Suitable Renewable Energy Source Research Articles

A CASE ABOUT THE SELECTION OF APPROPRIATE RENEWABLE ENERGY SOURCE FOR TURKEY BY USING CRITIC AND WASPAS METHODS

In our country, which is defined as rich in terms of renewable energy resources, these are important that; to be able to be used the existing renewable energy sources in the most efficient way as regional, minimize foreign dependency at the point of energy source. 
 The topic of this case is to be able to select the most appropriate renewable energy source for Türkiye by using multi-criteria decision methods, to be able to determine the eligiblity criterias in an effort to compare for six sorts of renewable energy sources which are solar, wind, geothermal, hidroelectric, biomass, wave and by collecting the correct datas related to these criterias, to create a study case by applying CRITIC, WASPAS methods on these datas and immediately afterwards to analyze the results of application in order to be able to provide an ease of evaluation for energy investments which will be in the future. 
 At the end of our calculations, wave energy was determined as the energy source with the highest WASPAS score (0.434). Wind energy (0.374) and geothermal energy (0.354) ranked as second and third, respectively. HydroEnergy (0.330), solar energy (0.328) and biomass energy (0.297) are energy sources with lower WASPAS scores. However, the ranking of results may vary according to other factors. 
 If other sources are taken into account, the results may be different. Because Every country, every region has different energy needs and resources. Therefore, decision makers should consider multiple criteria to select the most suitable renewable energy sources according to their conditions, by taking these factors into account.

Selection of suitable renewable energy sources for Turkey: SEM–COPRAS method integrated solution

Selection of suitable renewable energy sources for Turkey: SEM–COPRAS method integrated solution

Enhanced solar-driven water splitting by ZnO/CdTe heterostructure thin films-based photocatalysts

Solar-driven hydrogen production by water splitting using a photocatalyst is considered the most effective approach to produce hydrogen. Hydrogen is the most suitable renewable energy source. The efficiency of hydrogen production is still low. The efficiency of hydrogen production through photocatalysis can be enhanced by preparing a suitable and efficient photocatalyst. In this work, ZnO thin films were deposited on CdTe thin films at 600 °C, 650 °C, and 700 °C temperatures to form ZnO/CdTe heterostructure thin films by chemical vapor deposition (CVD) as photoelectrodes for water splitting. The photoelectrochemical properties showed that ZnO/CdTe heterostructure thin films have better photocurrent response compared to pristine ZnO and CdTe thin films. EIS results showed that the charge transfer at the electrode-electrolyte interface for ZnO/CdTe heterostructure thin films is much better than that of the pristine ZnO film. The ZnO/CdTe-700 °C heterostructure thin film has a 112-fold higher rate of photocatalytic hydrogen generation than pure ZnO.

Potentiality of Biogas Production from Waste in Bangladesh

Biogas is treated as a prominent renewable source in the world for mitigating fuel crises in developing countries. Using biogas technology toxic waste can be handled with an anaerobic process helping to generate natural fertilizers. So, it is a major concern for the researchers to find the proper solution by selecting a suitable renewable energy source in the present world. Biogas is treated as a type of biofuel that can be obtained from the fermentation of organic waste. The main goal of this research is to show the potential of a biogas generator in terms of cow dung, vegetable waste, kitchen waste, and poultry to generate biogas. The produced biogas from the decomposition of the organic waste can be utilized in electric power generation to fulfill the power demand of a house. From the analysis, it is seen that cow dung is the most powerful waste for the generation of biogas in comparison to other types of waste. The calculation shows that cow dung is almost 86.75 % more efficient than the kitchen waste and 44.49 % more efficient than the vegetable waste. And some practical data of a biogas power plant has been included to show the potentiality of biogas in the present world.

