Selection Of Energy Sources Research Articles

Decision making for renewable energy source selection using q-rung linear Diophantine fuzzy hypersoft aggregation operators

Decision making for renewable energy source selection using q-rung linear Diophantine fuzzy hypersoft aggregation operators

A strategic multi-criteria decision-making framework for renewable energy source selection in Saudi Arabia using AHP-TOPSIS

The Kingdom of Saudi Arabia (KSA) is targeting 50 % of its energy generation from renewable energy sources (RES) by 2030. However, a comprehensive approach is needed to prioritize the available RES in the kingdom. This study employs a survey-based approach which gathered insights from several academic and industrial experts and then utilizes analytic hierarchy process (AHP) and technique for order of preference by similarity to ideal solution (TOPSIS) methods to determine the optimal RES. In this case, hybrid RES (solar-wind, solar-geothermal, solar-biomass) is evaluated against single-source alternatives based on different criteria including cost-effectiveness, land conservation, low intermittency, resource potential, design simplicity, and social acceptance. The results showed that cost-effectiveness emerged as the predominant criterion with importance of 31 % followed by low intermittency and resource potential contributing with 24 % and 22 % in importance, respectively. Based on these findings, solar energy is recognized as the best RES, with a priority level of 23 % followed by the hybrid solar-wind and hybrid solar-geothermal, which attained priority levels of 20 and 16 %, respectively. Subsequently, a sensitivity analysis was carried out to assess the impact of varying criteria weights. The findings offer the decision maker useful insights into the priority of different RES in KSA.

A comprehensive design pipeline for FCEV powertrain configuration considering the evolutionary development process and extreme economic performance

Due to stringent emission regulations, the zero-emission hydrogen fuel cell electric vehicles (FCEVs) are gaining significant attention, but their slow power response requires careful selection of auxiliary energy sources and power systems to optimize energy efficiency. This paper presents a comprehensive design pipeline for the FCEV powertrain, encompassing methods for powertrain configuration design, feasible domain design for component parameters, and parameter matching. Initially, a powertrain configuration design method based on evolutionary game theory is introduced, forecasting trends in energy-efficient powertrain configurations using a dynamic cost function that adjusts based on the proportions of different configurations. Next, a feasible domain design method is developed to establish fixed constraints on component parameters, ensuring a fair balance between performance needs and overall costs, including development and lifecycle expenses associated with the powertrain configuration. Subsequently, dynamic programming (DP) is used for parameter matching, assessing the utmost energy-saving potential. The cost function in this method incorporates the degradation cost of powertrain components, underscoring the economic performance of the target FCEV over its lifespan. Finally, simulation assessments indicate that the proposed design pipeline effectively identifies the optimal powertrain configuration for FCEVs, endowing each possible configuration with exceptional economic efficiency across different component parameters.

CARD: Comprehensive approach based on relative difference for decision-making problems with dual evaluation forms − Application to sustainable renewable energy selection

Numerous multi-attribute decision-making (MADM) methods exist, each aiming to improve decision-making in complex scenarios involving multiple criteria. However, challenges remain, particularly in integrating both quantitative and qualitative evaluations and addressing issues related to attribute weighting and normalization. This study introduces a novel MADM method called the CARD method, designed to address these challenges. The CARD method offers a unified framework that combines direct and pairwise evaluations using logarithmic relative difference measures to compare alternatives in terms of relative superiority. Key innovations of the CARD method include: 1) developing a new utility function; 2) proposing a new closeness coefficient measure; 3) the ability to handle joint quantitative and qualitative inputs; and 4) introducing a new criterion satisfaction coefficient, the so-called strictness degree. These features enable the CARD method to effectively solve MADM problems involving mixed criteria. To demonstrate its applicability, we apply the CARD method to a case study on renewable energy source selection in Spain. The results confirm that wind energy is the optimal renewable energy source for Spain, highlighting its economic, engineering, and sustainable advantages. This study underscores the potential of the CARD method to enhance decision-making processes and provide valuable insights for policymakers and practitioners.

