A Weibull and finite mixture of the von Mises distribution for wind analysis in Mersing,Malaysia

Studies of wind direction receive less attention than that of wind speed; however, wind direction affects daily activities such as shipping, the use of bridges, and construction. This research aims to study the effect of wind direction on generating wind power. A finite mixture model of the von Mises distribution and Weibull distribution are used in this paper to represent wind direction and wind speed data, respectively, for Mersing (Malaysia). The suitability of the distribution is examined by the R² determination coefficient. The energy analysis, that is, wind power density, only involves the wind speed, but the wind direction is vital in measuring the dominant direction of wind so that the sensor could optimize wind capture. The result reveals that the estimated wind power density is between 18.2 and 25 W/m², and SSW is the most common wind direction for this data.     

Wind power potential assessment for three buoys data collection stations in the Ionian Sea using Weibull distribution function

The present article utilizes wind measurements from three buoys data collection stations in Ionian Sea to study the wind speed and power characteristics using the Weibull shape and scale parameters. Specifically, the site dependent, annual, and monthly mean patterns of mean wind speed, Weibull parameters, frequency distribution, most probable wind speed, maximum energy carrying wind speed, wind power density and wind energy density characteristics have been analyzed. The Weibull distribution was found to represent the wind speed distribution with more than 90% accuracy, in most of the cases. Moreover, the correlation between the percentages of times the wind speed was above cut-in-speed and the measured mean wind speed for the three selected sites, as the correlation between the aforementioned percentages and the scale parameter c were examined and were found linear. At all these sites, no definite increasing or decreasing trends in annual mean wind speed values could be detective over the data reporting period. The mean values of wind speed, scale parameter, most probable wind speed, maximum energy carrying wind speed, wind power and wind energy density values showed higher values during winter time and lower in summer time in Pylos and Zakynthos. Moreover, Pylos and Zakynthos were found to be the best sites from wind power harnessing point of view.     

Wind energy potential assessment and techno-economic performance of wind turbines in coastal sites of Buenos Aires province,Argentina

An assessment of wind energy potential was carried out in five sites (four onshore and one offshore) in South-West (SW) of Buenos Aires province (Argentina). We use high-resolution wind data (2 and 5 min) for the period 2009–2012. The power law was used to estimate the wind speed at 30, 40, and 60 m height from the anemometer position. Turbulence intensity and wind direction were analyzed. Statistical analyses were conducted using two-parameter Weibull distribution. A techno-economic analysis based on a set of commercial wind turbines was performed in those sites. The results derived from this work indicate that the SW of Buenos Aires province represents a promising area for the wind energy extraction, which would encourage the construction of wind farms for electricity generation.     

Offshore wind power potential of the Black Sea region in Turkey

Majority of the studies on offshore wind power potential assessment is limited to the examination of the wind speed only. This study examines the offshore wind power potential of the Black Sea coastal region in Turkey based on location selection criteria including territorial waters, military areas, civil aviation, shipping routes, pipelines and underground cables, social, and environmental concerns. Wind Atlas Analysis and Application Program (WAsP) is used to do the statistical analysis of wind speed and wind direction data for 20 locations in the Black Sea coastal region. WAsP results are then elaborated based on the location selection criteria for better assessment of offshore wind power utilization. The study reveals that there are limited numbers of locations for offshore wind power generation in the Black Sea region in spite of its long coastline. Moreover, there is a high need for a zoning change for Amasra shores in order to utilize high offshore wind power potential of Amasra. Our finding suggests that location selection criteria other than wind speed should definitely be considered for better assessment of the wind power potential of a region.     

A stochastic approach for the operation of a wind and pumped storage plant under a deregulated environment

To improve the competiveness in the energy market, it is necessary that the wind power plants provide guaranteed power generation, although, it is not possible to forecast power availability from wind power plant accurately. This paper presents a stochastic model and solution technique for the combined operation of wind and pumped storage power plants to improve the power availability and increasing the profit considering uncertainties of wind power generation. In this model, uncertainties in wind data have been forecasted for grid connected day-ahead market using Weibull distribution model. The imbalances in the forecasted wind data and the market demand have been reduced by operating the pumped storage power plant. In this stochastic mixed integer problem, pumped storage plant can take the supply either from the grid or from the wind power plant for the pumping operation to store the energy in order to utilize this energy during peak hours for increasing the overall revenue. The reliability of the pumped storage is improved by replacing the conventional unit with the adjustable speed type pumped storage unit. In order to prove the optimality of the solution, two case studies were considered. In case study–I, scheduling is provided by operating the conventional pumped storage unit, whereas in case study–II, adjustable speed pumped storage unit has been used. It has been found that the adjustable speed pumped storage unit has further reduced the imbalance between generated power and demand. The complete approach has been formulated and implemented using AMPL software.     

