Man-in-the-Middle Attack Test-bed Investigating Cyber-security Vulnerabilities in Smart Grid SCADA Systems

The increased complexity and interconnectivity of Supervisory Control and Data Acquisition (SCADA) systems in the Smart Grid has exposed them to a wide range of cyber-security issues, and there are a multitude of potential access points for cyber attackers. This paper presents a SCADA-specific cyber-security test-bed which contains SCADA software and communication infrastructure. This test-bed is used to investigate an Address Resolution Protocol (ARP) spoofing based man-in-the-middle attack. Finally, the paper proposes a future work plan which focuses on applying intrusion detection and prevention technology to address cyber-security issues in SCADA systems.

A Smart Grid Information System for Demand Side Participation: Remote Control of Domestic Appliances to Balance Demand

Due to the intermittent nature of renewable generation it is desirable to consider the potential of controlling the demand-side load to smooth overall system demand. The architecture and control methodologies of such a system on a large scale would require careful consideration. Some of these considerations are discussed in this paper; such as communications infrastructure, systems architecture, control methodologies and security. A domestic fridge is used in this paper as an example of a controllable appliance. A layered approach to smart-grid is introduced and it can be observed how each smart-grid component from physical cables, to the end-devices (or smart-applications) can be mapped to these set layers. It is clear how security plays an integral part in each component of the smart-grid so this is also an integral part of each layer. The controllable fridge is described in detail and as one potential smart-grid application which maps to the layered approach. A demonstration system is presented which involves a Raspberry Pi (a low-power, low-cost device representing the appliance controller).

Tracking smart grid hackers

The next-generation smart grid will rely highly on telecommunications infrastructure for data transfer between various systems. Anywhere we have data transfer in a system is a potential security threat. When we consider the possibility of smart grid data being at the heart of our critical systems infrastructure it is imperative that we do all we can to ensure the confidentiality, availability and integrity of the data. A discussion on security itself is outside the scope of this paper, but if we assume the network to be as secure as possible we must consider what we can do to detect when that security fails, or when the attacks comes from the inside of the network. One way to do this is to setup a hacker-trap, or honeypot. A honeypot is a device or service on a network which appears legitimate, but is in-fact a trap setup to catch breech attempts. This paper identifies the different types of honeypot and describes where each may be used. The authors have setup a test honeypot system which has been live for some time. The test system has been setup to emulate a device on a utility network. The system has had many hits, which are described in detail by the authors. Finally, the authors discuss how larger-scale systems in utilities may benefit from honeypot placement.

Securing the smart grid

The availability of electricity is fundamental to modern society. It is at the top of the list of critical infrastructures and its interruption can have severe consequences. This highly important system is now evolving to become more reliable, efficient, and clean. This evolving infrastructure has become known as the smart grid; and these future smart grid systems will rely heavily on ICT. This infrastructure will require many servers and due to the nature of the grid, many of these systems will be geographically diverse requiring communication links. At the heart of this ICT infrastructure will be security. At each level of the smart grid from smart metering right through to remote sensing and control networks, security will be a key factor for system design consideration. With an increased number of ICT systems in place the security risk also increases. In this paper the authors discuss the changing nature of security in relation to the smart grid by looking at the move from legacy systems to more modern smart grid systems. The potential planes of attack for future smart grid systems are identified, and the general anatomy of a cyber-attack is presented. The authors then introduce the various threat levels of different types of attack and the mitigation techniques that could be put in place for each. Finally, the authors' introduce a Phasor Measurement Unit (PMU) communication system (operated by the authors) that can be used as a test-bed for some of the proposed future security research.

Secure Communications in Smart Grid: Networking and Protocols

The key attributes of a smarter power grid include: pervasive interconnection of smart devices; extensive data generation and collection; and rapid reaction to events across a widely dispersed physical infrastructure. Modern telecommunications technologies are being deployed across power systems to support these monitoring and control capabilities. To enable interoperability, several new communications protocols and standards have been developed over the past 10 to 20 years. These continue to be refined, even as new systems are rolled out.

