Combined Generation and Optimization of a Wind-Solar-Battery Power System

Compared with other renewables, wind and solar have been established as proven future sources of energy, because of their environment-friendly, safe and cost-effective characteristics. However, there are some difficulties associated with combined utilization of solar and wind, e.g. intermittency of wind and of the solar radiation, and their variation do not match the time distribution of the demand. For this purpose, advanced network of multiple renewable energy systems with storage units have been proposed. Small-scale standalone combination of solar, wind and battery has been found effective in some independent power supply system. Proposed in this research on a standalone distributed hybrid power system which consists of solar power, wind power and battery storage. A control strategy is introduced to maximize the simultaneous energy harvesting from both renewable sources. The supervisory controller results in five contingencies considering the level of power generation available at each renewable energy source and the state of charge in the battery. Power converters interface the source with a common DC bus. The interfacing converter is controlled either as a current or a voltage source. A supervisory controller is proposed to accomplish the source type allocations and balance of energy in the operating contingencies. Simulation results demonstrate accurate operation of the controllers and functionality of the maximum power point tracking algorithm in each operating condition both for solar and for wind power

Integrated electromechanical wind turbine control for power system operation and load reduction

With the penetration level of wind power in electric power networks increasing rapidly all over the world, modern wind turbines are challenged to provide the same grid services as conventional synchronous power plants. The dynamic interaction between wind turbines and grid has to be assessed first before replacing large amount of conventional power plants by wind power. Over the last few years many power system operators have revised their grid codes and established more demanding requirements for wind power connection. In the past, when wind turbines were small, they were allowed to simply disconnect during a grid fault/disturbance. However, as wind turbine size has increased considerably, their fault ride-through capability has to be improved if the penetration of wind power is to be further increased. Wind turbine design and control need to be improved to optimize the compatibility of wind power and the grid. Among the various requirements that wind turbines have to meet, fault ride-through is of great importance and a very challenging one. Grid faults cause transients not only in the electrical system, but also in the wind turbine mechanical system. The dynamic performance of wind turbines is determined by both mechanical and electrical systems. From the mechanical point of view, the grid disturbance adds extra loads on wind turbine components. Severe grid faults may even lead to wind turbine emergency shut-down. From the electrical point of view, wind farms may lose power generation during a grid fault, which deteriorates the fault impact and slows down the fault recovery. Advanced control and active damping is required to improve wind turbine operation and assist it to remain connected during a grid fault. The novelty of this research is the study of the interaction between mechanical and electrical systems of the wind turbine. The detailed modelling of both the wind turbine mechanical and electrical dynamics not only helps to identify possible problems that wind turbines encounter during grid faults, but also allows adopting a combined approach to design the wind turbine controller. This thesis aims at improving the wind turbine fault ride-through capability and the ability of wind turbine to provide network support during grid disturbances. The main contents are as follows: The detailed model of wind turbine and grid including wind turbine mechanical model, wind turbine controller, synchronous and induction generator model, doubly fed induction generator (DFIG) controller and a generic network model are presented; A wind turbine fault ride-through strategy considering structural loads alleviation is proposed; A controller for asymmetrical fault ride-through of DFIG wind turbines is presented; The effect of having Power System Stabilizer (PSS) on wind turbine is investigated. A multi-band PSS controller for DFIG wind turbine is demonstrated.With the penetration level of wind power in electric power networks increasing rapidly all over the world, modern wind turbines are challenged to provide the same grid services as conventional synchronous power plants. The dynamic interaction between wind turbines and grid has to be assessed first before replacing large amount of conventional power plants by wind power. Over the last few years many power system operators have revised their grid codes and established more demanding requirements for wind power connection. In the past, when wind turbines were small, they were allowed to simply disconnect during a grid fault/disturbance. However, as wind turbine size has increased considerably, their fault ride-through capability has to be improved if the penetration of wind power is to be further increased. Wind turbine design and control need to be improved to optimize the compatibility of wind power and the grid. Among the various requirements that wind turbines have to meet, fault ride-through is of great importance and a very challenging one. Grid faults cause transients not only in the electrical system, but also in the wind turbine mechanical system. The dynamic performance of wind turbines is determined by both mechanical and electrical systems. From the mechanical point of view, the grid disturbance adds extra loads on wind turbine components. Severe grid faults may even lead to wind turbine emergency shut-down. From the electrical point of view, wind farms may lose power generation during a grid fault, which deteriorates the fault impact and slows down the fault recovery. Advanced control and active damping is required to improve wind turbine operation and assist it to remain connected during a grid fault. The novelty of this research is the study of the interaction between mechanical and electrical systems of the wind turbine. The detailed modelling of both the wind turbine mechanical and electrical dynamics not only helps to identify possible problems that wind turbines encounter during grid faults, but also allows adopting a combined approach to design the wind turbine controller. This thesis aims at improving the wind turbine fault ride-through capability and the ability of wind turbine to provide network support during grid disturbances. The main contents are as follows: The detailed model of wind turbine and grid including wind turbine mechanical model, wind turbine controller, synchronous and induction generator model, doubly fed induction generator (DFIG) controller and a generic network model are presented; A wind turbine fault ride-through strategy considering structural loads alleviation is proposed; A controller for asymmetrical fault ride-through of DFIG wind turbines is presented; The effect of having Power System Stabilizer (PSS) on wind turbine is investigated. A multi-band PSS controller for DFIG wind turbine is demonstrated

