Combined Optimal Dispatch of Thermal Power Generators and Energy Storage Considering Thermal Power Deep Peak Clipping and Wind Energy Emission Grading Punishment

Peak load and wind energy emission pressure rise more as wind energy penetration keeps growing,which affects the stabilization of the PS(power system).This paper suggests integrated optimal dispatching of thermal power generators and BESS(battery energy storage system)taking wind energy emission grading punishment and deep peak clipping into consideration.Firstly,in order to minimize wind abandonment,a hierarchical wind abandonment penalty strategy based on fuzzy control is designed and introduced,and the optimal grid-connected power of wind energy is determined as a result of minimizing the peak cutting cost of the system.Secondly,considering BESS and thermal power,the management approach of BESS-assisted virtual peak clipping of thermal power generators is aimed at reducing the degree of deep peak clipping of thermal power generators and optimizing the output of thermal power generators and the charging and discharging power of BESS.Finally,Give an example of how this strategy has been effective in reducing abandonment rates by 0.66% and 7.46% individually for different wind penetration programs,and the daily average can reduce the peak clipping power output of thermal power generators by 42.97 and 72.31 MWh and enhances the effect and economy of system peak clipping.

A positive trend in the stability of global offshore wind energy

The recognition on the trend of wind energy stability is still extremely rare,although it is closely related to acquisition efficiency,grid connection,equipment lifetime,and costs of wind energy utilization.Using the 40-year(1979–2018)ERA-Interim data from the European Center for Medium-Range Weather Forecasts,this study presented the spatial-temporal distribution and climatic trend of the stability of global offshore wind energy as well as the abrupt phenomenon of wind energy stability in key regions over the past 40 years with the climatic analysis method and Mann-Kendall(M-K)test.The results show the following 5 points.(1)According to the coefficient of variation(C_(v))of the wind power density,there are six permanent stable zones of global offshore wind energy:the southeast and northeast trade wind zones in the Indian,Pacific and Atlantic oceans,the Southern Hemisphere westerly,and a semi-permanent stable zone(North Indian Ocean).(2)There are six lowvalue zones for both seasonal variability index(S_(v))and monthly variability index(M_(v))globally,with a similar spatial distribution as that of the six permanent stable zones.M_(v) and S_(v) in the Arabian Sea are the highest in the world.(3)After C_(v),M_(v) and S_(v) are comprehensively considered,the six permanent stable zones have an obvious advantage in the stability of wind energy over other sea areas,with C_(v) below 0.8,M_(v) within 1.0,and S_(v) within 0.7 all the year round.(4)The global stability of offshore wind energy shows a positive climatic trend for the past four decades.C_(v),M_(v) and S_(v) have not changed significantly or decreased in most of the global ocean during 1979 to2018.That is,wind energy is flat or more stable,while the monthly and seasonal variabilities tend to shrink/smooth,which is beneficial for wind energy utilization.(5)C_(v) in the low-latitude Pacific and M_(v) and S_(v) in both the North Indian Ocean and the low-latitude Pacific have an obvious abrupt phenomenon at the end of the20th century.

A Detail Investigation on the Antarctic Wind Energy

The scientific development of wind energy based on local conditions is conducive to the urgent energy demand and environmental protection of Antarctic region.In this study,the ERA5 reanalysis data are used to evaluate the wind energy resources in the Antarctic region.A series of key indicators,such as wind power density,effective wind speed occurrence,energy level occurrence and stability,are comprehensively considered by using climate statistical analysis methods to analyze the temporal and spatial distribution characteristics of Antarctic wind energy resources.The results show that the Antarctic region contains abundant wind energy resources,which benefits the construction of scientific research stations.The superior areas are the Southern Ocean and the coast of the East Antarctica,followed by the Transantarctic Mountains,the coast of the Bellingshausen Sea and Amundsen Sea.These areas have advantages in terms of wind power density(500-2500 W/m2),effective wind speed occurrence(80%-90%),energy level occur-rence(60%-90%)and stability(Cv:0.6-1,Mv:1.2-1.8,Sv:0.8-1.2).The Antarctic’s wind energy resources in wind power density,effective wind speed occurrence and energy level occurrence in autumn and winter are better than those in summer,while the coefficient of variation in summer is worse than that in autumn and winter.