A wind-solar PV hybrid power system with battery backup for water pumping in remote localities

After energy, water is the most critical commodity to be made available to people to keep them alive. Saudi Arabia has vast land and people are living in all regions. Most of these are connected to national grid but some are not, especially in remote areas like in the north, south, and west south. Pumping water in remote areas for domestic needs like agriculture and animals beside human needs is essential and require regular power supply. The present idea of wind-PV-Battery hybrid power system based on 100% renewable source is being proposed to utilize and tested in some of the regions on experimental bases. Of the five locations chosen for the purpose, namely Dhahran, Riyadh, Jeddah, Guriat and Nejran, some are good from both wind and solar intensity point of view some have good winds only and some good solar only. Nearly optimal size of PV-Wind water pumping system is determined for each of these sites considering the availability of solar and wind energy distributions throughout the year in these sites. It is shown that the monthly total water pumping capacity when using nearly optimal PV-Wind water pumping system is fairly uniform throughout the year except for the sites of Guriat and Riyadh. In these sites higher water pumping capacity is observed during the spring and summer months. On the other hand the cost of underground water pumping is found to vary between 6 to 12 US¢/m³ for the five sites considered.     

A novel wind speed forecasting model for wind farms of Northwest China

Wind resources are becoming increasingly significant due to their clean and renewable characteristics, and the integration of wind power into existing electricity systems is imminent. To maintain a stable power supply system that takes into account the stochastic nature of wind speed, accurate wind speed forecasting is pivotal. However, no single model can be applied to all cases. Recent studies show that wind speed forecasting errors are approximately 25% to 40% in Chinese wind farms. Presently, hybrid wind speed forecasting models are widely used and have been verified to perform better than conventional single forecasting models, not only in short-term wind speed forecasting but also in long-term forecasting. In this paper, a hybrid forecasting model is developed, the Similar Coefficient Sum (SCS) and Hermite Interpolation are exploited to process the original wind speed data, and the SVM model whose parameters are tuned by an artificial intelligence model is built to make forecast. The results of case studies show that the MAPE value of the hybrid model varies from 22.96% to 28.87 %, and the MAE value varies from 0.47 m/s to 1.30 m/s. Generally, Sign test, Wilcoxon’s Signed-Rank test, and Morgan--Granger--Newbold test tell us that the proposed model is different from the compared models.     

Nonlinear control of a wind turbine based on nonlinear estimation techniques for maximum power extraction

This work proposes nonlinear estimators with nonlinear controllers, for variable speed wind turbine (VSWT) considering that either the wind speed measurement is not available or not accurate. The main objective of this work is to maximize the energy capture from the wind and minimizes the transient load on the drive train. Controllers are designed to adjust the generated torque for maximum power output. Estimation of effective wind speed is required to achieve the above objectives. In this work the estimation of effective wind speed is done by using the Modified Newton Rapshon (MNR), Neural Network (NN) trained by different training algorithms and nonlinear time series based estimation. Initially the control strategies applied was the classical ATF (Aerodynamic torque feed forward) and ISC (Indirect speed control), however due their weak performance and unmodeled WT disturbances, nonlinear static and dynamic feedback linearization techniques with the above wind speed estimators are proposed.     

A GIS-based technique for linking landscape characteristics to non-point source nitrogen export potential: implications for contributing areas management

A Nitrate-N Leaching Index (NLI) is calculated and the results indicate that nitrogen loss in the study area occurs through both leaching and surface runoff. A non-linear regression model of trapping efficiency was combined with a first order decay model to examine the impact of soil characteristics, slope, vegetative cover, land use and distance to streams on the spatial pattern of non-point source nitrogen inputs to streams. The model evaluates the statistical significance of each landscape factor and provides an easy interpretation of the landscape delivery ratio of nitrogen based on a pixel-based characterisation of the watershed. The model was validated by comparing the distributions of the observed and estimated monthly nitrogen concentrations. The exploratory GIS-based method presented here can improve the understanding of the impact of landscape characteristics on nitrate-nitrogen contributing areas and therefore assist watershed management efforts.     

A hybrid model based on smooth transition periodic autoregressive and Elman artificial neural network for wind speed forecasting of the Hebei region in China

Wind energy, one of the most promising renewable and clean energy sources, is becoming increasingly significant for sustainable energy development and environmental protection. Given the relationship between wind power and wind speed, precise prediction of wind speed for wind energy estimation and wind power generation is important. For proper and efficient evaluation of wind speed, a smooth transition periodic autoregressive (STPAR) model is developed to predict the six-hourly wind speeds. In addition, the Elman artificial neural network (EANN)-based error correction technique has also been integrated into the new STPAR model to improve model performance. To verify the developed approach, the six-hourly wind speed series during the period of 2000–2009 in the Hebei region of China is used for model construction and model testing. The proposed EANN-STPAR hybrid model has demonstrated its powerful forecasting capacity for wind speed series with complicated characteristics of linearity, seasonality and nonlinearity, which indicates that the proposed hybrid model is notably efficient and practical for wind speed forecasting, especially for the Hebei wind farms of China.     

