Wind Turbine: Recent Trends

WIND TURBINE: CHALLENGES AND ASPIRATION

Wind Turbine (WT), one of the most promising renewable energy technologies is deemed as a feasible alternative to traditional fossil fuel generators due to its negative impact on the environment and its abundance and prevalence of supportive technicalities. However, substantial Wind Turbine projects should overcome certain requirements to meet their growing needs and supply electrical power systems to accomplish sustainable development goals. In this literature review, design and manufacturing challenges of WT and associated control and maintenance difficulties, investment feasibility, legal issues as well as the scope of the future improvements have been considered.

Design of Wind Turbine Blade

While designing a wind turbine blade, it is crucial to keep in mind the manufacturing limitation. It has been proposed that the optimization algorithm significantly reduces the design space and the time is taken (Stylianidis, Macquart, and Maheri, 2014). By utilizing chord linearization and aerofoil blending, the researchers investigated the manufacturing constraints by dividing WT's design into sub-problems to maintain the balance of blade cost reduction and high stiffness. Though their analysis paved a way to improve blade efficiency by boosting the optimization algorithm speed to achieve a near-optimal solution, it significantly highlighted the importance of the right assumption during the sub-division process. To evaluate the significance of lightweight and efficient blade design, reviewers (Masal and Mankar, 2017) mentioned that ‘lift drag ratio’ flourishes while choosing pre-selected aerofoil or designing entirely new. Nonetheless, their experiment is not flawless in terms of stresses and deflections observed in the proposed model.

Deep water installation of Vertical Axis Wind turbine

Deep water installations proclaim a high maintenance cost due to cabling, water depth, and the topical wind resources. In a deep offshore floating application study, while examining the aerodynamic modeling of Vertical Axis Wind turbine (VAWT), the researchers (Hand, Cashman, and Kelly, 2017) found that the computational requirement is reasonably low. Considering aerodynamic effects, their findings exploited the cascade model and a dynamic stall model so that an iterative time-management scheme might provide numerical efficiency and stability. Moreover, the need for wind-sensing and orientation mechanisms can be significantly eliminated, promoting reliability, minimizing expense, and surpassing some of the Horizontal Axis Wind Turbine's structural limitations. However, the investigators completely ignored the gravity of tangential force co-efficient, which is highly dependent on static airfoil experimental data, restricting the model used only as an initial design tool. Thus, one potential improvement is to add a more detailed dynamic stall model while not undergoing the high computational penalty. A similar experiment (Shires, 2013) noted that Aerogenerator VAWT is a highly cost-effective model due to its simplifying installation and maintenance purpose while taking account of life-cycle cost for the whole structure and obtaining a compromise between aerodynamic efficacy and structural constraints.

Manufacturing of Wind Turbine

Wind Turbine Manufacturers always emphasize on novel and robust machines and techniques to enhance its electric production capability. It has been noted that WT could be quickly manufactured and combined on-site by utilizing the Additive Manufacturing(AM) process where a 3D object is fabricated through the 'build-up of thin layers of a base material’(Bassett, Carriveau and Ting, 2015). AM provides excellent flexibility while creating shallow and hollow components which cannot be equipped through subtractive mode. The main advantage of 3DP is that Designers can build a prototype rapidly and test particular feature properties of WT within a measured circumstance. 3D printed files can be shared spontaneously within online communities and modified according to the project's need. Therefore, this process promises to decrease cost and reduce waste. However, the researchers neglected the effect of print size limitations and, remarkably, reinforcement techniques and print optimization. Another researcher (Sainz, 2015) suggested that WT Blade manufacturing's advancement can be ensured by automating the process by minimizing life cycle times and heightening accuracy. Advanced tooling systems and sophisticated technology, for example, Ultra-precise molding, can be employed to validate quality assurance.

