborated by RLC circuits of LVIs. The potential instability factors, resulting in poor damping against voltage oscillation, are also revealed. Thus, dynamic stability enhancement method is further proposed to compensate for the negative damping caused by positive feedbacks of VIDC and CPL, and super-capacitor is added to alleviate rapid voltage changes. Accordingly, the passivity property of system impedance is strengthened and the stability can be evaluated by Nyquist plot. Finally, the simulation and experiment results have validated the low-frequency oscillation analysis and stability enhancement method.