scholarly journals Integrated wind farm layout and control optimization

2020 ◽  
Vol 5 (4) ◽  
pp. 1551-1566
Author(s):  
Mads M. Pedersen ◽  
Gunner C. Larsen
Keyword(s):  
Wind Turbine ◽  
Wind Farm ◽  
Design Space ◽  
Wind Farm Layout ◽  
Control Optimization ◽  
Mean Wind Speed ◽  
The Individual ◽  
Full Design ◽  
And Control ◽  
Selection Of

Abstract. The objective of this paper is to investigate the joint optimization of wind farm layout and wind farm control in terms of power production. A successful fulfilment of this goal requires the following: (1) an accurate and fast flow model, (2) selection of the minimum set of design parameters that rules or governs the problem, and (3) selection of an optimization algorithm with good scaling properties. For control of the individual wind farm turbines with the aim of wind farm production optimization, the two most obvious strategies are wake steering based on active wind turbine yaw control and wind turbine derating. The present investigation is limited to wind turbine derating. A high-speed linearized computational fluid dynamics (CFD) Reynolds-averaged Navier–Stokes (RANS) solver models the flow field and the crucial wind turbine wake interactions inside the wind farm. The actuator disc method is used to model the wind turbines, and utilizing an aerodynamic model, the design space of the optimization problem is reduced to only three variables per turbine – two geometric and one carefully selected variable specifying the individual wind turbine derating setting for each mean wind speed and direction. The full design space is spanned by these (2N+NdNsN) parameters, where N is the number of wind farm turbines, Nd is the number of direction bins, and Ns is the number of mean wind speed bins. This design space is decomposed into two subsets, which in turn define a nested set of optimization problems to achieve a significantly faster optimization procedure compared to a direct optimization based on the full design space. Following a simplistic sanity check of the platform functionality regarding wind farm layout and control optimization, the capability of the developed optimization platform is demonstrated on a Swedish offshore wind farm. For this particular wind farm, the analysis demonstrates that the expected annual energy production can be increased by 4 % by integrating the wind farm control into the design of the wind farm layout, which is 1.2 % higher than what is achieved by optimizing the layout only.

scholarly journals Integrated wind farm layout and control optimization

2020 ◽  
Author(s):  
Mads M. Pedersen ◽  
Gunner C. Larsen
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Wind Farm ◽  
Design Space ◽  
Wind Farm Layout ◽  
Control Optimization ◽  
Mean Wind Speed ◽  
The Individual ◽  
And Control ◽  
Selection Of

Abstract. Design of an optimal wind farm topology and wind farm control scheduling depends on the chosen metric. The objective of this paper is to investigate the influence of optimal wind farm control on the optimal wind farm layout in terms of power production. A successful fulfilment of this goal requires: 1) an accurate and fast flow model; 2) selection of the minimum set of design parameters that rules the problem; and 3) selection of an optimization algorithm with good scaling properties. For control of the individual wind farm turbines, the two most obvious strategies are wake steering based on active wind turbine yaw control and wind turbine derating. The present investigation is a priori limited to wind turbine derating. A high-speed linearized CFD RANS solver models the flow field and the crucial wind turbine wake interactions inside the wind farm. The actuator disk method is used to model the wind turbines, and utilizing an aerodynamic model, the design space of the optimization problem is reduced to only three variables per turbine – two geometric and one carefully selected variable specifying the individual wind turbine derating setting for each mean wind speed and direction. The full design space spanned by these (2N + Nd Ns N) parameters, where N is the number of wind farm turbines, Nd is the number of direction bins, and Ns is the number of mean wind speed bins. This design space is decomposed in two subsets, which in turn define a nested set of optimization problems to achieve the fastest possible optimization procedure. Following a simplistic sanity check of the platform functionality regarding wind farm layout and control optimization, the capabilities of the developed optimization platform is demonstrated on the Swedish offshore wind farm. For this particular wind farm, the analysis demonstrates that the expected annual energy production can be increased by 4 % by integrating the wind farm control in the design of the wind farm layout, which is 1.2 % higher than what is achieved by optimizing the layout only.

scholarly journals Evaluation of the impact of active wake control techniques on ultimate loads for a 10 MW wind turbine

2022 ◽  
Vol 7 (1) ◽  
pp. 1-17
Author(s):  
Alessandro Croce ◽  
Stefano Cacciola ◽  
Luca Sartori
Keyword(s):  
Wind Turbine ◽  
Energy Production ◽  
Wind Farm ◽  
Control Techniques ◽  
Control Optimization ◽  
Cost Of Energy ◽  
The Individual ◽  
The Cost ◽  
Wind Statistics ◽  
The Impact