Maintenance issue of Wind Turbine

Since wind conditions fluctuate over time and are exceptionally unpredictable, it is essential to regulate the optimum maintenance schedules. Proposing a failure model, distinguished researchers (Zhu, Castanier, and Bettayeb, 2019) argued that periodic maintenance planning and reactive maintenance are vital to economize logistic cost and optimize decision strategy. They assessed that Life distribution and Failure rate models establish the ongoing study. However, these previous studies overlooked the realistic consequences such as weather conditions that challenge the decision tools, embracing the complication of strategic objectives. Though they could integrate healthy prognostic information, they astonishingly failed to provide appropriate real-time objective comparative information, ultimately leading to further research. Similarly, applying the concept of Failure Mode Effective Analysis, researchers (Chan and Mo, 2017) concluded that the effective way of a resource is crucial to prevent premature failures, downtime loss, and repairing cost. Likewise, a recent study exhibited that an automated maintenance programming framework might be deployed to monitor wind speed and wind gust data by executing automated scheduling of tasks (Yürü?en et al., 2020). This study's feasible scope might be to arrange a master plan for multiple WT in a solo visit by considering short-term forecasts.

Control Technique of Wind Turbine

Control strategies are also vital to attain optimum efficiency from a Wind Turbine. Eminent researchers (Apata and Oyedokun, 2020) justified that cost-effectiveness and maximum power generation of a Wind Turbine are reliant on its stall control and the nature of power electronics in wind systems. Recent progression in Power Electronic System and Multiple Power Point Tracking Techniques has enormously influenced the multiple enhancements in WT systems' control. As a result, the Electric pitch controller and hybrid controller claim zero risks of leaking hydraulic fluids under high pressure. Nevertheless, there is still concern about moderating structural loads. By employing sensors and actuators, smart rotor applications can be handy. Similarly, other researchers (Njiri and S?ffker, 2016) recommended that a multi-variable control method manipulating pitch and generator torque helps maintain a balance between optimum power production and load reduction.

Legal challenges of Wind Turbine

Successful Wind Turbine Projects hinge on both a mixture of legitimacy and dexterity in the procedures. Through conducting an interview based in western democratic societies, researchers (Juerges, Leahy, and Newig, 2018) supported that Polycentric governance systems help to alleviate friction between different actors involved in wind power projects' decision-making. Although this mode of administration is efficient in adopting circumstances, it significantly lacks autonomy. A momentous study (Liljenfeldt, 2015) upheld the claim of 'administrative barrier,' exhibiting the lack of co-operation among substantial stakeholders. Noticeable researchers (Co?ar, Grieco and Tintelnot, 2015) recorded the consequence of fixed and variable border costs by calculating a structural oligopoly model with cross-border trade and heterogeneous firms. However, the investigators deliberately disregarded the magnitude of bureaucratic, linguistic, or cultural differences enacting border frictions.

Investment criteria of Wind Turbine

Investments in Wind Turbine projects would be profitable if economic feasibility permits. Researcher (Mulder, 2008) evaluated the ‘economic attractiveness pattern’ by interpreting four diverse criteria, namely Tobin'sQ, Euler equation estimation, investment accelerator model, and the effective marginal tax rate. He indicated that the investment could be hindered due to a shortfall of compatible space and a shortcoming of infrastructure. Similarly, energy trading differences create the economic uncertainties in resource quality and macroeconomic factors (Aquila et al., 2020). Likewise, reviewers (Sakka et al., 2020) performed a feasibility study explaining that economic durability is affected by wind potential. Yet, none of these investigators underlined electricity spot price and annual maintenance cost.

Destiny of Wind Turbine

Currently, there is a lot of research happening regarding the advancement of Wind Turbine competency. Investigators (al Mhdawi and Al-Raweshidy, 2018) envisioned of a software-defined quadcopter model, which gathers wind speed data from a mobile IoT vehicle base station. This proposed model performs well in heterogeneous conditions, employing insignificant total transmission power while emitting data through tracking down the ideal waypoint that encircles optimal wind speed and humidity levels. A possible extension of this study might contain different controllers from other domains to extend the network scalability with minor power consumption techniques. Other leading researchers (Sierra-Garcia and Santos, 2021) conceived of a ‘neuro-estimator’ based on a neural network that is nurtured online to respond to variations of wind conditions in the atmosphere. Even though the reviewers were susceptible to verify the proficiency of the proposed intelligent control approach, they missed the opportunity to examine the design of a real prototype of a wind turbine.

To recapitulate, Wind Power as a substitute to conventional fossil fuel has been spreading swiftly. Though this mode of Renewable Energy foreshadows a dazzling future, it indicatively lacks a commitment to encounter the rising needs. Future Wind Turbine Technology would be more design and manufacturing friendly, outplaying the existing obstruction in control and maintenance field. Hence, it is expected that hefty investment in this sector might help reduce the ongoing gap.

