Download or read book Simulation and Optimization of Wind Farm Operations Under Stochastic Conditions written by Eunshin Byon and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation develops a new methodology and associated solution tools to achieve optimal operations and maintenance strategies for wind turbines, helping reduce operational costs and enhance the marketability of wind generation. The integrated framework proposed includes two optimization models for enabling decision support capability, and one discrete event-based simulation model that characterizes the dynamic operations of wind power systems. The problems in the optimization models are formulated as a partially observed Markov decision process to determine an optimal action based on a wind turbine's health status and the stochastic weather conditions. The rst optimization model uses homogeneous parameters with an assumption of stationary weather characteristics over the decision horizon. We derive a set of closed-form expressions for the optimal policy and explore the policy's monotonicity. The second model allows time-varying weather conditions and other practical aspects. Consequently, the resulting strategy are season-dependent. The model is solved using a backward dynamic programming method. The bene ts of the optimal policy are highlighted via a case study that is based upon eld data from the literature and industry. We nd that the optimal policy provides options for cost-e ective actions, because it can be adapted to a variety of operating conditions. Our discrete event-based simulation model incorporates critical components, such as a wind turbine degradation model, power generation model, wind speed model, and maintenance model. We provide practical insights gained by examining di erent maintenance strategies. To the best of our knowledge, our simulation model is the rst discrete-event simulation model for wind farm operations. Last, we present the integration framework, which incorporates the optimization results in the simulation model. Preliminary results reveal that the integrated model has the potential to provide practical guidelines that can reduce the operation costs as well as enhance the marketability of wind energy.
Download or read book Modeling Simulation and Optimization of Wind Farms and Hybrid Systems written by Karam Maalawi and published by BoD – Books on Demand. This book was released on 2020-03-25 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: The reduction of greenhouse gas emissions is a major governmental goal worldwide. The main target, hopefully by 2050, is to move away from fossil fuels in the electricity sector and then switch to clean power to fuel transportation, buildings and industry. This book discusses important issues in the expanding field of wind farm modeling and simulation as well as the optimization of hybrid and micro-grid systems. Section I deals with modeling and simulation of wind farms for efficient, reliable and cost-effective optimal solutions. Section II tackles the optimization of hybrid wind/PV and renewable energy-based smart micro-grid systems.
Download or read book A STOCHASTIC SIMULATION FRAMEWORK FOR CONDITION BASED OPERATION AND MAINTENANCE OF WIND TURBINES written by Dwarakanath Jagannath and published by . This book was released on 2011 with total page 88 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Operation and maintenance are significant contributors to the cost of energy in the wind energy industry. In order to minimize the cost, it is essential to develop a cost effective maintenance strategy. In this project, a stochastic simulation framework for condition-based operation and maintenance of wind turbines is developed. Within the developed simulation framework, a stochastic damage growth model is employed for the modeling of time-dependent performance degradation of wind turbines based on the failure rate information obtained through historic operational data available in the literature. Various cost attributes such as repair, inspection, and loss of energy production due to turbine failures etc. involved in the operation and maintenance process are considered. Through the simulation, statistical information of operation and maintenance process are considered. Through the simulation, statistical information of operation and maintenance costs can be estimated to analyze the influence of various decision making parameters to reach an optimal maintenance strategy which minimizes the total costs incurred over the life span of a wind turbine. Two case studies for offshore wind turbines, with single failure mode and with two different failure modes, are used to demonstrate the developed simulation framework."- Abstract.
