Wind Energy Sources Research Articles

Wind power assessment in the Caribbean region of Colombia, using ten-minute wind observations and ERA5 data

The Caribbean region of Colombia is a strategic source of wind energy for Colombia’s economic development. However, current estimates of wind energy potential for this region are based on low-resolution observations from a sparse set of weather stations that falls short of the temporal and spatial scales required by the wind energy sector. We present a novel characterization of the wind resource over the Colombian Caribbean, using 10-min average wind records from 13 meteorological stations and comparing the results with newer ERA5 reanalysis data to generate reliable information for the feasibility and operational stages of wind farms. According to the 10-min observations, average wind speeds in the region are in a 2.2 m s−1 to 8.3 m s− 1 range. Based on Weibull distributions and hourly Wind Power Density (WPD) calculations, we found several locations that offer commercial wind potential, with many having WPD above 800 W m−2. Furthermore, our estimates based on ERA5 show a wide offshore region in the Caribbean with a WPD over 800 W m−2 yearlong. Finally, we calculate the Annual Energy Production (AEP) for the stations with promising potential, obtaining capacity factors around 50%, comparable to those of the most productive wind farms worldwide.

Dynamic Control of Integrated Wind Farm Battery Energy Storage Systems for Grid Connection

The intermittent nature of wind power is a major challenge for wind as an energy source. Wind power generation is therefore difficult to plan, manage, sustain, and track during the year due to different weather conditions. The uncertainty of energy loads and power generation from wind energy sources heavily affects the system stability. The battery energy storage system (BESS) plays a fundamental role in controlling and improving the efficiency of renewable energy sources. Stochasticity of wind speed and reliability of the main system components are considered. This paper presents a dynamical control system based on model predictive control (MPC) in real time, to make full use of the flexibility and controllability of energy storage to mitigate problems of wind farm variability and intermittency. The control scheme first plans the expected output, then stochastic optimization is used to optimize grid integrated wind farm BESS output power, develop an optimal operation strategy for BESS, and prevent some unpredictable conditions that may have impacts on the stability of the system. The results show that the proposed method can reduce grid-connected wind power fluctuations, limit system faults, control command for the BESS in the dispatching period, and ensure system stability for grid connection.

Distributed Energy Resources Based Microgrid: Review of Architecture, Control, and Reliability

To accomplish feasible large-scale integration of distributed energy resources (DER) into the existing grid system, microgrid implementation has proven to be the most effective. This article reviews the vital aspects of DER based microgrid and presents simulations to investigate the impacts of DER sources, electric vehicles (EV), and energy storage system (ESS) on practicable architectures' resilient operation. The focus is primarily on the concept and definition of microgrid, comparison of control strategies (primary, secondary, and tertiary strategies), energy management strategies, power quality (PQ) issues associated with DER based microgrid, and state-of-the-art entities such as ESS and EV's applications toward microgrid reliability. Following discussion on the different attributes of DER sources-based microgrid, simulations are performed to verify the results of the past works on the effects of solar, wind energy sources, ESS, and EVs on the microgrid frequency response. Additional simulations are conducted to assess the influences of DERs, ESS, EVs, and their operational strategies on the microgrid reliability aspects.

Regional evaluation of renewable energy sources in Turkey by new integrated AHP-MARCOS methodology: a real application

ABSTRACT In this study, it was aimed to determine the regional priorities of renewable energy sources in Turkey. Unlike the literature, renewable energy sources were selected on a regional basis. While criteria weights were obtained by the AHP method, the alternative ranking was found for each region by the MARCOS method. While investment cost was determined as the most important criterion, it was determined as a result of the application of the MARCOS method that the energy sources that should be preferred firstly were hydro energy sources in Eastern Anatolia, Mediterranean, Southeastern Anatolia and Black Sea Region, wind energy sources in Marmara and Aegean Region, and solar energy sources in Central Anatolia Region.

The use of wind turbines and the problem of icing

The world’s energy demand is increasing. Wind energy plays an important role in meeting this demand. Investments in wind energy have been increasing in recent years. It can be said that the source of wind energy will be unlimited since there will be wind as long as there is sun. Most governments meet a large energy need by generating electricity from wind. At the end of 2019, the total amount of electricity generated from wind was 650 GW. Wind energy capacity is increasing with offshore wind pairs. Offshore wind turbines are a new field and research studies are ongoing. Wind turbines have the capacity to be installed anywhere in the world, and each government will have its own energy source. There is a problem of icing in wind power plants installed in cold climates. With this problem, efficiency in wind turbines decreases. Many methods have been found and developed in studies on icing problems. In this article, wind turbines were investigated, states’ perspectives on wind energy, developments and investments in wind energy, and the problem of icing were examined. Many articles in the literature have been reviewed and a solution to the icing problem of wind turbine blades has been sought.

