Energy function for a grid-tied, droop-controlled inverter

Hart, Philip J.; Lesieutre, Bernard C.

doi:10.1109/naps.2014.6965437

Cited by 50 publications

(21 citation statements)

References 4 publications

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“…Construct the corresponding matrix A ii and matrix B vv according to the MPF theory. A ii and B vv are expressed in (17) and (18), respectively (18) where k p2 is the proportional coefficient of the PI control in the inverter link, k p4 is the proportional coefficient of the PI control in the rectification link; k p is the proportional coefficient of the PI control in the DC/DC link, ∂ 2 B(v)/∂u dl 2 is shown in (11); other parameters are consistent with those in Fig. 7.…”

Section: Stability Criterion Derivation Of Single-pet Distribution Nesupporting

confidence: 66%

“…The matrix A ii and matrix B vv of the single-PET distribution network are given in (17) and (18), respectively. The minimum eigenvalue of the matrix L −1/2 A ii L −1/2 is easy to be determined as…”

Section: Influence Of Pi Control Gain On System Stabilitymentioning

confidence: 99%

“…It is difficult to directly establish the Lyapunov function of power electronic devices. To tackle this problem, the inverter was transformed to a synchronous machine to establish the Lyapunov function in [16]; the TS (Takagi-Sugeno) fuzzy model method and genetic algorithm were used to establish the Lyapunov function of the DC power supply system with constant power load in [17]. Yet in these research studies, derivation of the Lyapunov function were cumbersome, and the stability criterion was not obtained in an analytical form.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Large‐disturbance stability analysis method based on mixed potential function for AC/DC hybrid distribution network with PET

Zhao

Zheng

Han

et al. 2020

IET Generation, Transmission & Distribution

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Section: Stability Criterion Derivation Of Single-pet Distribution Nesupporting

confidence: 66%

Section: Influence Of Pi Control Gain On System Stabilitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Large‐disturbance stability analysis method based on mixed potential function for AC/DC hybrid distribution network with PET

Zhao

Zheng

Han

et al. 2020

IET Generation, Transmission & Distribution

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“…Although some attempts have been done in order to determine the energy function of a system, there is no straight method in order to define it [15,29]. In most cases, PE-based units are considered as energy sources that are coupled into the main systems [9,31]. In order to find the energy function for the PE-based units, the synchronous machine equivalent of the VSC is defined in [32].…”

Section: Computation Complexitymentioning

confidence: 99%

Large-Signal Stability Modeling for the Grid-Connected VSC Based on the Lyapunov Method

et al. 2018

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In this paper, a Lyapunov-based method is used in order to determine the stability boundaries of the grid-connected voltage source converter (VSC). To do so, a state space model of the VSC is used to form the Lyapunov function of the system. Then, by using the eigenvalues of the Lyapunov function, the system stability boundaries will be determined. It is shown that the grid-connected VSC works in its stable mode when all of its Lyapunov function’s eigenvalues are positive. The proposed model validity is tested by time-domain simulation. Simulation results show that the method is credible in determining the stability margin of the grid-connected VSC.

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“…9a is the average power obtained from the original instantaneous power with a low-pass filtering process. It should be noted that using the average power obtained through the low-pass filtering is a common practice for droop-controlled DGs in controlling an MG [36][37][38], which helps to mitigate the impact of load unbalance and harmonic distortion on the droop control algorithms. Fig.…”

Section: Robustness Testmentioning

confidence: 99%

Agent‐based distributed and economic automatic generation control for droop‐controlled AC microgrids

Zang

Zeng

et al. 2016

IET Generation, Transmission & Distribution

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Microgrids (MGs) are presented as a cornerstone of smart grid, which can integrate renewable energy sources environmentally, friendly, and reliably. Hierarchical control strategies, i.e. primary droop control, second automatic generation control (AGC), and tertiary economic dispatch (ED), are widely used to control and optimise an MG. However, the gap between large time-scale ED and small time-scale AGC may decrease the economical efficiency of an MG. To address this problem, this study proposes a distributed economic AGC (EAGC) algorithm. The algorithm is fully distributed, as each distributed generator is assigned with an agent and the agents only require the local measurements and communication with its neighbours. Compared with centralised algorithms, the distributed control algorithm is easy to fulfil the plug-and-play requirements and reduces costs to modify the architecture of an MG. Furthermore, the proposed EAGC algorithm is suitable for all possible operation modes of an MG, i.e. islanded mode, grid-connected mode, and transition mode. To improve the robustness against agent loss or communication link fault, the topology of agents' communication network is designed to satisfy the N − 1 rule. The effectiveness of the proposed algorithm is demonstrated through the simulation tests which involve plenty of case studies.

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Energy function for a grid-tied, droop-controlled inverter

Cited by 50 publications

References 4 publications

Large‐disturbance stability analysis method based on mixed potential function for AC/DC hybrid distribution network with PET

Large‐disturbance stability analysis method based on mixed potential function for AC/DC hybrid distribution network with PET

Large-Signal Stability Modeling for the Grid-Connected VSC Based on the Lyapunov Method

Agent‐based distributed and economic automatic generation control for droop‐controlled AC microgrids

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