Download or read book In operation Learning of Optimal Wind Farm Operation Strategy written by Joan Oliva Gratacós and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In a wind farm, power losses due to wind turbine wake effects can be up to 30-40% under certain conditions. As the global installed wind power capacity increases, the mitigation of wake effects in wind farms is gaining more importance. Following a conventional control strategy, each individual turbine maximizes its own power production without taking into consideration its effects on the performance of downstream turbines. Therefore, this control scheme results in operation conditions that yield suboptimal power production. In order to increase the overall wind farm power production, a cooperative control strategy can be used, which coordinates the control actions among the wind turbines in the wind farm. This work further investigates the model-free Bayesian Ascent optimization algorithm using SimWindFarm and a standalone Dynamic Wake Meandering model-based simulation tool An advantage of such optimization approach is that the control strategy adapts to operational conditions in the wind farm and is not model-dependent. An approximation of the wind farm power function is constructed using GP regression to fit the control action inputs and the noisy measured power outputs, which is then maximized to determine the optimal control inputs. This estimation is updated in every iteration, allowing the control system to learn from the target system while performing the optimization. The usage of all historical data, along with a trust region constraint in the sampling of new inputs, contribute to a fast convergence rate with gradual changes of the control actions. The developed learning technique is implemented in a wind farm controller and tested in both SimWindFarm and standalone Dynamic Wake Meandering model-based simulation tools. With the conducted tests, performance of the algorithm is assessed considering the different dynamics in the wind farm, thus obtaining an accurate representation of real farm operation. The developed controller reliably improves farm efficiency, even with uncertainty present in measurements. Compared to traditional control strategies, an increase in total wind farm power production is obtained when using a cooperative control strategy. Such enhancement in wind farm performance would result in an improvement of wind farm economics and hence in further growth of wind-energy based power generation.
Download or read book Power System Operation with Large Scale Stochastic Wind Power Integration written by Tao Ding and published by Springer. This book was released on 2016-09-17 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses the uncertainties of wind power modeled as interval numbers and assesses the physical modeling and methods for interval power flow, interval economic dispatch and interval robust economic dispatch. In particular, the optimization models are set up to address these topics and the state-of-the-art methods are employed to efficiently solve the proposed models. Several standard IEEE test systems as well as real-world large-scale Polish power systems have been tested to verify the effectiveness of the proposed models and methods. These methods can be further applied to other research fields that are involved with uncertainty.
Download or read book Applied Simulation and Optimization written by Miguel Mujica Mota and published by Springer. This book was released on 2015-04-06 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presenting techniques, case-studies and methodologies that combine the use of simulation approaches with optimization techniques for facing problems in manufacturing, logistics, or aeronautical problems, this book provides solutions to common industrial problems in several fields, which range from manufacturing to aviation problems, where the common denominator is the combination of simulation’s flexibility with optimization techniques’ robustness. Providing readers with a comprehensive guide to tackle similar issues in industrial environments, this text explores novel ways to face industrial problems through hybrid approaches (simulation-optimization) that benefit from the advantages of both paradigms, in order to give solutions to important problems in service industry, production processes, or supply chains, such as scheduling, routing problems and resource allocations, among others.
Download or read book Handbook of Dynamic Data Driven Applications Systems written by Frederica Darema and published by Springer Nature. This book was released on 2023-10-16 with total page 937 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Second Volume in the series Handbook of Dynamic Data Driven Applications Systems (DDDAS) expands the scope of the methods and the application areas presented in the first Volume and aims to provide additional and extended content of the increasing set of science and engineering advances for new capabilities enabled through DDDAS. The methods and examples of breakthroughs presented in the book series capture the DDDAS paradigm and its scientific and technological impact and benefits. The DDDAS paradigm and the ensuing DDDAS-based frameworks for systems’ analysis and design have been shown to engender new and advanced capabilities for understanding, analysis, and management of engineered, natural, and societal systems (“applications systems”), and for the commensurate wide set of scientific and engineering fields and applications, as well as foundational areas. The DDDAS book series aims to be a reference source of many of the important research and development efforts conducted under the rubric of DDDAS, and to also inspire the broader communities of researchers and developers about the potential in their respective areas of interest, of the application and the exploitation of the DDDAS paradigm and the ensuing frameworks, through the examples and case studies presented, either within their own field or other fields of study. As in the first volume, the chapters in this book reflect research work conducted over the years starting in the 1990’s to the present. Here, the theory and application content are considered for: Foundational Methods Materials Systems Structural Systems Energy Systems Environmental Systems: Domain Assessment & Adverse Conditions/Wildfires Surveillance Systems Space Awareness Systems Healthcare Systems Decision Support Systems Cyber Security Systems Design of Computer Systems The readers of this book series will benefit from DDDAS theory advances such as object estimation, information fusion, and sensor management. The increased interest in Artificial Intelligence (AI), Machine Learning and Neural Networks (NN) provides opportunities for DDDAS-based methods to show the key role DDDAS plays in enabling AI capabilities; address challenges that ML-alone does not, and also show how ML in combination with DDDAS-based methods can deliver the advanced capabilities sought; likewise, infusion of DDDAS-like approaches in NN-methods strengthens such methods. Moreover, the “DDDAS-based Digital Twin” or “Dynamic Digital Twin”, goes beyond the traditional DT notion where the model and the physical system are viewed side-by-side in a static way, to a paradigm where the model dynamically interacts with the physical system through its instrumentation, (per the DDDAS feed-back control loop between model and instrumentation).
