Advanced Converter Control Techniques for Improving the Performances of DFIG based Wind Turbines

Unter den alternativen erneuerbaren Energiequellen hat Windenergie in den letzten zehn Jahren den größten Stellenwert im Energieerzeugungssystem erlangt. Die Erhaltung bzw. die Verbesserung der Zuverlässigkeit des Stromversorgungsnetzes mit zunehmenden Windenergieanlagen und deren optimale Nutzung ist eine der wichtigsten Aufgaben. Die Windenergieanlagen sind im Netzbetrieb bestimmten in Netzanschlussrichtlinien angegebenen Anschlussregeln unterworfen. Dies erfordert eine detaillierte Untersuchung von Windenergieanlagen in verschiedenen operativen Szenarien, so dass geeignete Lösungen empfohlen werden können, insbesondere bezüglich Umrichter-Regelung, die die Hauptrolle im Gesamtsystem spielen. In dieser Forschung wurde der doppelt-gespeiste Asynchrongenerator, der immer noch am häufigsten verwendeter Windturbinentyp ist, für eine detaillierte Untersuchung ausgewählt. Sowohl das Betriebsverhalten im stationären Betrieb allgemein als auch unter Berücksichtigung von zwei alternativen Pulsweiten-Modulation (PWM)-Typen und verschiedenen Umrichter-Topologie, untersucht. Vergleichskriterien sind die erzeugte maschinenseitige „common mode“ Spannung, Gesamtverzerrung der Stromwelle im Niederspannungsnetz, Umrichter-Leistungsverluste und Blindleistung-Einspeisefähigkeit. Zusätzlich werden die Anzahl der Komponenten im kompletten Umrichter-System und die geschätzten Kosten als Vergleichskriterien herangezogen. Bezüglich des ersten Szenarios, der Einfluss unterschiedlicher PWM-Typen auf Umrichter Verlustleistung, die Blindleistung-Einspeisefähigkeit und die gesamte harmonische Verzerrung wurden im Detail untersucht, und der am besten geeignete PWM-Typ bezüglich optimaler Leistungskriterien sowie Drehzahlbereiche vorgeschlagen. Im zweiten Szenario wurden zwei verschiedene Umrichter-Topologie, nämlich zweistufiger „Back-to-Back“ Umrichter und dreistufiger „Neutral-Point-Clamped (NPC)“ „Back-to-Back“ Umrichter wurden im Simulationsmodell implementiert, und auf der Grundlage der Simulation Ergebnisse ihre Eignung in Bezug auf Kosten gegen die anfallenden Betriebsvorteile verglichen. Schließlich wurde ein neues Schutzschema für „Fault-Ride-Through“ im dreistufigen „Backto- Back“ NPC-Umrichter als Alternative zum konventionellen Schutzschema mit Chopper im Gleichspannung-Zwischenkreis vorgeschlagen. Das vorgeschlagene Schema zeigt ein sehr ähnliches dynamisches Verhalten wie das konventionelle Schema, wenn die inneren IGBTs des maschinenseitigen Wechselrichters (MWR) für etwa zweifachen Nennstrom der Überstromschutzgrenze ausgelegt werden. Außerdem ermöglicht eine einfachere Bedienung ohne höhere Anzahl von Komponenten. Die Verwendung von inneren IGBTs mit höherem Nennstrom erhöht die Kosten der MWR. Jedoch werden die Gesamt Kosten um etwa 15% weniger, da der Chopper im Gleichspannung-Zwischenkreis dadurch überflüssig gemacht wird.Among the renewable energy alternatives, wind energy has made the biggest impact on the total energy production in the last decade. Maintaining or improving the reliability of the wind turbine system in power generation sector with optimal performances is one of the important tasks. Especially the wind turbines connected to the grid are subjected to certain electricity grid connection regulations specified in grid codes. A detailed study of the performance of wind turbine systems in various case scenarios is necessary, so that appropriate solutions can be recommended, especially in the converter controls which play the major role in the overall system. In this thesis, the doubly fed induction generator (DFIG) which is still the most widely used wind turbine type is selected for detailed investigation. Its performances during steady state operation in two alternative scenarios, namely, using different pulse width modulation (PWM) types and using different converter topologies, are investigated. The performance criteria include generated common mode voltage at machine side converter (MSC), current total harmonic distortion in the low voltage network, converter power losses and reactive power capability. Additionally, the component counts in the converter and its estimate cost are compared. Regarding the first scenario, the influence of different PWM types on the converter power losses, the reactive power capability and the total harmonic distortion has been investigated in detail, and the most suitable PWM type depending on the optimal performance criteria as well as operational speed range is proposed. In the second scenario, two different converter topologies, namely back-to-back two-level converter and back-to-back three-level neutral point clamped (NPC) converter were implemented in the simulation model, and on the basis of the simulation results their performances in terms of cost against the accruing operational advantages are compared. Finally, a new protection scheme for fault ride-through in back-to-back three-level NPC converter is proposed as an alternative to conventional protection scheme using DC-link chopper. The proposed scheme shows a very similar dynamic behaviors with the conventional scheme when the inner IGBTs of the MSC are designed for about two times higher current rating than the over-current protection limit. Furthermore, it implements simpler operation without higher component count. The need for the inner IGBTs with higher current rating significantly increases the cost of the MSC. However, the total cost of the DFIG system is slightly reduced about 15% by the elimination of the DC-link chopper circuit

