Feasibility study of the grid connected 10 MW installed capacity PV power plants in Saudi Arabia

Energy-related activities are a major contributor of greenhouse gas (GHG) emissions. A growing body of knowledge clearly depicts the links between human activities and climate change. Over the last century the burning of fossil fuels such as coal and oil and other human activities has released carbon dioxide (CO2) emissions and other heat-trapping GHG emissions into the atmosphere and thus increased the concentration of atmospheric CO2 emissions. The main human activities that emit CO2 emissions are (1) the combustion of fossil fuels to generate electricity, accounting for about 37% of total U.S. CO2 emissions and 31% of total U.S. GHG emissions in 2013, (2) the combustion of fossil fuels such as gasoline and diesel to transport people and goods, accounting for about 31% of total U.S. CO2 emissions and 26% of total U.S. GHG emissions in 2013, and (3) industrial processes such as the production and consumption of minerals and chemicals, accounting for about 15% of total U.S. CO2 emissions and 12% of total ...

Solar power is the fastest-growing energy source in the world. New technologies can help to generate more power from solar energy. The present paper aims to encourage people and the government to develop solar energy-based power projects to achieve sustainable energy infrastructures, especially in developing countries. In addition, this paper presents a solar energy road map to attract investors to invest in clean energy technology to help reduce the effect of global warming and enhance sustainable technological development. Therefore, the first objective of the paper is to analyze and compare the monthly global solar radiation for five different locations in Northern Cyprus using the measured data collected from the Meteorological Department and estimated values collected from the satellite imagery database. In addition, the mean hourly meteorological parameters including global solar radiation, air temperature, sunshine, and relative humidity are analyzed statistically and the type of distribution functions are selected based on skewness and kurtosis values. Accordingly, estimating global solar radiation improves solar power generation planning and reduces the cost of measuring. Therefore, models of a surface were analyzed by means of polynomial adjustments considering the values of R-squared. Finally, this study provides a comprehensive and integrated feasibility analysis of a 100 MW grid-connected solar plant project as an economic project in the selected region to reduce electricity tariffs and greenhouse gas (GHG) emissions. RETScreen Expert software was used to conduct the feasibility analysis in terms of energy production, GHG emissions, and financial parameters for the best location for the installation of a 100 MW grid-connected photovoltaic (PV) plant. Finally, the results concluded that the proposed solar system could be used for power generation in Northern Cyprus.

Over the last few years, the electric energy demand in the Kingdom of Saudi Arabia (KSA) has increased many folds due to several factors including increased population, industrialization, economic activities, and urbanization. The main source of electric power generation in KSA is the burning of petroleum products. Almost one third of greenhouse gas (GHG) emissions are contributed from the electric power generation sector, mainly, by burning diesel and natural gas. As a result, it makes it necessary to consider alternate forms of electricity generation in order to cut down emissions and to keep sustainable growth alive. The government has planned to diversify energy sources and suppliers. In recent years, energy generation from renewable sources including solar photovoltaic (PV), wind, concentrated solar power (CSP), biomass, geothermal, and tidal, has been given more importance. The ambitious Saudi Vision 2030 targets of 58.7 GW of power generation from renewable energy sources will cause a significant reduction in GHG emissions from the energy sector. This article systematically reviews the impact of renewable energy generation on GHG emissions. The detailed breakdown of GHG emission is discussed. Then, the status of renewable energy generation is investigated, focusing on the technical and economic potentials. The correlation of renewable energy generation and GHG emissions is then explained. The most distinguishing feature of this review is that it provides a comprehensive list of recommendations to reduce GHG emissions. The discussions and recommendations of this article will support decision makers, system planners, industry personnel, researchers, and academics to develop sustainable energy pathways for the Kingdom.

The techno‐economic analyses of 67 MW and 144 MW photovoltaics (PV) power plants are performed and the results are compared with the diesel power plants situated in two cities in the Kingdom of Saudi Arabia. The feasibility analysis is conducted with the aim to show the technical and economic viability of replacing the conventional fossil fuel‐based plants with clean production systems in the country. The production capacity of the proposed PV plants based on the single‐axis tracking configuration is around 35% higher than that of the tilted‐fixed configuration, equivalent to a reduction in the production cost by more than 20% for both the plants. PV plants with a tracking system can produce up to 23% excess electricity than the base‐case diesel plants. Moreover, the production costs at the Bisha plant can be as low as 1.77 ¢/kWh, considering the credit resulting from the reduction of greenhouse gas (GHG) emissions. The feasibility of installing a 144 MW PV plant in six cities in the country is also evaluated. The results indicate that the average cost of electricity production is 2.22 ¢/kWh and the average annual reduction of GHG emissions is 462 tCO2/GWh with the replacement of a diesel power plant of similar capacity. The effects of subsidies, feed‐in tariff rates, and electricity export escalation rates are also evaluated.

