Power System Control Centers Research Articles

Identification and Estimation of Erroneous Transmission Line Parameters Using PMU Measurements

The accurate knowledge of the transmission line parameters can be beneficial for several monitoring and control applications accommodated in the power system control center. Actually transmission line parameters are stored in the control center databases (assuming that they are time invariant); however, the databases might be obsolete and contain erroneous parameters. This paper proposes a methodology for identifying and estimating the erroneous transmission line parameters using measurements provided by phasor measurement units (PMUs) and estimated states provided by a state estimator. The main advantage of the proposed methodology is that for the identification of the erroneous transmission lines and the estimation of the line parameters only one PMU is required for the monitoring of the transmission line (i.e., capture measurements related to the transmission line). The proposed methodology is tested in the IEEE 14- and 118-bus systems.

Decomposition-Coordinating Method for Parallel Solution of a Multi-area Combined Economic Emission Dispatch Problem

<p>Multi-area Combined Economic Emission Dispatch (MACEED) problem is an optimization task in power system operation for allocating the amount of generation to the committed units within the system areas. Its objective is to minimize the fuel cost and the quantity of emissions subject to the power balance, generator limits, transmission line and tie-line constraints. The solutions of the MACEED problem in the conditions of deregulation are difficult, due to the model size, nonlinearities, and the big number of interconnections, and require intensive computations in real-time. High-Performance Computing (HPC) gives possibilities for the reduction of the problem complexity and the time for calculation by the use of parallel processing techniques for running advanced application programs efficiently, reliably and quickly. These applications are considered as very new in the power system control centers because there are not available optimization methods and software based on them that can solve the MACEED problem in parallel, paying attention to the existence of the power system areas and the tie-lines between them. A decomposition-coordinating method based on Lagrange’s function is developed in this paper. Investigations of the performance of the method are done using IEEE benchmark power system models.</p>

Development of a Data Acquisition, Storage and Retrieval System for the Real-Time Solution of the Economic Dispatch Problem

The economic dispatch problem is solved within the power system control center based on the data received from the load centers. The power system engineer has to adjust the generator settings at regular intervals to match the available power generation with the required load demand. This is not a trivial task as the power system operating in real-time presents the challenge of acquiring, storing and retrieving the real-time data which has been stored within the database, in order to solve the economic dispatch problem in real-time. This paper focuses on the development of a system for the acquisition, storage and retrieval of the real-time power system data using the LabVIEW and MATLAB software environments. The RSCAD model development and simulation software together with the Real-Time Digital Simulator (RTDS) allows one to generate actual real-time data from a simulation model. The real-time data is used to solve the economic dispatch problem for a five-and eleven bus power systems from an Indian power network using the Lagrange’s algorithm in the MATLAB software environment. The lab scale plant setup comprising of the simulation model and Real-Time Digital Simulator (RTDS), NI-USB-6343 data acquisition card, and two personal computers, together with the obtained results is presented.

Statistical method for on-line voltage collapse proximity estimation

This paper is aimed to propose a reliable method for estimating the voltage collapse proximity through a model obtained using statistical techniques. In the model building process a database is required, therefore the Voltage Collapse Proximity Index (VCPI) is used to obtain previous readings for different contingencies and loading conditions. This analytical proposal could be combined with existing equipment in the power system control centers for future on-line applications. The proposed method is applied to the IEEE 14-bus test system and the 190-bus Mexican equivalent. Results indicate that the proposed strategy is a reliable choice.

Vehicle-to-Grid Control for Supplementary Frequency Regulation Considering Charging Demands

Electric vehicles (EVs) as distributed storage devices have the potential to provide frequency regulation services due to the fast adjustment of charging/discharging power. In our previous research, decentralized vehicle-to-grid (V2G) control methods for EVs were proposed to participate in primary frequency control. In this paper, our attention is on bringing a large number of EVs into the centralized supplementary frequency regulation (SFR) of interconnected power systems. An aggregator is the coordinator between EVs and the power system control center. The aggregator calculates the total frequency regulation capacity (FRC) and expected V2G (EV2G) power of EVs based on the data communicated between the aggregator and individual EVs or EV charging stations. With FRC and EV2G power, a V2G control strategy is proposed for the aggregator to dispatch regulation requirements to EVs and EV charging stations. In individual EV charging stations, the FRC is calculated on the basis of the V2G power at present time, and EV2G power is presented considering both frequency regulation and charging demands. Besides, V2G control strategies are developed to distribute regulation requirements to each EV. Simulations on an interconnected power grid based on a practical power grid in China have demonstrated the effectiveness of the proposed strategies.