Application of four machine-learning methods to predict short-horizon wind energy

Renewable energy has garnered attention due to the need for sustainable energy sources.Wind power has emerged as an alternative that has contributed to the transition towards cleaner energy.As the importance of wind energy grows,it can be crucial to provide forecasts that optimize its performance potential.Artificial intelligence(AI)methods have risen in prominence due to how well they can handle complicated systems while enhancing the accuracy of prediction.This study explored the area of AI to predict wind-energy production at a wind farm in Yalova,Turkey,using four different AI approaches:support vector machines(SVMs),decision trees,adaptive neuro-fuzzy inference systems(ANFIS)and artificial neural networks(ANNs).Wind speed and direction were considered as essential input parameters,with wind energy as the target parameter,and models are thoroughly evaluated using metrics such as the mean absolute percentage error(MAPE),coefficient of determination(R~2),and mean absolute error(MAE).The findings accentuate the superior performance of the SVM,which delivered the lowest MAPE(2.42%),the highest R~2(0.95),and the lowest MAE(71.21%)compared with actual values,while ANFIS was less effective in this context.The main aim of this comparative analysis was to rank the models to move to the next step in improving the least efficient methods by combining them with optimization algorithms,such as metaheuristic algorithms.

Sustainability of Wind Energy under Changing Wind Regimes—A Case Study

A method was introduced to assess the sustainability of energy production over the lifetime (~20 y) of wind turbines. Community Earth System Model simulations were downscaled for the tourist seasons (mid-May to mid-September) of 2006 to 2012 (CESM-P1) and 2026 to 2032 (CESM-P2) to obtain a reference and projected wind-speed climatology, respectively. The wind speeds served to calculate the potential power output and capacity factors of seven turbine types. CESM-P1 wind-speed climatology, power output, and capacity factors were compared to those derived from wind speeds obtained by numerical weather forecasts for reference to known standard to wind-farm managers. Juneau, Alaska served as a virtual testbed as this region is known to experience changes in wind speeds in response to the Pacific Decadal Oscillation. CESM-P2 suggested about 2% decrease for wind speeds between the speeds at cut-in and rated power, and about 8% - 10% decrease in potential wind-power output. This means that in regions of decadal climate variations, the sustainability of wind-energy production should be part of the decision-making process. The study demonstrated that using mean values of wind-speeds can provide qualitative knowledge about decreases/increases in potential energy production, but not about the magnitude. Using the total individual wind-speed data of all seasons provided the same amount of total power output than summing up the power outputs of individual seasons. The main advantage of calculating individual seasonal wind-power outputs, however, is that it theoretically permits assessment of interannual variability in power output and capacity factors. Comparison to a known standard may help stakeholders in understanding of uncertainty and interpretation of projected changes.

Individual and local scale interactions and adaptations to wind energy development:A case study of Oklahoma,USA

Wind energy development receives broad support but is often opposed at the local level due to nuisance concerns and uncertainties about how it affects the landowners living due to the turbines and the broader community.Lo-cal opposition to wind energy development can be a powerful force slowing or even ending its implementation in a given region.Oklahoma,USA is currently ranked as 4^(th)in the United States in current wind energy production and has seen significant pushback from some local communities as a renewable energy resource.Previous studies have examined wind energy development’s impact on rural education income,and property values of different communities in Oklahoma.However,funding information on how wind energy development affects the individu-als living alongside the turbines are limited.Using fifteen interviews with landowners,site-managers,community representatives,and pro-wind non-profit organization representatives,this study finds that individuals who live in proximity to wind energy development,particularly those involved in the agricultural industry,have created novel and unique uses for wind farm infrastructure.It also finds that local perceptions of wind energy production are mostly positive and provides increased knowledge of how wind energy development affects the individuals and communities that are hosting the turbines and related infrastructure.