Performance of Crossflow Wind Turbines in In-line Configuration and Opposite Rotation Direction

Wind energy sources must be investigated to produce electrical energy from a renewable source. Crossflow wind turbines are suitable for use because they have several advantages such as self-starting ability, low noise, and excellent stability. They have the potential to be applied as small wind turbines in urban districts because of their small maximum coefficient of power (Cp), which is 10% of that of other small wind turbines. To enhance the performance of crossflow wind turbines, we changed the turbine to rotate in the opposite direction in the in-line configuration. Turbine performance testing was tested using a wind tunnel. The characteristics of crossflow wind turbines were investigated, then turbine performance was analyzed and discussed. The maximum power coefficient obtained was 0.169 (Cp) with the configuration of 12 turbine blades at a wind speed of 10 m/s. The maximum torque coefficient obtained was 0.703. The overall results show that the crossflow wind turbine in in-line configuration with opposite rotation can improve the performance of wind turbines.

Power transport needs for the German power grid for a major demand coverage by wind and solar power

The contribution of fluctuating wind and solar energy sources to the German electrical energy demand has increased from 12% up to 40% within the last 10 years and leads to higher infrastructure requirements due to the different spatiotemporal characteristics of wind and solar energy generation. However, common investigations of the energy system exhibit a limited spatiotemporal resolution of power or are based only on simulation models. Therefore, real measurement data regarding the energy demand and the generated energy from 95 German ZIP code regions are investigated to support current infrastructure decisions for the power system. In particular, the residual regional power generation with different wind and solar shares and the resulting power flows are calculated as the solution of a cost optimization problem without energy storage. As a result, a heterogeneous power distribution is identified with a medium surplus in northern and eastern regions and deficits in western and southern Germany. Furthermore, maximum regional coverage of the energy demand by solar and wind energy exists with respect to the share of wind and solar energy generation. For an extrapolation scenario of the average renewable energy to 100% of the average demand, the optimal share is 53% solar and 47% wind power. As a conclusion, a balance of the spatiotemporal fluctuations between renewable energy generation and demand is feasible with appropriate changes in the power grid system, e.g., load management.

Rüzgâr Hızı Haritalarının Oluşturulmasında Kullanılan Enterpolasyon Yöntemlerinin Karşılaştırılması: Balıkesir Örneği

Dünyada artan enerji ihtiyacıyla beraber yenilenebilir enerji kaynaklarına olan talep de gün geçtikçe artmaktadır. Enerji ihtiyacındaki bu artış, devletleri ve özel sektör yatırımcılarını yenilenebilir enerji kaynaklarına yönlendirmektedir. Yeryüzündeki en önemli yenilenebilir enerji kaynaklarından biri de rüzgâr enerjisidir. Son yıllarda rüzgâr enerjisinin yenilenebilir enerji kaynakları ile üretilen enerji miktarındaki payı artmaktadır. Bu artışta rüzgâr enerjisinin çevre dostu olması ve kendini yenileyebilmesi gibi özellikleri sayesinde sürdürülebilir bir enerji kaynağı olmasının etkisi büyüktür. Bu anlamda, rüzgâr enerjisinden en yüksek verimi alabilmek için santrallerin doğru konumlandırılması başka bir ifade ile santral yer seçimi hususu büyük öneme sahiptir. Rüzgâr enerji santrallerinin yer seçiminde literatürdeki en önemli parametrelerden biri rüzgâr enerjisi kaynağı ve buna bağlı olarak rüzgâr hızıdır. Rüzgâr hızı haritalarının oluşturulabilmesi için belirli sayıda istasyondan elde edilen noktasal hız verilerinin çalışma alanına yayılması gerekmektedir. Bu çalışmada, Balıkesir ilinde yer alan 32 adet meteoroloji istasyonundan elde edilen rüzgâr hızı verileri yardımıyla Balıkesir ili sınırları içinde IDW, Kriging, Natural Neighbor, Spline ve Trend olmak üzere beş farklı enterpolasyon yöntemi ile rüzgâr hızı haritaları oluşturulmuş ve kullanılan enterpolasyon yöntemleri karesel ortalama hata değerlerine göre karşılaştırılmıştır.

