Modeling Wind-Turbine Power Curves: Effects of Environmental Temperature on Wind Energy Generation

Global warming represents a serious challenge, which requires the adoption of renewable energy technologies worldwide. However, it can negatively affect the availability of renewable energy resources, such as wind, which are needed for electricity generation. In this context, there is an increasing need for more accurate evaluations of wind turbine power curves. A novel methodology to model the power curves of wind turbines, which combines the use of artificial neural networks (ANN) and Fuzzy logic rules, is proposed in this paper. This methodology assesses the role of environmental temperature in the power curve and the impact of temperature increases on wind energy production. The application of this methodology is illustrated with the simulation of the impact of global warming on the electricity generation of a wind farm. Due to the non-linear relationship between the power output of a turbine and its primary and derived parameters, it is shown that ANN combined with an expert system formed by a Fuzzy logic module fit power curve modeling processes well. The application of the methodology shows that an increase in temperatures would trigger a small reduction in the performance of wind turbines.

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Numerical and experimental investigations of the impacts of the integration of wind energy into distribution network

10.51415/10321/3743 ◽

2021 ◽

Author(s):

◽

Ramesh Kumar Behara

Keyword(s):

Renewable Energy ◽

Wind Energy ◽

Wind Turbine ◽

Wind Power ◽

Distribution Systems ◽

Electrical Power ◽

Distribution Network ◽

Experimental Investigations ◽

Doubly Fed ◽

The Impact

The growing needs for electric power around the world has resulted in fossil fuel reserves to be consumed at a much faster rate. The use of these fossil fuels such as coal, petroleum and natural gas have led to huge consequences on the environment, prompting the need for sustainable energy that meets the ever increasing demands for electrical power. To achieve this, there has been a huge attempt into the utilisation of renewable energy sources for power generation. In this context, wind energy has been identified as a promising, and environmentally friendly renewable energy option. Wind turbine technologies have undergone tremendous improvements in recent years for the generation of electrical power. Wind turbines based on doubly fed induction generators have attracted particular attention because of their advantages such as variable speed, constant frequency operation, reduced flicker, and independent control capabilities for maximum power point tracking, active and reactive powers. For modern power systems, wind farms are now preferably connected directly to the distribution systems because of cost benefits associated with installing wind power in the lower voltage networks. The integration of wind power into the distribution network creates potential technical challenges that need to be investigated and have mitigation measures outlined. Detailed in this study are both numerical and experimental models to investigate these potential challenges. The focus of this research is the analytical and experimental investigations in the integration of electrical power from wind energy into the distribution grid. Firstly, the study undertaken in this project was to carry out an analytical investigation into the integration of wind energy in the distribution network. Firstly, the numerical simulation was implemented in the MATLAB/Simulink software. Secondly, the experimental work, was conducted at the High Voltage Direct Centre at the University of KwaZulu-Natal. The goal of this project was to simulate and conduct experiments to evaluate the level of penetration of wind energy, predict the impact on the network, and propose how these impacts can be mitigated. From the models analysis, the effects of these challenges intensify with the increased integration of wind energy into the distribution network. The control strategies concept of the doubly fed induction generator connected wind turbine was addressed to ascertain the required control over the level of wind power penetration in the distribution network. Based on the investigation outcomes we establish that the impact on the voltage and power from the wind power integration in the power distribution system has a goal to maintain quality and balance between supply and demand.

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The Impact of Ice Formation on Wind Turbine Performance and Aerodynamics

Journal of Solar Energy Engineering ◽

10.1115/1.4003187 ◽

2011 ◽

Vol 133 (1) ◽

Cited By ~ 33

Author(s):

S. Barber ◽

Y. Wang ◽

S. Jafari ◽

N. Chokani ◽

R. S. Abhari

Keyword(s):