A Comparative Study of Renewable Energy Sources for Power Generation in Rural Areas

In recent years, the demand for reliable and sustainable power generation in rural areas has increased due to the lack of access to traditional power grids and the need to reduce reliance on fossil fuels. Renewable energy sources such as solar, wind, and biomass have emerged as viable options for meeting the energy needs of rural communities. This paper proposes a Multi-Criteria Decision Analysis (MCDA) framework for comparing different renewable energy sources for power generation in rural areas. The MCDA framework takes into account multiple criteria such as economic feasibility, environmental impact, and technical feasibility to provide a comprehensive analysis of the different renewable energy sources. The proposed MCDA framework is applied to compare four renewable energy sources: solar power, wind power, hydro power, and biomass power. The results of the MCDA analysis are presented and discussed, and recommendations are provided for the selection of the most suitable renewable energy source for power generation in rural areas.

On Renewable Energy Source Selection Methodologies Utilizing Picture Fuzzy Hypersoft Information with Choice and Value Matrices

In a decision-making problem, the uncertainty component of refusal and abstain along with the sub-parametrization features in the information are not catered by intuitionistic fuzzy/Pythagorean fuzzy sets. In the present communication, we first introduce the novel notion of picture fuzzy hypersoft matrix along with various important binary operations and properties. The inclusion of the novel notion of picture fuzzy hypersoft matrices allows the decision makers to define their preference in a more general sub-parameterized linguistic form for the evaluation of available alternatives. The proposition concentrates on presenting a robust decision-making framework for identifying the optimal and most suitable renewable energy source. In this regard, the revised definition of picture fuzzy hypersoft choice matrix/weighted choice matrix (PFHSCM/PFHSWCM), value matrix, and total score matrix have been presented. Further, two algorithms of decision-making for the selection of the best renewable energy sources have been provided along with appropriate illustrations and ranking descriptions. A numerical example has also been worked out for the sake of illustrating the proposed algorithms. Finally, for establishing the robustness of the MCDM algorithms, a necessary comparative analysis has been carried out successfully.

Performance and emission evaluation of CI engine fueled with ethanol diesel emulsion using NiZnFe2O4 nanoparticle additive

Diesel engines are widely used due to their higher thermal efficiency and lower Hydrocarbon (HC) emissions. The price fluctuation of petroleum fuel; the none-renewability and different hazardous emissions from petro-diesel, researchers are searching for a suitable renewable energy source for diesel engine. Ethanol is one of the promising alternative fuels that could be used to power diesel engine. Some of the techniques so far tried are ethanol fumigation, dual injection and blending. The former techniques need different engine modification to enable the additional systems to work on the existing engines. Blending is the best technique to substitute the existing diesel fuel as long as we prepare it as per the current diesel fuel minimum requirement. For this specific case micro emulsion of ethanol in diesel fuel with emulsifier is prepared by using magnetic stirrer and bath type ultrasonicator. Nickel Zinc Iron Oxide (NiZnFe2O4) nanoparticle is added in one of the selected emulsion which is having 10% ethanol in three different dose as additive to see the effect on the performance and emission variation of the emulsion compared with diesel fuel. The performance of the prepared sample fuels are tested on a test rig with single cylinder diesel engine. The emission is measured by using exhaust gas analyzer and smoke opacity meter. The specific fuel consumption, brake torque and brake power of E5 (95% diesel and 5% ethanol), E10 (90% diesel and 10% ethanol) and E15 (85% diesel and 15% ethanol) are evaluated and the result showed 27, 34 and 37% increment in fuel consumption; 15, 5 and 15% reduction in brake torque and the power reduction is 19, 7 and 12% respectively. E10 is selected for further test with addition of the nanoparticle with 25, 50 and 100ppm named as E103N25 (E10 with 25ppm NiZnFe2O4 nanoparticle), E103N50 (E10 with 50ppm NiZnFe2O4 nanoparticle) and E102N100 (E10 with 100 ppm NiZnFe2O4 nanoparticle). The result showed fuel consumption reduction by 16, 27 and 27% torque output increment of 1, 2 and 2% and power output increment of 5, 7 and 7% respectively compared with E10. The emission result revealed that the HC emission reduced by 50, 58 and 71% for E103N25, E103N50 and E103N100 fuel samples respectively, Carbon monoxide (CO) emission reduced by 67, 80 and 81% for E103N25, E103N50 and E103N100 fuel samples respectively. The reduction in smoke emission is reduced by 60, 69 and 61% for E103N25, E103N50 and E103N100 fuel samples respectively. Nitrogen oxide (NOX) and Carbon dioxide (CO2) emissions increased with the amount of nanoparticle added in to the fuel.

