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High-quality generator dynamic models are critical to reliable and accurate power systems studies and planning. With the availability of PMUs, measurement-based approach for model validation has gained significant prominence. In this approach, the quality of a model is analyzed by visually comparing measured generator response with the model-based simulated response for large system disturbances. This paper proposes a new set of performance metrics to assess the model validation results to facilitate automation of the model validation process. In the proposed methodology, first, the slow governor response and comparatively faster oscillatory response are separated, and then a separate set of performance metrics is calculated for each of these two components. These proposed metrics quantify the mismatch between the actual and model-based response in a comprehensive manner without missing any information enabling automation of the process. Furthermore, in this paper, we are also proposing that the sensitivity analysis for model calibration be performed with respect to the proposed metrics for the systematic identification of key parameters. Results obtained using both simulated and real-world case-studies validate the effectiveness of the proposed performance metrics for model validation and their application to the sensitivity analysis for model calibration. [ABSTRACT FROM AUTHOR]

Being important information of both network conditions and energy trading, distribution locational marginal prices (DLMPs) are greatly useful for distribution network (DN) management. The goal of this paper is to develop a market mechanism that motivates price-making agents to trade active and reactive power at DLMPs. According to the optimal power flow problem based on second-order cone (SOC) relaxation, we first design the market rules that allow agents to strategically submit proposals of price and power generation/consumption. The market rules induce a noncooperative game between the DN operator and distributed generators. We prove that DLMP pricing can be implemented at any generalized Nash equilibrium (GNE) of the game. We also show that economic properties of strong budget balance, individual rationality, and system cost minimization can be achieved at any GNE. A decentralized algorithm is developed to reach a GNE of the game. Further, based on the convex-concave procedure, an extension of the market mechanism is proposed to cope with the situations that SOC relaxation is inexact. In simulation, the proposed market mechanism is compared with other game-theoretic models, and the economic properties are verified. [ABSTRACT FROM AUTHOR]

The extensive application of information and communication technology (ICT) can effectively improve the operational performance of active distribution systems (ADSs). On the other hand, the use of ICT may expose the systems to cyberattacks. Since feeder automation (FA) in advanced ADS provides fast-responding self-healing capability to restore service during an outage, the potential effect of cyberattacks on ADS becomes more devastating. In this paper, two simple yet powerful cyberattack methods targeting remote terminal units (RTUs) are proposed. The physical response of ADS to malicious cyberattacks on FA is elaborately investigated considering the output fluctuation of distributed generators. The impact of this specific cyberattack on ADS is quantified by a risk assessment index measured in scale and in duration to full restoration. The probability of RTU potentially being attacked is modeled based on search theory. Furthermore, a Bayesian attack graph model is applied and designed to quantify the probability of successfully exploiting the currently known and zero-day vulnerabilities. The proposed methodology is tested and validated via using a modified three-feeder ADS and the IEEE 123 Node Test Feeder. [ABSTRACT FROM AUTHOR]

This paper presents a risk-based procedure for obtaining the best network automation scenario in the presence of uncertainty in distribution networks where performance-based regulation of continuity of supply is used. The proposed approach takes into account the uncertainty in loads, failure rates, and interruption duration. It employs fuzzy sets, fuzzy mixed integer linear programming algorithm, and a tool for managing risk to determine the optimal number, type and location of different types of automation devices in the presence of the aforementioned uncertainty. The presented approach considers performance-based (reward/penalty) schemes for an extended group of network reliability indices (SAIFI, SAIDI, MAIFI, and ASIDI) along with the cost of new automation devices and cost of relocation of the existing devices. [ABSTRACT FROM AUTHOR]

To enable an in-depth study of active cyber-physical distribution network, a cyber subsystem model is urgently needed to describe the performance in distribution communication. The methods for quantifying the interactions between subsystems, especially indirect interactions, have not been adequately studied in the existing research. In this paper, a novel model is developed to evaluate the validity of cyber link considering dynamic routing, delay, and communication error, particularly the cyber traffic. Then, an analytical method is presented to quantify the impact of cyber faults considering the functionality validity during distribution automation. And the reliability of cyber and physical subsystems is evaluated based on nonsequential and sequential Monte Carlo methods, respectively. Finally, a test system for reliability evaluation is established to analyze the influences of cyber faults. In addition, sensitivity analyses on the impact of cyber network traffic, element failure rate, and network topology and access communication technology are carried out. The obtained results could provide useful insights into planning and operation of active cyber-physical distribution networks. [ABSTRACT FROM AUTHOR]