Download or read book Spatio Temporal Data Analytics for Wind Energy Integration written by Lei Yang and published by Springer. This book was released on 2014-11-14 with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt: This SpringerBrief presents spatio-temporal data analytics for wind energy integration using stochastic modeling and optimization methods. It explores techniques for efficiently integrating renewable energy generation into bulk power grids. The operational challenges of wind, and its variability are carefully examined. A spatio-temporal analysis approach enables the authors to develop Markov-chain-based short-term forecasts of wind farm power generation. To deal with the wind ramp dynamics, a support vector machine enhanced Markov model is introduced. The stochastic optimization of economic dispatch (ED) and interruptible load management are investigated as well. Spatio-Temporal Data Analytics for Wind Energy Integration is valuable for researchers and professionals working towards renewable energy integration. Advanced-level students studying electrical, computer and energy engineering should also find the content useful.
Download or read book Wind Farm Simulation and Layout Optimization in Complex Terrain written by Jeffery Allen and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Wind Farm Dynamics and Power Optimization in Realistic Atmospheric Boundary Layer Conditions written by Michael Frederick Howland and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The study of wind farms within realistic atmospheric boundary layer (ABL) conditions is critical to understand the governing physics of the system and to design optimal operational protocols. Aerodynamic wake interactions between individual wind turbines typically reduce total wind farm energy production 10-20% and increase the cost of electricity for this resource. Further, in large wind farms, the collective farm efficiency is in part dictated by the interaction between the wind farm and the turbulent ABL and, correspondingly, the vertical transport of kinetic energy into the turbine array. Coriolis forces, arising from the projection of Earth's rotation into a non-inertial rotating Earth-fixed frame, modify the interaction of a wind farm with the ABL. The traditional approximation made in typical ABL simulations assumes that the horizontal component of Earth's rotation is negligible in the atmospheric boundary layer. When including the horizontal component of Earth's rotation, the boundary layer and wind farm physics are a function of the geostrophic wind direction. The influence of the geostrophic wind direction on a wind farm atmospheric boundary layer was characterized using conventionally neutral and stable boundary layer large eddy simulations (LES). In the Northern hemisphere, geostrophic winds from west-to-east establish the horizontal component of Earth's rotation as a sink term in the shear Reynolds stress budget whereas the horizontal component manifests as a source term for east-to-west geostrophic winds. As a result, the magnitude of entrainment of mean kinetic energy into a wind turbine array is modified by the direction of the geostrophic wind, and correspondingly, the boundary layer height and wind speed and direction profiles depend on the geostrophic wind direction. Historically, wind farm control protocols have optimized the performance of individual wind turbines which results in aerodynamic wake interactions and a reduction in wind farm efficiency. Considering the wind farm as a collective, a physics- and data-driven wake steering control method to increase the power production of wind farms is developed. Upwind turbines, which generate turbulent energy-deficit wake regions which impinge on downwind generates, are intentionally yaw misaligned with respect to the incident ABL wind. While the yaw misaligned turbine may produce less power than in yaw aligned operation, the downwind generators may significantly enhance their production, increasing the collective power for the farm. The wake steering method developed combines a physics-based engineering wake model with state estimation techniques based on the assimilation of the wind farm power production data, which is readily available for control decisions at operational wind farms. Analytic gradients are derived from the wake model and leveraged for efficient yaw misalignment set-point optimization. The open-loop wake steering control methodology was tested in a multi-turbine array at a utility-scale operational wind farm, where it statistically significantly increased the power production over standard operation. The analytic gradient-based wind farm power optimization methodology developed can optimize the yaw misalignment angles for large wind farms on the order of seconds, enabling online real-time control. The dynamics of the ABL range from microscale features on the order of meters to mesoscale meteorological scales on the order of hundreds of kilometers. As a result of the broad range of scales and diversity of competing forces, the wind farm interaction with the turbulent ABL is a complex dynamical system, necessitating closed-loop control which is able to dynamically adapt to the evolving wind conditions. In order to rapidly design and improve dynamic closed-loop wind farm controllers, we developed wind farm LES capabilities which incorporate Coriolis and stratification effects and which permit the experimentation of real-time control strategies. Dynamic, closed-loop wake steering controllers are tested in simulations with full Coriolis effects and, altogether, the results indicate that closed-loop wake steering control can significantly increase wind farm power production over greedy operation provided that site-specific wind farm data is assimilated into the optimal control model.
