SCADA System Research Articles

Detecting Cyberattacks on Electrical Storage Systems through Neural Network Based Anomaly Detection Algorithm.

Distributed Energy Resources (DERs) are growing in importance Power Systems. Battery Electrical Storage Systems (BESS) represent fundamental tools in order to balance the unpredictable power production of some Renewable Energy Sources (RES). Nevertheless, BESS are usually remotely controlled by SCADA systems, so they are prone to cyberattacks. This paper analyzes the vulnerabilities of BESS and proposes an anomaly detection algorithm that, by observing the physical behavior of the system, aims to promptly detect dangerous working conditions by exploiting the capabilities of a particular neural network architecture called the autoencoder. The results show the performance of the proposed approach with respect to the traditional One Class Support Vector Machine algorithm.

Data-Driven, Web-Based Parameter Identification for a Reduced-Order Model of the Chilean Power System

The current need for power-system control-room operational tools to increase real-time situational awareness has led to various proposals on data analytics algorithms to obtain operational information from SCADA and PMU power system networks. Most of the proposals are implemented in simulation, with reduced practical significance for system operators. This work proposes a web-based simple algorithm to identify the dynamic parameters of a reduced-order model of power system frequency dynamics that is implemented with industrial hardware on a PMU network in the Chilean power system. To demonstrate the applicability of the proposed tool, the algorithm is implemented in a web page with real-time monitoring of the frequency of the Chilean power system, so that utilities and academic institutions with access to PMU measurements can apply the proposed concepts regardless of the topology of the monitored system.

Turbine-level clustering for improved short-term wind power forecasting

At the present time, new types of data are collected at a turbine level, and can be used to enhance the skill of short-term wind power forecasts. In particular, high resolution measurements such as wind power and wind speed are gathered using SCADA systems. These data can be used to build turbine-tailored forecasting models, but at a higher computational cost to predict the production of the overall wind farm compared to a single farm-level model. Thus, we explore the potential of the DBSCAN clustering algorithm to group wind turbines and build forecasting models at a cluster-level to find a middle ground between forecasting accuracy and computational cost. The proposed approach is evaluated using SCADA data collected in two Irish wind farms.

Система предотвращения аварийных ситуаций производственных технологических объектов на основе ситуационной математической модели

The main criterion characterizing the efficiency of the equipment of an industrial facility is its operation without failures and damages. To reduce the emergency rate, there has been proposed an emergency prevention system targeted at identifying the technological situation at the facility, predicting its further development, and also de-veloping the control actions to return the facility to normal operation. The task of identifying pre-emergency and emergency situations for technological objects is realized as a particular task of recognizing a technological situation based on a situational mathematical model of an object. The situational mathematical model of the object is implemented as a set of production rules that reflect the knowledge of experts about the identification of pre-emergency situations at the object, as well as possible trajectories for bringing the control object into normal operation. A three-level grouping of the rules of the situational mathematical model by security levels is proposed. The features of the formation of the rules of the situational mathematical model in the processing of qualitative information about the object are considered. Based on the situational mathematical model, a method for identifying pre-emergency situations is proposed, the stages of the method implementation are described. An algorithm of functioning the emergency prevention system has been developed. The interaction scheme of the proposed emergency prevention system and the process control system based on the SCADA system is determined. The use of the proposed system will improve the safety and stability of the operation of hazardous technological facilities

An evolutionary approach with reliability priority to design Scada systems for water reservoirs

An evolutionary approach with reliability priority to design Scada systems for water reservoirs

Smart water supply system: a quasi intelligent diagnostic method for a distribution network