Microprocessor-based relays protecting against fault current have revolutionized power automation industry. The leverage using commercially available information communication technologies has been the currency for future cyberinfrastructure deployment, which enables plausible electronic manipulation that can affect system operation. The bus differential protection has been recognized as one of the most critical protection schemes, if compromised, that would disconnect a large number of components within a substation. A hypothesized substation outage is the worst case scenario of intrusion attack events. This paper proposes an impact analysis of critical cyber assets in substations that capture historical load and topology conditions. This is to identify critical substations and other “nightmare” hypothesized combinations for security protection planning. The proposed metrics of attack scenarios incorporate electronic instrumentation in relation to the physical system for impact and dependency evaluation. Combinatorial verification of these hypothesized events based on the proposed reverse pyramid model (RPM) is validated using IEEE 30- and 118-bus systems. [ABSTRACT FROM PUBLISHER]

Implementing automation system in distribution networks needs a huge investment that usually cannot be funded entirely in a short period of time. So distribution companies (DISCOs) should develop long-term plans to equip their network with automation technologies as far as economically justifiable. Aiming to provide a methodology for development such plans, this paper presents a novel multistage planning model for implementing distribution automation system considering all main hardware and software infrastructures. The proposed method optimally determines the type, location, and time in which an equipment or infrastructure must be added to network considering the network capacity expansion plan. The objective function of the planning problem is to maximize the net present value of the DISCO's profit in the planning time horizon. In this method, the optimization problem is solved using the genetic algorithm approach as a promising technique in solving the mixed integer nonlinear programming problems. The proposed method is evaluated on an illustrative test network and the obtained results are presented and discussed. [ABSTRACT FROM PUBLISHER]

Power systems training and education faces serious challenges due to the rising complexity of energy systems. This paper presents a simulation-based training platform for educating students and power systems professionals in complex Smart Grid applications. The system is split into parts like electrical grid or controls and specialized, domain-specific tools are then coupled to be able to simulate the overall behavior. Experiences with the developed education and training material and the corresponding modeling and simulation environment are discussed. The usage of advanced modeling and simulation approaches, especially when providing new functionality via coupling of simulation, is an accessible way to train and educate students efficiently in the complex and interdisciplinary area of power systems. [ABSTRACT FROM PUBLISHER]

In this paper, the development of an educational tool to improve the learning process about electrical power distribution and utilization systems in power system courses is presented. Usually, power system courses cover several concepts from the generation of electrical energy, transportation, interconnection, transformation, protection, distribution to final consumption. Most concepts are taught using theoretical circuit analysis, mathematical models and simulations in the classroom and laboratories. To improve the learning of some concepts, some technical tours to power stations and substations are made whenever possible. However, experimental exercises in power system courses are very difficult to implement due to safety reasons since most power equipment operates with high voltages. To mitigate this problem and motivate students in this area, a new power system educational tool to simulate electrical power distribution and utilization systems is proposed. The proposed system was developed using a Programmable Logic Controller (PLC) and other industrial equipment. The proposed pedagogical activities of the educational project and the results achieved with this new update are discussed in this study. [ABSTRACT FROM AUTHOR]

For economic reasons, expansions of transmission networks are based on a compromise between capital cost and security of power system operation. At the same time, the power system must withstand typical highly likely contingencies. Various emergency state control systems, also called special protections, prevent emergencies following less likely contingencies. This paper describes overloads emergency state control (OLEC) used for the alleviation of overload in transmission networks near a power plant. Such control uses the functions of automated power reduction of generating units and has been implemented for a large steam power plant. The OLEC presented here uses different methods of generation curtailment for steam generation units. A case study illustrates the efficiency of the proposed control method. [ABSTRACT FROM AUTHOR]

This paper proposes the description of an original smart-grids test bed aimed at teaching novel feeder automation functions to students from both university and industry origins. With this test bed, a lab class proposes to students, first, to develop feeder automation functions using scientific software and, then, to experiment by practically testing them on an emulated distribution grid platform, called PREDIS. This platform includes real medium-voltage reduced-scale loads, generators, and a supervisory control and data acquisition system. The presented lab class is part of a dedicated complete pedagogic module with lectures and experiments. Through the development, the tests and the deployments of their own solutions in an actual distribution grid, the students learn by doing from theory to practice the complete chain of smart-grids solutions: from the electrical to the communication layers. [ABSTRACT FROM PUBLISHER]