Sustainable Soft Computing Techniques for Site Selection of Optimal Renewable Energy Source to Reduce Carbon Emission in India - A Mini Review

Sustainable Soft Computing Techniques for Site Selection of Optimal Renewable Energy Source to Reduce Carbon Emission in India - A Mini Review

Powering the Future: An Integrated Framework for Clean Renewable Energy Transition

The transition to renewable energy has been recognized as a crucial step in addressing climate change and achieving greenhouse gas reduction targets, but it can also cause energy sprawl if not planned properly. Clean renewable energy communities (CREC) are emerging globally as an approach for decentralized energy systems and an alternative to traditional centralized energy systems. CREC aim to lower the energy carbon footprint, enhance local energy resilience, and improve the quality of life of residents. Through a comprehensive literature review, this study reviews metrics that can assess the impact of energy transition plans and support decision-making to select technologies that create efficient, reliable, and accessible energy systems. It classifies these metrics into a five-dimensional sustainability approach including environmental, technical, social, economic, and political and institutional dimensions. The paper proposes a conceptual framework to guide decision-makers in recognizing the role of sustainable land development, sustainable energy planning, and resiliency as an integrated approach to energy transition planning. This framework stresses mapping the place-based potential for clean renewable energy at various scales, highlights the importance of resilience in energy planning, and addresses challenges associated with energy source selection, built environment efficiency, and the energy trade. While the framework can serve as a starting point for evaluating energy transition plans, further work is needed to address the limitations of existing metrics and identify additional evaluations for mixed-energy land use that are critical to managing energy sprawl in terms of ecosystem services and other land uses.

Impact of Agricultural Technical Efficiency on Farm-Gate Emission: An Implementation of Environmental Kuznets Curve in Asian Developing Countries

<p>The Environmental Kuznets Curve (EKC) explains that economic activities in developing countries, including agriculture, increase environmental damage. Increased technical efficiency is one approach that is frequently suggested for reducing the negative impacts of farming practices. Unfortunately, there are no studies that investigate this at the macro (national) level. This study examines the impact of technical efficiency on farm-gate emissions in Asian developing countries. Data were collected from 25 developing countries in Asia from 1992 to 2021 and were analyzed using frontiers and the generalized method of moments. The findings demonstrate that technical efficiency is insufficient to prevent increases in CO<sub>2</sub>, CH<sub>4</sub>, and N<sub>2</sub>O emissions. This finding is consistent with the EKC. Gas emissions also rise because of gross domestic product (GDP) and population growth. Human development is the only way to prevent a rise in emissions of these 3 gases. Meanwhile, renewable energy and food prices have varying impacts on CO<sub>2</sub>, CH<sub>4</sub>, and N<sub>2</sub>O emissions reduction. Therefore, based on these findings, it is suggested that developing countries increase the utilization of natural production factors and organic farming, improve human capital development, and conduct a wise selection of renewable energy sources.</p>

Environmental impact of ISO 14001 certification in promoting sustainable development: The moderating role of innovation and structural change in BRICS, MINT, and G7 economies

Since the industrial era, the selection of energy sources to facilitate economic advancement has been criticized because of the resulting ecological calamity. This has prompted the introduction of radical approaches such as ISO 14001, which tackles the drivers of pollution. Therefore, this study analyses the ISO 14001—environment nexus from three distinct points of view: BRICS, MINT, and G7 countries from 1999–2020. Also, our work fills an extant gap in assessing structural change and innovation’s role in augmenting the relationship. The Driscoll and Kraay estimator is employed as an analytical tool for cross-sectional dependence and slope homogeneity, while the fixed effects approach provides sufficient robustness checks on the findings. While some outcomes vary per bloc, others are relatively similar across the three blocs. That is: (1) ISO 14001 shows an abatement portfolio for only the G7 bloc, and the Full sample. (2) Structural change showed potential for abating carbon emissions in all blocs. (3) Technology led to an increase in pollution in all blocs except for the MINT economy. (4) ICT in the form of mobile phones also help reduce carbon emissions in all three blocs except for their composite. (5) Renewable energy helps reduce carbon emission in all blocs except for G7. ISO 14001 shows the potential to encourage green growth. As a result, policymakers should work to enhance ISO 14001 certification, which might serve as a management tool to promote sustainable development.

Cosine and cotangent similarity measures for intuitionistic fuzzy hypersoft sets with application in MADM problem

Intuitionistic fuzzy hypersoft sets (IFHSSs) are a novel model that is projected to address the limitations of Intuitionistic fuzzy soft sets (IFSSs) regarding the entitlement of a multi-argument domain for the approximation of parameters under consideration. It is more flexible and reliable as it considers the further classification of parameters into their relevant parametric valued sets. In this paper, we proposed some trigonometric (cosine and cotangent) similarity measures and their weighted trigonometric similarity measures (SMs). Trigonometric Similarity measures (SMs) for intuitionistic fuzzy hypersoft sets (IFHSSs) are significantly implied to check the similarity measures and help to determine the similarity between different factors. Also, in order to evaluate the validity of the significant study and apply the results to a daily life problem. We use them to solve problems involving the selection of renewable energy sources. According to several technical contributing factors, the analysis identifies the ideal location for the implementation of the energy production units. Future case studies with many features and additional bifurcation along with multiple decision-makers can use the suggested methodologies. Also, several existing structures, such as fuzzy, Pythagorean fuzzy, Neutrosophic theories, etc., can be utilized with the suggested method.