Dynamic optimal power flow with cross entropy covariance matrix adaption evolutionary strategy for systems with electric vehicles and renewable generators

Modern power systems which integrate renewable energy sources (RESs), such as wind or solar energy sources and plug-in electric vehicles (PEVs), need to carry out the uncertainty due to the access of demanded or injected power. Therefore, it is necessary to consider uncertainty costs in optimal power flow problems. To develop the uncertainty cost functions, log-normal probability distribution function (PDF) for solar irradiance, normal PDF for unloading and loading behavior of PEVs, and Rayleigh PDF for wind speed are considered. In this work, a dynamic optimal power flow (DOPF) model is formulated by considering the uncertainties of RESs and PEVs. A newly hybrid metaheuristic algorithm named cross entropy (CE) covariance matrix adaption evolutionary strategy (CMAES) is proposed to evaluate the DOPF problem in a modified IEEE 118-bus system. The application of adaptive step length in the CMAES method improves the local exploitation capability, while the CE method is used in the initial stage for global exploration due to its fast convergence. Simulation results indicate that the proposed technique can solve the DOPF problems with RESs and PEVs effectively and can provide high-quality solutions compared to different techniques. The conventional statistical method called ANOVA test is performed for comparative analysis of different techniques. The results of this test show the validation of CE-CMAES compared to different optimization techniques. Therefore, the proposed method could be easily and efficiently applied by power system operators in real-time optimal power flow operations.

Damage Detection in Composite Materials Using Tap Test Technique and Neural Networks

The wind energy sources promote the generation of electricity, being environmentally safe, clean and its use has been growing in Brazil, especially in the northeastern states with the implementation of new wind farms. Wind turbines, however, are subject to weather, risk of animal shocks, materials carried by the wind, and the vibrations of the system itself. The blade is the most important component of a wind turbine and is the one with the greatest risk of failure. They are usually made of a composite fiber-reinforced polymer matrix and balsa wood as structural reinforcement. As the material composing this blade has heterogeneous and anisotropic characteristics, conventional inspection techniques are not considered effective. The non-destructive Tap Test technique can be a safe option in composite materials because it does not suffer from these limitations. The objective of this work is to inspect composite plates of polymeric resin used in wind turbines with discontinuities using the non-destructive Tap Test technique, where regions with and without defect were analyzed. The collected signals from an accelerometer and a microphone were processed, to allow the extraction of features and the recognition of discontinuities with the aid of a neural network.

Evaluation of energy alternatives for sustainable development of energy sector in India: An integrated Shannon’s entropy fuzzy multi-criteria decision approach

In this paper, conventional and renewable energy sources for sustainable development of energy sector in India are evaluated from multiple perspectives including economic, technical, social, environmental, political, and flexible criteria. An integrated Shannon’s entropy multi-criteria decision making (MCDM) method has been used for the evaluation and assessment of these sources. Thermal, gas, nuclear, solar, wind, biomass, and hydro energy options are used as the alternatives in the decision model. Shannon’s entropy method is applied to determine the weights of decision criteria, and fuzzy analytical hierarchy process (AHP) method is applied to prioritize sustainable energy alternatives. The output of the proposed model was compared with six different fuzzy MCDM techniques for the establishment of correlation index. Solar energy was shown to be particularly well suited for India followed by wind and hydro energy sources. Later, the study has developed fourteen scenarios, considering the first five sustainable energy sources (solar, wind, hydro, biomass, and gas power), to evaluate the optimal energy mix scenario for the sustainable development of energy sector in India. An optimal energy mix scenario carries the heroic development of solar, wind, and hydro energy with cross border import-export facility for the time frame of the year 2030.

A Polynomial Chaos-based Approach to Quantify Uncertainties of Correlated Renewable Energy Sources in Voltage Regulation

Renewable energy sources (RESs) and flexible loads have introduced significant uncertainties in the operation and control of power systems especially voltage regulation at the distribution system level. Assessing the impacts of uncertainties on power system behavior and response has become a key factor for modern power system operation and planning. Although several probabilistic methods have been used for quantifying uncertainties such as Monte Carlo simulation and perturbation techniques, they are computationally expensive and cannot be directly embedded in power system models. Also, the existence of more than one source of randomization requires complicated correlation models via intensive statistical approaches. To overcome the aforementioned challenges, this article proposes a generalized polynomial chaos (gPC) based approach to quantify the impacts of uncertainties resulting from RESs and load variations on voltage magnitudes of distribution systems through propagating uncertainties in the system under study. In the gPC, the behavior of each random variable is transformed into a series of orthogonal polynomials that can be easily evaluated. A correlation matrix is calculated and used to estimate the proper values of each RES. The proposed method is implemented on several systems including the IEEE 13-node, the IEEE 123-node, the 240-node, and the 8500-node distribution systems integrated with solar and wind energy sources at various locations. The results show that the proposed algorithm provides high efficiency and significant reduction in computation time in comparison with Monte Carlo simulation.