Economic and employment impacts of offshore wind for Ireland: A value chain analysis

ABSTRACT

The imminent development of a number of offshore wind farms in the Republic of Ireland presents a sizable opportunity to stimulate the Irish economy through the growth of an indigenous and globally competitive offshore wind supply chain. This study uses a value chain analysis to evaluate the economic and employment potential of the offshore wind sector for Ireland. The analysis is based on the expenditure on products and services required to develop an offshore wind farm, the planned capacity of projects in the pipeline, and the ability of Irish companies to supply the sector. Results suggest that by 2030, 2.5–4.5GW of domestic offshore wind development could create between 11,424 and 20,563 supply chain jobs and generate between €763 m and €1.4bn in gross value added. This is the first study to estimate domestic GVA potential for the sector.     

Energy production and sustainability: A study of Belo Monte hydroelectric power plant

The increase in energy demand due to economic and population growth necessitates the expansion of the Brazilian energy supply. Hydropower energy, a renewable energy source, arguably clean, presents an energy solution for many countries such as Brazil, with large hydric reservoirs, which help them reduce energy dependence on fossil and imported fuel sources. However, it must be emphasized that without careful planning, the creation of hydropower plants will cause severe social and environmental damage due to the large areas that need to be flooded for the implementation of these plants. The installation of hydropower plants floods vast forest areas, causing loss of biodiversity, displacement of native Brazilian people and riverside populations, and changes to the water acid levels and the natural course of rivers. To mitigate these effects, authorities must first conduct a study on installation possibilities and potential socio‐environmental consequences, to be interpreted and used by the agents involved. Aiming to analyze the social‐environmental impacts of the hydropower plants, this research seeks to investigate the capacity of mitigation of the negative effects of the implementation of the hydropower plants, specifically with regard to the Belo Monte plant, Brazil.     

An economic and environmental assessment of carbon capture and storage (CCS) power plants: a case study for the City of Kiel

In the not too distant future several power plants throughout Europe will have to be replaced and the decision has to be made whether to build coal-fired power plants with carbon capture and storage (CCS). In a study for the city of Kiel in northern Germany only an 800 MW coal power plant reaches a required minimum for rentability. This study looks at an additional economic and environmental evaluation of a coal plant with CCS. We find that in two out of three carbon and energy price scenarios integrated gasification combined cycle (IGCC) plants with CCS have the greatest rentability. Pulverised coal (PC) plants with CCS can only compete with other options under very favourable assumptions. Life-cycle emissions from CCS are less than 70% of a coal plant – compared with at least more than 80% when only considering direct emissions from plants. However, life-cycle emissions are lower than in any other assessed option.     

A well to wire LCA model development and sensitivity analysis for carbon footprint of combined cycle power plants in Iranian electricity network

The present research introduces a well to wire pseudo comprehensive carbon footprint model for combined cycle power plants. The mentioned model integrates land use change model, operational model and transmission and distribution model into one comprehensive model. The parameters which their effects are considered in the integrated model are: fuel type, fuel transmission type, emission for fuel extraction and processing, own consumption of the plant, degradation, site ambient condition, transmission and distribution losses. For quantifying the effectiveness of each parameter, sensitivity analyses based on different life cycle scenarios are performed. The result shows that the effect of land use change is negligible. The carbon footprint of electrical energy produced in combined cycle plant until it is delivered to the end users varies from 321 to 522 g CO₂ eq/kWh.     

Water quality indices appraisal and health risk assessment of nitrate,mercury and lead in water distribution network: A case study of Robat Karim in Tehran,Iran

Groundwater is a basic source of drinking water supply for urban and rural areas. This is especially the case for communities located in arid and semi-arid regions that rely on groundwater for drinking purposes. The present study set out to assess the potential health impacts of water impurities and to investigate the qualitative status of drinking water in Robat Karim rural areas, located in southwest Tehran, Iran. A total of 66 samples were collected from the water distribution network of 11 villages (33 sampling points, on two occasions) during September 2020 and were tested in terms of the most common quality parameters such as pH, mercury (Hg), lead (Pb), copper (Cu), zinc (Zn), chloride (Cl^–), chlorate (ClO₃^–), nitrite (NO₂^–), nitrate (NO₃^–), and flouride (F^–). Multiple methods and indexes including water quality index (WQI), hazard quotient (HQ), and hazard index (HI), were worked out to assess the quality of water and health risk assessment of NO₃^– Pb²⁺ and Hg²⁺. The results revealed that 33% and 90% of sampling sites have significantly high nitrate and total hardness (TH) concentrations, exceeding the maximum permissible limits set by World Health Organization (WHO; 50 and 200 mg/L, respectively). Furthermore, five sampling points exhibited poor WQIs mainly related to NO₃^– and TH. HQ values higher than 1 for nitrate were noticed in most sampling locations. Except for one sampling point, the HQ obtained for Pb²⁺ and Hg²⁺ were below 1 indicating no obvious health hazard. This study represents that children and infants are at higher risk of chronic toxicity by excess NO₃^– intake. The health hazard that is yet imposed on the community by NO₃^– necessitates regular monitoring of drinking water, the use of advanced technologies to purify water or otherwise alternative resources should be proposed.