Self-healing Power System Research Articles

Detection and Prevention of Unintentional Formation of Loops in Self-Healing Power Systems and Microgrids

Self-healing or self-assembling power systems that rely on local measurements for decision making can provide significant resilience benefits, but they also must include safeguards that prevent the system from self-assembling into an undesirable configuration. One potential undesirable configuration would be the formation of closed loops for which the system was not designed, a situation that can arise any time that two intentional-island systems can be connected in more than one place, e.g. if tie-line breakers are included in the self-assembling system. This paper discusses the unintentional loop formation problem in self-assembling systems and presents a method for mitigating it. This method involves calculating the correlation or the mean absolute error (MAE) between the two local frequency measurements made on either side of a line relay. The correlation and MAE between these frequencies changes significantly between the loop and non-loop cases, and this difference can be used for loop detection. This paper presents and explains the method in detail, presents evidence that the method's underlying assumptions are valid, and demonstrates in PSCAD two implementations of the method. The paper concludes with a discussion of the strengths and weaknesses of the proposed method.

Power Systems Stability through Piecewise Monotonic Data Approximations – Part 1: Comparative Benchmarking of L1PMA, L2WPMA and L2CXCV in Overhead Medium-Voltage Broadband over Power Lines Networks

This first paper assesses the performance of three well-known piecewise monotonic data approximations ( i.e. , L1PMA, L2WPMA, and L2CXCV) during the mitigation of measurement differences in the overhead medium-voltage broadband over power lines (OV MV BPL) transfer functions. The contribution of this paper is triple. First, based on the inherent piecewise monotonicity of OV MV BPL transfer functions, L2WPMA and L2CXCV are outlined and applied during the determination of theoretical and measured OV MVBPL transfer functions. Second, L1PMA, L2WPMA, and L2CXCV are comparatively benchmarked by using the performance metrics of the percent error sum (PES) and fault PES. PES and fault PES assess the efficiency and accuracy of the three piecewise monotonic data approximations during the determination of transmission BPL transfer functions. Third, the performance of L1PMA, L2WPMA, and L2CXCV is assessed with respect to the nature of faults — i.e. faults that follow either continuous uniform distribution (CUD) or normal distribution (ND) of different magnitudes—. The goal of this set of two papers is the establishment of a more effective identification and restoration of the measurement differences during the OV MV BPL coupling transfer function determination that may significantly help towards a more stable and self-healing power system. Citation:  Lazaropoulos, A. G. (2017). Power Systems Stability through Piecewise Monotonic Data Approximations – Part 1: Comparative Benchmarking of L1PMA, L2WPMA and L2CXCV in Overhead Medium-Voltage Broadband over Power Lines Networks. Trends in Renewable Energy , 3(1), 2-32. DOI: 10.17737/tre.2017.3.1.0029

Feasibility Study of Centralized Multi-agent Self-healing Power System with Superconducting Fault Current Limiter

Recently, self-healing power systems have evolved towards centralized instructions and control functions. This paper delineates the feasibility analysis of self-healing power systems using Multi-Agent System (MAS) with Superconducting Fault Current Limiter (SFCL). For a complex power system included various microgrid, it is conceivably doubtful to expect that centralizing the aggregate system control function is practical. Hence, this paper is especially keen on settling on online decision by using smart microgrid control agents that collaborate during normal and fault situations. The control decision is taken by all agents which are deployed at different parts of the circuit. These agents collect their respective circuit information and send to the main central agent. Super conducting fault current limiter is an innovative electric equipment which has the ability to limit peak value of fault current within the first cycle of the fault current. However, a scarcity of research regarding the implementation of SFCL with the multi-agent system in a micro grid is felt. The centralized MAS with SFCL exposed in this paper help to support an enabling technology of future self-healing power system. Feasibility analysis of the proposed centralized MAS with SFCL for self-healing power system has been done by considering faults in different locations of the grid.

