| 1. |
- Ahonen, Mikko, PhD, post-doc researcher, 1968-, et al.
(författare)
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Voltage transients measurements and power line communication
- 2016
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Ingår i: 2016 57th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON). - : IEEE. - 9781509037315 ; , s. 1-4
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Konferensbidrag (refereegranskat)abstract
- Power line communication (PLC) connects energy producers with energy consumers. In the European Union stricter guidelines are under development to limit disturbances in the 2-150 kHz frequency range, because devices utilising PLC do not work. This study measured voltage transients in 22 locations and identified sources for noise. Home environments and public buildings were measured. Measurements were conducted in the frequency range of 150 kHz-500 kHz (according to EN 55011 to EN 55022) and in the lower frequency range of 3 kHz to 95 kHz. Results indicate that voltage transients are generated mostly by switching mode power supplies, pumps, rectifiers, inverters and even low quality smart meters. Several of these devices exceeded PLC standard level, 122 dBμV. Additionally we demonstrate that basic power quality recordings do not provide enough information to mitigate PLC problems occurring within microseconds and frequency specific voltage transient measurements are needed.
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| 2. |
- Uzunoglu, Bahri, et al.
(författare)
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Particle filter joint state and parameter estimation of dynamic power systems
- 2016
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Ingår i: 2016 57th International Scientific Conference On Power And Electrical Engineering Of Riga Technical University (RTUCON). - 9781509037315
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Konferensbidrag (refereegranskat)abstract
- Intermittent renewable energy sources in distributed generation will increase the chance of sudden unpredictable changes in the system states and parameters of dynamic power systems. To track the changes of the power systems, system state and parameter estimation methods that can track the near real-time dynamics of the power systems are needed. Power system operators still employ simulation studies using off-line models that are built based on prior knowledge gained through information via simulated typical scenarios which does not make use of posterior knowledge of neither parameter space nor state space of the dynamics of the power systems. Dynamic models of a power system has increasingly more important role in power system operations since they impact the operational conditions of dynamical power system. In this study, we propose a particle filter based state and parameter estimation method to improve modelling accuracy, which determines the best set of model parameters using realtime measurement data. This can be achieved via measurements by Phasor Measurement Units (PMU) or Remote Terminal Units (RTU) that can capture the system dynamic responses in real time. In addition, parameters of the system can also be estimated. Herein the load will he the parameter of the system that needs to be estimated jointly with the states. Joint state and parameter estimation for power systems via employing Bayesian particle filter is being introduced in this study.
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