A Controller for Optimum Electrical Power Extraction from a Small Grid-Interconnected Wind Turbine

[EN] Currently, wind power is the fastest-growing means of electricity generation in the world. To obtain the maximum efficiency from the wind energy conversion system, it is important that the control strategy design is carried out in the best possible way. In fact, besides regulating the frequency and output voltage of the electrical signal, these strategies should also extract energy from wind power at the maximum level of efficiency. With advances in micro-controllers and electronic components, the design and implementation of efficient controllers are steadily improving. This paper presents a maximum power point tracking controller scheme for a small wind energy conversion system with a variable speed permanent magnet synchronous generator. With the controller, the system extracts optimum possible power from the wind speed reaching the wind turbine and feeds it to the grid at constant voltage and frequency based on the AC-DC-AC conversion system. A MATLAB/SimPowerSystems environment was used to carry out the simulations of the system. Simulation results were analyzed under variable wind speed and load conditions, exhibiting the performance of the proposed controller. It was observed that the controllers can extract maximum power and regulate the voltage and frequency under such variable conditions. Extensive results are included in the paper.This work was partially supported by the Spanish Ministry of Education, Culture and Sports-reference FPU16/04282.García-Sánchez, TM.; Mishra, AK.; Hurtado-Perez, E.; Puche-Panadero, R.; Fernández-Guillamón, A. (2020). A Controller for Optimum Electrical Power Extraction from a Small Grid-Interconnected Wind Turbine. Energies. 13(21):1-16. https://doi.org/10.3390/en13215809S1161321Fernández-Guillamón, A., Villena-Lapaz, J., Vigueras-Rodríguez, A., García-Sánchez, T., & Molina-García, Á. (2018). An Adaptive Frequency Strategy for Variable Speed Wind Turbines: Application to High Wind Integration Into Power Systems. Energies, 11(6), 1436. doi:10.3390/en11061436Fernández-Guillamón, A., Sarasúa, J. I., Chazarra, M., Vigueras-Rodríguez, A., Fernández-Muñoz, D., & Molina-García, Á. (2020). Frequency control analysis based on unit commitment schemes with high wind power integration: A Spanish isolated power system case study. International Journal of Electrical Power & Energy Systems, 121, 106044. doi:10.1016/j.ijepes.2020.106044Huber, M., Dimkova, D., & Hamacher, T. (2014). Integration of wind and solar power in Europe: Assessment of flexibility requirements. Energy, 69, 236-246. doi:10.1016/j.energy.2014.02.109Fernández-Guillamón, A., Martínez-Lucas, G., Molina-García, Á., & Sarasua, J.-I. (2020). Hybrid Wind–PV Frequency Control Strategy under Variable Weather Conditions in Isolated Power Systems. Sustainability, 12(18), 7750. doi:10.3390/su12187750Fernández‐Guillamón, A., Vigueras‐Rodríguez, A., & Molina‐García, Á. (2019). Analysis of power system inertia estimation in high wind power plant integration scenarios. IET Renewable Power Generation, 13(15), 2807-2816. doi:10.1049/iet-rpg.2019.0220Fernández-Guillamón, A., Das, K., Cutululis, N. A., & Molina-García, Á. (2019). Offshore Wind Power Integration into Future Power Systems: Overview and Trends. Journal of Marine Science and