scholarly journals Performance Analysis of Renewable Energy Resources in Rural Areas: A Case Study of Solar Energy

2020 ◽  
Vol 39 (1) ◽  
pp. 1-12
Author(s):  
Jackson J. Justo ◽  
Aviti T. Mushi
Keyword(s):  
Power Generation ◽  
Rural Areas ◽  
Solar Power ◽  
Coastal Region ◽  
Solar Pv ◽  
Renewable Energy Resources ◽  
Solar Module ◽  
Storage Mechanism ◽  
Pv Systems

his paper presents an overview of the recent development trends of solar photovoltaic (PV) systems and the performance in the Tanzanian context. The two types of solar power generation that are considered in this paper are: i) solar PV systems and ii) concentrated solar power (CSP). The two are compared in terms of cost of energy and energy storage mechanism. Moreover, the effect of ambient temperature on the solar PV module is analyzed. In addition, a detailed analysis on using solar axis tracking to increase the power generation is also presented. The extent to which the cell surface temperature and orientation of the solar module which determine the power generation is modeled. Since Tanzania has the possibility to utilize the solar irradiance in the Coastal region to generate solar power, and therefore it is selected as the case study in this paper. 

Optimal allocation of solar PV systems in rural areas using genetic algorithms: a case study

2013 ◽  
Vol 6 (4) ◽  
pp. 301-306 ◽  
Author(s):  
M.H. Albadi ◽  
A.S. Al-Hinai ◽  
N.N. Al-Abri ◽  
Y.H. Al-Busafi ◽  
R.S. Al-Sadairi
Keyword(s):  
Genetic Algorithms ◽  
Rural Areas ◽  
Optimal Allocation ◽  
Solar Pv ◽  
Pv Systems

scholarly journals Development and sizing of a grid-connected solar PV power plant for Canaanland community

2019 ◽  
Vol 8 (1) ◽  
pp. 69
Author(s):  
Adeyemi A. Alabi ◽  
Anthony U. Adoghe ◽  
Oluwasikemi G. Ogunle ◽  
Claudius O. A Awosope
Keyword(s):  
Power Generation ◽  
Power Plant ◽  
Power Plants ◽  
Solar Power ◽  
Profile Analysis ◽  
Photovoltaic System ◽  
Solar Pv ◽  
Pv Systems ◽  
Solar Photovoltaic System ◽  
Storage Units

High costs of installation and maintenance as a result of storage units discourage the use of solar Photovoltaic system for power generation. To reduce these costs, Solar PV systems can be installed without storage units alongside conventional power generation systems. Such that the Solar systems cater for the daytime loads while the conventional generation system caters for loads at other times. This research paper explored the potential of installing Stand-Alone solar PV systems without storage to satisfy the daytime load demand of the Canaanland community. The load profile analysis of the Canaanland community was carried out from load consumption data and the solar power plants were designed based on this analysis. Simulation was carried out using the PV Syst 6.43 software and the result from the design was analyzed. The study revealed that the solar power plant will serve the daytime load of the community during the period of 10:30am-4:30pm daily satisfying the peak and base loads (5.16MW and 0.78MW) of the Canaanland community respectively.

Towards a labelling for green energy production units: Case study of off-grid solar PV systems

Energy ◽  
2020 ◽  
Vol 208 ◽  
pp. 118149
Author(s):  
Yao K. Azoumah ◽  
Alain K. Tossa ◽  
Rock A. Dake
Keyword(s):  
Energy Production ◽  
Green Energy ◽  
Solar Pv ◽  
Pv Systems

scholarly journals Assessment of Stand-Alone Residential Solar Photovoltaic Application in Sub-Saharan Africa: A Case Study of Gambia

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Sambu Kanteh Sakiliba ◽  
Abubakar Sani Hassan ◽  
Jianzhong Wu ◽  
Edward Saja Sanneh ◽  
Sul Ademi
Keyword(s):  
Life Cycle Cost ◽  
Meteorological Data ◽  
Developed Countries ◽  
Sub Saharan Africa ◽  
Solar Pv ◽  
Pv Systems ◽  
Photovoltaic Application ◽  
Sub Saharan ◽  
Electrical Demand

The focus of this paper is the design and implementation of solar PV deployment option, which is economical and easy to maintain for remote locations in less developed countries in Sub-Saharan Africa. The feasibility of stand-alone solar PV systems as a solution to the unstable electricity supply and as an alternative to the conventional resource, “diesel generators,” is presented. Moreover, a design of a system is carried out, such that the electrical demand and site meteorological data of a typical household in the capital, Banjul, is simulated. Likewise, the life cycle cost analysis to assess the economic viability of the system, along with the solar home performance, is also presented. Such system will be beneficial to the inhabitants of Gambia by ensuring savings in fuel costs and by reducing carbon emissions produced by generators. The selection of appropriate-sized components is crucial, as they affect the lifetime, reliability, and initial costs. The design presented in this study represents a solution for domestic houses to adopt the system according to the location and environment, in order to meet electricity demand.

