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Item type:Publication, Access status: without files , Resilience of smart integrated energy systems(Springer, 2023-08-05); ; ; ; Energy systems, particularly power systems as critical infrastructures, are of supreme importance to society. The current significant developments, namely evolving producer and consumer characteristics (e.g., volatile and hard-to-predict renewables), higher growth of sector-coupling solutions, and on top, sophisticated control and digitalization solutions – transforming the energy systems into a complex cyber-physical system of systems – jeopardize the operation of the overall system. If it fails to make the new energy system as robust and resilient as the current system, the consequences can be drastic and a threat to society. This chapter defines the resilience concept and presents the current practices and methods to evaluate and enhance the resilience of smart energy systems. To this end, after providing a comprehensive background to the paradigm shift, resilience metrics suggested by communities such as IEEE and Cigré are presented – focusing mainly on power systems. A multi-domain approach that outlines resilience indexes for heat, gas, and electricity sectors is also presented to as a more holistic methodology. In addition, it is explained how emerging technologies such as digital twins and artificial intelligence can support the evaluation of system resilience. This chapter also motivates key resilience strategies and addresses the state-of-art approaches in two important categories: (1) situational awareness and system knowledge and (2) operational flexibility and adaptive mechanism. Different examples of these categories, such as anomaly-aware monitoring systems, software-defined networking, and cellular concepts, are provided here – from mutually cyber and physical viewpoints.Publicationtype: Book part44 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Reliability-sensitive optimization for provision of ancillary services by tempo-spatial correlated distributed energy resourcesIn this paper, a reliability-sensitive optimization approach for the provision of ancillary services from distributed energy resources is proposed. The main focus here is on small-scale renewable energy sources such as wind turbines and PV arrays, which are highly distributed, and the generated power is weather dependent and intermittent. Therefore, providing a reliable ancillary service through these unreliable resources is a complicated problem addressed here. In this paper, the tempo-spatial correlation between these renewable resources is mathematically modeled by pair-copula functions and included in the reliability evaluation procedure using the non-sequential Monte Carlo simulation method. An optimization problem is formulated using proposed joint reliability model to find the minimum number of renewable resources to provide ancillary services within a desired reliability level. The proposed optimization model is applied to real wind farms in Lower Saxony in Germany to provide the spinning reserve service. The results prove that including the correlation concept in the reliability evaluation procedure leads to the more realistic scenarios that play an essential role in maintaining the service’s reliability level.Publicationtype: Conference Paper22 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , A comprehensive analysis of threats and countermeasures in virtualized cyber-physical energy systems(Institution of Engineering and Technology (IET), 2021-09); ; ; High integration of distributed energy resources raises the challenge of reliable operation to power system operators. In order to improve the ability to monitor and control power systems, automation systems are necessary. However, the operational flexibility of automation systems to deal with abnormal situations is currently limited. In this regard, virtualization as a key enabling technology to improve the operational flexibility in Cyber-Physical Energy Systems has been proposed. To this end, grid services (e.g. state estimation, coordinated voltage control), which are traditionally bound to hardware, are separated from underlying computation platforms. This provides modularity and isolation of grid services, which enables monitoring, managing and deploying them independently. However, virtualizing grid services, resulting in increased system complexity, can cause new security concerns. This paper analyzes virtualized Cyber-Physical Energy Systems from a security viewpoint and identifies associated security threats. Based on security requirements and potential solutions addressed by IEC 62351 security standard, a set of studies is conducted to analyze the effect of traditional security mechanisms, when applied to virtualized Cyber-Physical Energy Systems. Finally, possible software solutions and recommendations that protect the system against threats are proposed. Future research directions and open problems are stated at the end.Publicationtype: Conference Paper27 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Model identification and parameter tuning of dynamic loads in power distribution grid: Digital twin approachWith the ongoing changes in power systems, not only on the generation side but also on the load side, new approaches are necessary to monitor and control power systems. Therefore, this paper investigates the Digital Twin technology for power system loads with a novel parameter identification method based on Bayesian Inference. A framework for load model Digital Twins is proposed based on an existing model, and a novel approach to load model identification is investigated and compared to existing methods. Even though Bayesian Inference relies on prior knowledge of the model, compared to other approaches, it returns a Probability Density Function for the whole model and each model parameter and fares very well with sparse data as well as an increased level of measurement noise. The results promise to use Bayesian Inference as the primary identification method for a Digital Twin as proposed in this paper. This Digital Twin framework can be utilized to overcome new challenges arising for power system control and monitoring.Publicationtype: Conference Paper67 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Performance Assessment of State Estimation in Cyber-Physical Energy Systems(2021-06-28); ; ; ; In addition to various advantages, the strong interaction between power systems and Information and Communication Technologies (ICT) makes Cyber-Physical Energy Systems susceptible to new disturbances. State estimation (SE) is a vital part of the energy management system, for several other monitoring, management, and control services. Failure of state estimation leads to loss of situational awareness, which in turn has a detrimental impact on the grid operation. Therefore, it is essential to monitor the performance of state estimation considering various disturbances. This paper