PARAGON: an approach for parallelization of power system contingency analysis using Go programming language

SUMMARY With the recent emphasis on N-k contingency analysis (CA) and expansion of power systems, the computational demand of CA has greatly increased to ensure power system security. The serial execution platforms are proving to be insufficient to cater to this demand. This paper presents PARAGON, an efficient approach for parallelization of power system contingency analysis using Go programming language. PARAGON uses Google's Go language to parallelize CA over multiple cores using goroutines. The main contribution of this paper is implementation of work-stealing scheduler on widely used multicore processors using concurrent programming language, which can be easily adopted by power system control centers to accelerate legacy codes. Simulations have been performed using a large power system with hundreds of contingencies, and contingency analysis has been parallelized using 2, 4, 8, 12, and 16 cores. The results show that PARAGON provides large computational advantage over serial execution and also outperforms a conventional scheduling technique, namely master-slave scheduling. Copyright © 2014 John Wiley & Sons, Ltd.

SOSPO-SP: Secure Operation of Sustainable Power Systems Simulation Platform for Real-Time System State Evaluation and Control

New challenges are arising in managing power systems as these systems become more complex due to the use of high levels of distributed generation, mainly based on renewable energy sources, and due to the competitive environment within the power sector. At the same time, the use of phasor measurement units (PMUs) provides more information and enables wide-area monitoring with accurate timing. One of the challenges in the near future is converting the high quantity and quality of information provided by PMUs into useful knowledge about operational state of a global system. The use of real-time simulation in closed loop is essential to develop and validate new real-time applications of wide-area PMU data. This paper presents a simulation platform developed within the research project Secure Operation of Sustainable Power Systems (SOSPO). The SOSPO simulation platform (SOSPO-SP) functions in a closed loop integrating new real-time assessment methods to provide useful information to operators in power system control centers, and to develop new control methodologies that handle emergency situations and avoid power system blackouts.

Rapid-Charging Navigation of Electric Vehicles Based on Real-Time Power Systems and Traffic Data

Electric vehicles (EVs) have attracted growing attention in recent years. However, daily charging of EVs, in particular rapid charging, may impact power systems, especially during peak hours, and the effects may occur in different places as traffic conditions change. To address these issues, we describe an integrated rapid-charging navigation strategy that considers both the traffic conditions and the status of the power grid. The system is based on an intelligent transport system (ITS), and contains four modules: a power system control center (PSCC), an ITS center, charging stations, and EV terminals. The PSCC calculates the available charging capacity and station charging capacity based on power grid data and transmits the results to the charging stations. The charging stations determine their charging plans and estimate the available charging power for future EVs (CPFE), and transmit these data to the ITS center. After receiving CPFE data and traffic data from the ITS center, the EV terminal estimates the total time for charging (TTC) for different stations, which includes the driving time, waiting time, and charging time. The driver can view these results and choose to be navigated to the charging station corresponding to the minimum TTC. The modular design of the navigation system reduces data transmission, which protects the drivers' privacy since they can choose which charging station to use and are not required to send any data to the ITS system. Simulation results demonstrate the feasibility of the proposed method for different working conditions for power system and traffic conditions.

Data Framing Attack on State Estimation

A new mechanism aimed at misleading a power system control center about the source of a data attack is proposed. As a man-in-the-middle state attack, a data framing attack is proposed to exploit the bad data detection and identification mechanisms currently in use at most control centers. In particular, the proposed attack frames meters that are providing correct data as sources of bad data such that the control center will remove useful measurements that would otherwise be used by the state estimator. The optimal design of a data framing attack is formulated as a quadratically constrained quadratic program (QCQP). It is shown that the proposed attack is capable of perturbing the power system state estimate by an arbitrary degree controlling only half of a critical set of measurements that are needed to make a system unobservable. Implications of this attack on power system operations are discussed, and the attack performance is evaluated using benchmark systems.

Computational Approaches for Bad Data Handling in Power System Synchrophasor Networks

Abstract The state estimators used in real-time power system control centers now process bad data as a standard routine. With the introduction and deployment of phasor measurement units (PMUs), it is possible to model power systems, even with their time-varying nature, in real-time. However, PMUs remain vulnerable to providing bad data for several reasons. In this paper, a new intelligent framework, the cellular computational netwo rk (CCN), is introduced for the decentralized predictive modeling and dynamic state estimation (DSE) of a power system with PMU data. The CCN-based DSE is resilient to interactions between multiple segments of bad data from one or more PMUs.