The grid integration of large scale photovoltaic (PV) power plants represents many challenging tasks for system stability, reliability and power quality due to the intermittent nature of solar radiation and the site accessibility issues where most PV power plants are located over a wide area. In order to enable real-time monitoring and control of large scale PV power plants, reliable two-way communications with low latency are required which provide accurate information for the electrical and environmental parameters as well as enabling the system operator to evaluate the overall performance and identify any abnormal conditions and faults. This work aims to design a communication network architecture for the remote monitoring of large-scale PV power plants based on the IEC 61850 Standard. The proposed architecture consists of three layers: the PV power system layer, the communication network layer, and the application layer. The PV power system layer consists of solar arrays, inverters, feeders, buses, a substation, and a control center. Monitoring parameters are classified into different categories including electrical measurements, status information, and meteorological data. This work considers the future plan of PV power plants in Saudi Arabia. In order to evaluate the performance of the communication network for local and remote monitoring, the OPNET Modeler is used for network modeling and simulation, and critical parameters such as network topology, link capacity, and latency are investigated and discussed. This work contributes to the design of reliable monitoring and communication of large-scale PV power plants.

Purpose This paper focuses on the commitment of a leading Middle Eastern country – Saudi Arabia – to the United Nations (UN) Sustainable Development Goals (SDGs), particularly SDG13, climate preservation. This paper aims to investigate the determinants of greenhouse gas emissions by examining their correlation with economic growth, population growth, renewable energies, forest area, digitalization and monetary policy. Design/methodology/approach This research observes greenhouse gas (GHG) emissions and the potential influencing factors during 1990–2023. It employs the autoregressive distributed lag model (ARDL) after testing the stationarity of the variables. Findings The findings show that population growth, gross domestic product (GDP) growth, percentage of individuals using the internet and forest rents are significant determinants of carbon oxide (CO2) emissions. Further, methane (CH4) emissions are significantly associated with population growth, GDP growth, percentage of individuals using the internet and renewable internal freshwater resources. Nitrous oxide (N2O) emissions depend significantly on the percentage of individuals using the internet and renewable internal freshwater resources. Practical implications This research helps policymakers in Saudi Arabia and worldwide identify the factors moderating GHG emissions, and accordingly design targeted interventions. These initiatives would substantially reduce GHG and further global climate goals. Additionally, focusing on Saudi Arabia, a significant emerging country in the Middle East, has broader implications. The findings offer insights that extend beyond its borders, providing valuable lessons for governments in the Middle East and worldwide to assess and improve their initiatives toward SDG13. Therefore, monitoring greenhouse gas emissions in this key country boosts global progress toward the UN’s 2030 Agenda for Sustainable Development. Furthermore, this paper aligns with the Principles for Responsible Management Education (PRME) by leveraging academic and managerial strategies toward sustainability and climate action initiatives. Originality/value This study adds to the limited literature on the determinants of GHG emissions in the Middle Eastern region, particularly in Saudi Arabia. In addition to CO2, it also focuses on CH4 and N2O emissions. It shows the beneficial effect of renewable internal freshwater resources. It uses the ARDL model to distinguish between the short- and long-run associations.

Major US electric utility climate pledges have the potential to collectively reduce power sector emissions by one-third

Nowadays, the global climate change has been a worldwide concern and the greenhouse gases (GHG) emissions are considered as the primary cause of that. The United Nations Conference on Environment and Development (UNCED) divided countries into two groups: Annex I Parties and Non-Annex I Parties. Since Iran and all other countries in the Middle East are among Non-Annex I Parties, they are not required to submit annual GHG inventory report. However, the global climate change is a worldwide phenomenon so Middle Eastern countries should be involved and it is necessary to prepare such a report at least unofficially. In this paper the terminology and the methods to calculate GHG emissions will first be explained and then GHG emissions estimates for the Iranian power plants will be presented. Finally the results will be compared with GHG emissions from the Canadian electricity generation sector. The results for the Iranian power plants show that in 2005 greenhouse gas intensity for steam power plants, gas turbines and combined cycle power plants were 617, 773, and 462 g CO2eq/kWh, respectively with the overall intensity of 610 g CO2eq/kWh for all thermal power plants. This GHG intensity is directly depend on efficiency of power plants. Whereas, in 2004 GHG intensity for electricity generation sector in Canada for different fuels were as follows: Coal 1010, refined petroleum products 640, and natural gas 523 g CO2eq/kWh, which are comparable with same data for Iran. For average GHG intensity in the whole electricity generation sector the difference is much higher: Canada 222 vs. Iran 610g CO2eq/kWh. The reason is that in Canada a considerable portion of electricity is generated by hydro-electric and nuclear power plants in which they do not emit significant amount of GHG emissions. The average GHG intensity in electricity generation sector in Iran between 1995 and 2005 experienced 13% reduction. While in Canada at the same period of time there was 21% increase. However, the results demonstrate that still there are great potentials for GHG emissions reduction in Iran’s electricity generation sector.