Wind Energy ◽

Wind Turbine ◽

Swiss Alps ◽

Test Facility ◽

Ice Formation ◽

Predictive Tool ◽

Lower Altitude ◽

Turbine Performance ◽

The Impact ◽

Power Curves

Wind energy is the world’s fastest growing source of electricity production; if this trend is to continue, sites that are plentiful in terms of wind velocity must be efficiently utilized. Many such sites are located in cold, wet regions such as the Swiss Alps, the Scandinavian coastline, and many areas of China and North America, where the predicted power curves can be of low accuracy, and the performance often deviates significantly from the expected performance. There are often prolonged shutdown and inefficient heating cycles, both of which may be unnecessary. Thus, further understanding of the effects of ice formation on wind turbine blades is required. Experimental and computational studies are undertaken to examine the effects of ice formation on wind turbine performance. The experiments are conducted on a dynamically scaled model in the wind turbine test facility at ETH Zurich. The central element of the facility is a water towing tank that enables full-scale nondimensional parameters to be more closely matched on a subscale model than in a wind tunnel. A novel technique is developed to yield accurate measurements of wind turbine performance, incorporating the use of a torquemeter with a series of systematic measurements. These measurements are complemented by predictions obtained using a commercial Reynolds-Averaged Navier–Stokes computational fluid dynamics code. The measured and predicted results show that icing typical of that found at the Guetsch Alpine Test Site (2330 m altitude) can reduce the power coefficient by up to 22% and the annual energy production (AEP) by up to 2%. Icing in the blade tip region, 95–100% blade span, has the most pronounced effect on the wind turbine’s performance. For wind turbines in more extreme icing conditions typical of those in Bern Jura, for example, icing can result in up to 17% losses in AEP. Icing at high altitude sites does not cause significant AEP losses, whereas icing at lower altitude sites can have a significant impact on AEP. Thus, the classification of icing is a key to the further development of prediction tools. It would be advantageous to tailor blade heating for prevention of ice buildup on the blade’s tip region. An “extreme” icing predictive tool for the project development of wind farms in regions that are highly susceptible to icing would be beneficial to wind energy developers.

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Fault-Tolerant Control of a Wind Turbine Generator Based on Fuzzy Logic and Using Ensemble Learning

Energies ◽

10.3390/en14165167 ◽

2021 ◽

Vol 14 (16) ◽

pp. 5167

Author(s):

Jordi Cusidó ◽

Arnau López ◽

Mattia Beretta

Keyword(s):

Fuzzy Logic ◽

Renewable Energy ◽

Wind Energy ◽

Wind Turbine ◽

Wind Turbines ◽

Fault Tolerant ◽

Fault Tolerant Control ◽

Turbine Generator ◽

Fast Wind ◽

Installed Capacity

Wind energy is a form of renewable energy with the highest installed capacity. However, it is necessary to reduce the operation and maintenance costs and extend the lifetime of wind turbines to make wind energy more competitive. This paper presents a power-derating-based Fault-Tolerant Control (FTC) model in 2 MW three-bladed wind turbines implemented using the National Renewable Energy Laboratory’s (NREL) Fatigue, Aerodynamics, Structures, and Turbulence (FAST) wind turbine simulator. This control strategy is potentially supported by the health status of the gearbox, which was predicted by means of algorithms and quantified in an indicator denominated as a merge developed by SMARTIVE, a pioneering of in this idea. Fuzzy logic was employed in order to decide whether to down-regulate the output power or not, and to which level to adjust to the needs of the turbines. Simulation results demonstrated that a reduction in the power output resulted in a safer operation, since the stresses withstood by the blades and tower significantly decreased. Moreover, the results supported empirically that a diminution in the generator torque and speed was acheived, resulting in a drop in the gearbox bearing and oil temperatures. By implementing this power-derating FTC, the downtime due to failure stops could be controlled, and thus the power production noticeably grew. It has been estimated that more than 325,000 tons of CO2 could be avoided yearly if implemented globally.

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Wind Data Analysis and Wind Flow Simulation Over Large Areas

Mathematical Modelling in Civil Engineering ◽

10.2478/mmce-2014-0005 ◽

2014 ◽

Vol 10 (1) ◽

pp. 38-45

Author(s):

Angel Terziev ◽

Ivan Antonov ◽

Rositsa Velichkova

Keyword(s):

Renewable Energy ◽

Wind Energy ◽

Renewable Energy Sources ◽

Energy Sources ◽

Wind Flow ◽

Energy Potential ◽

Wind Potential ◽

Wind Energy Potential ◽

The Impact

Abstract Increasing the share of renewable energy sources is one of the core policies of the European Union. This is because of the fact that this energy is essential in reducing the greenhouse gas emissions and securing energy supplies. Currently, the share of wind energy from all renewable energy sources is relatively low. The choice of location for a certain wind farm installation strongly depends on the wind potential. Therefore the accurate assessment of wind potential is extremely important. In the present paper an analysis is made on the impact of significant possible parameters on the determination of wind energy potential for relatively large areas. In the analysis the type of measurements (short- and long-term on-site measurements), the type of instrumentation and the terrain roughness factor are considered. The study on the impact of turbulence on the wind flow distribution over complex terrain is presented, and it is based on the real on-site data collected by the meteorological tall towers installed in the northern part of Bulgaria. By means of CFD based software a wind map is developed for relatively large areas. Different turbulent models in numerical calculations were tested and recommendations for the usage of the specific models in flows modeling over complex terrains are presented. The role of each parameter in wind map development is made. Different approaches for determination of wind energy potential based on the preliminary developed wind map are presented.