Energetic, economic, and greenhouse gas emissions assessment of biomass and solar photovoltaic systems for an industrial facility

The industrial sector is responsible for nearly 25% of direct and more than 35% of cumulative global energy-related greenhouse gas (GHG) emissions. This study evaluates the feasibility and comparative analysis of on-site solar photovoltaic (PV) and biomass-fed boilers based on historical energy consumption and demand to reduce dependence on grid-supplied electricity and coal-fired boiler for a rice processing industrial plant. The analysis includes energetic, economic, and GHG emissions assessments and covers (a) Solar PV systems, (b) Biomass fuels, and (c) Co-firing scenarios. Financial analysis of solar PV considers both company-owned and bank-financed systems of fixed and double axis tracking technologies. Biomass fuels include 100% wood, 100% rice husk, and a 50%–50% wood-rice husk mix. Historical energy consumption shows that annual electricity demand is 4,479 MWh, costing $537,480 and producing 2,307 tCO 2 emissions. Feasibility of 1MW, company-owned fixed axis solar PV plant shows a yearly electricity production of 1,544 MWh with 0.031 $/kWh levelized cost and reducing 733 tCO 2 with a payback period of 2.8 years. The base case scenario for boiler operations consists of 3,746 tons of coal burning, costing $427,075 and producing 11,840 tCO 2 emissions. Rice husk fuel study shows a 19% fuel cost savings, a 1.7-year payback period, and 11,612 tCO 2 GHG emission reductions. It is concluded that biomass-based rice husk fuel feedstock is the most suitable renewable energy source (RES) for this industrial facility and can reduce 82% of cumulative annual GHG emissions. Furthermore, energy efficiency improvements and off-site carbon credits provide additional opportunities to achieve net-zero GHG emissions for plant operations.

Conceptual framework for integration on renewable energy sources for marine port electrification

In our days electrical energy demand for marine ports in order to cooperate climate change related with zero emissions exhaust gases for the ships has been increased. In order to adapt the situation for the marine port and not use the main grid powered by traditional power stations using fossil fuels, the insertion of renewable energy sources is recommended. The situation created many problems due to variable energy output of renewables and storage system required to be integrated. The authors of this paper propose a decision support framework for the identification and evaluation of the various renewable energy sources and their integration into marine port grid using the Analytic Hierarchy Process and taking into account a number of criteria, as well as, the energy requirements of port activities (i.e.: cold ironing, electrical moving assets, electrical handling devices, etc.). The Kaliningrad sea fishery port (Russia) is used as a case study. The use of hydrogen and hi- pressure as a storage of excessive energy is also to be considered. The proposed framework will advise decision-makers and port stakeholders on choosing the most suitable renewable energy source in the context of a zero-emission port

A framework for evaluating sustainable renewable energy sources under uncertain conditions: A case study

The need for energy sources in India has increased abnormally in recent years due to industrial and societal growth. To meet this demand, it was a necessary choice of renewable energy sources (RESs) as a solution to lack of nonrenewable energy sources. Due to the multiplicity of involved factors, selecting the most appropriate RESs is a multiattribute decision making (MADM) problem. There is a large number of work associated with the development of MADM techniques, especially under ambiguous and uncertain conditions. However, the effective embedding of uncertainty and ambiguity and in decision-making remains a difficult challenge, and thus this study introduces a new framework for solving the problem of selecting the most suitable RESs which is based on the neutrosophic set and TODIM (an acronym in Portuguese of interactive and multicriteria decision-making) method. It also reduces human intervention by being systematically applied. First, it transforms the linguistic terms presented into neutrosophic values and implements systematic techniques to compute missing values in the decision matrix using the case-based technique. Second, it calculates the weight of every linguistic variable as well as those of the decision-makers (DMs) and weighted attributes. Furthermore, it creates an aggregated single valued neutrosophic decision matrix for DMs. Finally, it calculates the overall dominance-degree matrix, derives the overall values, and ranks the alternatives. It is applied to select RESs in Karnataka, India, and the obtained results show that wind energy is the most suitable RES for India, with small hydroenergy second most appropriate.

