Exploring Cyber Security Issues and Solutions for Various Components of DC Microgrid System

Nowadays, considering the growing demand for the DC loads and simplified interface with renewable power generation sources, DC microgrids could be cost effective solution for the power supply in small scale area. the supervisory control and data acquisition (SCADA) system maintain the bidirectional power communication through the internet connectivity with the microgrid. However, this intelligent and interactive feature may pose a cyber-security threat to the power grid. this work aims to exploring cyber-security issues and their solutions for the DC microgrid system. To mitigate the adverse effects of various cyber-attacks such as the False Data Injection (FDI) attack, Distributed Denial of Service (DDoS) attack etc., two new techniques based on non-linear and proportional-integral (PI) controllers have been proposed. Simulation results obtained from MATLAB/Simulink software demonstrate the effectiveness of the proposed methods in mitigating the adverse effects of cyber-attacks on the DCMG system performance

Model Predictive Control Design for the Secondary Frequency Control of Microgrid Considering Time Delay Attacks

Fast depleting fossil fuels and growing awareness of environmental protection have raised worldwide concerns, aiming to build a sustainable and smart energy ecosystem. Renewable energy generation plays an important role in providing clean power supply. However, the integration of a bulk renewable generation system would also introduce new forms of disturbances and uncertainties to impact the power quality, threatening the secure operation of the distribution network. Microgrid, as an emerging technology, is quite appealing to be interfaced with distribution systems due to its potential economic, environmental, and technical benefits. The microgrid differs from the “smart grid” with different control strategies to accomplish the goal of helping the power grid with load balancing and voltage control and assisting power markets. A hierarchical control structure for the microgrid is commonly designed to address all above issues both in islanded mode and grid-connected mode. On the other hand, concerns about cybersecurity threats in the microgrid are steadily rising, and enormous number of economic losses would occur if defense strategies are not stipulated and carried out. In the modern power system, distributed control system, intelligent measuring devices and Internet of Things (IoT) are highly recommended in microgrid systems, which lead to the vulnerability of communication channels. Cyber threats such as false data injection (FDI) attacks, denial of service (DoS) attacks, and time-delay switch attacks (TDS) can be effortlessly implemented through information and communication centers, compromising the secure operation of power systems. By theoretically analyzing the AC microgrid simulation model, the MPC control strategies, and the modified MPC method based on GCC estimation will be studied in this thesis. In the second chapter, this thesis summarizes the start-art-of microgrid control, introducing a hierarchical control structure: primary control, secondary control, and tertiary control. These control levels differ in their speed of response, the time frame in which they operate, and infrastructure requirements. We focus on the centralized secondary frequency control system, which compensates the frequency deviation caused by primary control—P/f method. Then, in Chapter 3, the isolated AC MG frequency control system including WTG, DEG, PV panel and energy storage system with MPC controller is modeled. Three case studies are designed in MATLAB/Simulink to illustrate the advantages of the MPC method compared with the traditional PI controller. In the next Chapter, since state estimation based on precise status feedback of the system components is essential for the MPC controller to calculate corresponding control signal, the status feedback attack to BESS and FESS is considered. Correspondingly, an online status switching method is proposed to detect the original statuses of BESS and FESS, updating the state estimation function to obtain desirable performance of frequency regulation. Last, considering the time delay attack hacked by the adversary in the sensor, a modified MPC method based on GCC estimation is proposed to detect and track time delay attacks online. The model of proposed method to regulate frequency deviation is built in MATLAB. There are three case studies in this part: a constant time-delay attack with 0.1 pu load increase; a time-varying delay attack with 0.1 pu load increase; and a time-varying delay attack with changing load disturbance. By analyzing results of three cases, the effectiveness of the modified MPC method is proved

Model Predictive Control Design for the Secondary Frequency Control of Microgrid Considering Time Delay Attacks

