Graph Partitioning Algorithms for Control of AC Transmission Networks: Generator Slow Coherency, Intentional Controlled Islanding, and Secondary Voltage Control

The vast size of a modern interconnected power grid precludes controlling and operating it as a single object. Subdividing a power grid into a number of internally coherent areas allows to cope with its inherent complexity and to enable more efficient control structures. This thesis focuses on discovering the power system structure to facilitate the definition of control areas for wide-area monitoring, protection and control (WAMPAC) applications. Graph partitioning is a well-developed discipline whose potential is not fully recognized in the power system domain. Particularly, spectral graph partitioning methods are shown to be very promising. Their efficiency is first demonstrated by accurately selecting the number and extent of control zones for secondary voltage control (SVC). Next, it is shown that grouping generators with similar slow rotor angle dynamics can also be efficiently tackled through spectral graph partitioning. The final topic is constrained graph partitioning subject to node grouping constraints, which is related to intentional controlled islanding (ICI). As both solution time and accuracy are critical for ICI, a new polynomial-time heuristic algorithm is proposed that is more accurate than comparable state-of-the-art methods.Intelligent Electrical Power Grid

D-Decomposition Based Robust Discrete-Time Current Regulator for Grid-Connected VSI

The D-decomposition method allows to design control structures with prescribed locations of closed loop poles. Unlike the root locus method, D-decomposition natively handles two variable regulator parameters, which makes it suitable for more complex control structures. Moreover, an extension to more than two variable parameters is straightforward. In this paper, the advantages of the D-decomposition method are illustrated by synthesizing a robust low-order current regulator for a grid-connected voltage source inverter (VSI) with LCL filter. It is shown how to visualize the complete region in the low dimensional regulator parameter space satisfying certain robust performance criteria (with robust stability being a special case). The paper concludes by simulation results validating the robustness properties of the designed low-order regulator under substantial grid impedance variations

D-Decomposition Based Robust Discrete-Time Current Regulator for Grid-Connected VSI

The D-decomposition method allows to design control structures with prescribed locations of closed loop poles. Unlike the root locus method, D-decomposition natively handles two variable regulator parameters, which makes it suitable for more complex control structures. Moreover, an extension to more than two variable parameters is straightforward. In this paper, the advantages of the D-decomposition method are illustrated by synthesizing a robust low-order current regulator for a grid-connected voltage source inverter (VSI) with LCL filter. It is shown how to visualize the complete region in the low dimensional regulator parameter space satisfying certain robust performance criteria (with robust stability being a special case). The paper concludes by simulation results validating the robustness properties of the designed low-order regulator under substantial grid impedance variations.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Intelligent Electrical Power Grid

Synchronized measurement technology supported AC and HVDC online disturbance detection

In electric power system, disturbance detection has become an important part of grid operation and refers to the detection of a voltage and current excursion caused by the wide variety of electromagnetic phenomena. This paper proposes a computationally efficient and robust algorithm for synchronized measurement technology (SMT) supported online disturbance detection, suitable for AC and HVDC grids. The proposed algorithm is based on the robust median absolute deviation sample dispersion measure to locate dataset outliers. The algorithm is capable of identifying the disturbance occurrence and clearance measurement sample based on the dynamic criteria, driven by present power system conditions. The effectiveness of the proposed algorithm is verified by real-time simulations using a cyber-physical simulation platform, as a co-simulation between the SMT supported electric power system model and underlying ICT infrastructure. The presented results demonstrate effectiveness of the proposed algorithm, making it suitable for an AC and HVDC online disturbance detection application or as a pre-step of backup protection schemes.Intelligent Electrical Power Grid

Spectral MST-Based Graph Outlier Detection With Application to Clustering of Power Networks

An increasing number of methods for control and analysis of power systems relies on representing power networks as weighted undirected graphs. Unfortunately, the presence of outliers in power system graphs may have a negative impact on many of these methods. In addition, detecting outliers can be a relevant task on its own. Motivated by the low number of outlier detection algorithms focusing on weighted undirected graphs, this paper proposes an efficient and effective method to detect loosely connected graph clusters below a certain number of nodes. The essence of the method lies in the efficient examination of the spectral minimal spanning tree of the input graph. The obtained results on several large test power networks validate the high outlier detection performance of the proposed method and its high computational efficiency.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Intelligent Electrical Power Grid