Constantly developing monitoring systems provide a large amount of raw data. In many cases, the operators of water supply systems (WSS) have already reached their perception limit for analysing information. Therefore, the managing process of the WSS requires quasi-intelligent informatics systems, the main purpose of which is to minimise the WSS operating costs in addition to maintaining the proper water delivery to customers. It can be achieved by the detection of abnormal functioning of WSS operations (leakages, water outages). The standard SCADA monitoring systems, in most cases, are not able to distinguish a significant water leakage and water tank filling process. Such cases occur relatively often in complex water supply systems with many water tanks. The aim of this paper is to present the quasi intelligent method of detecting abnormal WSS functioning, including its concepts and effects after a 3 month period operation. The essence of the detection method is the integration of numerical model (built-in Bentley WaterGEMS software) and SCADA monitoring system. The monitoring data are constantly compared to the simulation results and when accepted accordance limits are exceeded, the appropriate alerts are generated. Such solution cause the WSS operator does not need to analyse SCADA system indications constantly. The additional application of the method enables the detection of essential water leakages.

Wind power forecasting using ensemble learning for day-ahead energy trading

Wind power forecasting is a field characterised by sudden weather-related events, turbine failures and constraints imposed by the electricity grid. Nowadays, different energy markets add the extra challenge of requiring predictions at the minute level a day forward for bidding-processes. This is to avoid trading energy as a bulk and match demand. In this context, we present a novel approach to predict power generation at high frequencies one day in advance, which handles constraints such as curtailment and turbine degradation. This has been tested over historical data from SCADA systems and historical forecasts from wind speed providers for eight windfarm locations in Ireland over two years. Our work was performed in two phases. First, we undertook a preliminary study to analyse the relationship between all combinations of observed wind, forecasted wind and electrical power. Secondly, a wide variety of Machine Learning algorithms were run over each of the locations in order to assess the degrees of predictability of different algorithms and regions. Most of the algorithms benchmarked improve linear wind to power mappings besides the high degree of noise in this domain. Our analysis and experimental results show how boosting ensembles are a cost-effective solution in terms of runtime among other Machine Learning algorithms predicting wind power a day ahead.

A novel solution for controlling hardware components of accelerators and beamlines.

A novel approach to the remote-control system for the compact multi-crystal energy-dispersive spectrometer for X-ray emission spectroscopy (XES) applications has been developed. This new approach is based on asynchronous communication between software components and on reactive design principles. In this paper, the challenges faced, their solutions, as well as the implementation and future development prospects are identified. The main motivation of this work was the development of a new holistic communication protocol that can be implemented to control various hardware components allowing both independent operation and easy integration into different SCADA systems.

Automated load shedding period control system for distribution utility

The authors have described a low-cost wi-fi allotted load shedding system that can be used in both high and low-power applications. The proposed technique employs PLCC to perform partial load shedding or full load shedding based on input power in power transformer locations where a SCADA system cannot be employed. In case of over current drawn, the cutting edge sensor prevents the transformer from damage. This paper presents a design to compute and control the voltage and provide a full or partial load shedding solutions to domestic and industrial consumers.

AUTOMATED CONTROL SYSTEM OF TECHNOLOGICAL PROCESS (ACS TP)

The article considers aspects of the creation and development of automated process control systems. A comparative analysis of the main types of IS RD, as well as the peculiarities of their use are shown. Stages of development and further development of automatic control systems (ACS) were identified and considered. Devices of automated process control systems and integration of SCADA systems into the structure of ACS were studied. Existing challenges were identified and possible prospects for improvement and development were presented. It was concluded that the rational use of artificial intelligence to increase the efficiency of technological process automation.

AUTOMATION OF CONTROL OF ROOM DEEP OIL PUMP USINGTRACE MODE SCADA SYSTEMS

The issues of automation of technological processes are relevant for all industries. The article discusses the issues of automating the control of the operation of oil pumping units widely used in oil production using the TRACE MODE SCADA system from AdAstrA Research Group.
 
 To control the operation of a sucker rod pump of an oil pumping unit, the use of dynamometers is widespread in world practice. Technically, it is easier to carry out a more generalized control of the operation of an oil pumping unit using a wattmetergram, which displays the dependence of the active power consumed by the drive on time or the position of the polished rod. The results of power measurements are transmitted via communication channels to the computer of the SCADA system. Further, preliminary processing of the results of the control of the wattmeter diagram and the calculation of parameters characterizing the operation of the oil pumping unit are performed.
 