Abstract. Wind farm control is one of the solutions recently proposed to increase the overall energy production of a wind power plant. A generic wind farm control is typically synthesized so as to optimize the energy production of the entire wind farm by reducing the detrimental effects due to wake–turbine interactions. As a matter of fact, the performance of a farm control is typically measured by looking at the increase in the power production, properly weighted through the wind statistics. Sometimes, fatigue loads are also considered in the control optimization problem. However, an aspect which is rather overlooked in the literature on this subject is the evaluation of the impact that a farm control law has on the individual wind turbine in terms of maximum loads and dynamic response under extreme conditions. In this work, two promising wind farm controls, based on wake redirection (WR) and dynamic induction control (DIC) strategy, are evaluated at the level of a single front-row wind turbine. To do so, a two-pronged analysis is performed. Firstly, the control techniques are evaluated in terms of the related impact on some specific key performance indicators, with special emphasis on ultimate loads and maximum blade deflection. Secondarily, an optimal blade redesign process is performed with the goal of quantifying the modification in the structure of the blade entailed by a possible increase in ultimate values due to the presence of wind farm control. Such an analysis provides for an important piece of information for assessing the impact of the farm control on the cost-of-energy model.

Control Proxy Functions for Sequential Design and Control Optimization

2011 ◽  
Vol 133 (9) ◽  
Author(s):  
Diane L. Peters ◽  
P. Y. Papalambros ◽  
A. G. Ulsoy
Keyword(s):  
Simultaneous Optimization ◽  
Sequential Optimization ◽  
Control Optimization ◽  
Smart Products ◽  
System Solution ◽  
Optimal System Design ◽  
Problem Formulations ◽  
And Control ◽  
Sequential Strategy ◽  
Selection Of

Optimal system design of “smart” products requires optimization of both the artifact and its controller. When the artifact and the controller designs are independent, the system solution is straightforward through sequential optimization. When the designs are coupled, combined simultaneous optimization can produce system-optimal results, but presents significant computational and organizational complexity. This paper presents a method that produces results comparable with those found with a simultaneous solution strategy, but with the simplicity of the sequential strategy. The artifact objective function is augmented by a control proxy function (CPF), representing the artifact’s ease of control. The key to successful use of this method is the selection of an appropriate CPF. Four theorems that govern the choice and evaluation of a CPF are given. Each theorem is illustrated using a simple mathematical example. Specific CPFs are then presented for particular problem formulations, and the method is applied to the optimal design and control of a micro-electrical mechanical system actuator.

Study on a global control strategy for rotation speed with different work states in variable-speed constant-frequency wind turbines

2011 ◽  
Vol 225 (7) ◽  
pp. 968-976 ◽  
Author(s):  
G Zheng ◽  
H Xu ◽  
X Wang ◽  
J Zou
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Control Strategy ◽  
Control Strategies ◽  
Stable Operation ◽  
Constant Frequency ◽  
Global Control ◽  
Control Rules ◽  
The Individual ◽  
And Control

This paper studies the operation of wind turbines in terms of three phases: start-up phase, power-generation phase, and shutdown phase. Relationships between the operational phase and control rules for the speed of rotation are derived for each of these phases. Taking into account the characteristics of the control strategies in the different operational phases, a global control strategy is designed to ensure the stable operation of the wind turbine in all phases. The results of simulations are presented that indicate that the proposed algorithm can control the individual phases when considered in isolation and also when they are considered in combination. Thus, a global control strategy for a wind turbine that is based on a single algorithm is presented which could have significant implications on the control and use of wind turbines.

Multi-Criteria Selection of Wind Turbine Using TOPSIS Approach

2020 ◽  
Author(s):  
Shafiqur Rehman ◽  
Salman A. Khan ◽  
Luai M. Alhems
Keyword(s):  
Wind Turbine ◽  
Wind Farm ◽  
Selection Process ◽  
Geographical Location ◽  
Real Data ◽  
Maximum Energy ◽  
Decision Criteria ◽  
Topsis Approach ◽  
Selection Of

