Time delay effects in the control of synchronous electricity grids

Böttcher, Philipp; Otto, Andreas; Kettemann, Stefan; Agert, Carsten

doi:10.1063/1.5122738

Cited by 19 publications

(8 citation statements)

References 43 publications

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“…While both the power-grid frequency dynamics and the stochastic nature of the power-grid frequency have been intensely studied, we require a better understanding of the interaction of frequency dynamics with both stochastic fluctuations and market behaviour. The dynamics of the power-grid variables, including frequency, voltage, reactive power, etc., may be modelled with arbitrary complexity based on various models [7,10,[15][16][17][18]. Simultaneously, stochastic modelling of fluctuations within the power grid [17,19] still often uses Gaussian noise models [13,20,21], while non-Gaussian statistics [8,22] as well as deterministic events caused by trading [23] are rarely included.…”

Section: Introductionmentioning

confidence: 99%

Data-Driven Model of the Power-Grid Frequency Dynamics

et al. 2020

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The energy system is rapidly changing to accommodate the increasing number of renewable generators and the general transition towards a more sustainable future. Simultaneously, business models and market designs evolve, affecting power-grid operation and power-grid frequency. Problems raised by this ongoing transition are increasingly addressed by transdisciplinary research approaches, ranging from purely mathematical modelling to applied case studies. These approaches require a stochastic description of consumer behaviour, fluctuations by renewables, market rules, and how they influence the stability of the power-grid frequency. Here, we introduce an easy-to-use, data-driven, stochastic model for the power-grid frequency and demonstrate how it reproduces key characteristics of the observed statistics of the Continental European and British power grids. We offer executable code and guidelines on how to use the model on any power grid for various mathematical or engineering applications.

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Section: Introductionmentioning

confidence: 99%

Data-Driven Model of the Power-Grid Frequency Dynamics

et al. 2020

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“…These control mechanisms and operational boundaries are especially interesting when designing new grids involving concepts such as smart grids [8], prosumers [9], or microgrids [10], and their interaction with the grid frequency. Furthermore, due to the increased usage of renewable energies, synchronous machines are replaced by power electronics, such as inverters, posing additional challenges on ensuring frequency stability [11]. Inverterbased generators do not have any innate inertia, leading to the frequency of the power grid becoming more volatile, unless additional stabilisers are included in the system [12].…”

Section: Introductionmentioning

confidence: 99%

Stochastic properties of the frequency dynamics in real and synthetic power grids

Anvari

Gorjão

Timme

et al. 2020

Phys. Rev. Research

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The frequency constitutes a key state variable of electrical power grids. However, as the frequency is subject to several sources of fluctuations, ranging from renewable volatility to demand fluctuations and dispatch, it is strongly dynamic. Yet, the statistical and stochastic properties of the frequency fluctuation dynamics are far from fully understood. Here, we analyse properties of power grid frequency trajectories recorded from different synchronous regions. We highlight the non-Gaussian and still approximately Markovian nature of the frequency statistics. Further, we find that the frequency displays significant fluctuations exactly at the time intervals of regulation and trading, confirming the need of having a regulatory and market design that respects the technical and dynamical constraints in future highly renewable power grids. Finally, employing a recently proposed synthetic model for the frequency dynamics, we combine our statistical and stochastic analysis and analyse in how far dynamically modelled frequency properties match the ones of real trajectories.

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“…Characterized by a large share of volatile distributed generation units, e.g., solar or wind power plants, future energy networks will require novel control approaches such as grid-forming power inverters to maintain stability [22,23]. As this involves measurements and processing, delays are expected to play a critical role [24][25][26]. Understanding their influence on stability is thus vital to ensure security of supply and prevent blackouts.…”

Section: Main Applicationmentioning

confidence: 99%

Delay master stability of inertial oscillator networks

Börner

Schultz

Ünzelmann

et al. 2020

Phys. Rev. Research

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Time lags occur in a vast range of real-world dynamical systems due to finite reaction times or propagation speeds. Here we derive an analytical approach to determine the asymptotic stability of synchronous states in networks of coupled inertial oscillators with constant delay. Building on the master stability formalism, our technique provides necessary and sufficient delay master stability conditions. We apply it to two classes of potential future power grids, where processing delays in control dynamics will likely pose a challenge as renewable energies proliferate. Distinguishing between phase and frequency delay, our method offers an insight into how bifurcation points depend on the network topology of these system designs.

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Time delay effects in the control of synchronous electricity grids

Cited by 19 publications

References 43 publications

Data-Driven Model of the Power-Grid Frequency Dynamics

Data-Driven Model of the Power-Grid Frequency Dynamics

Stochastic properties of the frequency dynamics in real and synthetic power grids

Delay master stability of inertial oscillator networks

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