Implementation of slow coherency based controlled islanding using DIgSILENT powerfactory and MATLAB

Intentional controlled islanding is a novel emergency control technique to mitigate wide-area instabilities by intelligently separating the power network into a set of self-sustainable islands. During the last decades, it has gained an increased attention due to the recent severe blackouts all over the world. Moreover, the increasing uncertainties in power system operation and planning put more requirements on the performance of the emergency control and stimulate the development of advanced System Integrity Protection Schemes (SIPS). As compared to the traditional SIPS, such as out-of-step protection, ICI is an adaptive online emergency control algorithm that aims to consider multiple objectives when separating the network. This chapter illustrates a basic ICI algorithm implemented in PowerFactory. It utilises the slow coherency theory and constrained graph partitioning in order to promote transient stability and create islands with a reasonable power balance. The algorithm is also capable to exclude specified network branches from the search space. The implementation is based on the coupling of Python and MATLAB program codes. It relies on the PowerFactory support of the Python scripting language (introduced in version 15.1) and the MATLAB Engine for Python (introduced in release 8.4). The chapter also provides a case study to illustrate the application of the presented ICI algorithm for wide-area instability mitigation in the PST 16 benchmark system.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Intelligent Electrical Power Grid

Slow Coherency Identification and Power System Dynamic Model Reduction by using Orthogonal Structure of Electromechanical Eigenvectors

Identifying generator coherency with respect to slow oscillatory modes has numerous power system use cases including dynamic model reduction, dynamic security analysis, or system integrity protection schemes (e.g., power system islanding). Despite their popularity in both research and industry, classic eigenvector-based slow coherency techniques may not always return accurate results. The multiple past endeavors to improve their accuracy often lack a solid mathematical foundation. Motivated by these deficiencies, we propose an alternative consistent approach to generator slow coherency. Firstly, a new approach is introduced to accurately detect slow coherent generators by effectively minimizing generic normalized cuts. As a by-product, the new approach can also guide the choice of the number of slow coherent groups. Secondly, it is shown that the combination of the the proposed slow coherency approach and an enhanced version of the inertial generator aggregation method allows to produce accurate dynamic equivalents even if the selected number of generator groups is relatively low.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Intelligent Electrical Power Grid

Discovering Clusters in Power Networks from Orthogonal Structure of Spectral Embedding

This paper presents an integrated approach to partition similarity graphs, the task that arises in various contexts in power system studies. The approach is based on orthogonal transformation of row-normalized eigenvectors obtained from spectral clustering to closely fit the axes of the canonical coordinate system. We select the number of clusters as the number of eigenvectors that allows the best alignment with the canonical coordinate axes, which is a more informative approach than the popular spectral eigengap heuristic. We show a link between the two relevant methods from the literature and on their basis construct a robust and time-efficient algorithm for eigenvector alignment. Furthermore, a graph partitioning algorithm based on the use of aligned eigenvector columns is proposed, and its efficiency is evaluated by comparison with three other methods. Lastly, the proposed integrated approach is applied to the adaptive reconfiguration of secondary voltage control (SVC) helping to achieve demonstrable improvements in control performance.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Intelligent Electrical Power Grid

Implementation of slow coherency based controlled islanding using DIgSILENT powerfactory and MATLAB

Intentional controlled islanding is a novel emergency control technique to mitigate wide-area instabilities by intelligently separating the power network into a set of self-sustainable islands. During the last decades, it has gained an increased attention due to the recent severe blackouts all over the world. Moreover, the increasing uncertainties in power system operation and planning put more requirements on the performance of the emergency control and stimulate the development of advanced System Integrity Protection Schemes (SIPS). As compared to the traditional SIPS, such as out-of-step protection, ICI is an adaptive online emergency control algorithm that aims to consider multiple objectives when separating the network. This chapter illustrates a basic ICI algorithm implemented in PowerFactory. It utilises the slow coherency theory and constrained graph partitioning in order to promote transient stability and create islands with a reasonable power balance. The algorithm is also capable to exclude specified network branches from the search space. The implementation is based on the coupling of Python and MATLAB program codes. It relies on the PowerFactory support of the Python scripting language (introduced in version 15.1) and the MATLAB Engine for Python (introduced in release 8.4). The chapter also provides a case study to illustrate the application of the presented ICI algorithm for wide-area instability mitigation in the PST 16 benchmark system.</p