Energy choice and women’s economic empowerment among the rural households in Southern Ethiopia

Access to reliable and affordable energy is crucial for women to carry out household duties efficiently, including cooking and cleaning. However, many women in developing countries still lack access to modern energy sources, which strains their time, health, and overall well-being. This study investigates the relationship between women’s economic empowerment and energy choices among rural households in the Southern Nations, Nationalities, and Peoples region of Ethiopia. Utilizing a multi-stage cluster sampling design, 569 households were selected from six randomly chosen woredas (districts). Employing a multinomial model, the research explores factors influencing energy source selection. The findings reveal that a majority of households rely on traditional energy sources, with a positive correlation observed between women’s economic empowerment, as measured by the CWEEI, and the adoption of modern energy sources. Additionally, household size and income significantly predict energy source choices. This study underscores the pivotal role of women’s economic empowerment in promoting cleaner energy use in rural settings. Policymakers and program implementers are urged to consider household size and income levels when formulating effective energy programs and interventions.

Spherical fuzzy sets based integrated DEMATEL, ANP, VIKOR approach and its application for renewable energy selection in Turkey

Renewable energy continues occupying the global agenda for the low-carbon transition. Identifying suitable sources for renewable energy involves different criteria and alternatives, which can be defined as a Multi-Criteria Decision-Making (MCDM) problem. MCDM methods can be enriched with Group Decision Making (GDM) to merge individual judgments into group opinions, as well as with fuzzy sets to better simulate human opinions. To handle uncertainties of DMs’ preferences, a recently developed fuzzy set extension, the Spherical Fuzzy Sets (SFSs), is combined in this study with different MCDM tools to establish a decision support tool for the energy source selection problem. This article proposes a novel MCDM approach that integrates SF-DEMATEL (Spherical Fuzzy Decision-Making Trial and Evaluation Laboratory), SF-ANP (Spherical Fuzzy Analytic Network Process), and SF-VIKOR (Spherical Fuzzy Vlse Kriterijumska Optimizacija Kompromisno Resenje) algorithms in a GDM environment and presents its application in a case study for selecting renewable energy sources in Turkey. Comparing wind, geothermal, solar, hydropower, and biogas, the proposed method highlighted both wind and solar energy as a compromise solution as the most suitable options for Turkey. It has been found that compared to similar fuzzy sets, SFS can better reflect the hesitation degree to address the lack of knowledge and errors in the membership function definitions. The robustness and plausibility of these findings are demonstrated with sensitivity and comparative analyses, suggesting this MCDM method can also be applied to similar problems in other settings.

The evaluation of renewable energy alternatives in Turkey using intuitionistic-fuzzy EDAS methodology

In recent years, high energy costs, increases in carbon emissions, and concerns about energy supply security have led countries to prioritize renewable energy sources in their sustainable energy policies. The selection and ranking of alternative renewable energy sources is a critical issue in establishing an effective energy policy and ensuring environmental improvement at the national and global levels. This study evaluates Turkey’s best renewable energy options using the institutional fuzzy assessment based on distance to mean solution (IF-EDAS) method and aims to find Turkey’s best renewable energy alternative. The decision model alternatively uses wind, solar, geothermal, biomass, wave, hydroelectric, and hydrogen energy options. According to the study’s empirical findings, while the best alternative renewable energy source for Turkey is solar energy, the best criterion in terms of criteria evaluation is “Technology Maturity”. The study also carried out sensitivity analysis, and the results were shared.