Fast depleting fossil fuels and growing awareness of environmental protection have raised worldwide concerns, aiming to build a sustainable and smart energy ecosystem. Renewable energy generation plays an important role in providing clean power supply. However, the integration of a bulk renewable generation system would also introduce new forms of disturbances and uncertainties to impact the power quality, threatening the secure operation of the distribution network. Microgrid, as an emerging technology, is quite appealing to be interfaced with distribution systems due to its potential economic, environmental, and technical benefits. The microgrid differs from the “smart grid” with different control strategies to accomplish the goal of helping the power grid with load balancing and voltage control and assisting power markets. A hierarchical control structure for the microgrid is commonly designed to address all above issues both in islanded mode and grid-connected mode. On the other hand, concerns about cybersecurity threats in the microgrid are steadily rising, and enormous number of economic losses would occur if defense strategies are not stipulated and carried out. In the modern power system, distributed control system, intelligent measuring devices and Internet of Things (IoT) are highly recommended in microgrid systems, which lead to the vulnerability of communication channels. Cyber threats such as false data injection (FDI) attacks, denial of service (DoS) attacks, and time-delay switch attacks (TDS) can be effortlessly implemented through information and communication centers, compromising the secure operation of power systems. By theoretically analyzing the AC microgrid simulation model, the MPC control strategies, and the modified MPC method based on GCC estimation will be studied in this thesis. In the second chapter, this thesis summarizes the start-art-of microgrid control, introducing a hierarchical control structure: primary control, secondary control, and tertiary control. These control levels differ in their speed of response, the time frame in which they operate, and infrastructure requirements. We focus on the centralized secondary frequency control system, which compensates the frequency deviation caused by primary control—P/f method. Then, in Chapter 3, the isolated AC MG frequency control system including WTG, DEG, PV panel and energy storage system with MPC controller is modeled. Three case studies are designed in MATLAB/Simulink to illustrate the advantages of the MPC method compared with the traditional PI controller. In the next Chapter, since state estimation based on precise status feedback of the system components is essential for the MPC controller to calculate corresponding control signal, the status feedback attack to BESS and FESS is considered. Correspondingly, an online status switching method is proposed to detect the original statuses of BESS and FESS, updating the state estimation function to obtain desirable performance of frequency regulation. Last, considering the time delay attack hacked by the adversary in the sensor, a modified MPC method based on GCC estimation is proposed to detect and track time delay attacks online. The model of proposed method to regulate frequency deviation is built in MATLAB. There are three case studies in this part: a constant time-delay attack with 0.1 pu load increase; a time-varying delay attack with 0.1 pu load increase; and a time-varying delay attack with changing load disturbance. By analyzing results of three cases, the effectiveness of the modified MPC method is proved

Cybersecurity Strategy against Cyber Attacks towards Smart Grids with PVs

Cyber attacks threaten the security of distribution power grids, such as smart grids. The emerging renewable energy sources such as photovoltaics (PVs) with power electronics controllers introduce new potential vulnerabilities. Based on the electric waveform data measured by waveform sensors in the smart grids, we propose a novel cyber attack detection and identification approach. Firstly, we analyze the cyber attack impacts (including cyber attacks on the solar inverter causing unusual harmonics) on electric waveforms in distribution power grids. Then, we propose a novel deep learning based mechanism including attack detection and attack diagnosis. By leveraging the electric waveform sensor data structure, our approach does not need the training stage for both detection and the root cause diagnosis, which is needed for machine learning/deep learning-based methods. For comparison, we have evaluated classic data-driven methods, including -nearest neighbor (KNN), decision tree (DT), support vector machine (SVM), artificial neural network (ANN), and convolutional neural network (CNN). Comparison results verify the performance of the proposed method for detection and diagnosis of various cyber attacks on PV systems

Evolution of microgrids with converter-interfaced generations: Challenges and opportunities

© 2019 Elsevier Ltd Although microgrids facilitate the increased penetration of distributed generations (DGs) and improve the security of power supplies, they have some issues that need to be better understood and addressed before realising the full potential of microgrids. This paper presents a comprehensive list of challenges and opportunities supported by a literature review on the evolution of converter-based microgrids. The discussion in this paper presented with a view to establishing microgrids as distinct from the existing distribution systems. This is accomplished by, firstly, describing the challenges and benefits of using DG units in a distribution network and then those of microgrid ones. Also, the definitions, classifications and characteristics of microgrids are summarised to provide a sound basis for novice researchers to undertake ongoing research on microgrids

Energy management system benchmarking for a remote microgrid

El presente trabajo analiza el efecto que tiene la estrategia de control adoptada en el sistema de gestión de energía de una microrred en el rendimiento económico y el impacto medioambiental asociado a su operación. Las microrredes aisladas son una solución para la electrificación de áreas remotas que debido a su localización geográfica no pueden ser conectadas a la red eléctrica. La estructura de estos sistemas permite la integración de energía proveniente de generación distribuida, principalmente renovable. El abaratamiento de los colectores fotovoltaicos, el autoconsumo y los incentivos medioambientales ofrecidos a este tipo de generación son algunos de los factores que impulsan la adopción de este tipo de redes. Sin embargo, los retos técnicos asociados a las microrredes con un alto índice de penetración renovable hacen necesario un sistema de gestión de la energía que se adapte a las necesidades del sistema. Asimismo, para garantizar un suministro eléctrico de calidad e ininterrumpido, es necesario el uso de sistemas de almacenamiento eléctrico, que el sistema de control debería gestionar adecuadamente tomando en consideración las previsiones de la demanda y solares. Como caso de estudio se ha tomado la isla Isabela, situada en el archipiélago de Galápagos al oeste de Ecuador. A partir de octubre de 2017 esta isla contará con un sistema eléctrico conformado por 922 kW de generación solar, 1625 kW de generación térmica y un sistema de almacenamiento de baterías Ion-Litio de 258kWh de capacidad. A través de la simulación de tres estrategias de control se pretende analizar qué controlador se adapta mejor a las necesidades del sistema.This documents analyses the effect the control strategy followed by the energy management system of a microgrid has on is economic performance and the environmental impact associated to its operation. Isolated microgrids appear as a solution to the electrification of remote communities that due to their geographical location cannot be connected to the main grid. The architecture of this systems enables the integration of electricity generated from distributed energy resources, in particular renewable generation. The decrease in prices of solar PV collectors, self consumption and the economic incentives given to clean energy generation in many countries are pushing forward the adoption of this kind of electrical grids. However, the challenges associated to the operation of microgrids with a high index of renewable penetration require an energy management system that is designed around the specific needs of the system. Moreover, in order to guarantee the quality and continuity of the supply, the use os energy storage systems is necessary, which will need to be managed appropriately by the energy management system, taking into account the demand predictions and the solar forecast. The island Isabela, which belongs to the Galapagos archipelago located west from Ecuador, has been taken as a case study. From October 2017 the islands electrical system will from an energy mix of 922 kW solar PV,1625 kW diesel generators and a 258 kWh Lithium-Ion batteries storage system. Through the simulation of three control strategies the aim is to determine which controller is most suitable for the control operation of the island.Ingeniería de la Energí