An Ultra‑Durable Windmill‑Like Hybrid Nanogenerator for Steady and Efficient Harvesting of Low‑Speed Wind Energy

Wind energy is one of the most promising and renewable energy sources;however,owing to the limitations of device structures,collecting low-speed wind energy by triboelectric nanogenerators(TENGs)is still a huge challenge.To solve this problem,an ultra-durable and highly efficient windmill-like hybrid nanogenerator(W-HNG)is developed.Herein,the W-HNG composes coupled TENG and electromagnetic generator(EMG)and adopts a rotational contact-separation mode.This unique design efficiently avoids the wear of friction materials and ensures a prolonged service life.Moreover,the generator group is separated from the wind-driven part,which successfully prevents rotation resistance induced by the friction between rotor and stator in the conventional structures,and realizes low-speed wind energy harvesting.Additionally,the output characteristics of TENG can be complementary to the different performance advantages of EMG to achieve a satisfactory power production.The device is successfully driven when the wind speed is 1.8 m s−1,and the output power of TENG and EMG can achieve 0.95 and 3.7 mW,respectively.After power management,the W-HNG has been successfully applied as a power source for electronic devices.This work provides a simple,reliable,and durable device for improved performance toward large-scale low-speed breeze energy harvesting.

A comprehensive review of miniatured wind energy harvesters

Following the current rapid development of the Internet of Things(IoT)and wireless condition monitoring systems,energy harvesters which use ambient energy have become a key part of achieving an energy-autonomous system.Miniature wind energy harvesters have attracted widespread attention because of their great potential of power density as well as the rich availability of wind energy in many possible areas of application.This article provides readers with a glimpse into the state-of-the-art of miniature wind energy harvesters.The crucial factors for them to achieve high working efficiency under lower operational wind speed excitation are analyzed.Various potential energy coupling mechanisms are discussed in detail.Design approaches for broadening operational wind-speed-range given a variety of energy coupling mechanisms are also presented,as observed in the literature.Performance enhancement mechanisms including hydrodynamic configuration optimization,and non-linear vibration pick-up structure are reviewed.Conclusions are drawn and the outlook for each coupling mechanisms is presented.

Discussion on the Assessment Method of Wind Energy Resources by Using Regional Meteorological Data

The exploitation status of wind energy resources was analyzed, and the distribution of wind energy resources and regional meteorological stations were introduced, and then the assessment method of wind energy resources by using data from regional meteorological station was studied taking Huangjin Regional Meteorological Station in Xinning County in Hunan Province for example, besides, corresponding software was compiled. By means of SQL database and program, the method was used simply and easily and had positive meaning for the development of wind energy resources and excavation of wind farm in inland region.

Joint Model of Wind Speed and Corresponding Direction Based on Wind Rose for Wind Energy Exploitation

As a common and extensive datum to analyze wind,wind rose is one of the most important components of the meteorological elements.In this study,a model is proposed to establish the joint probability distribution of wind speed and direction using grouped data of wind rose.On the basis of the model,an algorithm is presented to generate pseudorandom numbers of wind speed and paired direction data.Afterward,the proposed model and algorithm are applied to two weather stations located in the Liaodong Gulf.With the models built for the two cases,a novel graph representing the continuous joint probability distribution of wind speed and direction is plotted,showing a strong correlation to the corresponding wind rose.Moreover,the joint probability distributions are utilized to evaluate wind energy potential successfully.In cooperation with Monte Carlo simulation,the model can approximately predict annual directional extreme wind speed under different return periods under the condition that the wind rose can represent the meteorological characters of the wind field well.The model is beneficial to design and install wind turbines.

A Novel Hybrid MPPT for Wind Energy Conversion Systems Operating under Low Variations in Wind Speed

This manuscript presents a new approach MPPT (Maximum Power Point Tracking) for improving and optimizing the performance of a Wind Energy Conversion System (WECS) operating for small variations in wind speed by combining sliding mode control and fuzzy logic control. The proposed method consists of optimizing the sliding mode controller by the fuzzy controller. The main purpose of the Sliding Mode control-Fuzzy Logic controller (SM-FL) is to ensure the robustness (by eliminating certain disadvantages of the sliding mode control such as the phenomenon of chattering) and the stability of the control system in the case of small variations in conditions atmospheric (here variation of the wind). Our system consists of a wind turbine, a Permanent Magnet Synchronous Generator (PMSG) and a DC-DC boost converter connected to a continuous load. The performances of the method suggested are compared with those of fuzzy logic and fuzzy-Proportional Integral (FL-PI) in term speed of convergence, of tracking time and tracking efficiency. The results of numerical simulation of our system confirmed the best performance of this method.