Networked Microgrids for Self-Healing Power Systems

This paper proposes a transformative architecture for the normal operation and self-healing of networked microgrids (MGs). MGs can support and interchange electricity with each other in the proposed infrastructure. The networked MGs are connected by a physical common bus and a designed two-layer cyber communication network. The lower layer is within each MG where the energy management system (EMS) schedules the MG operation; the upper layer links a number of EMSs for global optimization and communication. In the normal operation mode, the objective is to schedule dispatchable distributed generators (DGs), energy storage systems (ESs), and controllable loads to minimize the operation costs and maximize the supply adequacy of each MG. When a generation deficiency or fault happens in an MG, the model switches to the self-healing mode and the local generation capacities of other MGs can be used to support the on-emergency portion of the system. A consensus algorithm is used to distribute portions of the desired power support to each individual MG in a decentralized way. The allocated portion corresponds to each MG’s local power exchange target, which is used by its EMS to perform the optimal schedule. The resultant aggregated power output of networked MGs will be used to provide the requested power support. Test cases demonstrate the effectiveness of the proposed methodology.

Special Issue on Smart Grid

Recently many utilities, manufacturers, researchers, government leaders around the world are working on a very sophisticated issue, Smart Grid, to modernize both the electric power transmission and distribution grids for the future. As a suitable subject for special issue for the Journal of Advanced Computational Intelligence and Intelligent Informatics (JACIII), I found that Smart Grid with its impacts on many fields is a timely subject though related to the fundamental concept of this Journal on Intelligence and real-world applications and so forth. Smart grids are intelligent and self-healing power systems which integrate intelligent transmission network with IT and collect, distribute, and process information about the behavior of all power suppliers and consumers in order to improve reliability, power quality, and to reduce electricity costs. Using a key issue, smart meter, enables smart grids to have smart real time monitoring on a regional and national scale to control and management the grids to avoid or mitigate the system-wide blackouts. In this special issue, we hope to explore breakthrough and new contributions useful to achieve the goal of smart grid. Three papers were selected for this special issue: The first paper proposes a novel idea though a strategic system in energy and environment required in smart grid. Managing sources combination including solar energy as well as the production trading is a new kind of risk management in smart grid. Important extensions of this study includes emissions management program accommodating uncertain and erratic renewable energy sources such as solar and wind energies. The second paper is related to communication aspect required for smart grid technology when renewable energy in small smart communities is interconnected to the smart grid. The simulation model developed in this paper is believed to be a useful tool in real-time power management system in smart grid. Third paper is selected as another hot subject in smart grids; the authors developed an extended procedure that obtains a unit commitment including a significant wind power penetration and PEVs as additional reserves. The shadow prices obtained by the trade-off analysis may provide a basis of evaluating the equivalent cost of the wind farms and the applying PEVs as the reserve and their contribution toward CO2 reduction. Finally, using this opportunity, I would like to thank the reviewers for spending their valuable time for evaluating the papers and quick response which made this special issue catch the time. I would also like to thank the JACIII editorial office for their great assistance for preparing this special issue.

SIGNAL PROCESSING TECHNIQUES FOR ESTIMATING POWER SYSTEM MODAL PARAMETERS

Smart Grid is expected to provide a reliable power supply with fewer and briefer outages, cleaner power, and self-healing power systems through advanced Power Quality (PQ) monitoring, analysis and diagnosis of the PQ measurements and identification of the root cause, and timely automated controls. It is important to understand that signal processing has been an integral part of advancing and expanding the horizons of this PQ research significantly and the capabilities and applications of signal processing for PQ are continually evolving. This paper thus presents a survey on the proven and emerging signal applications for enhancing PQ, focusing on algorithms for estimating system modal parameters because resonant frequencies and their damping information are critical signatures in evaluating the PQ. In particular, we discuss the need for investigating time-varying and nonlinear characteristics of the modal parameters due to dynamic changes in system operating conditions and introduce promising signal processing techniques for this purpose.