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Tourist Viewshed Externalities and Wind Energy Production

Agricultural and Resource Economics Review ◽

10.1017/age.2017.18 ◽

2017 ◽

Vol 46 (2) ◽

pp. 224-241 ◽

Cited By ~ 6

Author(s):

Jacob R. Fooks ◽

Kent D. Messer ◽

Joshua M. Duke ◽

Janet B. Johnson ◽

Tongzhe Li ◽

...

Keyword(s):

Wind Energy ◽

Wind Turbine ◽

Wind Turbines ◽

Energy Production ◽

Hotel Room ◽

Negative Effect ◽

The Impact ◽

Large Wind

This study uses an experiment where ferry passengers are sold hotel room “views” to evaluate the impact of wind turbines views on tourists’ vacation experience. Participants purchase a chance for a weekend hotel stay. Information about the hotel rooms was limited to the quality of the hotel and its distance from a large wind turbine, as well as whether or not a particular room would have a view of the turbine. While there was generally a negative effect of turbine views, this did not hold across all participants, and did not seem to be effected by distance or hotel quality.

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The Impact of Temporal Complexity Reduction on a 100% Renewable European Energy System with Hydrogen Infrastructure

10.20944/preprints201910.0150.v1 ◽

2019 ◽

Author(s):

Dilara Gulcin Caglayan ◽

Heidi Ursula Heinrichs ◽

Detlef Stolten ◽

Martin Robinius

Keyword(s):

Renewable Energy ◽

Wind Energy ◽

Alternative Energy ◽

Renewable Energy Sources ◽

Energy System ◽

Promising Alternative ◽

Renewable Energy System ◽

Hydrogen Infrastructure ◽

Storage Technologies ◽

The Impact

The transition towards a renewable energy system is essential in order to reduce greenhouse gas emissions. The increase in the share of variable renewable energy sources (VRES), which mainly comprise wind and solar energy, necessitates storage technologies by which the intermittency of VRES can be compensated for. Although hydrogen has been envisioned to play a significant role as a promising alternative energy carrier in a future European VRES-based energy concept, the optimal design of this system remains uncertain. In this analysis, a hydrogen infrastructure is posited that would meet the electricity and hydrogen demand for a 100% renewable energy-based European energy system in the context of 2050. The overall system design is optimized by minimizing the total annual cost. Onshore and offshore wind energy, open-field photovoltaics (PV), rooftop PV and hydro energy, as well as biomass, are the technologies employed for electricity generation. The electricity generated is then either transmitted through the electrical grid or converted into hydrogen by means of electrolyzers and then distributed through hydrogen pipelines. Battery, hydrogen vessels and salt caverns are considered as potential storage technologies. In the case of a lull, stored hydrogen can be re-electrified to generate electricity to meet demand during that time period. For each location, eligible technologies are introduced, as well as their maximum capacity and hourly demand profiles, in order to build the optimization model. In addition, a generation time series for VRES has been exogenously derived for the model. The generation profiles of wind energy have been investigated in detail by considering future turbine designs with high spatial resolution. In terms of salt cavern storage, the technical potential for hydrogen storage is defined in the system as the maximum allowable capacity per region. Whether or not a technology is installed in a region, the hourly operation of these technologies, as well as the cost of each technology, are obtained within the optimization results. It is revealed that a 100 percent renewable energy system is feasible and would meet both electricity demand and hydrogen demand in Europe.

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Dynamic response improvement of hybrid system by implementing ANN-GA for fast variation of photovoltaic irradiation and FLC for wind turbine

Archives of Electrical Engineering ◽

10.1515/aee-2015-0024 ◽

2015 ◽

Vol 64 (2) ◽

pp. 291-314 ◽

Cited By ~ 10

Author(s):

Maziar Izadbakhsh ◽

Alireza Rezvani ◽

Majid Gandomkar

Keyword(s):

Fuzzy Logic ◽

Wind Speed ◽

Dynamic Response ◽

Wind Turbine ◽

Hybrid System ◽

Pitch Angle ◽

Fuzzy Logic Controller ◽

Control Method ◽

Control Technique ◽

Power Curves

Abstract In this paper, dynamic response improvement of the grid connected hybrid system comprising of the wind power generation system (WPGS) and the photovoltaic (PV) are investigated under some critical circumstances. In order to maximize the output of solar arrays, a maximum power point tracking (MPPT) technique is presented. In this paper, an intelligent control technique using the artificial neural network (ANN) and the genetic algorithm (GA) are proposed to control the MPPT for a PV system under varying irradiation and temperature conditions. The ANN-GA control method is compared with the perturb and observe (P&O), the incremental conductance (IC) and the fuzzy logic methods. In other words, the data is optimized by GA and then, these optimum values are used in ANN. The results are indicated the ANN-GA is better and more reliable method in comparison with the conventional algorithms. The allocation of a pitch angle strategy based on the fuzzy logic controller (FLC) and comparison with conventional PI controller in high rated wind speed areas are carried out. Moreover, the pitch angle based on FLC with the wind speed and active power as the inputs can have faster response that lead to smoother power curves, improving the dynamic performance of the wind turbine and prevent the mechanical fatigues of the generator

