Analysis of hunting phenomena in power systems by means of electrical analogues

Shen, D. W. C.; Packer, Jeanette S.

doi:10.1049/pi-2.1954.0005

Cited by 4 publications

(6 citation statements)

References 11 publications

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“…We model the dynamics of each conventional generator using the standard swing equations [13], [14]. We denote the frequency of each generator by ω i which evolves according to θi = ω i , (1a)…”

Section: A Generators and Loadsmentioning

confidence: 99%

“…0 ) is the unique allocation that minimizes the steady state cost (13) subject to (12), where ∆P := n i=1 p in i + q r,0 i − D i ω * 0 . Proof: We start by characterizing the optimal solution of minimizing (13) subject to (12). Since the problem has a strictly convex objective with linear constraints then there is a unique solution that is characterized by the Karush-Kuhn-Tucker (KKT) conditions for optimality [28].…”

Section: A Steady State Performancementioning

confidence: 99%

“…On the one hand, while Theorem 1 shows indeed that droop control can be used to optimally allocate resources by carefully setting the parameters R r i = α r i and R g i = α g i , this tie between control parameters and economic efficiency makes it impossible to further improve the dynamic performance without incurring on an additional steady state cost (13). Therefore, if one wants to operate the system in an efficient steady state, then R r i cannot be used to improve the dynamic performance.…”

Section: The Need For a Better Solutionmentioning

confidence: 99%

“…We now show that our iDroop controllers provide the same steady state properties as traditional droop control. We do this by showing that iDroop achieves the minimum SS-Cost (13).…”

Section: A Steady State Optimalitymentioning

confidence: 99%

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iDroop: A Dynamic Droop controller to decouple power grid's steady-state and dynamic performance

Mallada

2016

2016 IEEE 55th Conference on Decision and Control (CDC)

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This paper presents a novel Dynam-i-c Droop (iDroop) control mechanism to perform primary frequency control with gird-connected inverters that improves the network dynamic performance. The work is motivated by the dynamic degradation experienced by the power grid due to the increase in asynchronous inverted-based generation. We show that the widely suggested virtual inertia solution suffers from unbounded noise amplification (infinite H2 norm) when measurement noise is considered. This suggests that virtual inertia could potentially further degrade the grid performance once broadly deployed.This motivates the proposed solution in this paper that overcomes the limitations of virtual inertia controllers while sharing the same advantages of traditional droop control. In particular, our iDroop controllers are decentralized, rebalance supply and demand, and provide power sharing. Furthermore, our solution can improve the dynamic performance without affecting the steady state solution. Our algorithm can be incrementally deployed and can be guaranteed to be stable using a decentralized sufficient stability condition on the parameter values. We illustrate several features of our solution using numerical simulations. arXiv:1612.05804v1 [math.OC]

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Section: A Generators and Loadsmentioning

confidence: 99%

Section: A Steady State Performancementioning

confidence: 99%

Section: The Need For a Better Solutionmentioning

confidence: 99%

“…We now show that our iDroop controllers provide the same steady state properties as traditional droop control. We do this by showing that iDroop achieves the minimum SS-Cost (13).…”

Section: A Steady State Optimalitymentioning

confidence: 99%

See 2 more Smart Citations

iDroop: A Dynamic Droop controller to decouple power grid's steady-state and dynamic performance

Mallada

2016

2016 IEEE 55th Conference on Decision and Control (CDC)

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“…This input-output decomposition provides a general modeling framework for power system dynamics that encompasses several existing models as special cases. For example, it can include the standard swing equations (Shen and Packer, 1954), as well as several different levels of details in generator dynamics, including turbine dynamics, and governor dynamics, see e.g., (Zhao et al, 2016). The main implicit assumption in Figure 1, which is standard in the literature and well justified in transmission networks (Kundur, 1994), is that voltage magnitudes and reactive power flows are constant.…”

Section: Introductionmentioning

confidence: 99%

Decentralized Robust Inverter-based Control in Power Systems

Pates,

Mallada

2016

Preprint

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This paper develops a novel framework for power system stability analysis, that allows for the decentralized design of inverter based controllers. The method requires that each individual inverter satisfies a standard H ∞ design requirement. Critically each requirement depends only on the dynamics of the components and inverters at each individual bus, and the aggregate susceptance of the transmission lines connected to it. The method is both robust to network and delay uncertainties, as well as heterogeneous network components, and when no network information is available it reduces to the standard decentralized passivity sufficient condition for stability. We illustrate the novelty and strength of our approach by studying the design of inverter-based control laws in the presence of delays.

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Decentralised Robust Inverter-based Control in Power Systems

Pates

Mallada

2017

IFAC-PapersOnLine

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Analysis of hunting phenomena in power systems by means of electrical analogues

Cited by 4 publications

References 11 publications

iDroop: A Dynamic Droop controller to decouple power grid's steady-state and dynamic performance

iDroop: A Dynamic Droop controller to decouple power grid's steady-state and dynamic performance

Decentralized Robust Inverter-based Control in Power Systems

Decentralised Robust Inverter-based Control in Power Systems

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