We propose an autonomous state estimation based on robotic concepts and advanced state estimation methods. An autonomous, intelligent monitoring infrastructure is proposed that reliably and automatically detects devices as they are plugged-in or -out; it identifies changes in system state and automatically updates the real-time model of the system. The real-time model is used for control, operation, and optimization of the system via application software that are not addressed in this paper. [ABSTRACT FROM PUBLISHER]

The nonlinear effects of a robust μ-synthesis power system stabilizer (MPSS) using a bifurcation subsystem-based control design methodology is studied in this paper. A normal form representation of the nonlinear power system model is introduced such that the nonlinear model can be approximated up to the second order. An MPSS is designed using a bifurcation subsystem-based control design methodology, and the second-order interaction indices of the system with MPSS and conventional excitation control are calculated. The analysis of the nonlinear effects shows that the MPSS becomes dominant in dynamics by replacing the inertial dynamics that were dominant in the original system. [ABSTRACT FROM AUTHOR]

Despite the plethora of Distribution Automation (DA) activity that occurred in the last two decades, very few utilities have embarked on large-scale DA implementation. The main reasons for this appears to have been uncertainty about which DA functions should be implemented and, second, the difficulty in financially justifying DA investments. The paper investigates the combination of DA functions that could best address Eskom s business requirements and, second, upon reaching this conclusion, proceeds to develop a model by which proposed investments in DA systems could be evaluated. [ABSTRACT FROM AUTHOR]

The frequency and damping of electromechanical modes offer considerable insight into the dynamic stability properties of a power system. The performance properties of three mode-estimation block-processing algorithms from the perspective of near real-time automated stability assessment are demonstrated and examined. The algorithms are: the extended modified Yule Walker (YW); extended modified Yule Walker with Spectral analysis (YWS); and sub-space system identification (N4SID). The YW and N4SID have been introduced in previous publications while the YWS is introduced here. Issues addressed include: stability assessment requirements; automated subset selecting identified modes; using algorithms in an automated format; data assumptions and quality; and expected algorithm estimation performance. [ABSTRACT FROM AUTHOR]

Renewable distributed resources, energy storage systems, and improved load control options are introducing new challenges in electric power distribution. It is necessary to integrate such smart grid concepts into formal power engineering curricula. To help meet this need, solar microgrid experiments are being developed at Drexel University. This work presents: first, an overview of the laboratory-scale microgrid equipment at Drexel; second, upgrades to the distribution energy management system in the Reconfigurable Distribution Automation and Control Laboratory; third, a detailed educational microgrid experiment; and fourth, corresponding pre- and postlaboratory assignments. In the experiment, students analyze a microgrid network in grid-powered, grid-interactive, and island modes with a renewable source that is not electrically (or physically) co-located with the utility supply. Students will observe power flow characteristics in each mode. In island mode, students will make network or load control decisions in order to satisfy the operating constraints, and then connect the renewable source to the node of their choice. [ABSTRACT FROM AUTHOR]

This letter presents the outcomes of a trial of an active network management (ANM) scheme on part of the North-Scotland electricity network. The ANM scheme has as its goal the facilitation of increased connections of distributed generation (DG) from renewable resources on the Orkney Isles. The ANM scheme is the first multigenerator application of ANM at distribution level in the U.K. The ANM scheme is briefly discussed prior to the trial of the ANM scheme being introduced. The implications of the trial for full ANM roll-out are discussed. The results of the trial of the ANM scheme are of direct relevance to those working in the areas of ANM, smart grids, and advanced distribution automation. The resuIts confirm that wind farms can be controlled within the thermal constraints of a distribution network subject to certain operating margin considerations. [ABSTRACT FROM AUTHOR]

Presents information on a study which developed a general polling procedure to identify electric power system conditions. Utilization of the capabilities and information provided by a wireless automated meter reading system; Methodology of the study; Results and discussion.

Outlines a five-year work of developing a distribution automation laboratory for undergraduate and graduate education at the Electrical Engineering Department of National Taiwan University. Development of distribution system model with a data acquisition system connected to a personal computer; Remote control of the switches in the distribution system; Description of the three important applications in distribution automation.

This letter describes an approach of applying the model- driven development in power systems. A component-based model-driven architecture, that gives full flexibility of the automation in source code generation, Is introduced. A design pattern to code generation is described. [ABSTRACT FROM AUTHOR]