Download or read book Handbook of Wind Power Systems written by Panos M. Pardalos and published by Springer Science & Business Media. This book was released on 2014-01-15 with total page 839 pages. Available in PDF, EPUB and Kindle. Book excerpt: Wind power is currently considered as the fastest growing energy resource in the world. Technological advances and government subsidies have contributed in the rapid rise of Wind power systems. The Handbook on Wind Power Systems provides an overview on several aspects of wind power systems and is divided into four sections: optimization problems in wind power generation, grid integration of wind power systems, modeling, control and maintenance of wind facilities and innovative wind energy generation. The chapters are contributed by experts working on different aspects of wind energy generation and conversion.
Download or read book Control and Operation of Grid Connected Wind Farms written by John N. Jiang and published by Springer. This book was released on 2016-05-31 with total page 146 pages. Available in PDF, EPUB and Kindle. Book excerpt: From the point of view of grid integration and operation, this monograph advances the subject of wind energy control from the individual-unit to the wind-farm level. The basic objectives and requirements for successful integration of wind energy with existing power grids are discussed, followed by an overview of the state of the art, proposed solutions and challenges yet to be resolved. At the individual-turbine level, a nonlinear controller based on feedback linearization, uncertainty estimation and gradient-based optimization is shown robustly to control both active and reactive power outputs of variable-speed turbines with doubly-fed induction generators. Heuristic coordination of the output of a wind farm, represented by a single equivalent turbine with energy storage to optimize and smooth the active power output is presented. A generic approximate model of wind turbine control developed using system identification techniques is proposed to advance research and facilitate the treatment of control issues at the wind-farm level. A supervisory wind-farm controller is then introduced with a view to maximizing and regulating active power output under normal operating conditions and unusual contingencies. This helps to make the individual turbines cooperate in such as way that the overall output of the farm accurately tracks a reference and/or is statistically as smooth as possible to improve grid reliability. The text concludes with an overall discussion of the promise of advanced wind-farm control techniques in making wind an economic energy source and beneficial influence on grid performance. The challenges that warrant further research are succinctly enumerated. Control and Operation of Grid-Connected Wind Farms is primarily intended for researchers from a systems and control background wishing to apply their expertise to the area of wind-energy generation. At the same time, coverage of contemporary solutions to fundamental operational problems will benefit power/energy engineers endeavoring to promote wind as a reliable and clean source of electrical power.
Download or read book Model Updating and Structural Health Monitoring of Horizontal Axis Wind Turbines Via Advanced Spinning Finite Elements and Stochastic Subspace Identification Methods written by Antonio Velazquez Hernandez and published by . This book was released on 2014 with total page 516 pages. Available in PDF, EPUB and Kindle. Book excerpt: Wind energy has been one of the most growing sectors of the nation's renewable energy portfolio for the past decade, and the same tendency is being projected for the upcoming years given the aggressive governmental policies for the reduction of fossil fuel dependency. Great technological expectation and outstanding commercial penetration has shown the so called Horizontal Axis Wind Turbines (HAWT) technologies. Given its great acceptance, size evolution of wind turbines over time has increased exponentially. However, safety and economical concerns have emerged as a result of the newly design tendencies for massive scale wind turbine structures presenting high slenderness ratios and complex shapes, typically located in remote areas (e.g. offshore wind farms). In this regard, safety operation requires not only having first-hand information regarding actual structural dynamic conditions under aerodynamic action, but also a deep understanding of the environmental factors in which these multibody rotating structures operate. Given the cyclo-stochastic patterns of the wind loading exerting pressure on a HAWT, a probabilistic framework is appropriate to characterize the risk of failure in terms of resistance and serviceability conditions, at any given time. Furthermore, sources of uncertainty such as material imperfections, buffeting and flutter, aeroelastic damping, gyroscopic effects, turbulence, among others, have pleaded for the use of a more sophisticated mathematical framework that could properly handle all these sources of indetermination. The attainable modeling complexity that arises as a result of these characterizations demands a data-driven experimental validation methodology to calibrate and corroborate the model. For this aim, System Identification (SI) techniques offer a spectrum of well-established numerical methods appropriated for stationary, deterministic, and data-driven numerical