References:

Hand, B., Cashman, A. and Kelly, G. (2017) A Low-Order Model for Offshore Floating Vertical Axis Wind Turbine Aerodynamics, IEEE Transactions on Industry Applications, Institute of Electrical and Electronics Engineers Inc., 53(1), pp. 512–520.

Stylianidis, N., Macquart, T. and Maheri, A. (2014) Aerodynamic design of wind turbine blades considering manufacturing constraints, In 3rd International Symposium on Environment Friendly Energies and Applications, EFEA 2014, Institute of Electrical and Electronics Engineers Inc.

Shires, A. (2013) Design optimisation of an offshore vertical axis wind turbine, Proceedings of Institution of Civil Engineers: Energy, 166(1), pp. 7–18.

Masal, S. P., Mankar, S. H., and Kale, S. A. 2017. Weight and cost reduction of a small wind turbine blade. In: 2nd International Conference for Convergence in Technology (I2CT). Mumbai, pp. 1089-1092, doi: 10.1109/I2CT.2017.8226296.

Bassett, K., Carriveau, R. and Ting, D. S. K. (2015) 3D printed wind turbines part 1: Design considerations and rapid manufacture potential, Sustainable Energy Technologies and Assessments, Elsevier Ltd, 11, pp. 186–193.

Sainz, J. A. (2015) New Wind Turbine Manufacturing Techniques, In Procedia Engineering, Elsevier Ltd, pp. 880–886.

Zhu, W., Castanier, B. and Bettayeb, B. (2019) A dynamic programming-based maintenance model of offshore wind turbine considering logistic delay and weather condition, Reliability Engineering and System Safety, Elsevier Ltd, 190.

Chan, D. and Mo, J. (2017) Life Cycle Reliability and Maintenance Analyses of Wind Turbines, In Energy Procedia, Elsevier Ltd, pp. 328–333.

Yürü?en, N. Y., Rowley, P. N., Watson, S. J. and Melero, J. J. (2020) Automated wind turbine maintenance scheduling, Reliability Engineering and System Safety, Elsevier Ltd, 200.

Apata, O. and Oyedokun, D. T. O. (2020) An overview of control techniques for wind turbine systems, Scientific African, Elsevier B.V.

Njiri, J. G. and S?ffker, D. (2016) State-of-the-art in wind turbine control: Trends and challenges, Renewable and Sustainable Energy Reviews, Elsevier Ltd, pp. 377–393.

Juerges, N., Leahy, J. and Newig, J. (2018) Actor perceptions of polycentricity in wind power governance, Environmental Policy and Governance, John Wiley and Sons Ltd, 28(6), pp. 383–394.

Co?ar, A. K., Grieco, P. L. E. and Tintelnot, F. (2015) Borders, geography, and oligopoly: Evidence from the wind turbine industry, Review of Economics and Statistics, MIT Press Journals, 97(3), pp. 623–637.

Liljenfeldt, J. (2015) Legitimacy and Efficiency in Planning Processes—(How) Does Wind Power Change the Situation?, European Planning Studies, Routledge, 23(4), pp. 811–827.

Aquila, G., de Queiroz, A. R., Balestrassi, P. P., Rotella Junior, P., Rocha, L. C. S., Pamplona, E. O. and Nakamura, W. T. (2020) Wind energy investments facing uncertainties in the Brazilian electricity spot market: A real options approach, Sustainable Energy Technologies and Assessments, Elsevier Ltd, 42.

Mulder, A. (2008) Do economic instruments matter? Wind turbine investments in the EU(15), Energy Economics, 30(6), pp. 2980–2991.

Sakka, E. G., Bilionis, D. v., Vamvatsikos, D. and Gantes, C. J. (2020) Onshore wind farm siting prioritization based on investment profitability for Greece, Renewable Energy, Elsevier Ltd, 146, pp. 2827–2839.

Sierra-Garcia, J. E. and Santos, M. (2021) Improving Wind Turbine Pitch Control by Effective Wind Neuro-Estimators, IEEE Access, Institute of Electrical and Electronics Engineers Inc., 9, pp. 10413–10425.

al Mhdawi, A. K. and Al-Raweshidy, H. S. (2018) SDQ-6WI: Software defined quadcopter-six wheeled IoT sensor architecture for future wind turbine placement, IEEE Access, Institute of Electrical and Electronics Engineers Inc., 6, pp. 53426–53437.