PMU Based Frequency Regulation Paradigm for Multi-Area Power Systems Reliability Improvement
Abstract : This work proposes a novel frequency regulation paradigm for multi-area interconnected power systems. The developed approach capitalizes on phasor measurement units (PMUs) advanced monitoring to overcome design limitations imposed by legacy supervisory control and data acquisition (SCADA) systems. For this, a novel measurement-based controller integrating primary and secondary regulation is proposed. First, taking advantage of PMUs synchronized measurements, novel centralized corrective actions are developed using dynamic data aggregation. These actions provide a foreknowledge of generators expected steady-state during the system dynamics, significantly improving the system frequency rebound and steady-state realization while ensuring null area control errors (ACE). Next, a new local power system stabilizing perspective is developed. This controller provides local counterweighting actions allowing for faster corrective actions without compromising the system dynamic response, i.e. mitigating oscillations and overshoots. The proposed approach design considers monitoring and communication system non-idealities, such as: latency, processing and waiting time, measurements synchronization and sampling resolution. In addition, stability and steady-state objectives are mathematically demonstrated, and comparative simulation case-studies developed. Obtained results indicate a meaningful improvement of power systems frequency regulation and reliability, including faster steady-state realization and rebound, mitigation of oscillations and overshoot, improved service capacity and higher reliability to cascade events.
? The disturbances that have affected the power system can be thoroughly studied and analyzed using the high reporting rate of the PMU.
? This helps in modifying the existing power system to a more stable system. The classification of the faults based on the signature patterns associated with each disturbance can be done with the help of PMU data.
? All the disturbances are tested in this system at different positions and the results where verified using the GUI developed in MATLAB.
? The post disturbance analysis cannot be efficiently done using the SCADA.
? In this paper, we consider a placement problem to ensure observability while achieving a desired level of reliability of observability.
? A placement model is developed considering the reliability of an individual PMU (p), to achieve a specified level of system-wide reliability (R). The problem is formulated as a two-stage optimization model.
? An integer linear programming (ILP) approach to solve this problem was proposed by, and subsequently extended by Gou to address the cases of redundancy, partial observability, and pre-existing conventional measurements.
• This paper proposes a new system for analyzing the PMU data and monitoring power system faults with minimum operator skill so that the post event information can be identified and handled effectively in the Load Dispatch Centers.
• Wavelet based signal processing methods with the intelligence of the fuzzy based classifiers to extract all the features in the PMU data is proposed.
• A new analysis methodology using the Lyapunov Exponent was proposed to analyse the transient stability condition.
• This paper focuses on building a system to identify various disturbances in the power grid. The system will be able to classify the different disturbances and faults that occur in the grid.
? System reliability is the probability that a system will perform its intended function for a given period of time under pre-specified operating conditions.
? Moreover, for a system to perform its intended functions, it is important that all components and subsystems contained in the system are highly reliable and able to perform specified functions within given requirements.
? Reliabilitybased models have been used widely in system design optimization to improve system functionality and reliability.
? This simple model is very effective in computing placement solutions with desired levels of system reliability, given the reliability of individual PMUs.
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