schemes, capable of predicting actual dynamic states (eigenrealizations) of traditional time-invariant dynamic systems. As a consequence, it is proposed a modified data-driven SI metric based on the so called Subspace Realization Theory, now adapted for stochastic non-stationary and timevarying systems, as is the case of HAWT's complex aerodynamics. Simultaneously, this investigation explores the characterization of the turbine loading and response envelopes for critical failure modes of the structural components the wind turbine is made of. In the long run, both aerodynamic framework (theoretical model) and system identification (experimental model) will be merged in a numerical engine formulated as a search algorithm for model updating, also known as Adaptive Simulated Annealing (ASA) process. This iterative engine is based on a set of function minimizations computed by a metric called Modal Assurance Criterion (MAC). In summary, the Thesis is composed of four major parts: (1) development of an analytical aerodynamic framework that predicts interacted wind-structure stochastic loads on wind turbine components; (2) development of a novel tapered-swept-corved Spinning Finite Element (SFE) that includes dampedgyroscopic effects and axial-flexural-torsional coupling; (3) a novel data-driven structural health monitoring (SHM) algorithm via stochastic subspace identification methods; and (4) a numerical search (optimization) engine based on ASA and MAC capable of updating the SFE aerodynamic model.
Download or read book Wind Power Electric Systems written by Djamila Rekioua and published by Springer Nature. This book was released on with total page 331 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Aerodynamics of Wind Turbines 2nd edition written by Martin O. L. Hansen and published by Routledge. This book was released on 2013-05-13 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: Aerodynamics of Wind Turbines is the established essential text for the fundamental solutions to efficient wind turbine design. Now in its second edition, it has been entirely updated and substantially extended to reflect advances in technology, research into rotor aerodynamics and the structural response of the wind turbine structure. Topics covered include increasing mass flow through the turbine, performance at low and high wind speeds, assessment of the extreme conditions under which the turbine will perform and the theory for calculating the lifetime of the turbine. The classical Blade Element Momentum method is also covered, as are eigenmodes and the dynamic behaviour of a turbine. The new material includes a description of the effects of the dynamics and how this can be modelled in an ?aeroelastic code?, which is widely used in the design and verification of modern wind turbines. Further, the description of how to calculate the vibration of the whole construction, as well as the time varying loads, has been substantially updated.
Download or read book Large Scale Offshore Wind Power in the United States written by Walter Musial and published by DIANE Publishing. This book was released on 2011 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a print on demand edition of a hard to find publication. Offshore wind power is poised to deliver an essential contribution to a clean, robust, and diversified U.S. energy portfolio. Capturing and using this large and inexhaustible resource has the potential to mitigate climate change, improve the environment, increase energy security, and stimulate the U.S. economy. The U.S. is now deliberating an energy policy that will have a powerful impact on the nation¿s energy and economic health for decades to come. This report provides a broad understanding of today¿s wind industry and the offshore resource, as well as the associated technology challenges, economics, permitting procedures, and potential risks and benefits. Charts and tables.
Download or read book Reliability and Risk Evaluation of Wind Integrated Power Systems written by Roy Billinton and published by Springer Science & Business Media. This book was released on 2013-03-15 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: The world is witnessing a rapid growth in wind and other renewable based electricity generation due to environmental concerns associated with electricity generation from the conventional sources. Wind power behaves quite differently than conventional electric power generating units due to its intermittent and diffuse nature. System planners and operators face the variability and uncertainty of wind power availability, and therefore, encounter considerable challenges in making decisions to maintain the adequacy and security of wind integrated power systems. This volume intends to bring out the original research work of researchers from academia and industry in understanding, quantifying and managing the risks associated with the uncertainty in wind variability in order to plan and operate a modern power system integrated with a significant proportion of wind power generation with an acceptable level of reliability. Accurate modeling of wind power variability and proper incorporation of the models in reliability and risk evaluation is very important for the planning and operation of electric power systems, and will play a crucial role in defining the requirement of various types of resources and services, such as storage and ancillary services in power systems.