Abstract The recent revolution in the use of renewable energy worldwide has opened many dimensions of research and development for sustainable energy. In this context, the use of wind energy has received notable attention. One critical decision in the development of a wind farm is the selection of the most appropriate turbine compatible with the characteristics of the geographical location under consideration in order to harness maximum energy. This selection process considers multiple decision criteria which are often in conflict with each other, as improving one criterion negatively affects one or more other criteria. Therefore, it is desired to find a tradeoff solution where all selection criteria are simultaneously optimized to the best possible level. This paper proposes a TOPSIS (The Technique for Order of Preference by Similarity to Ideal Solution) based approach for multi-criteria selection of wind turbine. Three decision criteria, namely, hub height, wind speed, and net capacity factor are used in the decision process. A case study is shown on real data collected from the Aljouf region located at an altitude of 753 meters above sea level in the northern part of Saudi Arabia. Seventeen turbines with rated capacities ranging from 1.5 GW to 3 GW from various manufacturers are evaluated. Results indicate that Vestas V110 turned out to be the most appropriate turbine for the underlying site.

Precision Computation of Wind Turbine Power Upgrades: An Aerodynamic and Control Optimization Test Case

2019 ◽  
Vol 141 (5) ◽  
Author(s):  
Davide Astolfi ◽  
Francesco Castellani ◽  
Mario Luca Fravolini ◽  
Silvia Cascianelli ◽  
Ludovico Terzi
Keyword(s):  
Wind Turbine ◽  
Power Output ◽  
Wind Farm ◽  
Residual Life ◽  
Test Case ◽  
Labor Costs ◽  
Passive Flow Control ◽  
Production Improvement ◽  
Input Variables ◽  
And Control

Wind turbine upgrades have recently been spreading in the wind energy industry for optimizing the efficiency of the wind kinetic energy conversion. These interventions have material and labor costs; therefore, it is fundamental to estimate the production improvement realistically. Furthermore, the retrofitting of the wind turbines sited in complex environments might exacerbate the stress conditions to which those are subjected and consequently might affect the residual life. In this work, a two-step upgrade on a multimegawatt wind turbine is considered from a wind farm sited in complex terrain. First, vortex generators and passive flow control devices have been installed. Second, the management of the revolutions per minute has been optimized. In this work, a general method is formulated for assessing the wind turbine power upgrades using operational data. The method is based on the study of the residuals between the measured power output and a judicious model of the power output itself, before and after the upgrade. Therefore, properly selecting the model is fundamental. For this reason, an automatic feature selection algorithm is adopted, based on the stepwise multivariate regression. This allows identifying the most meaningful input variables for a multivariate linear model whose target is the power of the upgraded wind turbine. For the test case of interest, the adopted upgrade is estimated to increase the annual energy production to 2.6 ± 0.1%. The aerodynamic and control upgrades are estimated to be 1.8% and 0.8%, respectively, of the production improvement.

Wind turbine selection for wind farm layout using multi-objective evolutionary algorithms

2014 ◽  
Vol 41 (15) ◽  
pp. 6585-6595 ◽  
Author(s):  
Francisco G. Montoya ◽  
Francisco Manzano-Agugliaro ◽  
Sergio López-Márquez ◽  
Quetzalcoatl Hernández-Escobedo ◽  
Consolación Gil
Keyword(s):  
Evolutionary Algorithms ◽  
Wind Turbine ◽  
Wind Farm ◽  
Wind Farm Layout ◽  
Multi Objective ◽  
Selection For

scholarly journals Wake behavior and control: comparison of LES simulations and wind tunnel measurements

2019 ◽  
Vol 4 (1) ◽  
pp. 71-88 ◽  
Author(s):  
Jiangang Wang ◽  
Chengyu Wang ◽  
Filippo Campagnolo ◽  
Carlo L. Bottasso
Keyword(s):  
Wind Tunnel ◽  
Wind Turbine ◽  
Wind Farm ◽  
Operating Conditions ◽  
Test Cases ◽  
Near Wake ◽  
Large Eddy ◽  
Control Comparison ◽  
High Turbulence ◽  
And Control

Abstract. This paper applies a large-eddy actuator line approach to the simulation of wind turbine wakes. In addition to normal operating conditions, a specific focus of the paper is on wake manipulation, which is performed here by derating, yaw misalignment and cyclic pitching of the blades. With the purpose of clarifying the ability of LES methods to represent conditions that are relevant for wind farm control, numerical simulations are compared to experimental observations obtained in a boundary layer wind tunnel with scaled wind turbine models. Results indicate a good overall matching of simulations with experiments. Low-turbulence test cases appear to be more challenging than moderate- and high-turbulence ones due to the need for denser grids to limit numerical diffusion and accurately resolve tip-shed vortices in the near-wake region.

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