Techno-economic feasibility study of autonomous hybrid wind and solar power systems for rural areas in Iran, A case study in Moheydar village

2015 ◽  
Vol 34 (5) ◽  
pp. 1521-1527 ◽  
Author(s):  
Abtin Ataei ◽  
Mojtaba Biglari ◽  
Mojtaba Nedaei ◽  
Ehsanolah Assareh ◽  
Jun-Ki Choi ◽  
...  
Keyword(s):  
Power Systems ◽  
Feasibility Study ◽  
Rural Areas ◽  
Solar Power ◽  
Economic Feasibility

scholarly journals Design and Implementation of Rural Electrification Framework using Photovoltaic

2020 ◽  
Vol 9 (5) ◽  
pp. 434-438
Keyword(s):  
Rural Areas ◽  
Rural Electrification ◽  
Solar Photovoltaic ◽  
Solar Pv ◽  
Pv System ◽  
Specific System ◽  
Policy Makers ◽  
Pv Systems ◽  
Design And Implementation ◽  
Solar Pv System

The need to electrify all rural areas in India is quite compelling. However, the focus has now shifted from traditional fuel-based systems to generate electricity to renewable sources for energy generation. Though there are subsidies and policies that encourage the use of solar Photovoltaic (PV) systems, there is a need for an appropriate framework. This framework could not only offer substantial directions but it would also act as grounds to enhance rural electrification in India using solar PVs. From this perspective, the current research attempts to structure an innovative framework for solar PV system that could facilitate rural electrification in India. In particular, the district of Damoh in Madhya Pradesh was chosen as there are many villages without electricity in this district. PVsyst software was utilized to simulate the outcomes that included mathematical models and diverse components based on PV, for simulation. Three designs were developed to facilitate the simulation. These included; PVs linked with microgrid devoid of battery, individual PV systems without microgrid link and solar PVs linked to microgrid with battey. The framework for rural electrification using solar PVs will offer policy makers with insights with regards to implementing PV systems. It will also offer inputs as to the feasibility of implementing a specific system on several parameters. These would comprise of; number of households within a village, detached households etc. Nonetheless, research in future is also warranted to explore the scope for other sources of renewable energy.

scholarly journals Analysis Of Solar Power Generation Forecasting Using Machine Learning Techniques

2021 ◽  
Vol 309 ◽  
pp. 01163
Author(s):  
K. Anuradha ◽  
Deekshitha Erlapally ◽  
G. Karuna ◽  
V. Srilakshmi ◽  
K. Adilakshmi
Keyword(s):  
Machine Learning ◽  
Power Generation ◽  
Random Forest ◽  
Regression Models ◽  
Solar Power ◽  
Machine Learning Techniques ◽  
Pv Systems ◽  
Solar Power Generation ◽  
Learning Techniques ◽  
Solar Power Forecasting

Solar power is generated using photovoltaic (PV) systems all over the world. Because the output power of PV systems is alternating and highly dependent on environmental circumstances, solar power sources are unpredictable in nature. Irradiance, humidity, PV surface temperature, and wind speed are only a few of these variables. Because of the unpredictability in photovoltaic generating, it’s crucial to plan ahead for solar power generation as in solar power forecasting is required for electric grid. Solar power generation is weather-dependent and unpredictable, this forecast is complex and difficult. The impacts of various environmental conditions on the output of a PV system are discussed. Machine Learning (ML) algorithms have shown great results in time series forecasting and so can be used to anticipate power with weather conditions as model inputs. The use of multiple machine learning, Deep learning and artificial neural network techniques to perform solar power forecasting. Here in this regression models from machine learning techniques like support vector machine regressor, random forest regressor and linear regression model from which random forest regressor beaten the other two regression models with vast accuracy.

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