Reliability Analysis of Boost Converters Connected to a Solar Panel Using a Markov Approach

In the past few decades, the energy shortage and global warming problems became a serious concern for humanity. To solve these problems, many countries have evolved renewable energy sources (RESs) such as solar, wind, hydro, tidal, geothermal, and biomass energy sources. Solar energy is usually harvested via a solar panel that is connected to a boost converter to supply the loads. The converter has a key role in the system, since it controls the voltage at the DC bus. If any accidental fault occurs in the converter, the solar panel cannot supply electricity to the loads. Therefore, reliability evaluation of the converter is usually warranted. In this study, reliability evaluation of boost converters connected to a solar panel is carried out using the Markov technique. This technique is widely employed to evaluate the reliability and availability of a system with fixed failure and repair rates. Using the Markov method, we found that the reliability of the typical specific converter considered is 0.9986 for and that its life expectancy or Mean-Time-To-Failure (MTTF) is .

Simulation of a microgrid for a non-interconnected zone that integrates renewable energies

This paper develops a simulation of a small electrical network (Microgid) that integrates renewable energies, the model of the micro network is made up of a solar energy source, a wind energy source, an energy storage element, a non-renewable source such as a diesel generator. The model of the microgrid represent a non-interconnected area from the electrical network in Colombia. The non-interconnected areas sometimes depend on unreliable connections to the grid integration of renewable energies could be the best option to guarantee energy in these sectors and allow generating projects with social impact. A possible solution to this deficit of energy is to supplement the production of energy with renewable energy plants from resources as sun or wind. The simulated model allowed to study the effects of the network in island mode and in interconnected mode, showing the imbalances that can be obtained by integrating renewable energies and storage systems. It is verified that with an inclusion of more than 30% of power in renewable energies there is the possibility of having load imbalances, which affect the frequency and cause instability in the network. It also verifies how a control system can regulate the load balance but must interact with the other energy sources.

A hypolimnetic aeration system to meet the hypolimnetic oxygen demand by increasing the natural assimilation capacity of a reservoir

AbstractHypolimnetic aeration is a viable method to increase the assimilation capacity of lakes. In this study two lakes, one relatively small pond were chosen where aeration equipment was installed and one larger reservoir lake where the required aeration amount was found by calculation. A laboratory‐scale hypolimnetic aeration system (HAS) was designed. A hybrid system using wind and solar energy was implemented which was scaled up from the lab‐scale system. The pilot‐scale system was tested in the smaller volume Borabey Pond and the system’s efficiency was assessed. An aerial hypolimnetic oxygen demand (AHOD) decrease by 33% was observed in the pond due to the operation of the HAS. It was found that, although renewable wind and solar energy sources are applicable for small water bodies, conventional energy sources are needed for large water bodies.

Energy, Exergy, and Thermo-Economic Analysis of Renewable Energy-Driven Polygeneration Systems for Sustainable Desalination

Reliable production of freshwater and energy is vital for tackling two of the most critical issues the world is facing today: climate change and sustainable development. In this light, a comprehensive review is performed on the foremost renewable energy-driven polygeneration systems for freshwater production using thermal and membrane desalination. Thus, this review is designed to outline the latest developments on integrated polygeneration and desalination systems based on multi-stage flash (MSF), multi-effect distillation (MED), humidification-dehumidification (HDH), and reverse osmosis (RO) technologies. Special attention is paid to innovative approaches for modelling, design, simulation, and optimization to improve energy, exergy, and thermo-economic performance of decentralized polygeneration plants accounting for electricity, space heating and cooling, domestic hot water, and freshwater production, among others. Different integrated renewable energy-driven polygeneration and desalination systems are investigated, including those assisted by solar, biomass, geothermal, ocean, wind, and hybrid renewable energy sources. In addition, recent literature applying energy, exergy, exergoeconomic, and exergoenvironmental analysis is reviewed to establish a comparison between a range of integrated renewable-driven polygeneration and desalination systems.