Techno-Economic Assessment of a Hybrid Renewable Energy System for a County in the State of Bahia

Installation of hybrid systems with storage is a way to maximize the amount of energy generated through exploring the complementarity of different sources. Understanding hybrid power plant (HPP) operation is crucial for optimizing new systems and reconfiguring existing plants, to their enhance efficiency. Alongside technical aspects, economic feasibility is also a fundamental feature. This study simulated an off-grid HPP to consider the energy consumption of Casa Nova in Bahia, Brazil. The methodology consisted of the selection of energy sources, choosing a reference location, acquisition of generation and operational data, modeling and simulating the system in different scenarios, and a financial analysis. HOMER Pro software Version 3.16.2 was used to optimize the plant configuration, and the outputs were evaluated using the perspectives of levelized cost of energy (LCOE), simple payback, and power load fulfillment. As a result, scenario 3 was the most competitive, emphasizing that the use of different energy sources increased the system generation capacity. However, the addition of battery energy system storage (BESS) resulted in a high LCOE when compared to individual sources, which demonstrated that the cost of battery integration is not yet nationally competitive. Moreover, the results highlighted the importance of research investments, energy governance, and regulation in promoting hybrid system adoption.

Selection of a reliable energy source suppling domestic hot water (DHW) system in the kindergarten – a case study

Renewable energy sources (RESs) are used more and more frequently as energy sources for heating and domestic hot water (DHW). However, there are many factors influencing the energy efficiency, thus also ecological benefits. Before making a decision what kind of RES is useful and reliable, a comprehensive analysis should be conducted taking into account technical, financial and ecological factors. This paper discusses different variants of energy sources that could be applied in a kindergarten building for preparing hot water, in place of existing solution (district heating system, DHS). An air heat pump (AHP) with photovoltaic panels (PV) were considered the most reliable energy sources in the analysed building, in terms of economic and environmental considerations. The simple payback time (SPBT) for this investment was estimated as 14.55 years. This solution causes the lowest CO2 emissions. Another system with solar collectors supplying hot water preparation in the heat center can be also recommended. The simple payback time in this case was slightly higher (14.94 years) and what is more, a decrease in CO2 emissions was observed compared to the actual conditions.

Effective hydropower renewable energy source selection using fuzzy neutrosophic boundary approximate area

Small hydropower plants in rural areas are contributing to marginal economic growth and social progress, but their social sustainability assessment is under-studied. Previous studies have shown that no single renewable energy source (RES) can fully meet all sustainability criteria, despite their focus on single-user systems. Scaled renewable energy systems have varying impacts across different systems, involving technical, environmental, social, and economic aspects. This paper proposes a Triangular Fuzzy Neutrosophic Numbers (TFNNs) as an extension of the multi-attributive border approximation area comparison (MABAC) method for hybrid multi-criteria decision-making (MCDM). The proposed method is utilized to assess the selection of hydropower as the most efficient and sustainable renewable energy source for society. Pairwise comparison matrices were used to determine priority vectors and weighted averages of indicators for seven criteria. The evaluation framework analyzed five key dimensions of hydropower plants. The most stable renewable energy source, pumped storage hydropower (60.78%), was found to be followed by run-of-river hydropower (56.39%), impoundment hydropower (50.03%), storage hydropower (39.78%), and offshore hydropower (07.95%). The study offers valuable insights for policymakers and implementer on sustainable electricity solutions for hydropower. Pumped storage hydropower (PSH) improves facility efficiency by ensuring optimal operation of coal and nuclear generators without energy loss. The system can provide a stable and reliable power storage solution for renewable energy sources like wind and solar.

Review and Bibliographic Analysis of Metaheuristic Methods in Multicriteria Decision‐Making: A 45‐Year Perspective Across International, Latin American, and Colombian Contexts

This study performs a systematic review and analysis of research on the use of multicriteria decision analysis (MCDA) methods for more than 45 years. More than 34,468 documents related to MCDA were identified in more than 130 countries, with an annual increase of 14.15% in scientific production. India, China, and Iran lead in number of publications, covering about 35%. The universities with the most publications include Islamic Azad University and Vilnius Gediminas Technical University. The main journals in this field are Expert Systems With Applications, Sustainability, and Journal of Cleaner Production. The most prolific authors are Zavadskas, E.; Wang, J.; Tzeng, GH; Zavadskas, EK; and Kahraman, C. The most popular methods are TOPSIS, AHP (analytic hierarchy process), VIKOR, PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluation), and ANP. LATAN, which includes countries such as Brazil, Chile, and Mexico, has increased the use of MCDA in recent years. Colombia has also shown a great interest in MCDA, especially in the selection of alternative energy sources and industrial suppliers. This method of literature review provides a comprehensive overview of research at MCDA and offers valuable information for future projects and studies.