 At the stage of data preprocessing, noise filtering is performed using TRACE MODE tools that provide data exchange with MS Excel, MS Access, MS Visual Basic packages. The use of moving average, median filtering, and B-splines methods for this is considered. It is shown that cubic B-splines are an effective method of analytical description and graphical representation of experimental data, reducing the total mean square of the error. The use of splines in comparison with the polynomial approximation gives a slightly better approximation. The results of filtering and calculations by means of the SCADA system are displayed on the dispatcher’s monitor, archived, documented, etc. Thus, the related software products SCADA TRACE MODE and MS allow you to effectively implement complex data processing algorithms.

Research on SCADA system security reinforcement method based on distributed Pareto algorithm

As the SCADA system develops continuously, the dissemination of malicious network behaviors has brought great risk to the normal operation of enterprises, meanwhile resulting in huge economic burden to personal work and life. Therefore, the security reinforcement strategy is crucial to the field of network security management and analysis of the SCADA system. Some researchers have started to investigate on how to minimize the cost of realizing the SCADA system reinforcement strategy. However, the SCADA system administrators are facing a very challenging problem, that’s the reinforcement budget is less than the minimal input of SCADA system security reinforcement. The core of this problem lies on how to choose a subset from massive security reinforcement strategies, so as to minimize the risks from not patching all essential security vulnerabilities within the budget. Based on a deep comparative analysis of existing multi-objective optimization technologies, this paper proposes a multi-objective optimization method based on system attack tree model, and uses Pareto algorithm to solve this problem. The experimental results demonstrate that the Pareto algorithm can effectively make the multi-objective decision in security reinforcement strategy, and can solve practical issues in actual SCADA system security reinforcement practice.

A novel centralized supervisory with distributed control system-based microgrid

Supervisory Control and Data Acquisition is a popular control and monitoring scheme and is predominantly used in many industrial systems. Driven by the motivation of extending the usage of the SCADA systems for microgrid, a novel centralized Supervisory Control and Data Acquisition System with Distributed Control Systems is proposed and validated for the microgrid. Supervisory instructions are issued from the central control system, whereas the local controllers are used to implement the exclusive control schemes required for the various subsystems. A wired sensor network is used to monitor the various vital parameters and a Graphical User Interface (GUI) is used for monitoring the status of operation of the various subsystems along with their parametric values. The proposed system is simulated in the MATLAB SIMULINK environment. An experimental verification prototype has also been carried out where a PC (Personal Computer) with a Graphical User Interface developed in C# and a microcontroller is used to act as an interface between the distributed controllers in the plant and the master control PC.

SCADA System for Next-Generation Smart Factory Environments

Today, in factories, production is spread into a wide area and became complicated. Complicated production requires a better monitoring and control system to improve efficiency. For this purpose, SCADA systems are used. SCADA systems allow industries to monitor, control and access to real-time data and data logging. Nowadays, all large-scale industries have SCADA systems. The cost of the SCADA system makes it unreachable for small and medium-size industries but a SCADA system that is designed by using C# programming language would be cheaper and could perform the same. In this study, a SCADA system has been developed to monitor and control the smart model factory system in AFSUAM. SCADA interface is created by using C# programming language and the communication between PLC and the SCADA is set by using Mitsubishi MX Component tool. With the developed SCADA system, the process of a product entering the factory as raw material, going through several processes and becoming a product from the supply chain to the distributor has been modeled on a sample marble factory model, and a graphical user interface has been created considering the purposes such as real-time monitoring, controlling, data logging and preventing errors in the context of this model.

Applying Sensor-Based Information Systems to Identify Unplanned Downtime in Mining Machinery Operation.

