Seamless switching power sharing control method in a hybrid DC‐AC microgrid by the isolated two‐stage converter based on SST

Li, Yue; Peng, Yonggang; Wang, Xiaoming

doi:10.1049/pel2.12135

Cited by 4 publications

(4 citation statements)

References 27 publications

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“…By substituting the secondary control signal obtained in (4) into (5), ω n,i and v n,i can be acquired. As shown in Figure 2, the above control signals are applied to the inverter-based DG control framework (Figure 2) to realize the overall regulation of AC microgrid.…”

Section: Secondary Frequency Controlmentioning

confidence: 99%

“…The microgrid, as the newly emerging and rapidly developing smart grid, has good integration capability, namely, it can integrate the energy generated by various small distributed energy systems and power generation equipment [1][2][3]. Therefore, it is often used in parallel power grids and isolated power grids [4,5]. In general, such a problem needs to be solved in the operation of AC microgrids, namely, adjusting the voltage and frequency of all DGs to be the same as that of the total grid [6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

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Self-Triggered Model Predictive Control of AC Microgrids with Physical and Communication State Constraints

Dong

Gan

et al. 2022

Energies

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In this paper, we investigate the secondary control problems of AC microgrids with physical states (i.e., voltage, frequency and power, etc.) constrained in the process of actual control, namely, under the condition of state constraint. On the basis of the primary control (i.e., droop control), the control signals generated by distributed secondary control algorithm are used to solve the problems of voltage and frequency recovery and power allocation for each distributed generators (DGs). Therefore, the model predictive control (MPC) with the mechanism of rolling optimization is adopted in the second control layer to achieve the above control objectives and solve the physical state constraint problem at the same time. Meanwhile, in order to reduce the communication cost, we designed the self-triggered control based on the prediction mechanism of MPC. In addition, the proposed algorithm of self-triggered MPC does not need sampling and detection at any time, thus avoiding the design of observer and reducing the control complexity. In addition, the Zeno behavior is excluded through detailed analysis. Furthermore, the stability of the algorithm is verified by theoretical derivation of Lyapunov. Finally, the effectiveness of the algorithm is proved by simulation.

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Section: Secondary Frequency Controlmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Self-Triggered Model Predictive Control of AC Microgrids with Physical and Communication State Constraints

Dong

Gan

et al. 2022

Energies

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“…In order to verify the effectiveness of the proposed control method and the correctness of the parameter analysis conclusion, a DC microgrid hardware in loop test platform has been built [23], as shown in Figure 8. The system is composed of RT-LAB real-time simulator, an actual digital signal processor (DSP) controller and a host computer.…”

Section: Hardware In the Loop Experimental Verificationmentioning

confidence: 99%

Entropy weight and grey relational analysis based virtual capacitance collaborative control for multiple energy storage units

Wang

Zhao

Meng

et al. 2022

IET Power Electronics

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Flexible virtual capacitance control (FVCC) for converter can improve the stability and dynamics of DC bus voltage, but among multiple converters, essential inertia distribution is capable of optimizing the performance. To improve the rationality of inertia distribution, a virtual capacitance collaborative control (VCCC) strategy for multiple energy storage units (ESUs) is proposed. Firstly, the system required total inertia is adjusted according to each individual battery's rated capacity and state‐of‐charge (SOC). Then comes the establishment of an evaluation mechanism, which takes the accounts of battery SOC margin, converter power margin and battery power regulation speed. The entropy weight and grey relational analysis are used to calculate each ESU's distribution coefficient and then adjust their virtual capacitance in real‐time. The results show that the adjustment and distribution of the total inertia are beneficial to controlling the SOC of the batteries within the safe range. The ESU with the smallest converter power margin or the slowest battery power regulation speed supports least virtual inertia, which can reduce the problems such as overload protection action or auxiliary power limitation, so as to improve the cooperative control effects. Finally, the effectiveness of the proposed control strategy is verified by hardware‐in‐the‐loop (HIL) simulation experiments.

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“…The multiple operating modes of the converter are integrated into a single functional loop in Ref. [20], which enhances the stability of the system and reduces transient fluctuations during mode switching. In Ref.…”

Section: Introductionmentioning

confidence: 99%

Improved Droop Control Strategy of Multiple Energy Storage Applications in an AC Microgrid Based on the State of Charge

Wang

2021

Electronics

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Distributed energy storage technology is used to stabilize the frequency and voltage of the microgrid operating in islanded mode. However, due to the inconsistent state of charge (SoC) of the energy storage unit (ESU), the active power output of the ESU cannot be shared reasonably. On the basis of stabilizing voltage and frequency, this paper presents a power exponential function droop control (PEFDC) strategy considering the SoC. In this control strategy, the ESU is allowed to adjust the output power adaptively according to its own SoC level during discharge and reaches SoC equilibrium. Simulation models are built to compare the PEFDC strategy with conventional droop control (CDC) and power function droop control (PFDC) approaches. The simulation results illustrate the superiority of the proposed control strategy over the other two methods. Finally, the hardware-in-the-loop experiment is conducted to verify the effectiveness of the PEFDC strategy.

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Seamless switching power sharing control method in a hybrid DC‐AC microgrid by the isolated two‐stage converter based on SST

Cited by 4 publications

References 27 publications

Self-Triggered Model Predictive Control of AC Microgrids with Physical and Communication State Constraints

Self-Triggered Model Predictive Control of AC Microgrids with Physical and Communication State Constraints

Entropy weight and grey relational analysis based virtual capacitance collaborative control for multiple energy storage units

Improved Droop Control Strategy of Multiple Energy Storage Applications in an AC Microgrid Based on the State of Charge

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