Selection of Suitable Renewable Energy Sources for Turkey: Sem-Copras Method Integrated Solution

Selection of Suitable Renewable Energy Sources for Turkey: Sem-Copras Method Integrated Solution

A novel PROMETHEE method based on GRA-DEMATEL for PLTSs and its application in selecting renewable energies

Environmental pollution has become a critical social problem in China. Evaluating and selecting suitable renewable energy sources for a city is vitally essential for its long-term sustainable development. Identifying the key factors that influence the evaluation system is another crucial process. Therefore, we address the evaluation problem using two steps: (1) applying a decision-making trial and evaluation laboratory (DEMATEL) method to analyze the relevant factors and (2) ranking the factors by the preference ranking organization method for enrichment of evaluations (PROMETHEE). As a result, we introduce a new DEMATEL method based on grey relation analysis (GRA) via objective data in a decision matrix. The new method not only avoids the instability of the traditional DEMATEL method by applying experts' subjective opinions to compare two factors but also addresses the challenges faced by decision-makers when making pairwise comparisons when the number of factors is too large. Moreover, because the PROMETHEE method effectively solves complex decision problems, we also propose a new PROMETHEE method concerning probabilistic linguistic term sets (PLTSs) to rank and select suitable renewable energies. To analyze the stability of the decision result, we present a novel mixed-integer linear programming (MILP) method that investigates the ranking results for all the factors simultaneously, rather than using only one as in traditional methods. Finally, we implement our method to evaluate renewable energy options in a western Chinese city, and the results show that our method is effective and reasonable in solving complex decision problems.

A Multicriteria Decision-Making Model for the Selection of Suitable Renewable Energy Sources

With the expansion of its industrial and manufacturing sectors, with the goal of positioning Vietnam as the world’s new production hub, Vietnam is forecast to face a surge in energy demand. Today, the main source of energy of Vietnam is fossil fuels, which are not environmentally friendly and are rapidly depleting. The speed of extraction and consumption of fossil fuels is too fast, causing them to become increasingly scarce and gradually depleted. Renewable energy options, such as solar, wind, hydro electrical, and biomass, can be considered as sustainable alternatives to fossil fuels. However, to ensure the effectiveness of renewable energy development initiatives, technological, economic, and environmental must be taken in consideration when choosing a suitable renewable energy resource. In this research, the authors present a multi-criteria decision-making model (MCDM) implementing the grey analytic hierarchy process (G-AHP) method and the weighted aggregates sum product assessment (WASPAS) method for the selection of optimal renewable energy sources for the energy sector of Vietnam. The results of the proposed model have determined that solar energy is the optimal source of renewable energy with a performance score of 0.8822, followed by wind (0.8766), biomass (0.8488), and solid waste energy (0.8135) based on the calculations of the aforementioned methods.

Stakeholders’ Recount on the Dynamics of Indonesia’s Renewable Energy Sector

The study described in this paper uses direct evidence from processes applied for the developing economy of Indonesia, as it defines the trajectory for its future energy policy and energy research agenda. The paper addresses the research gap to make explicit the process undertaken by key stakeholders in assessing and determining the suitability, feasibility, and dynamics of the renewable energy sector. Barriers and enablers that are key in selecting the most suitable renewable energy sources for developing economies for the renewable energy development have been identified from extensive analyses of research documents alongside qualitative data from the Focus Group Discussions (FGD). The selected FGD participants encompass the collective views that cut across the political, economic, social, technological, legal, and environmental aspects of renewable energy development in Indonesia. The information gained from the FGD gives insights into the outlook and challenges that are central to energy transition within the country, alongside the perceptions of renewable energy development from the influential stakeholders contributing to the process. It is notable that the biggest barriers to transition are centred on planning and implementation aspects, as it is also evident that many in the community do not adhere to the same vision.