Wind Energy Generation and Assessment of Resources in India

The gap between energy demand and its generation is constantly widening. People have started giving more emphasis on renewable sources of energy. This paper presents the estimation of potential for wind energy generation maps based on fixed wind turbine capacity. Although wind energy has developed substantially in recent years, we have only wind speed and wind potential density maps. Our attempt here is to generate wind energy generation potential maps. Major step in achieving this goal is modeling of wind energy conversion system using TRNSYS software. The model consists of three main components namely the weather, the turbines and energy conversion parameters. The weather data are provided from the meteorological database, namely Meteonorm. The simulated output is compared with actual wind generation of wind farms. After comparing our model results with the existing wind energy generation data, we have extended to compute the wind energy generation for all locations in India. For simulation, 4691 locations are identified considering 0.25° × 0.25° interval. The energy generation simulated data are compiled and developed into maps that are useful to all wind energy developers. The data generated and presented in the form of maps are for all the 30 states of India.

Resource Assessment of Wind Energy Potential of Mokha in Yemen with Weibull Speed

The increasing use of fossil fuels has a significant impact on the environment and ecosystem,which increases the rate of pollution.Given the high potential of renewable energy sources in Yemen and other Arabic countries,and the absence of similar studies in the region.This study aims to examine the potential of wind energy in Mokha region.This was done by analyzing and evaluating wind properties,determining available energy density,calculating wind energy extracted at different altitudes,and then computing the capacity factor for a few wind turbines and determining the best.Weibull speed was verified as the closest to the average actual wind speed using the cube root,as this was verified using 3 criteria for performance analysis methods(R^(2)=0.9984,RMSE=0.0632,COE=1.028).The wind rose scheme was used to determine the appropriate direction for directing the wind turbines,the southerly direction was appropriate,as the winds blow from this direction for 227 days per year,and the average southerly wind velocity is 5.27 m/s at an altitude of 3 m.The turbine selected in this study has a tower height of 100m and a rated power of 3.45 MW.The capacitance factor was calculated for the three classes of wind turbines classified by the International Electrotechnical Commission(IEC)and compared,and the turbine of the first class was approved,and it is suitable for the study site,as it resists storms more than others.The daily and annual capacity of a single,first-class turbine has been assessed to meet the needs of 1,447 housing units in Mokha region.The amount of energy that could be supplied to each dwelling was around 19 kWh per day,which was adequate to power the basic loads in the home.

Notice on a Case Study on the Utilization of Wind Energy Potential on a Remote and Isolated Small Wastewater Treatment Plant

Small wastewater treatment plants (WWTP) are frequently located, by necessity, in remote and isolated sites, which increases the difficulty of its energy supply. Some of them are located near the seaside, in environmental sensible zones, and due to tourism activity of these sites, seasonal effects related with population size fluctuation can occur, which can originate certain inefficiencies concerning WWTP design and energy supply. The objective of this paper is to describe a step by step procedure for evaluation of the wind potential of sites that are dependent of in-situ energy generation, as well as, a case study on the utilization of the potential wind energy in Magoito WWTP (5000 p.e.). The employed methodology comprised the collection of one year of in-situ wind data and its validation by comparison with historical data of about 10 years of a nearby anemometric station. The data provided by the two anemometric stations was statistically treated. It allowed the analysis of the results from the two stations are promissory in terms of wind availability and velocity. Finally, it comprised the simulation of the local wind conditions for a considerable larger area in order to find the best site for locating a wind turbine.

