scholarly journals Multi-criteria assessment of potential regions for wind power generation in the State of Rio de Janeiro

2020 ◽  
Vol 27 (3) ◽  
Author(s):  
Elias Rocha Gonçalves Júnior ◽  
Igor Cassiano Rangel ◽  
Allysson Rodrigues Teixeira Tavares ◽  
Elias Gomes Figueira Júnior ◽  
Milton Erthal Junior ◽  
...  

Abstract: Due to the current climatic conditions and concerns about the energy generation by renewable sources, wind energy becomes an alternative to meet the existing energy demand. This paper aims to analyze the most promising regions of the State of Rio de Janeiro for the implementation of wind farms for electricity generation. As an analysis tool, we intend to use the Analytic Hierarchy Process (AHP), due to its practicality, to assist in the state’s wind power atlas regions evaluation, identifying generating farms installation feasibility based on logistical, technical and economic aspects. Three suitable regions for wind farms installation were evaluated according to the following criteria: potencial for generation, land cost, interconnection cost to the grid, implementing zones e terrain-landform logistics. It was found that, for the Serrana Region, it is indicated the installation of a wind farm that operates at 50 meters in height, because it only has enough potential for equipment with this height. In the Lakes Region, it is appropriate to use wind turbines of 75 meters in height, highlighting it as the most promising for this equipment height, besides having the best logistics capacity of the three regions. Because it has a greater potential area than the other, the North Region provides a greater total production, also taking into account its greater efficiency in the aerogenerators to 100 meters of height, considering this region as the most appropriate. It is worth highlighting that, in this region, there is potential for installation in all the heights presented, scrutinizing the results obtained.

2014 ◽  
Vol 672-674 ◽  
pp. 361-366
Author(s):  
Ya Di Luo ◽  
Jing Li ◽  
Zi Ming Guo ◽  
Gui Rong Shi ◽  
Dong Sheng Wang ◽  
...  

According to the characteristics of the wind farm measuration and the impact of bad data on the state estimation, this paper introduces the reference value of measurement type and the bad data reference factor into the weight function, and then presents the calculation method of state estimation method for solving residual contamination problem caused by large-scale wind power integration. In order to improve the software computing speed and the data section real-time performance of robust state estimation, using parallel algorithms to do Givens transformation. Finally, the simulation tests of a regional power grid to prove that the proposed method can effectively identify telemetry bad data of wind farms eliminate residual pollution caused by it, which improve the speed and accuracy of the State Estimation.


Author(s):  
Nick Jelley

‘Wind power’ focuses on wind-based power and its potential as a renewable energy source. Single wind turbines, both large and small, can be used to provide power to homes or a community. Wind turbines for large power generation are usually deployed in wind farms, which are arrays of turbines. These are located in regions where the wind conditions are good, such as exposed ridges, high-altitude plains, mountain passes, coastal areas, and out at sea. Wind power produces essentially no global warming nor any pollution; only a small amount of associated carbon dioxide emissions from the fossil fuels used in the construction and operation of the wind farms. And it takes less than a year for a wind farm to generate the same amount of energy used in its manufacture. The sharp fall in the cost of electricity from wind farms, corresponding to a 20 per cent learning rate over the last decade, is such that onshore wind farms have now achieved cost competitiveness (grid-parity) with fossil-fuel-fired generators. By 2050, it is estimated that about a seventh of the world’s energy demand could be met by wind power.


Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4291
Author(s):  
Paxis Marques João Roque ◽  
Shyama Pada Chowdhury ◽  
Zhongjie Huan

District of Namaacha in Maputo Province of Mozambique presents a high wind potential, with an average wind speed of around 7.5 m/s and huge open fields that are favourable to the installation of wind farms. However, in order to make better use of the wind potential, it is necessary to evaluate the operating conditions of the turbines and guide the independent power producers (IPPs) on how to efficiently use wind power. The investigation of the wind farm operating conditions is justified by the fact that the implementation of wind power systems is quite expensive, and therefore, it is imperative to find alternatives to reduce power losses and improve energy production. Taking into account the power needs in Mozambique, this project applied hybrid optimisation of multiple energy resources (HOMER) to size the capacity of the wind farm and the number of turbines that guarantee an adequate supply of power. Moreover, considering the topographic conditions of the site and the operational parameters of the turbines, the system advisor model (SAM) was applied to evaluate the performance of the Vestas V82-1.65 horizontal axis turbines and the system’s power output as a result of the wake effect. For any wind farm, it is evident that wind turbines’ wake effects significantly reduce the performance of wind farms. The paper seeks to design and examine the proper layout for practical placements of wind generators. Firstly, a survey on the Namaacha’s electricity demand was carried out in order to obtain the district’s daily load profile required to size the wind farm’s capacity. Secondly, with the previous knowledge that the operation of wind farms is affected by wake losses, different wake effect models applied by SAM were examined and the Eddy–Viscosity model was selected to perform the analysis. Three distinct layouts result from SAM optimisation, and the best one is recommended for wind turbines installation for maximising wind to energy generation. Although it is understood that the wake effect occurs on any wind farm, it is observed that wake losses can be minimised through the proper design of the wind generators’ placement layout. Therefore, any wind farm project should, from its layout, examine the optimal wind farm arrangement, which will depend on the wind speed, wind direction, turbine hub height, and other topographical characteristics of the area. In that context, considering the topographic and climate features of Mozambique, the study brings novelty in the way wind farms should be placed in the district and wake losses minimised. The study is based on a real assumption that the project can be implemented in the district, and thus, considering the wind farm’s capacity, the district’s energy needs could be met. The optimal transversal and longitudinal distances between turbines recommended are 8Do and 10Do, respectively, arranged according to layout 1, with wake losses of about 1.7%, land utilisation of about 6.46 Km2, and power output estimated at 71.844 GWh per year.