Assessing the Impact of Insufficient Situation Awareness on Power System Operation

Situation awareness is a key factor in preserving power system security, as it enables effective and timely decision-making and reactions by the operators to an incident. Insufficient situation awareness results in a delayed, incorrect or deficient response, endangering power system stability. This factor was actually identified as one of the main causes of several electrical disturbances in the last decade. This paper identifies numerous factors that govern the formation of situation awareness in a power system control center. A multi-state model based on Markov modeling is proposed for assessing the impact of insufficient situation awareness on the probability of power system blackouts. The proposed model considers the level of situation awareness and the state of the information infrastructure. The workings of this model are illustrated using the IEEE 24-bus Reliability Test System.

A new method for simultaneous optimal placement of PMUs and PDCs for maximizing data transmission reliability along with providing the power system observability

In the hierarchical structure of a wide area measurement system (WAMS), the measurements obtained by phasor measurement units (PMUs) in a local area are first submitted to the related phasor data concentrator (PDC), and then to the power system control center. In this paper, a new method for the optimal placement of PMUs as well as PDCs in local networks of a WAMS is proposed. This method minimizes the probability of failures in data transmission from PMUs to PDCs. In the proposed method, first it is assumed that PMUs are installed on all system buses. Then, the redundant PMUs will be omitted one after the other in a multi-stage procedure. The multi-stage elimination procedure is such that in each stage the arrangement of PMUs–PDC with the highest reliability will be kept. The IEEE 14-, 30-, as well as 118-bus test systems are used to demonstrate the proposed algorithm and to verify the results. In numerical simulations, the power system observability is treated in various conditions such as the base case, N−1 condition and the case of considering the single line outage.

Operation Indices for Smart Power Dispatch Center Design

With the development of power systems, power grid within a control area becomes much more complicated due to increasing number of nodes and renewable energy interconnections. The role of power system control center is more critical in maintaining system reliable and security operations. Latest developed information and communication technologies provide a platform to enhance the functions and performance of power system control center. Smart power dispatch concept will be the trend of future control center development. In this paper, we start from the human factors of control center design and propose operation indices to reduce the information presented to the system operator. The operation indices will be the important criteria in situation awareness of a power grid. Past, present, future and capability states of a power grid are also proposed to provide better visions to the operator of system conditions. The basic ideas of operation indices and operation states are discussed in the paper. In the end, the design factors for a power dispatch cockpit are discussed.

Overview of System Identification for Power Systems from Measured Responses

Large interconnected power systems are arguably some of the most complicated man-made systems to understand and to characterize. The scale of the problem is immense, involving large numbers of generators, controllers, and transmission lines covering millions of square kilometers. Measurement technology has reached a point where Phasor Measurement Units (PMUs) are being widely installed in power systems all over the world. These devices provide time synchronized (via GPS) phasor measurements from throughout the power grid to Phasor Data Concentrators (PDCs) at power system control centers. These time series can be used to better characterize the system and hopefully, in the long term, to better control the system. This paper presents a tutorial on estimating power system characteristics from measured responses. About a given operating point, power system low-frequency dynamics are well modeled as a high-order, multi-input, multi-output linear system. Of primary interest is the estimation of the inter-area electromechanical modes of the system. These inter-area modes involve generators from one area of the system oscillating against generators in another area of the system. The modes are characterized by their frequency, damping, and shape. In August 1996, the western United States experienced a massive wide spread black out caused by an unstable inter-area mode, involving generators in the north swinging against generators in the south. This paper overviews the problem and examines several methods of estimating the electromechanical modes under different signal conditions. Several real-world examples are given for estimating the electromechanical modes from ambient, transient, or probing situations. When the system is probed, more general state-space and transfer-function models are estimated. Probing a power system with known inputs is challenging and is discussed in this paper. Estimation performance issues are also discussed.

An Alternative Method for Power System Dynamic State Estimation Based on Unscented Transform

An efficient, timely, and accurate state estimation is a prerequisite for most energy management system (EMS) applications in power system control centers. The emerging wide-area measurement systems (WAMSs) offer new opportunities for developing more effective methods to monitor power system dynamics online. Recently, alternative methods for power system state estimation have caught much attention. Due to the nonlinearity of state transition and observation equation, linearization and Jacobian matrix calculation are indispensible in the existing methods of power system state estimation. This makes WAMS' high performance compromised by burdensome calculation. In order to overcome the drawbacks, this study tries to develop an effective state estimation method without the linearization and Jacobian matrix calculation. Firstly, unscented transformation is introduced as an effective method to calculate the means and covariances of a random vector undergoing a nonlinear transformation. Secondly, by embedding the unscented transformation into the Kalman filter process, a method is developed for power system dynamic state estimation. Finally, some simulation results are presented showing accuracy and easier implementation of the new method.

