Solar power and policy powerlessness − perceptions of persuasion in distributed residential solar energy policy development

Abstract Developing nations have a critical need to increase electricity supply. Sudan has much unrealized potential for generating solar energy, particularly in the northern region. This research study focuses on designing a 1-GW solar power station in northern Sudan using the PVsyst7.0 software program. To determine the appropriate location for the solar-energy station, 14 criteria were evaluated. This process is generic and suitable for use in any other country. The method for conducting cash-flow estimates and return on investment is illustrated in the economic evaluation. The city of Dongola, the capital of the northern state, was selected because of its high annual irradiance on a horizontal surface at ~2333.2 kWh/m2. The simulation results show that the annual optimum tilt angle of inclination for photovoltaic (PV) modules is 30°, the energy production is 1 979 259 MWh/yr and the average annual performance rate is 0.810. In addition, the electric power consumption per capita in Sudan is 269 kWh/yr, so the proposed solar power plant with 1 979 259 MWh/yr can provide energy to 7.4 million people per year annually and reduce carbon emissions by ~18 million tons of carbon dioxide per year. Economic calculations show that the levelized cost of electricity (LCOE) is $0.06/kWh, the discounted payback period is ~11 years and the net present value is $635 291 000. As a result, the proposed grid-connected PV solar plant is considered economically, technically and environmentally feasible in Sudan.

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Weather-Driven Scenario Analysis for Decommissioning Coal Power Plants in High PV Penetration Grids

Energies ◽

10.3390/en14092389 ◽

2021 ◽

Vol 14 (9) ◽

pp. 2389

Author(s):

Samuel Matthew G. Dumlao ◽

Keiichi N. Ishihara

Keyword(s):

Solar Energy ◽

Scenario Analysis ◽

Power Plants ◽

Solar Power ◽

Flow Analysis ◽

Policy Decision ◽

Hourly Temperature ◽

Coal Power Plants ◽

Coal Power ◽

Pv Penetration

Despite coal being one of the major contributors of CO2, it remains a cheap and stable source of electricity. However, several countries have turned to solar energy in their goal to “green” their energy generation. Solar energy has the potential to displace coal with support from natural gas. In this study, an hourly power flow analysis was conducted to understand the potential, limitations, and implications of using solar energy as a driver for decommissioning coal power plants. To ensure the results’ robustness, the study presents a straightforward weather-driven scenario analysis that utilizes historical weather and electricity demand to generate representative scenarios. This approach was tested in Japan’s southernmost region, since it represents a regional grid with high PV penetration and a fleet of coal plants older than 40 years. The results revealed that solar power could decommission 3.5 GW of the 7 GW coal capacity in Kyushu. It was discovered that beyond 12 GW, solar power could not reduce the minimum coal capacity, but it could still reduce coal generation. By increasing the solar capacity from 10 GW to 20 GW and the LNG quota from 10 TWh to 28 TWh, solar and LNG electricty generation could reduce the emissions by 37%, but the cost will increase by 5.6%. Results also show various ways to reduce emissions, making the balance between cost and CO2 a policy decision. The results emphasized that investing in solar power alone will not be enough, and another source of energy is necessary, especially for summer and winter. The weather-driven approach highlighted the importance of weather in the analysis, as it affected the results to varying degrees. The approach, with minor changes, could easily be replicated in other nations or regions provided that historical hourly temperature, irradiance, and demand data are available.

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Predicting the Performance of Solar Power Generation Using Deep Learning Methods

Applied Sciences ◽

10.3390/app11156887 ◽

2021 ◽

Vol 11 (15) ◽

pp. 6887

Author(s):

Chung-Hong Lee ◽

Hsin-Chang Yang ◽

Guan-Bo Ye

Keyword(s):

Power Generation ◽

Solar Energy ◽

Power Output ◽

Power Plants ◽

Solar Power ◽

Photovoltaic Cell ◽

Power Prediction ◽

Seasonal Characteristics ◽

Variable Nature ◽

Solar Power Plants

In recent years, many countries have provided promotion policies related to renewable energy in order to take advantage of the environmental factors of sufficient sunlight. However, the application of solar energy in the power grid also has disadvantages. The most obvious is the variability of power output, which will put pressure on the system. As more grid reserves are needed to compensate for fluctuations in power output, the variable nature of solar power may hinder further deployment. Besides, one of the main issues surrounding solar energy is the variability and unpredictability of sunlight. If it is cloudy or covered by clouds during the day, the photovoltaic cell cannot produce satisfactory electricity. How to collect relevant factors (variables) and data to make predictions so that the solar system can increase the power generation of solar power plants is an important topic that every solar supplier is constantly thinking about. The view is taken, therefore, in this work, we utilized the historical monitoring data collected by the ground-connected solar power plants to predict the power generation, using daily characteristics (24 h) to replace the usual seasonal characteristics (365 days) as the experimental basis. Further, we implemented daily numerical prediction of the whole-point power generation. The preliminary experimental evaluations demonstrate that our developed method is sensible, allowing for exploring the performance of solar power prediction.

