Selection Of Renewable Energy Technologies Research Articles

Renewable Energy Technology Selection for Hotel Buildings: A Systematic Approach Based on AHP and VIKOR Methods

This study provides an assessment of renewable energy technology utilization in hotel buildings, which are significant structures in terms of energy consumption. The aim of the study is to determine suitable renewable energy technologies (RETs) for hotel buildings by defining criteria for evaluating RETs, assessing the relative importance of these criteria, and proposing a multi-criteria decision-making framework to solve the problem of selecting the most appropriate RETs during the design stage. The alternatives for RETs and the criteria for their evaluation are gathered through a literature review and expert consultations. Eight fundamental RETs used in hotel buildings (such as heat pumps, solar panels, biomass boilers, etc.) are examined, and nine selection criteria are analyzed. According to the weights determined by the Analytic Hierarchy Process (AHP) method, the initial investment cost is the most influential decision criterion, with a weight of 0.314. As a result of applying the AHP and VIKOR (Multi-Criteria Optimization and Compromise Solution) methods for technology selection, photovoltaic panels emerge as the top-ranked choice. This comprehensive evaluation provides stakeholders in the building production process of hotel buildings with detailed analyses and multi-criteria decision-making methods for selecting RETs.

Designing of new proposed technique for the multi-attribute choice problems: Application to the selection of renewable energy technologies in the Tunisian Electricity and Gas Society case study

The economic importance of the selection of alternative energies in the national scenario tends to be maintained with the optimistic forecast of an increase in production for the years to come in Tunisia. The problem of choosing multiple attributes for the selection of renewable energies is a set of concepts whose purpose is to help the user in a decision-making process. This help provided to the user is designed to be the most online with his preferences. The objective of this study is to answer the following question: How to decide to determine the optimal alternative energies from a large set of available outcomes for this case study according to the decision maker’s preferences? The purpose of this article was to solve multi-attribute choice problems by simultaneously using the choice to essentially define comparative superiority, inferiority, and the flow of non-inferiority as indicators of goodness/poverty evidence. We have developed a new method called Multi-Attribute Superiority, Inferiority and Non-Inferiority Selection Approach (MASINISA) based on the successive elimination Multi-Attribute Decision Making (MADM) to solve the selection of renewable energies in a certain environment: the case of the STEG Company in Tunisia. We can ascertain that the renewable energy technologies belonging to the screened set produced by the proposed MASINISA version were all judged admissible by the experts of the STEG.

Alleviating Energy Poverty through Renewable Energy Technology: An Investigation Using a Best-Worst Method-Based Quality Function Deployment Approach with Interval-Valued Intuitionistic Fuzzy Numbers

Renewable energy technology is suitable for reducing energy consumption and emissions, and the corresponding impact on energy poverty has aroused tremendous attention. This paper proposed the best-worst method- (BWM-) based quality function deployment (QFD) approach within interval-valued intuitionistic fuzzy number (IVIFN) to select the appropriate renewable energy technology for energy poverty alleviation. QFD is firstly used to explore the relationship between energy poverty reduction requirements (CRs), renewable energy technology selection criteria (TRs), and correlation among TRs. Interval-valued intuitionistic fuzzy (IVIF) BWM is then applied for obtaining the correlation among CRs. After that, the IVIF-QFD method is used to attain the weight of TRs, which are then used to evaluate the renewable energy technology alternatives through IVIF-VIKOR approach. The six representative renewable energy technologies, including wind energy, solar energy, biomass (direct combustion, combined heat and power, and gasification), and hydropower have been selected in the decision model, and the result shows that the large-scale hydropower could be selected as the best choice to reduce the energy poverty issues, whose interval numbers is [0, 0.2925]. Except for prioritization of the selected technologies, findings of this paper could also contribute to developing sustainable renewable energy policies and energy roadmaps.