DC-link protection for grid-connected photovoltaic system: a review

As the economic growth and population increase, the demand on energy supply has also increases. The disadvantages that energy production based on non-renewable energy sources bring to the environment has stimulate the idea of producing a clean and sustainable power in huge quantities from renewable energy sources such as solar and wind energy. In recent years, photovoltaic (PV) systems are mostly used due to its light and easy-installable characteristics. It has two approaches which are stand-alone PV system (off-grid) and grid-connected PV system. Although it is said to be the most promising renewable energy, it could not avoid from disturbance. In grid-connected PV system, faults could occur on the grid side, leading to the increase in DC-link voltage and overshoot grid current. These situations could stress electrical components and decrease power quality of the system. Therefore, many protection schemes have been introduced to overcome this matter. In this paper, the development of grid-connected PV system was expressed and the impacts of grid faults on were discussed. Several conventional protection schemes implemented in the grid-connected PV system were reviewed. In the end, this paper proposed a new protection scheme which namely zero protection scheme that has the same function to limit the overshoot in DC-link voltage

A comparative analysis of solar photovoltaic advanced fault detection and monitoring techniques

The non-linear I-V characteristics of the photovoltaic output have affected fault detection methods to work accurately. This scenario can cause hidden faults in the system and reduces overall productivity. Fault detection and monitoring techniques are evolving in photovoltaic fault management systems. Until recently, model-based technique, output signal analysis technique, statistically based technique, and machine learning techniques are the four main advanced fault detection methods that researchers have widely studied. This study has identified the limitations and advantages of previous photovoltaic fault detection and monitoring techniques, especially their applicability to all sizes of photovoltaic systems. This study proposes a multi-scale dual-stage photovoltaic fault detection and monitoring technique for better system safety, efficiency, and reliability. Challenges and suggestions for future research directions are also provided in this study. Overall, this study shall provide researchers and policymakers with a valuable reference for developing better fault detection and monitoring techniques for photovoltaic systems

A multi-scale dual-stage model for PV array fault detection, classification, and monitoring technique

The output generated by photovoltaic arrays is influenced mainly by the irradiance, which has non-uniform distribution in a day. This has resulted in the current-limiting nature and nonlinear output characteristics, and conventional protection devices cannot detect and clean faults appropriately. This paper proposes a low-cost model for a multi-scale dual-stage photovoltaic fault detection, classification, and monitoring technique developed through MATLAB/Simulink. The main contribution of this paper is that it can detect multiple common faults, be applied on multi-scale photovoltaic arrays regardless of environmental conditions, and be beneficial for photovoltaic system maintenance work. The experimental results show that the developed algorithm using supervised learning algorithms mutual with k-fold cross-validation has produced good performances in identifying six common faults of photovoltaic arrays, achieved 100% accuracy in fault detection, and achieved good accuracy in fault classification. Challenges and suggestions for future research direction are also suggested in this paper. Overall, this study shall provide researchers and policymakers with a valuable reference for developing photovoltaic system fault detection and monitoring techniques for better feasibility, safety, and energy sustainability

