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.

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.

Although the photovoltaic (PV) integrated dc-busbar electric vehicle charging station (EVCS) is a promising energy supply form for EVs, its inertialess and poor damping always lead to the potential system instability. In this article, inertia droop control (IDC) strategies are, thus, proposed for a bidirectional dc converter (Bi-C) to improve dynamic stability and provide a high-quality power supply for EVs. Compared with the virtual inertia and damping control (VIDC), the proposed IDC can be implemented by easily modifying conventional droop control, avoiding complex control structures. First, virtual inertia is achieved in the proposed IDC strategies in two ways: 1) dynamic virtual impedance and 2) adaptive droop algorithm. Damping support comes from the redesigned damping term featuring secondary voltage regulation to eliminate the voltage deviation. Then, a feedback analytic method is proposed to comprehend stability mechanisms from multiview, and a double-coordinate-based phasor diagram is developed as its analytical tool to observe the interaction among variables intuitively. Accordingly, IDC’s negative feedback property is revealed, and the impactors of system inertia, stiffness, and dissipation properties are explored. Dynamic performance and small-signal stability analysis are also presented to guide parameter selection and optimize the transient response. Experiment results verify that IDC has similar effects to VIDC while simplifying the control structure.

Taking actual engineering as a case study, this article provides a novel scheme of applying the inductive power filtering method (IPFM) to resolve the harmonic resonance issues in large-scale photovoltaic (PV) plant. By using IPFM's special structure and dual zero-impedance design, the impedance network of large-scale PV plant is reshaped while the performance of power filters is improved, so that the harmonic resonance due to the interaction between the inverters and the power grid is suppressed. First, the topology and components of the IPFM-based large-scale PV plant are introduced. The three-phase mathematical model in harmonic domain is then established. Based on the deduced transfer matrix, the simplified circuit of the studied large-scale PV plant is obtained. Moreover, the IPFM's resonance damping mechanisms on resonant frequency shift and harmonic amplification mitigation are analyzed. Both simulation and engineering tests verify the feasibility of the proposal.

This paper proposes an inertia‐emulation‐based cooperative control strategy for the multi‐parallel energy storage system (ESS) to meet the requirements of state‐of‐charge (SoC) balance, inertia enhancement and zero‐steady‐state voltage deviation. The inertia emulation loop (IEL) is constructed by analogy with DC motors to dampen voltage oscillation, while the secondary voltage recovery loop is derived from the circuit equivalence of an inductor to indicate the system stiffness. Moreover, to equalize SoCs of energy storage units (ESUs) dynamically, a SoC self‐balance algorithm is developed. The redefined SoC mismatch degree and balance speed adjustment factor k are introduced into the droop resistance, adjusting the SoC self‐balance rate and eliminating the SoC deviation among ESUs. The dynamic performance of the SoC self‐balance algorithm is analyzed and the small signal model of the DC microgrid (DC‐MG) with proposed strategy is established. Based on eigenvalue analysis and step response, the system stability is assessed, and the influence of control parameters on transient characteristics and stability margin is investigated. Considering power constraint, voltage deviation constraint and dynamic stability constraint, the optimal design method of k is given. Finally, simulation and experiment verify that the proposed control, without modifying hardware, performs better dynamic and static characteristics and can equalize SoC among ESUs in charge and discharge mode.