The selection of renewable energy technologies using a hybrid subjective and objective multiple criteria decision making method

The use of renewable energy technologies is a key factor for sustainable development but their selection from several alternatives is a difficult task that relies on the careful assessment of relevant criteria. While Multiple Criteria Decision Making (MCDM) methods have been used successfully in various renewable energy technology selection problems, the decision process becomes more challenging when preferential judgements are made on the basis of non-homogenous and imprecise input data, and when there is uncertainty due to disparities among decision makers. This paper presents a hybrid MCDM method capable of overcoming these problems by taking into account quantitative and qualitative data under a probabilistic environment in the context of group decision making. In this method, qualitative data is fuzzified and used along with quantitative data to develop a hybrid model. A coefficient factor allows decision makers to vary the weight of each quantitative model so that the resultant criteria weights and overall alternatives’ scores consider both subjective considerations and objective information. An example is presented to showcase the usability of the method developed for ranking and evaluating renewable energy technologies in the mining industry. In addition, the impact of different coefficient factors on the final results was assessed by means of sensitivity analysis. The results indicate that the method developed is able to minimise the loss of valuable objective information, caused by the subjective bias of qualitative weights during the evaluations, by adjusting the coefficient factors of the hybrid model during the calculations.

A multi-granular linguistic distribution-based group decision making method for renewable energy technology selection

The scarcity of resources requires a decrease in nonrenewable energy consumption, which progressively promotes the development of renewable energy due to its immense potential and environmental friendliness. Hence, the use of renewable energy technology is critical for realizing the economic effect, the environment effect and the social benefit unified. Generally, renewable energy technology selection is treated as a multiple criteria group decision making problem. However, decision makers are not allowed to express multiple preferences via personalized linguistic distribution assessments deliberating on diverse criteria in the existing approaches. This work proposes a multi-granular linguistic distribution-based group decision-making method by linking multi-granular linguistic distribution assessments and LINMAP (Linear Programming Technique for Multidimensional Analysis of Preference) method with a mathematical model that can simultaneously yield the credible weights of the considered criteria and prioritize the sequence of optimal renewable energy technologies. To this end, the linguistic distribution-based Hellinger distance measure and linguistic hierarchy-based multi-granular linguistic distribution transformation method are proposed. The decision framework is applied to a case study of power generation-based technology selection, generating reliable criteria weights and yielding acceptable outcomes based on collected assessments. Eventually, the sensitivity analysis and comparative analysis are conducted to verify the feasibility and practicability of our proposal. This flexible decision support technique is geared towards managers and strives to provide reference and inspiration for renewable energy technology selection.

Assessing the technical potential of ASEAN countries to achieve 100% renewable energy supply

Pathways to limit global temperature rise to 1.5 °C in line with the Paris Agreement long-term temperature goal and achievement of Sustainable Development Goals involve energy system transitions with strong uptake of renewables by 2050. Fossil fuels currently dominate the energy systems of the ASEAN countries, a region that has abundant untapped renewable resources. This paper expounds an approach of how the ASEAN region may substantially increase uptake of renewable energy. It provides an overview of the shortfalls in energy targets and investigates the technical potential of a selection of renewable energy technologies throughout the region.The findings demonstrate confidence that an energy system decarbonisation pathway for the ASEAN region is possible, however, current policies and action are lacking for achieving any level of decarbonisation by 2050. Further studies are necessary to refine the ASEAN region’s renewable resource technical potential as well as its commercial feasibility based on available technologies. Improvements are also necessary to build confidence in the accuracy of energy statistics to support such studies. Additionally, a review of the ASEAN region’s energy supply system would be required to inform such a feasibility study.