Engineering, 7(11), 399. doi:10.3390/jmse7110399Muñoz-Benavente, I., Hansen, A. D., Gómez-Lázaro, E., García-Sánchez, T., Fernández-Guillamón, A., & Molina-García, Á. (2019). Impact of Combined Demand-Response and Wind Power Plant Participation in Frequency Control for Multi-Area Power Systems. Energies, 12(9), 1687. doi:10.3390/en12091687Gil-García, I. C., García-Cascales, M. S., Fernández-Guillamón, A., & Molina-García, A. (2019). Categorization and Analysis of Relevant Factors for Optimal Locations in Onshore and Offshore Wind Power Plants: A Taxonomic Review. Journal of Marine Science and Engineering, 7(11), 391. doi:10.3390/jmse7110391Molina-Garcia, A., Fernandez-Guillamon, A., Gomez-Lazaro, E., Honrubia-Escribano, A., & Bueso, M. C. (2019). Vertical Wind Profile Characterization and Identification of Patterns Based on a Shape Clustering Algorithm. IEEE Access, 7, 30890-30904. doi:10.1109/access.2019.2902242Global Wind Report 2019https://gwec.net/global-wind-report-2019/Chagas, C. C. M., Pereira, M. G., Rosa, L. P., da Silva, N. F., Freitas, M. A. V., & Hunt, J. D. (2020). From Megawatts to Kilowatts: A Review of Small Wind Turbine Applications, Lessons From The US to Brazil. Sustainability, 12(7), 2760. doi:10.3390/su12072760Culotta, S., Franzitta, V., Milone, D., & Moncada Lo Giudice, G. (2015). Small Wind Technology Diffusion in Suburban Areas of Sicily. Sustainability, 7(9), 12693-12708. doi:10.3390/su70912693Nazir, M. S., Wang, Y., Bilal, M., Sohail, H. M., Kadhem, A. A., Nazir, H. M. R., … Ma, Y. (2020). Comparison of Small-Scale Wind Energy Conversion Systems: Economic Indexes. Clean Technologies, 2(2), 144-155. doi:10.3390/cleantechnol2020010García-Sánchez, T., Muñoz-Benavente, I., Gómez-Lázaro, E., & Fernández-Guillamón, A. (2020). Modelling Types 1 and 2 Wind Turbines Based on IEC 61400-27-1: Transient Response under Voltage Dips. Energies, 13(16), 4078. doi:10.3390/en13164078Fernández-Guillamón, A., Martínez-Lucas, G., Molina-García, Á., & Sarasua, J. I. (2020). An Adaptive Control Scheme for Variable Speed Wind Turbines Providing Frequency Regulation in Isolated Power Systems with Thermal Generation. Energies, 13(13), 3369. doi:10.3390/en13133369Tiwari, R., Padmanaban, S., & Neelakandan, R. (2017). Coordinated Control Strategies for a Permanent Magnet Synchronous Generator Based Wind Energy Conversion System. Energies, 10(10), 1493. doi:10.3390/en10101493Sajadi, M., De Kooning, J. D. M., Vandevelde, L., & Crevecoeur, G. (2019). Harvesting wind gust energy with small and medium wind turbines using a bidirectional control strategy. The Journal of Engineering, 2019(17), 4261-4266. doi:10.1049/joe.2018.8182Chavero-Navarrete, E., Trejo-Perea, M., Jáuregui-Correa, J. C., Carrillo-Serrano, R. V., & Ríos-Moreno, J. G. (2019). Expert Control Systems for Maximum Power Point Tracking in a Wind Turbine with PMSG: State of the Art. Applied Sciences, 9(12), 2469. doi:10.3390/app9122469Orlando, N. A., Liserre, M., Mastromauro, R. A., & Dell’Aquila, A. (2013). A Survey of Control Issues in PMSG-Based Small Wind-Turbine Systems. IEEE Transactions on Industrial Informatics, 9(3), 1211-1221. doi:10.1109/tii.2013.2272888Daili, Y., Gaubert, J.