This new hyper-connected communications infrastructure provides an environment rich in sub-systems and physical devices that are attractive to cyber-attackers. Indeed, as smarter grid operations become dependent on interconnectivity, the communications network itself becomes a target. Consequently, we examine cyber-attacks that specifically target communications, particularly state-of-the-art standards and protocols. We further explore approaches and technologies that aim to protect critical communications networks against intrusions, and to monitor for, and detect, intrusions that infiltrate Smart Grid systems.

Implementation Experiences from Smart Grid Security Applications and Outlook on Future Research

Experiences from smart grid cyber-security incidents in the past decade have raised questions on the applicability and effectiveness of security measures and protection mechanisms applied to the grid. In this chapter we focus on the security measures applied under real circumstances in today’s smart grid systems. Beginning from real world example implementations, we first review cyber-security facts that affected the electrical grid, from US blackout incidents, to the Dragonfly cyber-espionage campaign currently focusing on US and European energy firms. Provided a real world setting, we give information related to energy management of a smart grid looking also in the optimization techniques that power control engineers perform into the grid components. We examine the application of various security tools in smart grid systems, such as intrusion detection systems, smart meter authentication and key management using Physical Unclonable Functions, security analytics and resilient control algorithms. Furthermore we present evaluation use cases of security tools applied on smart grid infrastructure test-beds that could be proved important prior to their application in the real grid, describing a smart grid intrusion detection system application and security analytics results. Anticipated experimental results from the use-cases and conclusions about the successful transitions of security measures to real world smart grid operations will be presented at the end of this chapter.

Open Source Telecommunications Framework for Time-Series Data from Smart Grid Sensors.

This paper presents a framework for a telecommunications interface which allows data from sensors embedded in Smart Grid applications to reliably archive data in an appropriate time-series database. The challenge in doing so is two-fold, firstly the various formats in which sensor data is represented, secondly the problems of telecoms reliability. A prototype of the authors' framework is detailed which showcases the main features of the framework in a case study featuring Phasor Measurement Units (PMU) as the application. Useful analysis of PMU data is achieved whenever data from multiple locations can be compared on a common time axis. The prototype developed highlights its reliability, extensibility and adoptability; features which are largely deferred from industry standards for data representation to proprietary database solutions. The open source framework presented provides link reliability for any type of Smart Grid sensor and is interoperable with existing proprietary database systems, and open database systems. The features of the authors' framework allow for researchers and developers to focus on the core of their real-time or historical analysis applications, rather than having to spend time interfacing with complex protocols.

Optimatization of hybrid renewable energy systems on isolated microgrids : a smart grid approach

Tese de doutoramento, Sistemas Sustentáveis de Energia, Universidade de Lisboa, Faculdade de Ciências, 2016

Typical load profiles in the smart grid context – a clustering methods comparison

The present research paper presents five different clustering methods to identify typical load profiles of medium voltage (MV) electricity consumers. These methods are intended to be used in a smart grid environment to extract useful knowledge about customer’s behaviour. The obtained knowledge can be used to support a decision tool, not only for utilities but also for consumers. Load profiles can be used by the utilities to identify the aspects that cause system load peaks and enable the development of specific contracts with their customers. The framework presented throughout the paper consists in several steps, namely the pre-processing data phase, clustering algorithms application and the evaluation of the quality of the partition, which is supported by cluster validity indices. The process ends with the analysis of the discovered knowledge. To validate the proposed framework, a case study with a real database of 208 MV consumers is used.

Using demand response to deal with unexpected low wind power generation in the context of smart grid

Demand response is assumed an essential resource to fully achieve the smart grids operating benefits, namely in the context of competitive markets. Some advantages of Demand Response (DR) programs and of smart grids can only be achieved through the implementation of Real Time Pricing (RTP). The integration of the expected increasing amounts of distributed energy resources, as well as new players, requires new approaches for the changing operation of power systems. The methodology proposed aims the minimization of the operation costs in a smart grid operated by a virtual power player. It is especially useful when actual and day ahead wind forecast differ significantly. When facing lower wind power generation than expected, RTP is used in order to minimize the impacts of such wind availability change. The proposed model application is here illustrated using the scenario of a special wind availability reduction day in the Portuguese power system (8th February 2012).