A hybrid multi-criteria decision-making approach to solve renewable energy technology selection problem for Rohingya refugees in Bangladesh

The recent migration of Rohingya refugees from Myanmar has drawn significant attention to Bangladesh. To accommodate these refugees, the government of Bangladesh (GoB1) plans to shift them from Cox’s Bazar to Bhasan Char, which is an off-grid coastal area. Renewable energy technologies (RETs2) could, in fact, be the only option to electrify the region. However, a detailed analysis is required to justify the suitability of different RETs. For this reason, an Analytic Hierarchy Process (AHP3) integrated Combinative Distance-based Assessment (CODAS4) hybrid multi-criteria decision-making (MCDM5) method is proposed to identify the best RET in the study area. The present study considers solar-wind hybrid energy system, solar mini-grid and wind mini-grid RETs for investigation. In total, thirteen sub-criteria under four criteria covering technical, economic, environmental and socio-political aspects were selected based on the agreement of experts. AHP method was deployed to find the weights of the criteria. Finally, a new MCDM method, namely CODAS, was applied to obtain the rank of the RETs. The results reveal that the solar-wind hybrid energy system is the best technology as it obtains the highest appraisal score. A sensitivity analysis was carried out by changing a threshold parameter in CODAS method to check the consistency of the rank order. The comparative study identified the utility of the proposed hybrid MCDM method. Therefore, the proposed method can be identified as effective in enhancing the value of information and can be accepted as a useful tool to ease the decision making problem in the development of RETs in Bhasan Char for Rohingya refugees.

Evaluation of Renewable Energy Technology Based on Reliability Attributes Using Hybrid Fuzzy Dynamic Decision-Making Model

Socio-technical and economic attributes consideration are very important during a renewable energy technology selection for a community. When decision-makers considered these attributes under a dynamic nature, they arrive at a robust decision. Hence, this study proposes an integrated model for renewable energy technologies evaluation under a dynamic condition. We developed the model using dynamic intuitionistic fuzzy Einstein geometric averaging operator, intuitionistic fuzzy entropy, and the intuitionistic fuzzy technique for order of preference by similarity to ideal solution method (TOPSIS). This model’s applicability was tested using five renewable energy technologies - solar (PT1), wind (PT2), hydroelectricity (PT3), geothermal (PT4) and biomass (PT5) and five attributes (risk factor, payback reliability, social benefit, change in demand and cost). Based on five energy experts, from academia and industry, opinions, the proposed model identified biomass energy technology as the most suitable energy technology. Three existing multi-criteria models were used to verify the proposed model; the proposed model performance was consistent with the existing models’ results. From most suitable the least suitable, the model ranked these technologies PT5 > PT2 > PT3 > PT1 > PT4.

A novel VIKOR approach based on entropy and divergence measures of Pythagorean fuzzy sets to evaluate renewable energy technologies in India

Abstract The utilization of renewable energy sources or technologies has grown huge attention from the last few decades. The selection of renewable energy technologies is a laborious task for decision-makers. Therefore, the present study develops a new method using novel divergence and entropy measures of Pythagorean Fuzzy Sets (PFSs) and the Vlsekriterijumska Optimizacija I KOmpromisno Resenje (VIKOR) to evaluate renewable energy technologies. Recently, several studies have been presented regarding PFSs. However, there is very less investigation about the entropy measure of PFSs, particularly there is no study presented for a divergence measure of PFSs in the available literature. Consequently, this paper firstly develops novel information measures for PFSs. Next, the VIKOR method is extended to solve The Multiple-Criteria Decision Making (MCDM) problems with PFSs which the information of criteria weights is completely unidentified. To achieve the significant degrees of the Decision-Experts (DEs) and the criteria, new approaches are determined with the help of two developed measures including Pythagorean fuzzy-entropy and Pythagorean fuzzy-divergence. Moreover, an operation is utilized to PF weighted averaging operator for integrating the individual decision information into a group decision matrix. Further, the proposed PF-divergence measure is implemented to determine the particular measure of closeness of the alternatives in the present method. Finally, to exemplify the efficiency of the proposed approach, a selection problem of renewable energy technologies is presented where the evaluation of the energy alternatives versus each criterion is expressed in terms of Pythagorean Fuzzy Numbers (PFNs). The results of this study demonstrated that the proposed PF-VIKOR was effective to select and evaluate renewable energy technologies.