-P., Rahmani, L., & Harrag, A. (2019). Quantitative Feedback Theory design of robust MPPT controller for Small Wind Energy Conversion Systems: Design, analysis and experimental study. Sustainable Energy Technologies and Assessments, 35, 308-320. doi:10.1016/j.seta.2019.08.002Zhang, X., Huang, C., Hao, S., Chen, F., & Zhai, J. (2016). An Improved Adaptive-Torque-Gain MPPT Control for Direct-Driven PMSG Wind Turbines Considering Wind Farm Turbulences. Energies, 9(11), 977. doi:10.3390/en9110977Shafiei, A., Dehkordi, B. M., Kiyoumarsi, A., & Farhangi, S. (2017). A Control Approach for a Small-Scale PMSG-Based WECS in the Whole Wind Speed Range. IEEE Transactions on Power Electronics, 32(12), 9117-9130. doi:10.1109/tpel.2017.2655940Oliveira, T. D., Tofaneli, L. A., & Santos, A. Á. B. (2020). Combined effects of pitch angle, rotational speed and site wind distribution in small HAWT performance. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 42(8). doi:10.1007/s40430-020-02501-4Battisti, L., Benini, E., Brighenti, A., Dell’Anna, S., & Raciti Castelli, M. (2018). Small wind turbine effectiveness in the urban environment. Renewable Energy, 129, 102-113. doi:10.1016/j.renene.2018.05.062Jeong, H. G., Seung, R. H., & Lee, K. B. (2012). An Improved Maximum Power Point Tracking Method for Wind Power Systems. Energies, 5(5), 1339-1354. doi:10.3390/en5051339Zhu, Y., Cheng, M., Hua, W., & Wang, W. (2012). A Novel Maximum Power Point Tracking Control for Permanent Magnet Direct Drive Wind Energy Conversion Systems. Energies, 5(5), 1398-1412. doi:10.3390/en5051398Chen, J.-H., & Hung, W. (2015). Blade Fault Diagnosis in Small Wind Power Systems Using MPPT with Optimized Control Parameters. Energies, 8(9), 9191-9210. doi:10.3390/en8099191Syahputra, R., & Soesanti, I. (2019). Performance Improvement for Small-Scale Wind Turbine System Based on Maximum Power Point Tracking Control. Energies, 12(20), 3938. doi:10.3390/en12203938Aubrée, R., Auger, F., Macé, M., & Loron, L. (2016). Design of an efficient small wind-energy conversion system with an adaptive sensorless MPPT strategy. Renewable Energy, 86, 280-291. doi:10.1016/j.renene.2015.07.091Lopez-Flores, D. R., Duran-Gomez, J. L., & Chacon-Murguia, M. I. (2020). A Mechanical Sensorless MPPT Algorithm for a Wind Energy Conversion System based on a Modular Multilayer Perceptron and a Processor-in-the-Loop Approach. Electric Power Systems Research, 186, 106409. doi:10.1016/j.epsr.2020.106409Urtasun, A., Sanchis, P., San Martín, I., López, J., & Marroyo, L. (2013). Modeling of small wind turbines based on PMSG with diode bridge for sensorless maximum power tracking. Renewable Energy, 55, 138-149. doi:10.1016/j.renene.2012.12.035Kot, R., Rolak, M., & Malinowski, M. (2013). Comparison of maximum peak power tracking algorithms for a small wind turbine. Mathematics and Computers in Simulation, 91, 29-40. doi:10.1016/j.matcom.2013.03.010Muhsen, H., Al-Kouz, W., & Khan, W. (2019). Small Wind Turbine Blade Design and Optimization. Symmetry, 12(1), 18. doi:10.3390/sym12010018Qi, Z., & Lin, E. (2012). Integrated power control for small wind power system. Journal of Power Sources, 217, 322-328. doi:10.1016/j.jpowsour.2012.06.039Doll, C. N. H., & Pachauri, S. (2010). Estimating rural populations without access to electricity in developing countries through night-time light satellite imagery. Energy Policy, 38(10), 5661-5670. doi:10.1016/j.enpol.2010.05.014Zhang, S., & Qi, J. (2011). Small wind power in China: Current status and future potentials. Renewable and Sustainable Energy Reviews, 