Underground mining belongs to immensely complex processes and depends on many natural, technical and organizational factors. The main factor that hinders this process is the environmental conditions in which it is carried out. One of the problems associated with the use of increasingly modern machines in such conditions is the issue of unplanned downtime during their operation. This paper presents the developed methodology and IT system for recording breaks in the operation of mining machines and identifies their causes. The basis of this methodology is a sensor-based information system used to register mining machinery parameters, based on which interruptions in their operation can be determined. In order to register these parameters, an industrial automation system (together with a SCADA system supervising the process) was used, which is practically independent from the operator and enables continuous registration of these parameters. In order to identify the reasons for the recorded breaks, an IT tool was developed in the form of an application in the module of the integrated mining enterprise management support system (ERP system). This application enables (with a continuously updated database) the identification of the causes in question. Thus, the developed solution enables the objective registration of machine downtime and, for most cases, the identification of causes. The acquired knowledge, so far largely undisclosed, has created opportunities to improve the utilization level of machinery exploited in the mining production process. The paper discusses the methodology, together with the IT system, for identifying the causes of machine downtime and presents an example of its application for a shearer loader, which is the basic machine of a mechanized longwall system. The results indicate great potential for the application of the developed system to improve the efficiency of machinery utilization and the whole process of mining production.

Detecting Semantic Attack in SCADA System: A Behavioral Model Based on Secondary Labeling of States-Duration Evolution Graph

By violating semantic constraints that the control process impose, the semantic attack leads the Industry Control Systems (ICS) into an undesirable state or critical state. The spread of semantic attack has caused huge economic losses and casualties to critical infrastructure. Therefore, detecting semantic attack is referred to an urgent and critical task. However, few existing detecting techniques can achieve satisfactory effects in detecting semantic attack of ICS, due to the high requirements of complete critical state-based semantic behavior features description, joint detection on multivariate type state variables, and validity of field states datasets under semantic attacks. In an effort to deal with above challenges, We label device states databases with temporal characteristics and divide impacts on states of field devices under semantic attacks into three categories, including absent in states set, confused sequences, irregular frequency. On this basis, we establish a behavioral model based on secondary labeling of states-duration evolution graph (BMSLS), then implement an adaptive secure state-based semantic attack detection framework furtherly. Compared with the traditional Auto Regression (AR) algorithm, the newer time series correlation graph model, and other five deep learning algorithms, our proposed framework demonstrates the superior effect on the detection of semantic attack.

Unified Detection of Attacks Involving Injection of False Control Commands and Measurements in Transmission Systems of Smart Grids

Transmission system operation and monitoring, in the context of smart grids, are heavily dependent on the correctness or aptness of supervisory control commands. These command channels are a part of the SCADA system, which is vulnerable to cyber-attacks. Maliciously injected commands can cause a wide range of issues including blackouts. However, the literature addressing this problem is limited. In order to fill this gap, a generalized framework is proposed to achieve simultaneous detection of attacks against various types of control devices/equipments used in transmission systems, even if they are carried out stealthily. First, generalized mathematical models of such stealthy attacks are presented. Then, based on these attack models, changes in the measurement covariance matrix that occur during an attack are exploited to formulate the proposed approach. We first mathematically characterize these changes using the eigenvectors and trace of the covariance matrix and then use them to develop a detection metric. It is observed that when the model of a false data injection (FDI) attack is considered, the developed detection metric is also capable of detecting such attacks. The algorithm that results from the detection metric is a generalized framework for detection of attacks against all types of transmission system controls and measurements. Moreover, the algorithm is non-iterative, computationally inexpensive, and independent of both the type of state estimation and communication technology used. The proposed algorithm is found to be effective, when tested on the IEEE 118-bus system.