Aggregation of dual hesitant fuzzy heterogenous related information with extended Bonferroni mean and its application to MULTIMOORA

As an effective evaluation format, dual hesitant fuzzy sets (DHFSs) have became a powerful technique in addressing uncertainty and fuzziness in decision making. Considering the heterogenous interrelationship among attributes, we deeply investigate the extended Bonferroni mean (EBM) and the extended geometric Bonferroni mean (EGBM) under the dual hesitant environment. In this case, some attributes may be related to only a non-empty subset of the rest of the attributes, and others have no relationship with the remaining attributes. Concretely speaking, we develop the dual hesitant fuzzy extended Bonferroni mean (DHFEBM), the weighted dual hesitant fuzzy extended Bonferroni mean (WDHFEBM), the dual hesitant fuzzy extended geometric Bonferroni mean (DHFEGBM) and the weighted dual hesitant fuzzy extended geometric Bonferroni mean (WDHFEGBM) aggregation operators, respectively. At the same time, some of their special cases and properties are investigated. Then, based on the WDHFEBM and the WDHFEGBM operators, we further designs a DHFEBM-based MULTIMOORA method. Before the analysis, we determine the weight information of the attributes with the aid of the attribute significance of rough set theory in advance. Subsequently, the robustness of the ranking MULTIMOORA technique is enhanced by the Bonferroni mean (BM). Finally, an illustrative example of renewable energy technology selection demonstrates the applicability of the proposed method.

An Analysis of the Renewable Energy Technology Selection in the Southern Region of Bangladesh Using a Hybrid Multi-Criteria Decision Making (MCDM) Method

Bangladesh is a country of small char lands and islands. Most of these are out of national grid coverage. Therefore, renewable energy technology is the only solution to electrify. However, proper investigation and research is needed to select the most suitable renewable energy technology. In this study focus is given on the southern region of the country to select the best renewable technology. Based on the current available technology and potentiality of the renewable energy resources in the country five types of renewable energy technology are selected for the evaluation. These are solar, wind, biomass to electricity, biogas to electricity and solar-wind-battery hybrid energy system. To evaluate the best renewable energy technology Multiple-criteria decision analysis (MCDM) method is used where anintegrated Entropy-EDAS model is proposed to identify the best renewable energy technology in the study area. At first, the key criteria and sub-criteria were selected to analysis five (5) types of renewable energy technologies. These criteria were categorised as economic, technical, environmental, and socio-political.Additionally, 12 sub-criteria were selected under the umbrella of four main criteria. Then, the Shannon’s Entropy method was deployed to find the weights of the criteria and sub-criteria. Finally, a new MCDM method named Evaluation based on Distance from Average Solution (EDAS) was applied to select the best renewable energy technology in the study area. The results revealed that the Solar-Wind-Battery hybrid energy system is the best option. The outcome of this study and the decision model might be applicable to other isolated areas in the country, particularly in the southern region of Bangladesh.

Renewable Energy Technology Selection Problem Using Integrated H-SWARA-MULTIMOORA Approach

Due to the adaptation of recent pollution mitigation and justification policies there has been a growing trend for electricity generation from various renewable resources. The selection of the optimal renewable energy technology could be measured as a complex problem due to the complication of forthcoming circumstances in any country. Consequently, the proposed similar complex assessment problem can be tackled with the support of Multiple Attribute Decision Making (MADM) methods. The current research study investigates a technology selection problem by proposing a hybrid MADM approach based on the Step-Wise Weight Assessment Ratio Analysis (SWARA) approach with a hierarchical arrangement combined with the Multi-Objective Optimization on the basis of Ratio Analysis plus the full MULTIplicative form (MULTIMOORA). Ultimately, a conceptual case study regarding the selection of the optimal renewable energy technology based on a conceptual development project in Iran has been examined by the proposed combinative MADM methodology.