15(5), 2457-2460. doi:10.1016/j.rser.2011.02.009Rehman, S., & Sahin, A. Z. (2012). Wind power utilization for water pumping using small wind turbines in Saudi Arabia: A techno-economical review. Renewable and Sustainable Energy Reviews, 16(7), 4470-4478. doi:10.1016/j.rser.2012.04.036Park, J. H., Chung, M. H., & Park, J. C. (2016). Development of a small wind power system with an integrated exhaust air duct in high-rise residential buildings. Energy and Buildings, 122, 202-210. doi:10.1016/j.enbuild.2016.04.037Simic, Z., Havelka, J. G., & Bozicevic Vrhovcak, M. (2013). Small wind turbines – A unique segment of the wind power market. Renewable Energy, 50, 1027-1036. doi:10.1016/j.renene.2012.08.038Parag, Y., & Sovacool, B. K. (2016). Electricity market design for the prosumer era. Nature Energy, 1(4). doi:10.1038/nenergy.2016.32Kortabarria, I., Andreu, J., Martínez de Alegría, I., Jiménez, J., Gárate, J. I., & Robles, E. (2014). A novel adaptative maximum power point tracking algorithm for small wind turbines. Renewable Energy, 63, 785-796. doi:10.1016/j.renene.2013.10.036Emejeamara, F. C., Tomlin, A. S., & Millward-Hopkins, J. T. (2015). Urban wind: Characterisation of useful gust and energy capture. Renewable Energy, 81, 162-172. doi:10.1016/j.renene.2015.03.028Britter, R. E., & Hanna, S. R. (2003). FLOW AND DISPERSION IN URBAN AREAS. Annual Review of Fluid Mechanics, 35(1), 469-496. doi:10.1146/annurev.fluid.35.101101.161147Askarov, A., Andreev, M., & Ruban, N. (2020). Impact assessment of full-converter wind turbine generators integration on transients in power systems. THERMOPHYSICAL BASIS OF ENERGY TECHNOLOGIES (TBET 2019). doi:10.1063/5.0000832Pillay, P., & Krishnan, R. (1988). Modeling of permanent magnet motor drives. IEEE Transactions on Industrial Electronics, 35(4), 537-541. doi:10.1109/41.9176Shariatpanah, H., Fadaeinedjad, R., & Rashidinejad, M. (2013). A New Model for PMSG-Based Wind Turbine With Yaw Control. IEEE Transactions on Energy Conversion, 28(4), 929-937. doi:10.1109/tec.2013.2281814Ata, R., & Kocyigit, Y. (2010). An adaptive neuro-fuzzy inference system approach for prediction of tip speed ratio in wind turbines. Expert Systems with Applications, 37(7), 5454-5460. doi:10.1016/j.eswa.2010.02.068Anelion SW 3.5 GThttps://www.wind-turbine-models.com/turbines/950-anelion-sw-3.5-gtSalles, M. B. C., Hameyer, K., Cardoso, J. R., Grilo, A. P., & Rahmann, C. (2010). Crowbar System in Doubly Fed Induction Wind Generators. Energies, 3(4), 738-753. doi:10.3390/en3040738Kim, Y.-S., Chung, I.-Y., & Moon, S.-I. (2015). Tuning of the PI Controller Parameters of a PMSG Wind Turbine to Improve Control Performance under Various Wind Speeds. Energies, 8(2), 1406-1425. doi:10.3390/en8021406Widanagama Arachchige, L., Rajapakse, A., & Muthumuni, D. (2017). Implementation, Comparison and Application of an Average Simulation Model of a Wind Turbine Driven Doubly Fed Induction Generator. Energies, 10(11), 1726. doi:10.3390/en10111726Kim, C., Gui, Y., Zhao, H., & Kim, W. (2020). Coordinated LVRT Control for a Permanent Magnet Synchronous Generator Wind Turbine with Energy Storage System. Applied Sciences, 10(9), 3085. doi:10.3390/app10093085Das, K., Hansen, A. D., & Sørensen, P. E. (2016). Understanding IEC standard wind turbine models using SimPowerSystems. Wind Engineering, 40(3), 212-227. doi:10.1177/0309524x1664205