This study presents the results of an initial assessment of the technical and economic feasibility of a 5 megawatts (MW) net Solar Electric Photovoltaic (PV) power plant on the Island of Kauai, Hawaii. It analyzes three potential PV based designs of the solar power plant — single-axis tracking flat plate, fixed flat plate, and two-axis tracking concentrating photovoltaics (CPV) based on the solar insolation on Kauai. Greenhouse gas (GHG) avoided, energy production projection, capital costs, operation & maintenance (O&M) costs, and the levelized cost of energy (LCOE) of each PV design is developed for comparison. Regardless of the PV technology, the following factors may position solar PV power plant as a competitive alternative to conventional fossil-powered power plant: • Recent technology advances have occurred in concentrating solar collectors increasing overall efficiency; • Use of renewable energy can lead to reduced greenhouse gas (GHG) emissions; • Fossil fuels (e.g. natural gas and oil) retail prices are near record highs, increasing electricity rates. The assessment results show that single-axis tracking flat plate PV system are best suited for sites in Kauai as they accommodate the intermittent cloud cover of the region while following the sun from dawn until dusk as it crosses the sky.

SummaryFloating photovoltaic (FPV) plants present several benefits in comparison with ground-mounted photovoltaics (PVs) and could have major positive environmental and technical impacts globally. FPVs do not occupy habitable and productive areas and can be deployed in degraded environments and reduce land-use conflicts. Saving water through mitigating evaporation and improving water security in arid regions combined with the flexibility for deployment on different water bodies including drinking water reservoirs are other advantages of FPVs. They also have higher efficiency than ground-mounted PV solar and are compatible with the existing hydropower infrastructures, which supports diversifying the energy supply and its resilience. Despite the notable growth of FPVs on an international scale, lack of supporting policies and development roadmaps by the governments could hinder FPVs’ sustainable growth. Long-term reliability of the floating structures is also one of the existing concerns that if not answered could limit the expansion of this emerging technology.

With the increasing consumption of fossil fuel, reducing greenhouse gas (GHG) emissions has become a serious issue that has attracted worldwide attention. Therefore, Lebanon is currently interested in utilizing renewable energy technologies to reduce energy dependence on oil reserves and GHG emissions. The present study is focused on solar and wind power potential and the economic viability of wind/solar systems for the Rayak region in Lebanon for the first time. The input data sources for the study including the Meteorological data for wind speed and NASA database for solar energy. In the assessment of wind energy, a two-parameter Weibull distribution function was used to analyze the characteristics of wind speed. Yearly and seasonal Weibull parameters were calculated for 10 m height using the Maximum likelihood method. In addition, yearly and seasonal wind power density values were calculated. The results showed that the mean annual wind speed and wind power density values were 5.884 m/s and 124.534 W/m2, respectively, during the investigation period. It can be concluded that the value of wind power density at the region was classified as marginal wind power potential and high-scale wind turbines can be used to gather wind energy potential in the region. Furthermore, predicting wind speed depends on various atmospheric factors and random variables. Therefore, 63 ANN models are developed by varying the meteorological parameters to predict the daily wind speed in the selected region. All the models with various combinations are validated and the performances of the models are analyzed using root mean squared error. The results demonstrated that the most relevant input variables for predicting the daily wind speed were found to be temperature, pressure, and relative humidity. In the assessment of wind energy, average monthly global solar radiation data were evaluated. It is found that the annual global solar radiation was 1877.41 kWh/m2, which indicates the selected region has high solar resources and is categorized as an excellent potential class. Moreover, this study provides a comprehensive and integrated feasibility analysis of 100 MW grid-connected wind and solar projects economic projects that can be developed in the country to reduce the electricity crisis and GHG emissions. Several different economic and financial indicators were calculated. The results indicate that the wind farm is a more economical option than the solar plant because of the higher values of NPV, BCR, ALCS, and IRR as well as the lower values of EB, SB, and LCOE.