presents a model to assess the performance of the SE service by taking into consideration its requirements from both power and ICT domains. Following a review of existing approaches for performance assessment of the SE service in Smart Grids, a detailed description of the proposed model including its elements, metrics, and states is provided. The model is then evaluated using different scenarios considering the CIGRE MV benchmark grid.Publicationtype: Conference Paper45 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Power Systems Digital Twin under Measurement and Model Uncertainties: Network Parameter Tuning ApproachThis paper addresses how a power system Digital Twin (DT) can be structured, what it should be able to do, and how it can possibly be implemented with already known methods. To this end, a structural framework for the design of power system DTs is presented. The framework consists of functional blocks such as model execution and model validation, with which the core of the DT, the virtual entity, is be built. Subsequently, a power system DT has been studied. Here, established approaches of state and parameter estimation like the weighted least squares or extended Kalman filter have been used as parts of the functional blocks. Combined they form an adaptive model of the physical system, which can be used in the framework. In particular, it turns out that under certain circumstances the accuracy of potential sensor measurement data may not be sufficient to realize the described methods under field conditions.Publicationtype: Conference Paper74 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Wind Turbine Failure Prediction Model using SCADA-based Condition Monitoring SystemThe ultimate goal of a condition monitoring system for wind turbines (WT) is to predict the upcoming failures; this could be achieved using artificial intelligence techniques. In this paper, a model for detecting excessive temperature anomalies in key components of WT i.e. gearbox, generator and transformer is proposed. This model consists of integrated modules continuously interact following the never-ending learning paradigm based on artificial neural networks addressing the challenge of the limited pre-classified data and lacking of the concept to be learned for a system with continuous change of its operating conditions: (i) the Normal Behavior (NB) module estimates the temperature of the WT key components, (ii) the Expected Time To Failure (ETTF) module calculates the deviation between the estimated normal temperature and the real-time measurement data to predict the upcoming failure of WT key components a few hours before occurring a failure, (iii) in the Anomaly Detection (AD) module, the temperature deviation time series signal is divided into normal or abnormal clusters. The proposed methodology has been applied on a real wind farm data in Germany. The results show that the system could correctly detect a large number of WT upcoming failures, this implies the effectiveness and generalization of the proposed model in terms of classification accuracy.Publicationtype: Conference Paper99 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Real-time Test Platform for Enabling Grid Service Virtualisation in Cyber Physical Energy System(2020-09-01); ; ; ; The challenge of reliable operation in Cyber-Physical Energy Systems (CPES) is constantly increasing due to more participating actors and associated disruptive events. The supporting automation systems for monitoring, communication and control is a vital part for reliable operation, realized by grid services such as voltage control, frequency control, system restoration. However, to ensure the availability of these services during and after disruptive events is challenging. Management technologies such as virtualization are key drivers to provide the necessary flexibility to reallocate, orchestrate and update such grid services. This paper introduces a multidisciplinary real-time test platform for integration of grid service management in CPES. Furthermore, a detailed description of the test environment including real-time power system simulation, communication system simulation, grid virtualisation management kit and virtualized hardware-software components are provided. Finally, the test platform is evaluated by a set of scenarios for modified CIGRE MV grid and its communication infrastructure.Publicationtype: Conference Paper42 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Grid function virtualization for reliable provision of services in cyber-physical energy systems(IEEE, 2020-08); ; ; ; Provision of grid services in modern power systems is highly dependent on their automation systems for monitoring, communication and decision making. These automation systems are vital for the reliable operation of the grid during and after disruptive events. This papers explores the concept of Grid Function Virtualization (GFV) as a potential approach to enhance the operational flexibility of grid automation systems. To this end, a review on applications of virtualization in related domains including smart grids is presented. Furthermore, the GFV architecture along with its building blocks is discussed. The benefits of the proposed GFV concept in dealing with power system disruptions is then demonstrated via real time simulations with an ICT-enriched CIGRE MV benchmark grid.Publicationtype: Conference Paper52 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Virtualization management concept for flexible and fault-tolerant smart grid service provision(2020-05-02); ; ; ; In modern power systems, reliable provision of grid services (e.g., primary and ancillary services) are highly dependent on automation systems in order to have monitoring, processing, decision making and communication capabilities. The operational flexibility of automation systems is essential for the reliable operation of power systems during and after disruptive events. However, this is restricted by integrated hardware-software platforms. Therefore, it will be difficult to reconfigure control strategies during run time. This paper presents the concept of Grid Function Virtualization (GFV) as a potential approach to improve the operational flexibility of grid automation systems. GFV has been proposed to offer a new way to deploy and manage grid services by leveraging virtualization technology. The main idea of GFV is to run grid services (i.e., software implementation of services) independently from underlying hardware. To realize the important design considerations, the GFV architecture and its building blocks is elaborated in details. To this end, an exhaustive review of applications of virtualization in several domains is provided to show the importance of virtualization in improving flexibility and resource utilization. Finally, the advantages of the proposed concept to deal with disruptions in power systems is demonstrated in a proof of concept based on a CIGRE MV benchmark grid.Publicationtype: Journal Article45