Sliding mode control of renewable energy generation systems

As a result of decades of research and innovation in the renewable energy industry, advanced technologies have been developed for both wind and solar energy conversion systems. However, there are still some aspects of the systems that need to be enhanced to enable maximum and cost effective energy conversion. Wind is emerging as an alternative source for electrical power generation. Small-scale wind power generation system applications are becoming widespread because of rising fuel prices and the demand for reducing carbon emission. For such applications, vertical axis wind turbines (VAWT) appeal due to their ability to capture wind from different directions and their low noise-pollution. Wind energy and its conversion system are studied first. The need for advanced maximum power point tracking (MPPT) controllers is discussed in literature focusing on widely implemented algorithms. Sliding mode control theory has been studied and implemented in controlling wind power generation system (WPGS). The dynamic performance of the WPGS using sliding mode control has shown improved dynamic performance, overshoot errors eliminations and higher energy conversion ratios than the widely used proportional integral (PI) control. A new approach in WPGS control strategy by development of a novel soft control strategy based on the mathematical residue theorem has been introduced. The idea of using the residue theorem is to set a soft dynamic boundary for controlled variables around a reference point, so that controlled variables lie on a point inside this boundary. The stability of the system has been ensured by following the Forward Euler method. The developed control strategy has been implemented in different control techniques of a small-scale permanent magnet synchronous generator (PMSG) based WPGS. The introduction of the new control approach based on residue theorem has further improved the energy conversion ratio by 2:5%. Moreover, a wind speed estimation algorithm is provided and implemented to the proposed controllers to overcome the wind speed measurements issues, i.e. cost and accuracy. Furthermore, an improved back-EMF observer based on residual theorem has been designed to estimate the mechanical rotor speed of the PMSG using the stator current and voltage measurements. The improved back-EMF observer has overcome the well-known limitation of the classical back-EMF at low speed observation. In addition, the wind speed has been estimated using the calculated power obtained from the PMSG voltage and current measurements as well as the estimated rotor speed. Based on the wind and rotor speeds, the tip speed ratio (TSR) is calculated and controlled to its optimal value. A MPPT controller has been developed for photovoltaic power generation systems based on a sliding mode control scheme in stand-alone configuration. The developed controller provides a solution to atmospheric conditions measurement issues and it enhances the efficiency of the PV power system. In addition, the developed controller overcomes the power oscillation around the operating point which appears in most implemented MPPT techniques. The MPPT operation is achieved by regulating the input voltage of the PV system using DC-DC boost converter topology. Moreover, a single-ended primary inductor converter (SEPIC) topology has been employed in PV power systems. The restrictions on the application of SEPIC have been solved based on sliding mode control. The efficiency of the PV system has significantly improved

