Modeling 400 kV transmission grid with system protection and disturbance analysis

2017

Self Cite

A wide area monitoring system (WAMS) with reliable telecommunication infrastructure can be expanded and enhanced with additional protection and control functionalities using synchronized phasor data measurements. With that aim, we have developed a multifunctional line protection (MFLP) model with both system and back-up protection functions. Theoretical premises based on transmission and relay protection system knowledge, together with the experience gathered from the operation of existing wide area systems, were used to develop the proposed model. Four main groups of simulation scenarios were defined in order to test the newly implemented functions. The results of the simulation process confirm the assumptions underlying the design of our MFLP module. Simulation results are then used for definition of the protection criteria required for implementation of the wide area protection algorithm in a control center. Conclusions drawn from the protection responses of the proposed algorithm that strengthen the algorithm design process are elaborated in the paper. The main contribution of the paper is the design and development of a centralized MFLP algorithm based on synchronized phasor data that is able to issue a trip command to a circuit breaker before an out-of-step condition occurs.

Section: Introductionmentioning

confidence: 71%

Wide Area Information-Based Transmission System Centralized Out-of-Step Protection Scheme

Ivanković¹,

Kuzle

2017

Self Cite

“…Line differential protection is implemented on 400, 220 and 110 kV transmission lines. The algorithm of this line differential protection is based on synchronized measurement data, comparable with relay protection device functions [18].…”

Section: Advanced Protection Functions Of the Wampac Systemmentioning

confidence: 99%

Model for 400 kV Transmission Line Power Loss Assessment Using the PMU Measurements

Pavičić¹,

Ivanković³

et al. 2021

This paper presents an advanced model for monitoring losses on a 400 kV over-head transmission line (OHL) that can be used for measured data verification and loss assessment. Technical losses are unavoidable physical effects of energy transmission and can be reduced to acceptable levels, with a major share of technical losses on transmission lines being Joule losses. However, at 400 kV voltage levels, the influence of the electrical corona discharge effect and current leakage can have significant impact on power loss. This is especially visible in poor weather conditions, such as the appearance of fog, rain and snow. Therefore, loss monitoring is incorporated into exiting business process to provide transmission system operators (TSO) with the measure of losses and the accurate characterization of measured data. This paper presents an advanced model for loss characterization and assessment that uses phasor measurement unit (PMU) measurements and combines them with end-customer measurements. PMU measurements from the algorithm of differential protection are used to detect differential currents and angles, and this paper proposes further usage of these data for determining the corona losses. The collected data are further processed and used to calculate the amount of corona losses and provide accurate loss assessment and estimation. In each step of the model, cross verification of the measured and calculated data is performed in order to finally provide more accurate loss assessment which is incorporated into the current data acquisition and monitoring systems.

“…Probably the most suitable installation that imposes itself as an upgrade of the existing system is the usage of simple intelligent electronic devices (IEDs) [9,10]. Together with the increase of the renewable energy share that requires new paradigms and market designs [11], there is also an increasing need for improved monitoring and control possibilities in power systems.…”

Section: Introductionmentioning

confidence: 99%

Wind Power Monitoring and Control Based on Synchrophasor Measurement Data Mining

Klarić¹,

Kuzle

2018

Self Cite

More and more countries and utilities are trying to develop smart grid projects to make transformation of their power infrastructure towards future grids with increased share of renewable energy production and near zero emissions. The intermittent nature of solar and wind power can in general cause large problems for power system control. Parallel to this process, the aging of existing infrastructure also imposes requirements to utility budgets in the form of a need for large capital investments in reconstruction or maintenance of key equipment. Synchrophasor and other synchronized measurement technologies are setting themselves as one of the solutions for larger wind power integration. With that aim, in this paper one possible solution for wind power control through data mining algorithms used on a large quantity of data gathered from phasor measurement units (PMU) is described. Developed model and algorithm are tested on an IEEE 14 bus test system as well as on real measurements made on wind power plants currently in operation. One such wind power plant is connected to the distribution grid and the other one to the transmission grid. Results are analyzed and compared.