Hardware Development and Interoperability Testing of a Multivendor-IEC-61850-Based Digital Substation

Substations are becoming increasingly reliant on international electrotechnical commission (IEC)-61850-enabled devices. However, device compatibility with these standards does not guarantee interoperability when devices are taken from different manufacturers. If interoperability of multivendor devices can be achieved, then power utilities will be in a position to implement multivendor devices in substations. The study here presents the development and testing of a digital substation test platform that incorporates devices from different manufacturers. The process bus communication and protection operation of the intelligent electronic devices (IEDs) were tested to validate device interoperability. The testbed was tested for two IED process bus communications, generic object-oriented substation event (GOOSE) and sampled measured value (SMV). The GOOSE is travelling between IED to IED with an end-to-end (ETE) delay of 2 ms and the SMV read by the IEDs are the same as the injected real-time substation inputs 220 kV and 1 kA. Three IED protection studies (overcurrent, earth fault, and overvoltage) were performed, and IED response curves were obtained. In addition, data monitoring and client–server communications were studied using installed software tools. The testbed configuration in this study has faced some real-time challenges regarding differences in device edition, device firmware, and ethernet switch due to its multivendor approach. All the mentioned configuration issues were resolved in this study with successful testing and validation of the testbed. The study of this testbed will provide solutions to the problems associated with a multivendor system faced by substation engineers and will help them in opting for multivendor installations. This system can be extended in the future by installing more multivendor devices with complex network topology and a SCADA system.

Securing Remote State Estimation against Sequential Logic Attack of Sensor Data

The SCADA system, which is widely used in the continuous monitoring and control of the physical process of modern critical infrastructure, relies on the feedback control loop. The remote state estimation system triggers the control algorithm or control condition of the controller according to the monitoring data returned by the sensor. The controller sends the control command to the actuator, and the actuator executes the command to control the physical process. Since SCADA system monitoring and control data are usually transmitted through unprotected wireless communication networks, attackers can use false sensor data to trigger control algorithms to make wrong decisions, disrupt the physical processing of the SCADA system, and cause huge economic losses, even casualties. We found an attack strategy based on the sequential logic of sensor data. This kind of attack changes the time logic or sequence logic of the response data, so that the false data detector can be successfully deceived. This would cause the remote state estimation system to trigger wrong control algorithms or control conditions, and eventually disrupt or destroy the physical process. This paper proposes a sequential signature scheme based on the one-time signature to secure the sequential logic and transmission of sensor data. The security analysis proves that the proposed scheme can effectively resist counterfeiting, forgery, denial, replay attacks, and selective forwarding attacks.

Secured cloud SCADA system implementation for industrial applications

The proposed Remote SCADA System (RSS) is a smarter, faster and more reliable way to control high power machines and monitor their sensors, data, and failures. The proposed system focuses mainly on building our own complete SCADA software and not using open-source SCADA software. The proposed RSS can use unlimited number of added Remote Terminal Units (RTU) nodes and each of them can handling unlimited number of input/output and can be used under different operating systems like Windows and Android. Using RSS all machines can be monitored and controlled by a single click from anywhere at any time. By doing this a real-time response from RSS system can be achieved. It’s mainly based on standard communication techniques between remote nodes and single server-side application that talk to each node with its own ID and modify its instant database. So that every time accessing this web application, a real-time access to these nodes data and a virtual control room controls each General Purpose Input/Output (GPIO) in the selected node can be gotten. When a new event is happened in server-side program, it will be broadcasted to all related. On RSS there are two main points to deal with, the request latency and security of the system. This paper studied how the system latency and security are improved to obtain the needed values. The proposed RSS is a very secure program which have 4 security levels; authentication, authorization, RSA and CBC encryption system. Also, the encryption algorithms used in RSS are RSA and CBC block cipher encryption system. It is mixed way to prevent any attacker from breaking the cipher. First of all, RSA generates the public and private keys, and then CBC generates its Initialization vector and a random encryption key. Then a special function sends all of these keys encrypted with a pre-stored token in the data base and node memory which varied from node to another. Finally, node generates its private key from loaded public key. With this combination the speed of symmetric encryption system and the security of asymmetric encryption system can be achieved. On the other hand, the level of security firewalls needed to be Brocken by the attacker to brock the cipher is increased. The proposed system achieved low cost comparing with reported work; it is lower than Arduino + WIFI method by five times and 13 times lower than Raspberry-PI method. The proposed system is applied in educational systems, where it is used for teaching unlimited number of students Online.