Optimal Investment Strategy for Solar PV Integration in Residential Buildings: A Case Study in The Philippines

In developing countries, particularly in rural areas, long periods of power outages are experienced as the electricity grid is technically or economically unfeasible. As solar photovoltaic (PV) is the most potential and suitable source of renewable energy for these areas, this paper analyzes the economic viability of its integration in different types of residential buildings. Applying real optionsapproach under uncertainty in electricity prices, this study compares the attractiveness of adopting solar PV over continuing electricity from the grid focusing on various investment payment schemes including (i) full payment, (ii) distributed payment for 5 or 10 years without a down payment, and (iii) distributed payment for 5 or 10 years with 20% or 40% down payment. Applying the model with the case of the Philippines, the resultswith the full payment strategy obtain option values of USD 6888 for building type-I, USD 15349 for building type-II, USD 21204 for building type-III, USD 27870 for building type-IV, and USD 34251 for building type-V. These option values increase by 21.6% and 22.5% with distributed payment scheme to a 5- or 10-year period and increase by 5% and 13% for distributed payment with 40% and 20% down payment. These option values decrease with investments at later periods. Contrary to the conventional option valuation results of an optimal decision to wait, our findings show the otherwise as earlier investment reduces the risk of opportunity loss from delaying the adoption of solar PV. Among the payment schemes analyzed, the distribution of PV system cost in a 10-year installment periodwithout down payment shows to be the most optimal investment strategy which may encourage lower-income and risk-averse consumers whose decision to adopt solar PV is affected by cost barriers, economic status, and household income. The study suggests the government, particularly in developing countries, to support the integration of own-use solar PV in buildings through incentives and subsidies, as well as financial institutions to offer more affordable terms of payment that encourages low to medium income households to adopt solar PV.Further, this will not only augment the energy deficiency in these countries but also support the global aspirations of reducing greenhouse gas emissions and its adverse effects through gradually shifting to renewable sources of energy.

Evaluation approach for sustainable renewable energy systems under uncertain environment: A case study

The demand for energy in Egypt has increased dramatically due to the steady increase in economic and societal development. To meet this need, the use of more renewable energy resources is an essential part of the solution to the ultimate shortage of energy. Because of the multitude of factors involved, the selection of the most suitable renewable energy systems (RESs) is a multi-criteria decision-making (MCDM) problem. There are a good number of works associated with the design of MCDM methods, particularly under uncertain and ambiguous situations. However, efficient incorporation of ambiguity and uncertainty in decision making is still a challenging task, and thus this work proposes a hybrid MCDM approach for selecting the components of a sustainable RES under uncertain environments, utilizing different triangular neutrosophic numbers to deal with unclear information. This proposed hybrid approach starts with defining the relative importance of the selected sustainable criteria by using an Analytic Hierarchy Process (AHP). Later, in the second phase, this hybrid approach combines VIKOR and the TOPSIS to rank the RESs for a real-life case study. The results obtained indicate that concentrated solar power is the most suitable source of renewable energy for Egypt, with photoelectric power the second most suitable.

A Two-Stage Multiple Criteria Decision Making for Site Selection of Solar Photovoltaic (PV) Power Plant: A Case Study in Taiwan

At the heart of Covid-19 responses, the transition from fossil sources to green energy is an urgent issue for nations to address the crisis and secure sustainable economies. As a country in a seismically active zone that relies heavily on imported fossil fuels, Taiwan is vigorously taking the next step in renewable energy development, which is pivotal to securing its position in global supply chains. Solar energy is today the most suitable renewable energy source for Taiwan. However, land prices and policies, and challenges of scale still hinder its development. In this context, identifying optimal sites for solar photovoltaic (PV) construction is a crucial task for major energy stakeholders. In this paper, a two-stage approach, combining the data envelopment analysis (DEA) models and the analytic hierarchy process (AHP), has been done for the first time to identify the most suitable locations among 20 potential cities and counties of Taiwan for constructing solar PV farms. DEA models were applied to filter out the areas with the most potential by measuring their efficiency indices with temperature, wind speed, humidity, precipitation, and air pressure, as inputs, and sunshine hours and insolation, as outputs. The locations with perfect efficiency scores were then ranked with the AHP method. Five selected evaluation criteria (site characteristics, technical, economic, social, and environmental) and sub-criteria of each were utilized to prioritize the locations with solar energy potential. AHP was used to determine the relative weights of the criteria and sub-criteria and the final weights of the areas. For criteria weighting results, “support mechanisms,” “electric power transmission cost,” and “electricity consumption demand” with weights of 0.332, 0.122, and 0.086, respectively, were found as the most significant sub-criteria. The final ranking suggests Tainan, Changhua, and Kaohsiung as the top three most suitable cities for constructing solar PV energy systems.