Transition towards Renewable Energy Production? Potential in Smallholder Agricultural Systems in West Bengal, India

Renewable energy (RE) production promotes the efficient and sustainable utilization of natural resources at the local level. This study assessed smallholder farmers’ perceptions of RE production in two villages in West Bengal, India. The availability and potential of renewable resources and livelihood characteristics of smallholders were explored. Relevant factors for the selection of appropriate RE technologies were identified, based on the participatory, bottom-up Integrated Renewable Energy Potential Assessment. The research area has abundant solar resources and substantial amounts of organic residues and waste suitable for biodigestion. Important factors for RE technology selection, as stated by farmers, are: ease of daily activities, government support, and limited land requirements. Solar-photovoltaic (PV) systems providing sufficient electricity for household use and irrigation are considered the most appropriate. Key informants focus on initial investment costs, government support, and reduced energy expenditure. They favor solar-PV systems for household electrification. Second choice was an integrated food and energy system that combines solar-PV for irrigation and vermicomposting of organic residues/wastes for fertilizer production. Smallholder famers’ motivation to produce and use RE is high. Their perspective should be integrated in the design of RE-supporting policies and related programs to utilize local natural resources effectively and promote the transition towards renewable energy.

A novel integrated decision-making approach for the evaluation and selection of renewable energy technologies

The decision-making in energy sector involves finding a set of energy sources and conversion devices to meet the energy demands in an optimal way. Making an energy planning decision involves the balancing of diverse ecological, social, technical and economic aspects across space and time. Usually, technical and environmental aspects are represented in the form of multiple criteria and indicators that are often expressed as conflicting objectives. In order to attain higher efficiency in the implementation of renewable energy (RE) systems, the developers and investors have to deploy multi-criteria decision-making techniques. In this paper, a novel hybrid Decision Making Trial and Evaluation Laboratory and analytic network process (DEMATEL-ANP) model is proposed in order to stress the importance of the evaluation criteria when selecting alternative REs and the causal relationships between the criteria. Finally, complex proportional assessment and weighted aggregated sum product assessment methods are used to assess the performances of the REs with respect to different evaluating criteria. An illustrative example from Costs assessment of sustainable energy systems (CASES) project, financed by European Commission Framework 6 programme (EU FM 6) for EU member states is presented in order to demonstrate the application feasibility of the proposed model for the comparative assessment and ranking of RE technologies. Sensitivity analysis, result validation and critical outcomes are provided as well to offer guidelines for the policy makers in the selection of the best alternative RE with the maximum effectiveness.

Integrated assessment of renewable energy potential: Approach and application in rural South Africa

This paper presents the development and application of the Integrated Renewable Energy Potential Assessment (IREPA), employing a three-pronged approach: (i) literature review of renewable energy potential assessment methodologies, renewable energy technology (RET) selection factors and impact assessment methods; (ii) discussions with academic peers from natural and social sciences, and the private energy engineering sector; (iii) evaluation of the IREPA methodology through case-study research in a rural community in South Africa. Locally relevant social, institutional, environmental and techno-economic factors were explored through mutual knowledge exchange with smallholders and subsequently applied for appropriate RET selection. Three barriers to participatory decision-making were revealed: i) lack of knowledge ofrenewable energy among smallholders; ii) insufficient practical information dissemination in IREPA; iii) abstract nature of the analytical hierarchy process. The adaptions recommended by this research would render IREPA a suitable bottom-up approach for the assessment and effective implementation of RET, stimulating socio-economic development in rural areas.

Research on Renewable Energy Technology Selection Model Based on Fuzzy Comprehensive Evaluation in Beijing

At present, China is in a critical period of energy restructuring. Renewable energy industry bear to ensure national energy security and achieve the historic task of energy for sustainable development. To speed up technological innovation of renewable energy industry has been a priority. Conducting systematic research of renewable energy technologies selected, not only can grasp the advantages of renewable energy resources, a clear direction of development of industrial technology, but also to enrich and improve the industrial technology innovation management theory and methods to make a positive contribution. This paper established a renewable three-dimensional evaluation model of industrial technology development (technology needs dimension, technology dimension and the supply of integrated environmental dimensions) ,and took Beijing as an example to calculate the Beijing photovoltaic, wind power, biomass and small hydro renewable energy generation technology evaluation results.