Searching for sustainable electricity generation: The possibility of substituting coal and natural gas with clean energy

It is now a common consensus that there is a need to lessen the consumption of fossil fuels as they are the main cause of greenhouse gases. Electricity is one of the chief determinants of greenhouse gases emission as its generation is dominated by fossil fuels. Thus, it is imperative to decarbonize the electric power sector. The main objective of this work is, therefore, to examine the potentials to switch from fossil fuels to clean energy which comprises of nuclear power and the various renewable energy sources of solar energy, hydropower, wind energy, biofuels, and geothermal. Due to the unsuitability of the ordinary least squares (OLS) procedure in the face of severe multicollinearity, the ridge regression procedure was adopted to obtain the parameter estimates using the U.S. annual electricity sector data for the period 1985 to 2018. The results show that substantial substitution exists between clean energy and the fossil fuels of coal and natural gas in the U.S. electricity sector. The results also underscore the importance of energy resource in the process of economic growth and development of U.S. To fully harness the potentials of clean energy, the study recommends increased investment in each of the components of clean energy. This should be complemented with various policy instruments such as provisions of tax credits and feed-in tariffs for clean energy and imposition of tax on carbon consumption.

Impact of Renewable Energy Sources into Multi Area Multi-Source Load Frequency Control of Interrelated Power System

There is an increasing concentration in the influences of nonconventional power sources on power system process and management, as the application of these sources upsurges worldwide. Renewable energy technologies are one of the best technologies for generating electrical power with zero fuel cost, a clean environment, and are available almost throughout the year. Some of the widespread renewable energy sources are tidal energy, geothermal energy, wind energy, and solar energy. Among many renewable energy sources, wind and solar energy sources are more popular because they are easy to install and operate. Due to their high flexibility, wind and solar power generation units are easily integrated with conventional power generation systems. Traditional generating units primarily use synchronous generators that enable them to ensure the process during significant transient errors. If massive wind generation is faltered due to error, it may harm the power system’s operation and lead to the load frequency control issue. This work proposes binary moth flame optimizer (MFO) variants to mitigate the frequency constraint issue. Two different binary variants are implemented for improving the performance of MFO for discrete optimization problems. The proposed model was evaluated and compared with existing algorithms in terms of standard testing benchmarks and showed improved results in terms of average and standard deviation.

Chaotic darwinian particle swarm optimization for real-time hierarchical congestion management of power system integrated with renewable energy sources

The increasing penetration of renewable energy sources that have intermittent outputs challenge the Independent System Operator while managing transmission congestion. A new Real-Time Hierarchical Congestion Management (RHCM) technique is proposed that reschedules generators in two stages based on Available Congestion Clearing Time (ACCT) of the transmission lines in presence of renewable energy sources. Chaotic Darwinian Particle Swarm Optimization (CDPSO) is used for determining the optimal schedules of demand response loads and reschedules of conventional generators to mitigate congestion. The solar and wind energy sources are modelled using Rayleigh and Beta probability density functions; Latin Hyper cube sampling is adopted for sampling. IEEE 39 bus system is simulated for cases of overloads and contingencies and RHCM using CDPSO is tested to ensure the security of the system. The benefit of RHCM incorporating demand response is presented in terms of reduced congestion relieving costs and decreased power loss.

Efficient Electrocatalytic CO2 Reduction to C2+ Alcohols at Defect-Site-Rich Cu Surface

Summary Electrochemical CO2 reduction is a promising approach for upgrading excessive CO2 into value-added chemicals, while the exquisite control of the catalyst atomic structures to obtain high C2+ alcohol selectivity has remained challenging due to the intrinsically favored ethylene pathways at Cu surface. Herein, we demonstrate a rational strategy to achieve ∼70% faradaic efficiency toward C2+ alcohols. We utilized a CO-rich environment to construct Cu catalysts with stepped sites that enabled high surface coverages of ∗CO intermediates and the bridge-bound ∗CO adsorption, which allowed to trigger CO2 reduction pathways toward the formation alcohols. Using this defect-site-rich Cu catalyst, we achieved C2+ alcohols with partial current densities of > 100 mA·cm−2 in both a flow-cell electrolyzer and a membrane electrode assembly (MEA) electrolyzer. A stable alcohol faradaic efficiency of ∼60% was also obtained, with ∼500 mg C2+ alcohol production per cm2 catalyst during a continuous 30-h operation.