Information about the availability of solar radiation on horizontal surface is essential for the optimum design and study of solar energy systems. For a country like UAE, the efficient application of solar energy seems inevitable because of abundant sunshine available throughout the year. The traditional way of knowing the amount of global solar radiation (GSR) in a particular region is to install pyranometers at as many locations as possible in this region thus requiring daily maintenance and data recording, and consequently increasing cost of GSR data collection. Therefore, it is rather more economical to develop methods to estimate the GSR using climatological parameters (Akhlaque et al., 2009; Kassem et al., 2009; Falayi et al., 2008; El-Sebaii & Trabea, 2005). Many researchers estimated global solar radiation by using artificial neural networks. (Mohandes et al, 1998) applied ANN techniques to predict GSR using weather data from 41 stations in Saudi Arabia. Data from 31 stations was used in training the NN and the remaining data was used for testing. Input variables to the NN included 4 parameters: latitude, longitude, altitude and sunshine duration. Their sample data was not large enough to allow a credible comparison between the ANN models used and empirical regression models. (Lam et al., 2008) have used Artificial Neural networks ANNs to develop predication models for daily global solar radiation using measured sunshine duration for 40 cities covering 9 major thermal climatic zones and sub-zones in China. (Alam et al., 2009) used ANNs to estimate monthly mean hourly and daily diffuse solar radiation based on weather data from 10 Indian stations which have different climatic conditions. (Alawi & Hinai, 1998) applied ANNs to predict solar radiation in areas not covered by direct measurement instrumentation. The input data that was used for building the network were the location, month, mean pressure, mean temperature, mean vapor pressure, mean relative humidity, mean wind speed and mean duration of sunshine. (Tasadduq et al., 2002) have used neural networks for the prediction of hourly mean values of ambient temperature 24 hours in advance. Full year hourly values of ambient temperature are used to train a neural network model for a coastal location — Jeddah, Saudi Arabia. (Elminir et al., 2005) applied ANN modeling techniques to predict solar radiation data in different spectrum bands from data of meteorology for Helwan (Egypt) meteorology monitoring station. (Rehman & Mohandes, 2008) developed ANN-based estimation GSR for Abha city in Saudi Arabia; by

Solar Photovoltaic (PV) and Wind power plants are becoming increasingly cost competitive when compared with conventional thermal power plants and in the not far future may set the ceiling price of electricity in many markets. The Kingdom of Saudi Arabia (KSA) is internationally known for its hydrocarbon reserves but is less recognized for its renewable energy resources, especially wind energy. These renewable energy resources, although known as Variable Energy Resources (VERs), can be efficiently integrated into conventional power systems to provide stable and reliable electricity, whether for national power systems or for isolated Mini-grid power systems in KSA. Traditional capacity measures as Capacity Factor (CF) and Reserve Margin (RM) are not able to deal with the intermittency of Wind and PV power plants. Statistical and probabilistic measures coming from System's Adequacy methodology as Effective Load Carrying Capability (ELCC), Equivalent Firm Capacity (EFC) or Equivalent Conventional Power Plant (ECPP) are available to assess the capacity value of VERs. All of these methods are based on Generation Adequacy where VER is added to conventional power plants to fulfil the load. A case study was completed for a Mini-grid within the Saudi Electric Company's (SEC) Southern Operating Area (SOA) where the Loss of Load Probability (LOLP) for the conventional thermal power plant was estimated and the addition of VER is assessed by using ELCC. Based on the available load data and VER profiles for PV a Capacity Credit of 51.8% was estimated, declining at a rate of 2.2% per MWp of additional installed capacity. The ELCC for Wind was estimated to be 19.4%, declining at a rate of 1.4% per MW of additional installed capacity. It was also found that using VER improves the system reliability in terms of Loss of Load Expectation (LOLE). While excessive VER production does not impact LOLE it does impact the economics. A penetration of up to 25% wind or 30% PV does not result in curtailing VER production.

FPGA-based implementation of intelligent predictor for global solar irradiation, Part I: Theory and simulation

After introducing the Renewable Energy Portfolio Standard (RPS) system into the Korean electricity market in 2012 to promote the use of renewable energy, many MW-scale photovoltaic (PV) plants have been constructed nationwide in South Korea. In addition, the recent decrease in the cost of constructing PV plants has contributed greatly to the increase in the number of PV plants. The government of Jeju Island has a plan to make the island carbon-free by 2030. Moreover, Jeju is trying to develop electric power plants using renewable energy sources, such as wind and solar. Because many MW-scale PV plants will be constructed in the future on Jeju Island, reference data for the generation characteristics of the MW-scale PV plants operating in the island are needed. In this study, the Jeju Island was divided into 4 regions according to the weather similarity. In addition, the generation characteristics of MW PV plants were investigated and analyzed. The relationship between the sunshine duration and the electricity generated by the PV plant was almost linear and the sunshine duration in the 4 regions over the past 20 years were investigated. The relationship between the sunshine duration and the utilization rates of the PV plants was analyzed.