Efficiency-Prioritized Droop Control Strategy of AC Microgrid

Yuan, Wenbin; Li, Han; Liu, Dong; Deng, Fujin; Chen, Zhe

doi:10.1109/jestpe.2020.2967756

Cited by 40 publications

(35 citation statements)

References 35 publications

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“…P oi is the active power of the i-th DG. And Ploss_i is the power loss caused by converter including conduction loss and switching loss of the semiconductors as well as the power loss on filter inductors, which is a function of output power as [9]:…”

Section: A Operation Characteristic Modellingmentioning

confidence: 99%

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New Perspectives on Power Control of AC Microgrid Considering Operation Cost and Efficiency

Yuan

Chen

2021

IEEE Trans. Power Syst.

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This letter presents new perspectives on power control for AC microgrid considering operation cost and efficiency simultaneously. A multi-objective optimization model is first established. Then optimal operation conditions are derived by Lagrange Multiplier Method. Furthermore, a selfoptimization droop control strategy with subject to optimal operation conditions is proposed to improve the overall operation performance. Simulation and experimental results validate the effectiveness of the proposed optimization method and selfoptimization droop control strategy.

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Section: A Operation Characteristic Modellingmentioning

confidence: 99%

“…In [5]- [6], the inverter scheduling strategy is developed to improve the system efficiency by optimizing the number of operating inverters. In addition, several efforts have been made to improve system efficiency by dynamically regulating power sharing in DC microgrid [7]- [8] and AC microgrid [9].…”

Section: Introductionmentioning

confidence: 99%

New Perspectives on Power Control of AC Microgrid Considering Operation Cost and Efficiency

Yuan

Chen

2021

IEEE Trans. Power Syst.

Self Cite

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“…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]. The earliest method to deal with this problem is droop control, but due to the droop coefficient, there is always a certain deviation in the process of voltage and frequency regulation [10,11]. Therefore, on this basis, centralized [12], decentralized [13] and distributed [14] secondary control ideas are put forward, through the secondary control signal to adjust the voltage and frequency deviation.…”

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 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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“…In addition, inequality and asymmetry in feeder or cable impedance, which is a common problem in distribution networks, as well as the output impedance of DGs, make it challenging to precisely control the reactive power in an islanding mode. Another major problem of conventional droop control is its inability to distribute nonlinear loads and unbalanced loads considering multiple DGs [10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

“…In order to solve the problem of resistive networks, the reverse droop control method using the P-V and Q-f droop characteristics is proposed. The control approach proposed in [10] provide a reverse control method that allows multiple voltage source converters to operate in parallel in a MG. The proposed algorithm works well in both grid connected and islanding modes.…”

Section: Introductionmentioning

confidence: 99%

Droop Method Development for Microgrids Control Considering Higher Order Sliding Mode Control Approach and Feeder Impedance Variation

et al. 2021

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Due to the growing power demands in microgrids (MGs), the necessity for parallel production achieved from distributed generations (DGs) to supply the load required by customers has been increased. Since the DGs have to procure the demand in parallel mode, they are faced with several technical and economic challenges, such as preventing DGs overloading and not losing network stability considering feeder impedance variation. This paper presents a method that upgrades the droop controller based on sliding mode approach, so that DGs are able to prepare a suitable reactive power sharing without error even in more complex MGs. In the proposed strategy, the third-order sliding mode controller significantly reduces the V-Q error and increases the accuracy in adjusting the voltage at the DG output terminals. Various case studies conducted out in this paper validate the truthfulness of the proposed method, considering the stability analysis using Lyapunov function. Finally, by comparing the control parameters of the proposed technique with existing methods, the superiority, simplicity and effectiveness of the 3rd order sliding mode control (SMC) method are determined.

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Efficiency-Prioritized Droop Control Strategy of AC Microgrid

Cited by 40 publications

References 35 publications

New Perspectives on Power Control of AC Microgrid Considering Operation Cost and Efficiency

New Perspectives on Power Control of AC Microgrid Considering Operation Cost and Efficiency

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

Droop Method Development for Microgrids Control Considering Higher Order Sliding Mode Control Approach and Feeder Impedance Variation

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