A robust decision-making approach for the selection of an optimal renewable energy source in India

The evaluation of alternate energy sources to select an appropriate one has always been an important matter of consideration for investors and project engineers, especially for developing countries like India. This necessitates the need for a robust approach where the scope of the decision making process increases and the results can be analysed through different perspectives in scrutiny. This study presents a novel robust approach to assist in the decision making process in the field of sustainable energy and uses India as a case study to define the scope for India's renewable energy development. It implements Entropy and CRiteria Importance Through Intercriteria Correlation criteria weighting methods and eight distinct multi criteria decision making methods to rank the renewable energy sources so as to select the optimal one. The ranking results establish solar to be the best alternative for energy production in India. Wind and biomass stand at second and third places interchangeably in the aggregate rankings obtained in the case of Entropy and CRiteria Importance Through Intercriteria Correlation weights, whereas hydro is ranked last. Furthermore, sensitivity analysis is carried out to check the influence of the criteria weights on the decision, and to measure the stability and robustness of the methods used in this approach.

Mitochondrial metabolic flexibility is critical for CD8+ T cell antitumor immunity.

Mitochondria use different substrates for energy production and intermediatory metabolism according to the availability of nutrients and oxygen levels. The role of mitochondrial metabolic flexibility for CD8+ T cell immune response is poorly understood. Here, we report that the deletion or pharmacological inhibition of protein tyrosine phosphatase, mitochondrial 1 (PTPMT1) significantly decreased CD8+ effector T cell development and clonal expansion. In addition, PTPMT1 deletion impaired stem-like CD8+ T cell maintenance and accelerated CD8+ T cell exhaustion/dysfunction, leading to aggravated tumor growth. Mechanistically, the loss of PTPMT1 critically altered mitochondrial fuel selection-the utilization of pyruvate, a major mitochondrial substrate derived from glucose-was inhibited, whereas fatty acid utilization was enhanced. Persistent mitochondrial substrate shift and metabolic inflexibility induced oxidative stress, DNA damage, and apoptosis in PTPMT1 knockout cells. Collectively, this study reveals an important role of PTPMT1 in facilitating mitochondrial utilization of carbohydrates and that mitochondrial flexibility in energy source selection is critical for CD8+ T cell antitumor immunity.

Integrated energy planning approach for accelerating energy transition of households

The success of energy transition planning depends on several influential and variable factors that need to be considered and tracked in modeling to support policymakers. Expert-based energy models are mainly developed following the assumptions of experts and, in most cases, a limited number of stakeholders. This top-down modeling approach will provide satisfactory results in centrally managed energy sectors (electricity generation and distribution, district heating, etc.), where further decisions could be projected relatively precisely. However, the same approach will not provide such certain outcomes in energy sectors where numerous heterogeneous individuals make decisions about the energy future. Households are a typical example of such a sector. The future structure of energy consumption in this sector, selection of energy source, or application of specific technology, especially in households with individual heating systems, introduce significant uncertainty in expert-based energy modeling and the creation of policy. Besides prices, the decisions of households are influenced by their attitudes, social environment, and incentive measures, etc. The influence of these factors on the adoption of sustainable heating by households can be examined using a bottom-up modeling approach, like the agent-based simulation model. The output of the agent-based simulation model provides useful data that can be further incorporated as one of the main assumptions in scenario development in an expert-based energy model. This paper offers an integration of these two approaches (bottom-up and top-down) for the early assessment of supporting measures and mechanisms for accelerating the energy transition in the household sector. The integrated approach is applied and tested for exploring pathways and effects of policy measures on the transition of individual heating in the household sector in Serbia.

Selection of optimum green energy source under smart city environment for sustainable energy management and planning: An eclectic decision

The purpose of this paper is to present a decision support framework, able to assess and optimize the energy use in smart cities. This paper has taken a sincere endeavour to develop an innovative integrated analytical framework as a benchmark to understand to what extent the energy has been consumed in smart city spectrum. Initially five sectors (construction, water management, transport, waste treatment and public services) of smart city and their corresponding sub-factors are identified based on industry, academia partnership. Once the data were gathered, those were analysed using various statistical tools. This research is useful for the policymakers, executive people, especially those are working or involved in smart city development projects. The developed framework helps to identify the significant energy consumption sector and also suggest the suitable green energy alternatives for developing a cleaner and sustainable future. As this study discusses the various parameters related to smart city energy consumption sector in western India, it will have a huge practical potential on the proposed operational smart cities in India. Literature has witnessed minimum number of studies have been carried out on this proposed framework and that could improve the wellbeing of the people living in the cities.