The Evaluation and Selection of Renewable Energy Technologies in China

With the increasing pressure to international energy supply, greater climate and environment problem related to the traditional fossil energy, many countries have decided to develop the renewable energy vigorously. Renewable energy technologies include hydro, wind, solar, biomass, ocean energy and geothermal. Different countries and regions have different choices on renewable energy technology because of their different economic, technical and environmental conditions. The academic has paid more and more attention to the evaluation and selection of renewable energy technology. This paper builds a comprehensive evaluation index system for Chinese renewable energy technology based on analytic hierarchy process (AHP) and data envelopment analysis (DEA), from economic, technology efficiency, social and environmental benefits. The result shows that wind and solar power are more suitable for Chinese economic, technical, environmental and social requirements, followed by biomass, hydropower, ocean energy, geothermal energy.

Selecting Renewable Energy Technology via a Fuzzy MCDM Approach

Renewable energy technology selection, which has a strategic importance for many countries and companies, is one of the most challenging decisions due to the complex features and large number of alternatives. Of all renewable energy sources, solar photovoltaic (PV) energy has attracted more attention as the greatest promising option for industrial application. This paper proposes an extension of fuzzy multi-criteria decision making (MCDM) approach for selecting solar PV energy technologies. In the proposed approach, several PV technologies are used as the alternatives. The ratings of alternatives PV technologies under various criteria and the weights of criteria are assessed in linguistic terms represented by fuzzy numbers. These values are further averaged and normalized into a comparable scale. Then, the normalized weighted rating can be derived by interval arithmetic of fuzzy numbers. To avoid complicated aggregation of fuzzy numbers, these normalized weighted ratings are defuzzified into crisp values using the left and right indices ranking approach. Finally, this study applies the proposed fuzzy MCDM approach to solve a PV technologies selection problem, demonstrating its applicability and computational process.

Selection of renewable energy technologies for a developing county: A case of Pakistan

In this paper some renewable energy options for electricity generation for Pakistan are explored from multiple perspectives comprising technical, economical, social, environmental and political aspects. Analytic hierarchy process (AHP) has been used for the first time for the energy sector of Pakistan. An AHP model has been presented for the selection and prioritization of various renewable energy technologies for electricity generation. After accessing potential of the country for generating electricity from renewable resources, reviewing relevant scholarly literature and discussion with experts, an appropriate decision model has been formulated consisting of goal, criteria, sub-criteria and alternatives. Wind energy, solar photovoltaic, solar thermal and biomass energy options are used as the alternatives in the decision model. Besides ranking and prioritizing of these technologies, results of the proposed decision model can also be used for the development of long-term renewable energy policy and energy roadmap for the country. The findings of this research might also be highly relevant to other developing countries.

Selection of renewable energy technologies for Africa: Eight case studies in Rwanda, Tanzania and Malawi

Renewable energy technologies need to be implemented to improve the current lack of access to energy on the African continent. However, the implementation of renewable energy technologies in Africa often fails, or the technologies are found to be unsustainable in the longer term. Previous research determined eleven factors that should be taken into account for the selection of sustainable, renewable energy technologies in Africa. The purpose of this research was to confirm and build upon these findings by means of eight case studies that were conducted in Rwanda, Tanzania and Malawi. Various individuals from implementing agencies, as well as end users of the various technologies, were interviewed, while secondary data were gathered in the form of project reports and other documentation. The analyses of the data confirm the importance of the eleven factors that were previously identified. A final set of thirteen factors that should be used for the selection of renewable technologies are proposed.