Multi-terminal HVDC grids with inertia mimicry capability

The high-voltage multi-terminal dc (MTDC) systems are foreseen to experience an important development in the next years. Currently, they have appeared to be a prevailing technical and economical solution for harvesting offshore wind energy. In this study, inertia mimicry capability is added to a voltage-source converter-HVDC grid-side station in an MTDC grid connected to a weak ac grid, which can have low inertia or even operate as an islanded grid. The presented inertia mimicry control is integrated in the generalised voltage droop strategy implemented at the primary level of a two-layer hierarchical control structure of the MTDC grid to provide higher flexibility, and thus controllability to the network. Besides, complete control framework from the operational point of view is developed to integrate the low-level control of the converter stations in the supervisory control centre of the MTDC grid. A scaled laboratory test results considering the international council on large electric systems (CIGRE) B4 MTDC grid demonstrate the good performance of the converter station when it is connected to a weak islanded ac grid.Peer ReviewedPostprint (author's final draft

Autonomous take-off and landing of a tethered aircraft: a simulation study

The problem of autonomous launch and landing of a tethered rigid aircraft for airborne wind energy generation is addressed. The system operates with ground-based power conversion and pumping cycles, where the tether is repeatedly reeled in and out of a winch installed on the ground and linked to an electric motor/generator. In order to accelerate the aircraft to take-off speed, the ground station is augmented with a linear motion system composed by a slide translating on rails and controlled by a second motor. An onboard propeller is used to sustain the forward velocity during the ascend of the aircraft. During landing, a slight tension on the line is kept, while the onboard control surfaces are used to align the aircraft with the rails and to land again on them. A model-based, decentralized control approach is proposed, capable to carry out a full cycle of launch, low-tension flight, and landing again on the rails. The derived controller is tested via numerical simulations with a realistic dynamical model of the system, in presence of different wind speeds and turbulence, and its performance in terms of landing accuracy is assessed. This study is part of a project aimed to experimentally verify the launch and landing approach on a small-scale prototype.Comment: This is the longer version of a paper submitted to the 2016 American Control Conference 2016, with more details on the simulation parameter

Automatic Retraction and Full Cycle Operation for a Class of Airborne Wind Energy Generators

Airborne wind energy systems aim to harvest the power of winds blowing at altitudes higher than what conventional wind turbines reach. They employ a tethered flying structure, usually a wing, and exploit the aerodynamic lift to produce electrical power. In the case of ground-based systems, where the traction force on the tether is used to drive a generator on the ground, a two phase power cycle is carried out: one phase to produce power, where the tether is reeled out under high traction force, and a second phase where the tether is recoiled under minimal load. The problem of controlling a tethered wing in this second phase, the retraction phase, is addressed here, by proposing two possible control strategies. Theoretical analyses, numerical simulations, and experimental results are presented to show the performance of the two approaches. Finally, the experimental results of complete autonomous power generation cycles are reported and compared with first-principle models.Comment: This manuscript is a preprint of a paper submitted for possible publication on the IEEE Transactions on Control Systems Technology and is subject to IEEE Copyright. If accepted, the copy of record will be available at IEEEXplore library: http://ieeexplore.ieee.or

Automatic crosswind flight of tethered wings for airborne wind energy: modeling, control design and experimental results

An approach to control tethered wings for airborne wind energy is proposed. A fixed length of the lines is considered, and the aim of the control system is to obtain figure-eight crosswind trajectories. The proposed technique is based on the notion of the wing's "velocity angle" and, in contrast with most existing approaches, it does not require a measurement of the wind speed or of the effective wind at the wing's location. Moreover, the proposed approach features few parameters, whose effects on the system's behavior are very intuitive, hence simplifying tuning procedures. A simplified model of the steering dynamics of the wing is derived from first-principle laws, compared with experimental data and used for the control design. The control algorithm is divided into a low-level loop for the velocity angle and a high-level guidance strategy to achieve the desired flight patterns. The robustness of the inner loop is verified analytically, and the overall control system is tested experimentally on a small-scale prototype, with varying wind conditions and using different wings.Comment: This manuscript is a preprint of a paper accepted for publication on the IEEE Transactions on Control Systems Technology and is subject to IEEE Copyright. The copy of record is available at IEEEXplore library: http://ieeexplore.ieee.org