Ultra-short-term multi-node load forecasting – a composite approach

In the electric power system, grasping active and reactive load variation regularity of each node is a key problem for optimal dispatch, preventive control, security assessment and transmission capacity evaluation. This study presents a novel composite approach of ultra-short-term forecasting for multi-node active and reactive load. It proposes a hierarchy and sub-area idea to construct a framework of self-adapting dynamic load models. With load forecasting at the top layer implemented by the recursive least square support vector machines (RLS-SVM) algorithm, discrete state-space equations are established to describe the dynamic characteristics of the multi-node active load distribution factors and power factors, and then the Takagi–Sugeno (TS) fuzzy control technique is introduced to realise feedback compensation. The application of the proposed technique in the actual power system control centre of Shandong Province is verified and satisfactory results are found.

Risk management in power system control centres

This article is the result of investigations which indicated that conditions, particularly safety management, at power system control centres were either contributing factors or causal factors in the large-scale blackouts which occurred in 2003 all over the developed world. An exploratory research methodology was followed in an attempt to determine the baseline level of safety management within the control centres along with the applicability of the safety management concepts. The experience survey developed followed a flexible line of questioning which illuminated the context and produced both quantitative and qualitative data. The results indicated that there was no support for the proposition that the control centre business environment is becoming more complex and the risk management was not adequate; neither was there support for the proposition that the risk management strategies were based on more than one class of accident model. There was however support for the proposition that control centres do not use systemic accident models on which to base their accident prevention techniques. Key words: Risk management, accident prevention, safety management.

Real-time Simulation and Analyses of Ship Energy Management System Network

Ship Energy Management System (SEMS) was the ship power system management and control center based on network. The real-time and reliability of network was the foundation of SEMS reliable operation. The characteristics of SEMS were analyzed by comparing with the land energy management systems, and the network topology was proposed based on switched Ethernet. The major traffics of SEMS were classified by its real-time and modeled in OPNET. Then the factors which affected the traffic real-time transmission were analyzed, and for which the solution methods were given and tested. This simulation approach also provides a reference method to study the future SEMS network.

Energy Efficient Security Algorithm for Power Grid Wide Area Monitoring System

Modern power grid is the most complex human-made system, which is monitored by wide-area monitoring system (WAMS). Providing time-synchronized data of power system operating states, WAMS will play a crucial role in next generation smart grid protection and control. WAMS helps secure efficient energy transmission as well as reliable and optimal grid management. As the key enabler of a smart grid, numerous sensors such as PMU and current sensors transmit real-time dynamic data, which is usually protected by encryption algorithm from malicious attacks, over wide-area-network (WAN) to power system control centers so that monitoring and control of the whole system is possible. Security algorithms for power grid need to consider both performance and energy efficiency through code optimization techniques on encryption and decryption. In this paper, we take power nodes (sites) as platforms to experimentally study ways of energy consumptions in different security algorithms. First, we measure energy consumptions of various security algorithms on CrossBow and Ember sensor nodes. Second, we propose an array of novel code optimization methods to increase energy consumption efficiency of different security algorithms. Finally, based on careful analysis of measurement results, we propose a set of principles on using security algorithms in WAMS nodes, such as cryptography selections, parameter configuration, and the like. Such principles can be used widely in other computing systems with energy constraints.

Flexible open architecture design for power system control centers

That the new generation power system control centers need a paradigm shift in their architectural design to meet new challenges, is an established conclusion of many researchers. However, literature on comprehensive architectural design towards this direction is scarce. In this paper, an information architecture design is proposed for the power system control centers. Appropriate adoption of open standards such as the common information model (CIM) is endorsed. Further, initial development of an event information model for modeling high level power system events is mentioned. Proposed architecture focuses on the desired features such as openness, interoperability, flexibility, scalability, vendor independence and event orientation. The architecture comprises services arranged in layers, viz., data integration and access, event processing and plug-in services. The details of this architecture along with the intricate relationships between various layers and services depicting how the technologies could be integrated into a coherent whole are described in this paper. An illustrative example, from the Indian power sector domain has been used to demonstrate the usefulness of the proposed architecture.