Dynamic control of intermittent renewableenergy fluctuations in two-layer power grids

Q3 Physics and Astronomy
S. Olmi, Carl H. Totz, E. Scholl
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引用次数: 0

Abstract

In this work we model the dynamics of power grids in terms of a two-layer network, and use the Italian high voltage power grid as a proof-of-principle example. The first layer in our model represents the power grid consisting of generators and consumers, while the second layer represents a dynamic communication network that serves as a controller of the first layer. The dynamics of the power grid is modelled by the Kuramoto model with inertia, while the communication layer provides a control signal Pc i for each generator to improve frequency synchronization within the power grid. We propose different realizations of the communication layer topology and of the control signal, and test the control performances in presence of generators with stochastic power output. When using a control topology that allows all generators to exchange information, we find that a control scheme aimed to minimize the frequency difference between adjacent nodes operates very efficiently even against the worst scenarios with the strongest perturbations. On the other hand, for a control topology where the generators possess the same communication links as in the power grid layer, a control scheme aimed at restoring the synchronization frequency in the neighborhood of the controlled node turns out to be more efficient.
双层电网间歇性可再生能源波动的动态控制
在这项工作中,我们根据两层网络对电网的动态进行建模,并以意大利高压电网为原理验证示例。我们模型中的第一层代表由发电机和消费者组成的电网,而第二层代表作为第一层控制器的动态通信网络。电网的动态由具有惯性的Kuramoto模型建模,而通信层为每个发电机提供控制信号Pc i,以改善电网内的频率同步。我们提出了通信层拓扑和控制信号的不同实现,并测试了在具有随机功率输出的发电机存在的情况下的控制性能。当使用允许所有生成器交换信息的控制拓扑时,我们发现,即使在扰动最强的最坏情况下,旨在最小化相邻节点之间频率差的控制方案也能非常有效地运行。另一方面,对于发电机拥有与电网层中相同的通信链路的控制拓扑,旨在恢复受控节点附近的同步频率的控制方案被证明是更有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Cybernetics and Physics
Cybernetics and Physics Chemical Engineering-Fluid Flow and Transfer Processes
CiteScore
1.70
自引率
0.00%
发文量
17
审稿时长
10 weeks
期刊介绍: The scope of the journal includes: -Nonlinear dynamics and control -Complexity and self-organization -Control of oscillations -Control of chaos and bifurcations -Control in thermodynamics -Control of flows and turbulence -Information Physics -Cyber-physical systems -Modeling and identification of physical systems -Quantum information and control -Analysis and control of complex networks -Synchronization of systems and networks -Control of mechanical and micromechanical systems -Dynamics and control of plasma, beams, lasers, nanostructures -Applications of cybernetic methods in chemistry, biology, other natural sciences The papers in cybernetics with physical flavor as well as the papers in physics with cybernetic flavor are welcome. Cybernetics is assumed to include, in addition to control, such areas as estimation, filtering, optimization, identification, information theory, pattern recognition and other related areas.
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