Analysis and solutions of power harmonics in medium voltage distribution networks

Alghamdi, Thamer 2022. Analysis and solutions of power harmonics in medium voltage distribution networks. PhD Thesis, Cardiff University. Item availability restricted.

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Abstract

The transition toward more sustainable energy systems is driven mainly by greenhouse gas emissions reduction schemes and the growing demand for energy worldwide. Consequently, more Distributed Energy Resources (DER) based power sources and their enabling technologies such as Medium Voltage Direct Current (MVDC) systems are being integrated into the existing distribution networksto help meet such challenges. However, due to the presence of the Power Electronics (PE) based power converters interfacing these systems with the main power network, concerns related to power harmonics in today’s distribution networks must be addressed. To investigate the severity of power harmonics in the distribution networks with the presence of the MVDC converters, a detailed model of an MVDC converter including the switching behaviour of the semiconductor devices with a suitable control system and an interleaved Pulse-width Modulation (PWM) scheme was developed in this study. The key finding is that the proposed harmonic mitigation technique, the interleaved SPWM technique, has significantly reduced the Total Harmonic Distortion (THD) to 2% at the rated system capacity with no significant even-order harmonic components. The real data obtained from the power network of Albaha was also modelled and simulated in the frequency domain using the established harmonic models of the power system components to conductthe harmonic propagations study of the MVDC converter into the AC network. The MVDC converter harmonic performance in the Albaha power system revealed that the THDs at different voltage levels comply with the standard limits. Moreover, applications of Artificial Intelligence (AI), especially the optimization algorithms for power harmonic solutions have received considerable attention over recent years. Thus, in this research, the recently developed Manta Ray Foraging Optimization (MRFO) algorithm has been implemented for the optimal parameters design of a high-pass Passive Power Filter (PPF). An analytical harmonic analysis approach based on the Monte Carlo Simulation (MCS) was also proposed for PPF harmonic performance evaluation including uncertainties at the power network level. For the superiority validation of the MRFO algorithm, different optimizersthat have quite similar hunting and modelling strategies have been adopted. The MRFO algorithm has shown better solution-finding capability but relatively higher computational effort. By including uncertainties at the power network level, the harmonic performance of the optimally designed PPF proposed by the MRFO algorithm was investigated using a proposed MCS-based method, which has shown the significance of the PPF in terms of voltage distortions, system performance parameters, and the network’s hosting capacity for more renewable systems. The results imply that the optimally designed PPF can effectively attenuate the high-order harmonics and improved the system performance parameters over different operating conditions to continually comply with the standard limits. The proposed MCS method showed that the optimally designed PPF reduced the voltage and current distortions by roughly 54% and 30%, respectively, and improved the network hosting capacity by 10% for the worst-case scenario.Furthermore, DER-based power sources are predicted to cause significant harmonic distortions in today’s power networks due to the utilisation of power conversion systems, which are widely recognized as harmonic sources. Identifying the actual contribution of an offending harmonic source can be a challenging task, especially with multiple harmonic sources connected, changes in the system’s characteristic impedance, and the intermittent nature of renewable resources. Hence, a method based on an Artificial Neural Network (ANN) system including the location-specific data was proposed in this thesis to estimate the actual harmonic distortions of a harmonic source. The proposed method would help model the admittance of the harmonic source under the estimation, capture its harmonic performance over different operating conditions, and provide accurate harmonic distortions estimations. For this purpose, a simple power system was modelled and simulated, and the harmonic performance of a solar Photovoltaics (PV) system was used to train the ANN system and improve its prediction performance. Additionally, the expert ANN-based harmonic distortion estimator was validated in the IEEE 34-bus test feeder with different established harmonic sources, and it has estimated the individual harmonic components with a maximum error of less than 10% and a maximum median of 5.4%

Item Type:	Thesis (PhD)
Date Type:	Completion
Status:	Unpublished
Schools:	Engineering
Uncontrolled Keywords:	Power Harmonics, Medium Voltage Direct Current , Power distribution networks , Artificial neural network , Optimal PPF design , Manta Ray Foraging Optimization
Date of First Compliant Deposit:	18 November 2022
Last Modified:	18 Nov 2022 16:45
URI:	https://orca.cardiff.ac.uk/id/eprint/154266

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