OUTPUT MAXIMIZATION CONTROL FOR VSCF WIND ENERGY CONVERSION SYSTEM USING EXTREMUM CONTROL STRATEGY

The energy conversion optimization control strategy is presented for a family of horizontal-axis variablespeed fixed-pitch wind energy conversion systems,working in the partial load region.The system uses a variablespeed wind turbine(VSWT)driving a squirrel-cage induction generator(SCIG)connected to a grid.A new maximum power point tracking(MPPT)approach is proposed based on the extremum seeking control principles under the assumption that the wind turbine model and its parameters are poorly known.The aim is to drive the average position of the operation point close to optimality.Here the wind turbulence is used as search disturbance instead of inducing new sinusoidal search signals.The discrete Fourier transform(DFT)process of some available measures estimates the distance of operation point to optimality.The effectiveness of the proposed MPPT approach is validated under different operation conditions by numerical simulations in MATLAB/SIMULINK.The simulation results prove that the new approach can effectively suppress the vibration of system and enhance the dynamic performance of system.

Short-Term Wind Energy Forecasting Using Deep Learning-Based Predictive Analytics

Wind energy is featured by instability due to a number of factors,such as weather,season,time of the day,climatic area and so on.Furthermore,instability in the generation of wind energy brings new challenges to electric power grids,such as reliability,flexibility,and power quality.This transition requires a plethora of advanced techniques for accurate forecasting of wind energy.In this context,wind energy forecasting is closely tied to machine learning(ML)and deep learning(DL)as emerging technologies to create an intelligent energy management paradigm.This article attempts to address the short-term wind energy forecasting problem in Estonia using a historical wind energy generation data set.Moreover,we taxonomically delve into the state-of-the-art ML and DL algorithms for wind energy forecasting and implement different trending ML and DL algorithms for the day-ahead forecast.For the selection of model parameters,a detailed exploratory data analysis is conducted.All models are trained on a real-time Estonian wind energy generation dataset for the first time with a frequency of 1 h.The main objective of the study is to foster an efficient forecasting technique for Estonia.The comparative analysis of the results indicates that Support Vector Machine(SVM),Non-linear Autoregressive Neural Networks(NAR),and Recurrent Neural Network-Long-Term Short-Term Memory(RNNLSTM)are respectively 10%,25%,and 32%more efficient compared to TSO’s forecasting algorithm.Therefore,RNN-LSTM is the best-suited and computationally effective DL method for wind energy forecasting in Estonia and will serve as a futuristic solution.

Event-triggered mechanism based robust fault-tolerant control for networked wind energy conversion system

In this paper,a novel robust fault-tolerant control scheme based on event-triggered communication mechanism for a variable-speed wind energy conversion system(WECS)with sensor and actuator failures is proposed.The nonlinear WECS with event-triggered mechanism is modeled based on the Takagi-Sugeno(T-S)fuzzy model.By Lyapunov stability theory,the parameter expression of the proposed robust fault-tolerant controller with event-triggered mechanisms is proposed based on a feasible solution of linear matrix inequalities.Compared with the existing WECS fault-tolerant control methods,the proposed scheme significantly reduces the pressure of network packet transmission and improves the robustness and reliability of the WECS.Considering a doubly-fed variable speed constant frequency wind turbine,the eventtriggered mechanism based fault-tolerant control for WECS is analyzed considering system model uncertainty.Numerical simulation results demonstrate that the proposed scheme is feasible and effective.

Optimal Allocation of a Hybrid Wind Energy-Fuel Cell System Using Different Optimization Techniques in the Egyptian Distribution Network

This paper presents an optimal proposed allocating procedure for hybrid wind energy combined with proton exchange membrane fuel cell (WE/PEMFC) system to improve the operation performance of the electrical distribution system (EDS). Egypt has an excellent wind regime with wind speeds of about 10 m/s at many areas. The disadvantage of wind energy is its seasonal variations. So, if wind power is to supply a significant portion of the demand, either backup power or electrical energy storage (EES) system is needed to ensure that loads will be supplied in reliable way. So, the hybrid WE/PEMFC system is designed to completely supply a part of the Egyptian distribution system, in attempt to isolate it from the grid. However, the optimal allocation of the hybrid units is obtained, in order to enhance their benefits in the distribution networks. The critical buses that are necessary to install the hybrid WE/ PEMFC system, are chosen using sensitivity analysis. Then, the binary Crow search algorithm (BCSA), discrete Jaya algorithm (DJA) and binary particle swarm optimization (BPSO) techniques are proposed to determine the optimal operation of power systems using single and multi-objective functions (SOF/MOF). Then, the results of the three optimization techniques are compared with each other. Three sensitivity factors are employed in this paper, which are voltage sensitivity factor (VSF), active losses sensitivity factor (ALSF) and reactive losses sensitivity factor (RLSF). The effects of the sensitivity factors (SFs) on the SOF/MOF are studied. The improvement of voltage profile and minimizing active and reactive power losses of the EDS are considered as objective functions. Backward/forward sweep (BFS) method is used for the load flow calculations. The system load demand is predicted up to year 2022 for Mersi-Matrouh City as a part of Egyptian distribution network, and the design of the hybrid WE/PEMFC system is applied. The PEMFC system is designed considering simplified mathematical expressions. The economics of operation of both WE and PEMFC system are also presented. The results prove the capability of the proposed procedure to find the optimal allocation for the hybrid WE/PEMFC system to improve the system voltage profile and to minimize both active and reactive power losses for the EDS of Mersi-Matrough City.