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Will Strategy Prevail over Economics? An Analysis of Charanka Solar Park in Gujarat

South Asian Journal of Business and Management Cases ◽

10.1177/2277977916665978 ◽

2016 ◽

Vol 5 (2) ◽

pp. 162-167

Author(s):

Saif Siddiqui ◽

Sumaira Jan

Keyword(s):

Solar Energy ◽

Solar Power ◽

Power Production ◽

Energy Crisis ◽

Energy Sources ◽

Potential Source ◽

The World ◽

Made In

The Charanka Solar Park, one of the world’s largest multi-developer and multi-beneficiary solar parks, is the hub of solar power production in India. It contributes about 6 per cent to the total solar power production in the country. Although solar power is more expensive than the traditional power in the country, its sheen is still not high to make it a potential source to eliminate energy crisis not just in India but all across the world. Researchers are continuously pushing their envelope to explore as to why solar energy should be adopted over traditional energy sources irrespective of the fact that it is more expensive. The war between its financial and strategic viability is going on. Efforts are being made in the direction of reducing its costs and making it as a financially viable and strategically active option. This case is an attempt in the same direction. We are using Charanka Solar Park as a base to explore if there is any future for such projects in the country. There are projects which are no doubt operational but their long-term viability is truly questionable.

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Short Time Solar Power Forecasting Using Persistence Extreme Learning Machine Approach

E3S Web of Conferences ◽

10.1051/e3sconf/202129401002 ◽

2021 ◽

Vol 294 ◽

pp. 01002

Author(s):

Xiaoyan Xiang ◽

Yao Sun ◽

Xiaofei Deng

Keyword(s):

Solar Energy ◽

Extreme Learning Machine ◽

Power Output ◽

Smart Grids ◽

Large Scale ◽

Solar Power ◽

Learning Algorithm ◽

Power Performance ◽

Energy Prediction ◽

Learning Machine

Solar energy in nature is irregular, so photovoltaic (PV) power performance is intermittent, and highly dependent on solar radiation, temperature and other meteorological parameters. Accurately predicting solar power to ensure the economic operation of micro-grids (MG) and smart grids is an important challenge to improve the large-scale application of PV to traditional power systems. In this paper, a hybrid machine learning algorithm is proposed to predict solar power accurately, and Persistence Extreme Learning Machine(P-ELM) algorithm is used to train the system. The input parameters are the temperature, sunshine and solar power output at the time of i, and the output parameters are the temperature, sunshine and solar power output at the time i+1. The proposed method can realize the prediction of solar power output 20 minutes in advance. Mean absolute error (MAE) and root-mean-square error (RMSE) are used to characterize the performance of P-ELM algorithm, and compared with ELM algorithm. The results show that the accuracy of P-ELM algorithm is better in short-term prediction, and P-ELM algorithm is very suitable for real-time solar energy prediction accuracy and reliability.

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Tilt Angle Optimization and Formulation of Annual Adjustment Models for a Solar Power Plant Setup-able Site at Himachal Pradesh, India

International Journal of Innovative Technology and Exploring Engineering - Special Issue ◽

10.35940/ijitee.g5835.059720 ◽

2020 ◽

Vol 9 (7) ◽

pp. 1181-1185

Keyword(s):

Power Plant ◽

Solar Energy ◽

Tilt Angle ◽

Solar Power ◽

Performance Enhancement ◽

Diffuse Radiation ◽

Himachal Pradesh ◽

Solar Power Plant ◽

Solar Tracking ◽

Tracking Devices

Solar tracking devices are quite effective for collecting maximum solar radiations but for vastly spread solar energy collection plant, their usage is suppressed due to large cost involvement. The best alternative to this problem is adjustment of tilt angle at most appropriate position. In this study monthly optimum tilt angle have been identified for a solar power plant setup-able site Kalth (φ 30.85046˚, L 77.06153˚), situated at Himachal Pradesh, India. For diffuse radiation estimation, an isotropic model has been used. By considering the impracticality involved in monthly tilt angle adjustment, various annual adjustment models have been formulated for two, three and four annual adjustments. In order to estimate the increment in solar insolation by adopting these models, Performance Enhancement (PE) have been computed from the conventional method of setting the solar collector tilt equal to latitude angle. The results show that PE is maximum for monthly optimum tilt angles followed by M-4 which is a three annual adjustment model. Based on PE requirement, any of the proposed models can be selected for setting up solar energy collection plant at suggested site.