YENİLENEBİLİR ENERJİ KAYNAKLARININ ÇOK KRİTERLİ KARAR VERME TEKNİKLERİ İLE DEĞERLENDİRİLMESİ: TÜRKİYE ÖRNEĞİ

Turkey growing energy needs, depending on the technological developments and increasing population does not meet the existing reserves of fossil origin. As a result, we are a country that is highly dependent on foreign resources in terms of energy resources, and renewable energy sources. Increased environmental awareness and energy supply security make renewable energy sources very important. The aim of this study is to identify the most suitable renewable energy source alternative for Turkey using MCDM methods. Based on the information obtained from the evaluation forms filled with the opinions of experts in the Ministry of Energy and Natural Resources, criterion weighting with the AHP method and weighting of sources alternative with the COPRAS, MULTIMOORA method were calculated. In the study, 4 main criteria, 17 sub criteria and 5 alternative energy sources (Wind, Solar, Geothermal, Biomass, Hydraulics) were determined. As a result of the analysis, it was determined that hydroelectric, solar, wind, geothermal and biomass are respectively the most suitable renewable energy sources in both methods.

Ranking of renewable energy sources for regions in Turkey by fuzzy entropy based fuzzy COPRAS and fuzzy MULTIMOORA

Abstract The primary purpose of the study is to rank and evaluate renewable energy sources that are the only alternative of non-renewable energy sources, according to twenty-six regions in Turkey. Multi-criteria decision making methods are widely employed in the solution of energy selection problems because energy selection problems contain many criteria contradicting each other. In this study, the importance levels weights of the evaluation criteria were measured by the Fuzzy Entropy method. Later, with the Fuzzy COPRAS and Fuzzy MULTIMOORA methods, renewable energy sources alternative rankings were acquired for the regions. According to the fuzzy COPRAS results in Appendix 2, the hydroelectric energy source has been defined as the suitable renewable energy source alternative for seventeen regions. According to the fuzzy MULTIMOORA results in Appendix 2, the hydroelectric energy source has been determined as the suitable renewable energy source alternative in the first rank for eighteen regions. With this study, a resource is presented to regional investors to reach an investment decision for renewable energy sources. This study constitutes an indication for development agencies along with investors.

Assessment of abrasive powder behaviour during impact-abrasive wear of PCD elements

One of the most suitable renewable energy sources is geothermal energy (providing heating as well as electricity). In order to achieve a suitable depth of drilling (several kilometres), it is required to increase the wear resistance, durability and reliability of key components of the deep drills. The effect of abrasive powders on impact energy transmission and/or damping during wear of Polycrystalline Diamond (PCD) cutting elements was evaluated due to its highest resistance in abrasive conditions. The characteristic features of wear mechanism are presented and discussion is supported by SEM images and EDS maps. The strength of silica sand, quartzite, granite, basalt, marble, limestone, pumice is compared to the force transmitted through the contact zone, damping characteristics and stiffness of abrasive particles. It was found that the laboratory impact-abrasive device enables to initiate damage, characteristic for specific abrasive powder, imitating drilling of such mineral. The mechanism of wear of PCD elements in impact-abrasive conditions depends on the strength and shape of abrasive particles as well as on their behaviour during impact (impact energy damping). The wear of PCD elements in the impact-abrasive conditions was close to zero and their use in new generations of deep drills is expected.