2021 ◽  
pp. 0309524X2110438
Author(s):  
Carlos Méndez ◽  
Yusuf Bicer

The present study analyzes the wind energy potential of Qatar, by generating a wind atlas and a Wind Power Density map for the entire country based on ERA-5 data with over 41 years of measurements. Moreover, the wind speeds’ frequency and direction are analyzed using wind recurrence, Weibull, and wind rose plots. Furthermore, the best location to install a wind farm is selected. The results indicate that, at 100 m height, the mean wind speed fluctuates between 5.6054 and 6.5257 m/s. Similarly, the Wind Power Density results reflect values between 149.46 and 335.06 W/m2. Furthermore, a wind farm located in the selected location can generate about 59.7437, 90.4414, and 113.5075 GWh/y electricity by employing Gamesa G97/2000, GE Energy 2.75-120, and Senvion 3.4M140 wind turbines, respectively. Also, these wind farms can save approximately 22,110.80, 17,617.63, and 11,637.84 tons of CO2 emissions annually.


2013 ◽  
Vol 336-338 ◽  
pp. 1114-1117 ◽  
Author(s):  
Ying Zhi Liu ◽  
Wen Xia Liu

This paper elaborates the effect of wind speed on the output power of the wind farms at different locations. It also describes the correction of the power curve and shows the comparison chart of the standard power curve and the power curve after correction. In China's inland areas, wind farms altitude are generally higher, the air density is much different from the standard air density. The effect of air density on wind power output must be considered during the wind farm design.


Check List ◽  
2010 ◽  
Vol 6 (3) ◽  
pp. 432
Author(s):  
João Luiz Gasparini ◽  
Diogo Andrade Koski ◽  
Pedro L.V. Peloso

We present the first record of Urostrophus vautieri for the state of Espírito Santo and a distribution map for the species. This species was previoulsy known from the states of Minas Gerais, Rio de Janeiro, São Paulo, Paraná, Santa Catarina, and Rio Grande do Sul. The present record represent an extension of nearly 200 km to the North from the nearest published record for the species.


2013 ◽  
Vol 772 ◽  
pp. 619-621
Author(s):  
Zi Wei Bai

Advantages of wind power are self-evident, but the impact of wind power project on the local ecological environment and natural landscape is also increasingly subject to public attention. It mainly reflects in the visual pollution of the wind turbine (or natural landscape problems), noise, bird safety and electromagnetic interference. The paper analyzed the impact of wind farms on the environment, and recommended appropriate preventions and control measures to reduce it to an acceptable level.


2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Lihui Guo ◽  
Hao Bai

With the increasing penetration of wind power, the randomness and volatility of wind power output would have a greater impact on safety and steady operation of power system. In allusion to the uncertainty of wind speed and load demand, this paper applied box set robust optimization theory in determining the maximum allowable installed capacity of wind farm, while constraints of node voltage and line capacity are considered. Optimized duality theory is used to simplify the model and convert uncertainty quantities in constraints into certainty quantities. Under the condition of multi wind farms, a bilevel optimization model to calculate penetration capacity is proposed. The result of IEEE 30-bus system shows that the robust optimization model proposed in the paper is correct and effective and indicates that the fluctuation range of wind speed and load and the importance degree of grid connection point of wind farm and load point have impact on the allowable capacity of wind farm.


2013 ◽  
Vol 860-863 ◽  
pp. 1909-1913
Author(s):  
Hai Xiang Xu ◽  
Peng Wang ◽  
Xiao Meng Ren

At present, the technology of wind power forecasting isn‘t mature enough in china, so some grid-connected wind farms will be assessed when theirs power forecasting accuracy cant reach the assessment standard. In response to the situation, combined with the characteristics of WPSPS and wind farms, this paper designs a service mechanism that WPSPS help wind farms tracking generation schedule curve, namely, encouraging WPSPS to supply output compensation service for wind farm by market means to increase the accuracy of wind power forecasting. By this mechanism, not only WPSPS and wind farms will achieve win-win, but also the impact on the grid caused by fluctuations of wind powers output will reduce.


2014 ◽  
Vol 536-537 ◽  
pp. 470-475
Author(s):  
Ye Chen

Due to the features of being fluctuant, intermittent, and stochastic of wind power, interconnection of large capacity wind farms with the power grid will bring about impact on the safety and stability of power systems. Based on the real-time wind power data, wind power prediction model using Elman neural network is proposed. At the same time in order to overcome the disadvantages of the Elman neural network for easily fall into local minimum and slow convergence speed, this paper put forward using the GA algorithm to optimize the weight and threshold of Elman neural network. Through the analysis of the measured data of one wind farm, shows that the forecasting method can improve the accuracy of the wind power prediction, so it has great practical value.


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