ENERGY RESILIENCE IMPACT OF SUPPLY CHAIN NETWORK DISRUPTION TO MILITARY MICROGRIDS

The ability to provide uninterrupted power to military installations is paramount in executing a country's national defense strategy. Microgrid architectures increase installation energy resilience through redundant local generation sources and the capability for grid independence. However, deliberate attacks from near-peer competitors can disrupt the associated supply chain network, thereby affecting mission-critical loads. Utilizing an integrated discrete-time Markov chain and dynamic Bayesian network approach, we investigate disruption propagation throughout a supply chain network and quantify its mission impact on an islanded microgrid. We propose a novel methodology and an associated metric we term "energy resilience impact" to identify and address supply-chain disruption risks to energy security. A case study of a fictional military installation is presented to demonstrate how installation energy managers can adopt this methodology for the design and improvement of military microgrids.Outstanding ThesisLieutenant, United States NavyApproved for public release. Distribution is unlimited

Distributed energy resources and the application of AI, IoT, and blockchain in smart grids

Smart grid (SG), an evolving concept in the modern power infrastructure, enables the two-way flow of electricity and data between the peers within the electricity system networks (ESN) and its clusters. The self-healing capabilities of SG allow the peers to become active partakers in ESN. In general, the SG is intended to replace the fossil fuel-rich conventional grid with the distributed energy resources (DER) and pools numerous existing and emerging know-hows like information and digital communications technologies together to manage countless operations. With this, the SG will able to “detect, react, and pro-act” to changes in usage and address multiple issues, thereby ensuring timely grid operations. However, the “detect, react, and pro-act” features in DER-based SG can only be accomplished at the fullest level with the use of technologies like Artificial Intelligence (AI), the Internet of Things (IoT), and the Blockchain (BC). The techniques associated with AI include fuzzy logic, knowledge-based systems, and neural networks. They have brought advances in controlling DER-based SG. The IoT and BC have also enabled various services like data sensing, data storage, secured, transparent, and traceable digital transactions among ESN peers and its clusters. These promising technologies have gone through fast technological evolution in the past decade, and their applications have increased rapidly in ESN. Hence, this study discusses the SG and applications of AI, IoT, and BC. First, a comprehensive survey of the DER, power electronics components and their control, electric vehicles (EVs) as load components, and communication and cybersecurity issues are carried out. Second, the role played by AI-based analytics, IoT components along with energy internet architecture, and the BC assistance in improving SG services are thoroughly discussed. This study revealed that AI, IoT, and BC provide automated services to peers by monitoring real-time information about the ESN, thereby enhancing reliability, availability, resilience, stability, security, and sustainability

Network and System Management for the Security Monitoring of Microgrids using IEC 62351-7

Interest in adding renewable energy sources to the power grid has risen substantially in recent years. As a response to this growing interest, the deployment of microgrids capable of integrating renewable energy has become more widespread. Microgrids are independent power systems that deliver power from different kinds of Distributed Energy Resources (DERs) to local energy consumers more efficiently than the conventional power grid. The microgrid leverages advanced information and communication technologies for vital protection, monitoring, and control operations as well as for energy management. With the use of information technology comes the need to protect the microgrid information layer from cyberattacks that can impact critical microgrid power operations. In this research, a security monitoring system to detect cyberattacks against the microgrid, in near-real time, is designed and implemented. To achieve this, the system applies Network and System Management (NSM) for microgrid security monitoring, as specified by the IEC 62351-7 security standard for power systems. The specific contributions of this research are (i) an investigation on the suitability of NSM for microgrid security monitoring; (ii) the design and implementation of an NSM platform; (iii) the design and implementation of a security analytics framework for NSM based on deep learning models; (iv) the elaboration of a comprehensive microgrid simulation model deployed on a Hardware in the Loop (HIL) co-simulation framework; and (v) an experimental evaluation on the effectiveness and scalability of the NSM security monitoring platform for detection against microgrid attack scenarios, with a methodology being used to systematically generate the scenarios. The experimental results validate the usefulness of NSM in detecting attacks against the microgrid