A Review of Hybrid Renewable Energy Systems Based on Wind and Solar Energy: Modeling, Design and Optimization

In this chapter, an attempt is made to thoroughly review previous research work conducted on wind energy systems that are hybridized with a PV system. The chapter explores the most technical issues on wind drive hybrid systems and proposes possible solutions that can arise as a result of process integration in off-grid and grid-connected modes. A general introduction to wind energy, including how wind energy can be harvested, as well as recent progress and development of wind energy are discussed. With the special attention given to the issues related to the wind and photovoltaic (Wind-PV) systems. Throughout the chapter emphasis was made on modeling, design, and optimization and sensitivity analysis issues, and control strategies used to minimize risk as well as energy wastage. The reported reviewed results in this chapter will be a valuable researchers and practicing engineers involved in the design and development of wind energy systems

The Benefit and Importance of Mobile Satellite Signal in Northern Nigeria: GPS Approach

A Handheld GPS receiver as tool for training college students on mobile satellite signal propagation was designed using Global Positioning System (GPS) approach. These refer to the experimental setup of the equipment that is the connection done between the GPS receiver with a computer. The satellite propagation data received from the GPS satellite can be recorded continuously with an updates rate of 2 seconds. The experiment was carried out in an open space environment at predetermine locations using simple setup, where a cheap, readily and available portable GPS receiver were connected to the computer to acquire propagation data. The computer was equipped with a self-developed package graphical user interface (GUI) monitoring the propagation information from the GPS satellites and saving the data. The developed system can be set up anywhere at any location.  The sate-up will serve as a database for view and analysis of mobile satellite orbiting the sky of Northern part of Nigeria. Cost effective referring to a low-cost and readily available GPS receiver that can be easily set-up as compared to equipment designed specifically for an experimental purpose that is normally very expensive

Wind energy assessment and mapping using terrain nonlinear autoregressive neural network (TNARX) and wind station data

This paper presents the potential of generating wind power using soft computing model and ground station data. In reality, the process of wind resource assessment is to set up an experiment in the targeted locations, and measure the wind speed and direction. In this paper, a prediction model based on the terrain based neural network named terrain nonlinear autoregressive neural network (TNARX) is proposed to forecast the wind speed in the areas not covered by measurements using a ground station located nearby. The model has meteorological, physical and topographical as input, while the wind speed is the target variable. The suitability of the proposed model was judged using statistical measures. The paper shows characteristics of wind speed and the most prevailing wind directions. The variation of wind speed at 10–40 m heights was obtained and presented. Wind speed distribution modelling was carried out using five statistical models. It was found that Weibull and Gamma fits the wind speed of the studied areas. Wind power and energy density results show the areas falls within class 1, which is possible for harnessing energy content in wind for small scale purposes

Wind energy assessment and mapping using terrain nonlinear autoregressive neural network (TNARX) and wind station data

This paper presents the potential of generating wind power using soft computing model and ground station data. In reality, the process of wind resource assessment is to set up an experiment in the targeted locations, and measure the wind speed and direction. In this paper, a prediction model based on the terrain based neural network named terrain nonlinear autoregressive neural network (TNARX) is proposed to forecast the wind speed in the areas not covered by measurements using a ground station located nearby. The model has meteorological, physical and topographical as input, while the wind speed is the target variable. The suitability of the proposed model was judged using statistical measures. The paper shows characteristics of wind speed and the most prevailing wind directions. The variation of wind speed at 10–40 m heights was obtained and presented. Wind speed distribution modelling was carried out using five statistical models. It was found that Weibull and Gamma fits the wind speed of the studied areas. Wind power and energy density results show the areas falls within class 1, which is possible for harnessing energy content in wind for small scale purposes. © 2018 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license

Analysis of willingness to pay for carbon emission reduction by road users in northeastern Nigeria

This study investigates the willingness to pay for carbon reduction by road users in Northeastern Nigeria and addresses the lack of research on this topic in the region. A survey was conducted among 601 road users, and the data were analysed using descriptive and open-ended contingent valuation approach. The outcomes of the study showed that 65.7% of the surveyed road users were ready to pay for carbon offset, but at relatively low price point. However, 83% of the participants do not have experience on buying carbon emission. Additionally, 42.8% of the road users have a basic understanding of carbon offset program. The average open-ended willingness to pay for a carbon offset was found to be ₦100.73 per trip. The study recommends the need for a programme that will increase awareness and education to road users not only on carbon emission and climate change issues, but also on the importance of carbon offset programme for improving environmental sustainability of the region

Wind power generation via ground wind station and topographical feedforward neural network (T-FFNN) model for small-scale applications

This study presents the potential of harvesting wind energy in Sarawak, Malaysia based on the ground station and prediction models. A topographical feedforward neural network (T-FFNN) is proposed as an alternative to predict the wind speed in the areas where wind speed measurements are not done. The model has nine meteorological, geographical and topographical parameters as inputs while monthly winds speed as an output variable. The suitability of the model was assessed based on the mean absolute percentage error (MAPE). The most effective network design with lowest MAPE of 3.4% and correlation R between the predicted and the ground station wind speed of 0.91 was obtained. The study shows the characteristics of wind speed at 10–40 m heights. For the wind speed distribution, in addition to the widely applied Weibull and Rayleigh models, Gamma, Erlang and Lognormal are included. It was found that Gamma and Weibull outperform the others based on the three goodness-of-fit (GOF). An assessment of wind energy potential was performed using the measured and predicted wind speed data. The outcomes show that wind power density falls within class 1 (PD≤100 W/m2). Final results from micro-sitting investigating the performance of annual energy output (AEO) in the examined area are presented. The results indicate that the AEO differs with altitudes. In all the examined areas, the AEO values varied from about 5800–13,622 kWh/year. These results show the possibility of using wind energy for small-scale purpose

Wind energy potential in kuching areas of sarawak for small-scale power application

Energy is a catalyst for national development; most of the countries depend on hydrocarbon fuels for power generation. The traditional sources of energy are exorbitant and finite. In addition, they emit excessive carbon dioxide and other gases into the lower layer of the atmosphere, which influence the increase occurrence of global warming in the world. Recently, renewable energy's are gaining more attraction and attention in many parts of the globe, due to nonpolluting characteristics. Among the renewable, wind power has emerged as safest and cleanest resource that will satisfy the need of energy in a cost effective way. Wind energy system can suit the energy need for grid and stand-alone mode. This paper investigates the potential of wind energy in Kuching for small-scale power application. The study employed three years wind speed data spanning from 2010-2012 observed at the Kuching meteorological station. Details of the analysis carried out and potential of using wind energy systems are presented. Additionally, the output performances of two wind turbines are examined based on the computed Weibull distributio

Prevalence of anxiety and depression among the general population in Africa during the COVID-19 pandemic: a systematic review and meta-analysis

202205 bckwVersion of RecordOthersHong Kong Special Administrative Region Government; InnoHKPublishe