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Statistical power curve modeling to estimate wind turbine power output

Wind Engineering ◽

10.1177/0309524x19891671 ◽

2019 ◽

pp. 0309524X1989167

Author(s):

Bharti Dongre ◽

Rajesh Kumar Pateriya

Keyword(s):

Wind Turbine ◽

Statistical Power ◽

Polynomial Regression ◽

Smoothing Splines ◽

Optimal Number ◽

Specific Power ◽

Power Curve ◽

Curve Modeling ◽

A Site ◽

Power Curves

In the wind industry, the power curve serves as a performance index of the wind turbine. The machine-specific power curves are not sufficient to measure the performance of wind turbines in different environmental and geographical conditions. The aim is to develop a site-specific power curve of the wind turbine to estimate its output power. In this article, statistical methods based on empirical power curves are implemented using various techniques such as polynomial regression, splines regression, and smoothing splines regression. In the case of splines regression, instead of randomly selecting knots, the optimal number of knots and their positions are identified using three approaches: particle swarm optimization, half-split, and clustering. The National Renewable Energy Laboratory datasets have been used to develop the models. Imperial investigations show that knot-selection strategies improve the performance of splines regression. However, the smoothing splines-based power curve model estimates more accurately compared with all others.

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Does Combined Heat and Power Play the Role of a Bridge in Energy Transition? Evidence from a Cross-Country Analysis

Sustainability ◽

10.3390/su11041035 ◽

2019 ◽

Vol 11 (4) ◽

pp. 1035 ◽

Cited By ~ 5

Author(s):

Hyo-Jin Kim ◽

Jeong-Joon Yu ◽

Seung-Hoon Yoo

Keyword(s):

Power Generation ◽

Renewable Energy ◽

Electricity Generation ◽

Nuclear Power ◽

Energy Transition ◽

Parameter Estimate ◽

Combined Heat And Power ◽

Cross Country ◽

The Impact

In an era of energy transition involving an increase in renewable energy and a reduction in coal-fired power generation and nuclear power generation, the role of combined heat and power (CHP) as a bridging energy is highly emphasized. This article attempts to look empirically into the impact of increasing the share of renewable energy in total electricity generation on CHP share in total electricity generation in a cross-country context. Data from 35 countries during the period 2009–2015 were used, and the least absolute deviations estimator was applied to obtain a more robust parameter estimate. The results showed that a 1%p increase in the share of renewable energy significantly increased the CHP share by 0.87%p. Therefore, the hypothesis that CHP serves as bridge energy in the process of energy transition was established.

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A Smart Adaptive Switching Module Architecture Using Fuzzy Logic for an Efficient Integration of Renewable Energy Sources. A Case Study of a RES System Located in Hulubești, Romania

Sustainability ◽

10.3390/su12156084 ◽

2020 ◽

Vol 12 (15) ◽

pp. 6084

Author(s):

Simona-Vasilica Oprea ◽

Adela Bâra ◽

Ștefan Preda ◽

Osman Bulent Tor

Keyword(s):

Fuzzy Logic ◽

Renewable Energy ◽

Power Systems ◽

Electricity Generation ◽

Renewable Energy Sources ◽

Storage System ◽

Weather Conditions ◽

Energy Sources ◽

Fuzzy Logic Systems

Electricity generation from renewable energy sources (RES) has a common feature, that is, it is fluctuating, available in certain amounts and only for some periods of time. Consuming this electricity when it is available should be a primary goal to enhance operation of the RES-powered generating units which are particularly operating in microgrids. Heavily influenced by weather parameters, RES-powered systems can benefit from implementation of sensors and fuzzy logic systems to dynamically adapt electric loads to the volatility of RES. This study attempts to answer the following question: How to efficiently integrate RES to power systems by means of sustainable energy solutions that involve sensors, fuzzy logic, and categorization of loads? A Smart Adaptive Switching Module (SASM) architecture, which efficiently uses electricity generation of local available RES by gradually switching electric appliances based on weather sensors, power forecast, storage system constraints and other parameters, is proposed. It is demonstrated that, without SASM, the RES generation is supposed to be curtailed in some cases, e.g., when batteries are fully charged, even though the weather conditions are favourable. In such cases, fuzzy rules of SASM securely mitigate curtailment of RES generation by supplying high power non-traditional storage appliances. A numerical case study is performed to demonstrate effectiveness of the proposed SASM architecture for a RES system located in Hulubești (Dâmbovița), Romania.

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