Intelligent multi-player smart grid management considering distributed energy resources and demand response

The smart grid concept is rapidly evolving in the direction of practical implementations able to bring smart grid advantages into practice. Evolution in legacy equipment and infrastructures is not sufficient to accomplish the smart grid goals as it does not consider the needs of the players operating in a complex environment which is dynamic and competitive in nature. Artificial intelligence based applications can provide solutions to these problems, supporting decentralized intelligence and decision-making. A case study illustrates the importance of Virtual Power Players (VPP) and multi-player negotiation in the context of smart grids. This case study is based on real data and aims at optimizing energy resource management, considering generation, storage and demand response.

Layered smart grid architecture approach and field tests by ZigBee technology

This paper presents a layered Smart Grid architecture enhancing security and reliability, having the ability to act in order to maintain and correct infrastructure components without affecting the client service. The architecture presented is based in the core of well design software engineering, standing upon standards developed over the years. The layered Smart Grid offers a base tool to ease new standards and energy policies implementation. The ZigBee technology implementation test methodology for the Smart Grid is presented, and provides field tests using ZigBee technology to control the new Smart Grid architecture approach. (C) 2014 Elsevier Ltd. All rights reserved.

Evaluation of the Electric Vehicle Impact in the Power Demand Curve in a Smart Grid Environment

Smart grids with an intensive penetration of distributed energy resources will play an important role in future power system scenarios. The intermittent nature of renewable energy sources brings new challenges, requiring an efficient management of those sources. Additional storage resources can be beneficially used to address this problem; the massive use of electric vehicles, particularly of vehicle-to-grid (usually referred as gridable vehicles or V2G), becomes a very relevant issue. This paper addresses the impact of Electric Vehicles (EVs) in system operation costs and in power demand curve for a distribution network with large penetration of Distributed Generation (DG) units. An efficient management methodology for EVs charging and discharging is proposed, considering a multi-objective optimization problem. The main goals of the proposed methodology are: to minimize the system operation costs and to minimize the difference between the minimum and maximum system demand (leveling the power demand curve). The proposed methodology perform the day-ahead scheduling of distributed energy resources in a distribution network with high penetration of DG and a large number of electric vehicles. It is used a 32-bus distribution network in the case study section considering different scenarios of EVs penetration to analyze their impact in the network and in the other energy resources management.

Smart Grid Market Using Joint Energy and Ancillary Services Bids

The power systems operation in the smart grid context increases significantly the complexity of their management. New approaches for ancillary services procurement are essential to ensure the operation of electric power systems with appropriate levels of stability, safety, quality, equity and competitiveness. These approaches should include market mechanisms which allow the participation of small and medium distributed energy resources players in a competitive market environment. In this paper, an energy and ancillary services joint market model used by an aggregator is proposed, considering bids of several types of distributed energy resources. In order to improve economic efficiency in the market, ancillary services cascading market mechanism is also considered in the model. The proposed model is included in MASCEM – a multi-agent system electricity market simulator. A case study considering a distribution network with high penetration of distributed energy resources is presented.

Contextual Intelligent Load Management Considering Real-Time Pricing in a Smart Grid Environment

The use of demand response programs enables the adequate use of resources of small and medium players, bringing high benefits to the smart grid, and increasing its efficiency. One of the difficulties to proceed with this paradigm is the lack of intelligence in the management of small and medium size players. In order to make demand response programs a feasible solution, it is essential that small and medium players have an efficient energy management and a fair optimization mechanism to decrease the consumption without heavy loss of comfort, making it acceptable for the users. This paper addresses the application of real-time pricing in a house that uses an intelligent optimization module involving artificial neural networks.