Differential Impacts of Wind Energy on Sustainable Power Generation in Ghana

Ghana has a yearly development interest for power at a rate of 83.8% in 2010, and to 12% from 2020 to 2040 but this opportunity has been farfetched with the shocks in energy generation during 1983, 1994, 1997-98, and 2006-2007 era pushing the energy sector into crisis and a consequent adverse impact of 1.5% to GDP. This study, therefore, investigated the differential impacts of wind energy to sustainable power generation in Ghana by assessing the determinants of energy supply, energy demand and supply mix for energy development, the capacity of the energy sector to develop wind power and possible challenges in developing wind power energy in Ghana. An exploratory design that adopted both qualitative and quantities approaches was applied to the study. The study population involving 34 sample sizes was accessed from a 46 population made up of management/ministers of energy and counsellors or energy experts. The study concluded that the demand for energy in Ghana has increased over the years but without a commensurate increase in energy supply. Major reasons for the shortfall in energy supply have centred on the monopoly enjoyed by the major power producer which invariably places stress on its ability to supply energy to meet the increasing demand. It also came out that wind energy has the potential to contribute to the overall energy fortunes of Ghana. However, a focus on wind energy may not produce the required results of reducing the energy supply gap due to a preference for solar and natural gas oils. It was also noteworthy that the need to build capacity to develop and maintain wind energy through critical, current infrastructure stance of the Ghanaian energy sector would not make this agenda of developing wind energy a reality. More so, it is important to note that the need to enhance the current weak national policy, financial backing and bridge technology gap for wind energy would be needful to realise a vibrant investment into wind energy development.

Assessment of the Wind Energy Potential of Two Burundian Sites

1-year hourly wind speed data from two Burundian stations, namely Bujumbura and Muyinga, have been processed in this work to bring an efficient help for the planning and installation of wind energy conversion systems (WECS) at those localities. Mean seasonal and diurnal variations of wind direction and wind shear exponent have been derived. Two-parameter Weibull probability density functions (PDFs) fitting the observed monthly and annual wind speed relative frequency distributions have been implemented. As shown through three complementary statistical tests, the fitting technique was very satisfactory. A wind resource analysis at 10 m above ground level (AGL) has led to a mean power density at Bujumbura which is almost thirteen fold higher than at Muyinga. The use of the empirical power law to extrapolate wind characteristics at heights from 150 to 350 m AGL has shown that energy potential of hilltops around Muyinga was only suitable for small, individual scale wind energy applications. At the opposite, wind energy potential of ridge-tops and hilltops around Bujumbura has been found suitable for medium and large scale electricity production. For that locality and at those heights, energy outputs and capacity factors (CF or Cf) have been computed for ten selected wind turbines (WTs), together with costs of electricity (COE) using the present value of cost (PVC) method. Amongst those WTs, YDF-1500-87 and S95-2.1 MW have emerged as the best options for installation owing to their highest CF and lowest COE. Moreover, an analysis of those two quantities at monthly basis for YDF-1500-87 WT has led to its best performance in the dry season. Compared to the average present COE of household hydroelectricity consumption, results of this study have evidenced economical feasibility and benefit of WECS setting in selected Burundian sites in order to supplement traditional electricity sources.