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Photovoltaic power generation system

Materials Science Materials Review ◽

10.18063/msmr.v1i1.503 ◽

2018 ◽

Vol 1 (1) ◽

Author(s):

Huang Huanhai

Keyword(s):

Power Generation ◽

Renewable Energy ◽

Solar Energy ◽

Social Life ◽

Fossil Fuels ◽

Solar Power ◽

Environmentally Friendly ◽

Energy Status ◽

The World ◽

New Energy

The potential crisis of energy and the deterioration of ecological environment make the world's cumbersomedevelopment of renewable energy including new energy, including solar energy. Traditional energy in the coal, oil andnatural gas are evolved from ancient fossils, it is collectively referred to as fossil fuels. As the world's energy needscontinue to increase, fossil fuels will also be depleted, it is necessary to fi nd a new energy to replace the traditionalenergy. Solar energy is a clean renewable energy with mineral energy incomparable superiority. Modern society shouldbe a conservation-oriented society, and social life should also be a life-saving energy. At the same time, Premier WenJiabao also proposed on June 30, 2005 and stressed the need to speed up the construction of a conservation-orientedsociety. And solar energy as an inexhaustible new environmentally friendly energy has become the world's energyresearch work in the world an important issue. Is the world in the economic situation to take a simpler, economical,environmentally friendly and reliable building heating and heating energy-saving measures. This paper summarizes thecurrent global energy status, indicating the importance of solar power and prospects. Details of the various solar powergeneration methods and their advantages, and made a comparison of this power generation parameters. At the sametime pointed out that the diffi culties faced by solar power and solutions, as well as China's solar power of the favorableconditions and diffi culties. The future of China's solar energy made a prospect.

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Photovoltaics: solar energy resources and the possibility of their use

Ecological Chemistry and Engineering S ◽

10.1515/eces-2016-0001 ◽

2016 ◽

Vol 23 (1) ◽

pp. 9-32

Author(s):

Tadeusz Rodziewicz ◽

Aleksander Zaremba ◽

Maria Wacławek

Keyword(s):

Energy Storage ◽

Solar Energy ◽

Power Plants ◽

Solar Power ◽

Power Industry ◽

Energy Resources ◽

Photovoltaic Power ◽

New Ideas ◽

World Records

Abstract In this paper possibilities and limits of use of solar energy (like the best efficiencies of PV cells, world records and ‘notable exceptions’) were shown. Also some new ideas and concepts in photovoltaics (like new photovoltaic power plants or energy storage) were presented. Additionally authors try to predict development of solar power industry.

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ASSESSMENT OF SURFACE DOWNWELLING SHORTWAVE RADIATION IN 2021-2050 IN LAAYOUNE − SAKIA EL HAMRA REGION, MOROCCO

EUREKA Physics and Engineering ◽

10.21303/2461-4262.2019.00863 ◽

2019 ◽

Vol 2 ◽

pp. 23-29

Author(s):

Youssef El Hadri ◽

Valeriy Khokhlov ◽

Mariia Slizhe ◽

Kateryna Sernytska ◽

Kateryna Stepanova

Keyword(s):

Solar Energy ◽

Spatial Resolution ◽

Cloud Cover ◽

Power Plants ◽

Solar Power ◽

Regional Climate ◽

Energy Resources ◽

Shortwave Radiation ◽

Total Cloud Cover ◽

Solar Power Plants

Morocco's energy system is highly dependent on external energy markets. According to the Ministry Energy, Mines and Sustainable Development today more than 93 % of energy resources are imported to Morocco. In 2008 the Moroccan Government has developed a National Energy Strategy, and one of its priority areas is to increase the share of renewable technologies in the country's energy sector. Morocco is rich in solar energy resources. Studies on the assessment of the Morocco’s solar energy potential indicate, among other benefits, low additional costs when using solar installations compared to losses associated with the solution of future climate problems and lack of resources. The plan envisages the commissioning of solar power plants in Ouarzazate, Ain Ben Mathar, Boujdour, Tarfaya and Laayoune by 2020. The aim of this research is determination of the characteristics of the distribution of Surface Downwelling Shortwave Radiation in the area of the solar power Boujdour, Tarfaya and Laayoune, located in the Laayoune − Sakia El Hamra region in 2021−2050. The data from regional climate modeling with high spatial resolution of the CORDEX-Africa project are used in this research. The RCM modeling is carried out for the region of Africa, in a rectangular coordinate system with a spatial resolution of ~ 44 km. Then, from the modeling data, values are highlighted for the territory of Laayoune − Sakia El Hamra region. Model calculation is performed taking into account the greenhouse gas concentration trajectory of RCP 4.5 calculated using 11 regional climate models. As a result of the simulation for the period 2021−2050, average monthly values of the Surface Downwelling Shortwave Radiation "RSDS" (W/m2) are derived, on the basis of which the mean values for the period of time are calculated. For more detailed information, average monthly total cloud cover values "TC" (%) for the period under study are calculated. Analysis of the change in RSDS in 2021–2050 relative to the recent climatic period is shown that in the Laayoune − Sakia El Hamra region we can expect an increase or retention of its values. The annual run of the RSDS has one maximum in June and one minimum in December. In the future, the distribution of RSDS in the Laayoune − Sakia El Hamra region will have a significant impact on proximity to the Atlantic Ocean, where an increased amount of total cloud cover significantly reduces the amount of incoming radiation. In the location of solar power plants in the near future, the current RSDS values are expected to be maintained, which creates favorable conditions for the further development of the renewable energy industry in this area and increasing its productivity.

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