An Intelligent Data-Driven Approach for Electrical Energy Load Management Using Machine Learning Algorithms

Data-driven electrical energy efficiency management is the emerging trend in electrical energy forecasting and management. This fusion of data science, artificial intelligence, and electrical energy management has turned out to be the most precise and robust energy management solution. The Smart Energy Informatics Lab (SEIL) of the Indian Institute of Technology (IIT) conducted an experimental study in 2019 to collect massive data on university campus energy consumption. The comprehensive comparative study preparatory to the recommendation of the best candidate out of 24 machine learning algorithms on the SEIL dataset is presented in this work. In this research work, an exhaustive parametric and empirical comparative study is conducted on the SEIL dataset for the recommendation of the optimal machine learning algorithm. The simulation results established the findings that Bagged Trees, Fine Trees, and Medium Trees are, respectively, the best-, second-best-, and third-best-performing algorithms in terms of efficacy. On the contrary, a reverse ranking is observed in terms of efficiency. This is grounded in the fact that Bagged Trees is most effective algorithm for the said application and Medium Trees is the most efficient one. Likewise, Fine Trees has the optimum tradeoff between efficacy and efficiency

A Hybrid Soft Computing Framework for Electrical Energy Optimization

Electricity is a significant and essential player in the modern world economy. It translates into the social, economic, and sectorial growth of any region. The scarcity of these resources demands a highly efficient and robust energy management system (EMS). In the recent literature, many artificial intelligence algorithms have been proposed to cater to the need for efficient and real-time decision-making. Moreover, the hybridization of these algorithms has also been proposed for optimum decision-making. In this paper, a hybrid soft-computing-based framework has been proposed for intelligent energy management and optimization. The proposed model has based on the evolutionary neuro-fuzzy approach that can predict the energy demand as an objective function and optimize the energy within the given constraints. The future extension of this work will be the implementation and validation of the proposed framework on either a real application dataset or dataset opted from the benchmark repositor

A Novel Deep Learning Architecture for Data-Driven Energy Efficiency Management (D2EEM) - Systematic Survey

The Energy Management System (EMS) is the cost-effectiveness, robustness, and flexible approach for energy efficiency management (EEM). Data-Driven Energy Efficiency Management (D2EEM) is a recent advancement in EMS. The D2EEM is the blend of data science and artificial intelligence for EEM. Due to the highly tolerant to the performance plateau and unconstraint to the feature extraction, Deep Learning (DL) facilitates handling big data-driven problems of EEM. To the best of the knowledge, the accurate and robust D2EEM is the pressing need. Moreover, the accurate pre-trained DL network for EEM is not available in the recent literature. In this work, a comprehensive study is presented to devise a D2EEM. Moreover, the architecture is suggested in connection to the research gap

Comparative Study on the Performances of PV System with Various Combinations of Converter Topologies and PWM Types

Increasing demand for electricity generated from renewable energy sources forced power utility provider to develop more and larger power plant. In Malaysia, among renewable energy sources, photovoltaic (PV) is the most reliable. Hence, large-scale PV power plants have been developed and many more to be developed in the future. In case of large GridConnected PV (GCPV) power plant, the converter which is nonlinear load will generate Total Harmonic Distortion (THD) into the electrical power system. Harmonic generated by the PV system may downgrade the quality of power grid and affect the reliability and safety. In addition, other main concerns in GCPV system are switching losses of the switching devices in the converter and the cost of the converter. These performances can be improved by the right choice of Pulse Width Modulation (PWM) type and converter topology. This paper will discuss which PWM type and converter topology should be chosen to produce the optimal performance based on THD, switching losses and cost. In general, the best combination is a two-level converter with continuous PWM (CPWM) where the cost is almost half compared to the three-level converter and having optimal value in the combined performance of THD and switching losses