Inter-area oscillations: Identifying causes of poor damping using phasor measurement units

Antoine, Olivier; Maun, Jean Claude

doi:10.1109/pesgm.2012.6345408

Cited by 6 publications

(2 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As the CPSS design is based on the linearized system model, the large interconnected grid introduces different controlling signals to the stabilizer under different operating conditions to effectively dampen the small frequency oscillations (Kundur, 1994; Rogers, 2000). Even in recent times, the entire power grid has faced challenges caused by low-frequency oscillations, especially inter-area oscillations, which may lead to islanding or even blackouts (Antoine and Maun, 2012; Kosterev et al , 1999).…”

Section: Conceptual Details Of Wide-area Power System Stabilizer For ...mentioning

confidence: 99%

Gaussian quantum particle swarm optimization-based wide-area power system stabilizer for damping inter-area oscillations

Mony

Peter

Devaraj

2021

WJE

View full text Add to dashboard Cite

Purpose The extensive increase in power demand has challenged the ability of power systems to deal with small-signal oscillations such as inter-area oscillations, which occur under unseen operating conditions. A wide-area measurement system with a phasor measurement unit (PMU) in the power network enhances the observability of the power grid under a wide range of operating conditions. This paper aims to propose a wide-area power system stabilizer (WAPSS) based on Gaussian quantum particle swarm optimization (GQPSO) using the wide-area signals from a PMU to handle the inter-area oscillations in the system with a higher degree of controllability. Design/methodology/approach In the design of the wide-area stabilizer, a dead band is introduced to mitigate the influence of ambient signal frequency fluctuations. The location and the input signal of the wide-area stabilizer are selected using the participation factor and controllability index calculations. An improved particle swarm optimization (PSO) technique, namely, GQPSO, is used to optimize the variables of the WAPSS to move the unstable inter-area modes to a stable region in the s-plane, thereby improving the overall system stability. Findings The proposed GQPSO-based WAPSS is compared with the PSO-based WAPSS, genetic algorithm-based WAPSS and power system stabilizer. Eigenvalue analysis, time-domain simulation responses and performance index analysis are used to assess performance. The various evaluation techniques show that GQPSO WAPSS has a consistently good performance, with a higher damping ratio, faster convergence with fewer oscillations and a minimum error in the performance index analysis, indicating a more stable system with effective oscillation damping. Originality/value This paper proposes an optimally tuned design for the WAPSS with a wide-area input along with a dead-band structure for damping the inter-area oscillations. Tie line power is used as the input to the WAPSS and optimal tuning of the WAPSS is performed using an improved PSO algorithm, known as Gaussian quantum PSO.

show abstract

Section: Conceptual Details Of Wide-area Power System Stabilizer For ...mentioning

confidence: 99%

Gaussian quantum particle swarm optimization-based wide-area power system stabilizer for damping inter-area oscillations

Mony

Peter

Devaraj

2021

WJE

View full text Add to dashboard Cite

show abstract

“…The work proposed in [11] aims at identifying the causes of low damping and to predict the damping using regression trees. In [12] the sensitivity of damping to operating conditions is explored with different approaches-relative sensitivity estimation, artificial neural networks and decision trees-with the aim to derive actions for damping improvement.…”

Section: Statistical Analysis and Forecasting Of Damping In The Nordimentioning

confidence: 99%

Statistical Analysis and Forecasting of Damping in the Nordic Power System

Sulla

Koivisto

Seppänen

et al. 2015

IEEE Trans. Power Syst.

View full text Add to dashboard Cite

This paper presents an application of multiple linear regression (MLR) to extract significant correlations between damping of electromechanical modes and system operating conditions and to forecast future damping values, based on existing day-ahead market forecasts for power flows and generation. The presented analysis uses measurements from the Nordic power system. First, a static MLR model is developed to explain the variability of the damping of the 0.35-Hz inter-area mode in the Nordic system. Together with the static model, a dynamic MLR model is used for forecasting the damping 24 hours ahead, using day-ahead market forecasts. Test results indicate the proposed methods are able to correctly predict about 90% of the low damped operating conditions observed during a year, if day-ahead market forecasts are accurate. These results suggest that the methods could be used to issue early warnings about future operating conditions with low damping.Index Terms-Damping forecast, electromechanical oscillations, multiple linear regression (MLR), phasor measurement unit (PMU) data.

show abstract