Towards efficient implementation of solar plants: A priority analysis through multi-criteria decision approach

In manufacturing firms, there is a critical need for proper maintenance of manufacturing facilities. The maintenance process enhances customer satisfaction and reliability of the products, and increases the profit of the manufacturer. Therefore, a proper maintenance policy selection is a critical issue for manufacturers, as an inefficient maintenance policy affects not only the direct cost of the firm but also the other aspects. In the present study, maintenance policy selection at the level of the firm rather than the equipment level is shown, and for selection various criteria have been identified. The presented work not only provides the best alternatives but also provides an alternative ranking, which facilitates decision-makers in choosing alternatives according to their constraints. These selection criteria are different in nature, as some give a crisp value, whereas others are defined in linguistic terms. To select the appropriate maintenance policy, a distance-based fuzzy multicriteria decision-making (MCDM) approach has been employed. The proposed method provides the means for integrating the economic figure of merit with the strategic performance variables. The MCDM approach is efficient in incorporating data, in the form of linguistic variables, triangular fuzzy numbers, and crisp numbers, into the evaluation process of maintenance policy alternatives. A comprehensive example illustrates the application of the distance-based fuzzy MCDM approach.

Selection of materials using compromise ranking and outranking methods

Websites are important in every organisation and tremendous effort is made to design websites that not only look and feel good, but are usable and of high quality. Nevertheless, one critical task is how to evaluate these websites to ensure that users are satisfied with its quality and usability. Although a variety of methods and approaches have been proposed, there is currently an increase in research efforts to model website quality and usability evaluation from the point of view of decision-makers which existing methods do not handle. Thus, this has led to the application of multi-criteria decision-making (MCDM) approaches in the evaluation of websites to handle complexity in decision-making. This paper, therefore, provides a review of the various MCDM methods that have been used in the usability and quality evaluation of websites. The search strategy which was adopted identified a total of 63 published articles in peer-reviewed journals and international conferences between 2005 and 2017. From the research questions formulated for the study, the papers were classified into various MCDM approaches, website genre, number and list of criteria used over the years and the localization of websites based on country. Some of the findings showed that the Analytical Hierarchy Process approach integrated with fuzzy logic has been the most common method over the years. In addition, e-commerce websites make up the most common website genre. Besides, currently most active websites are from Turkey and five is the average number of criteria for the evaluation of website quality and usability.

A comprehensive review of multi criteria decision making approaches based on interval type-2 fuzzy sets

Evaluation of extracting biomass energy using a strategic decision support system

Over the past decade, Multi-Criteria Decision Making (MCDM) has become a foundational tool in energy system design. Numerous technical methodologies and algorithms are available for evaluating and designing energy systems, optimizing either single or multiple criteria. MCDM aids decision-makers (DMs) in solving complex problems, such as site and supplier selection, ranking, and assessment. This paper provides a comprehensive review of both historical and contemporary MCDM techniques referenced in the literature. India is a rapidly developing and highly populated country with a high demand for energy to sustain its economic growth. To meet this demand, the Indian government want to achieve a target to increase the share of renewable energy upto 40% of the total installed capacity by year 2030. This target is a clear indication of the potential for hybrid renewable energy in India. We select solar and wind energy sources among various renewable energy sources based on various study that choose the optimal site selection criteria among them. we provide an overview of recent research on the application of MCDM for the selection of renewable hybrid power plants and identify that social factor is one of the main criteria that play a crucial role in site selection. Several MCDM methods have been applied to the selection of renewable hybrid power plants and compare them for optimal result. The use of sustainable MCDM techniques can help in the evaluation of the suitability of the sites based on multiple criteria. It increases the flexibility and sensitivity of the decisionmaking efforts in such type of approach. This approach allows to comprehensively and effectively assess and tackle the impending issues in the field of renewable energy. These techniques can use in site selection in other industry.

The study prioritizes sub‐watersheds (SWs) from the Taleqan Watershed in Iran based on Flood Generation Potential (FGP) using Multi‐Criteria Decision Making (MCDM) approaches, including Condorcet, Borda scoring, Fallback bargaining algorithms (Game Theory [GT]), and Best‐Worst Method (BWM), and compares the results with observed discharge data. Based on a review of reliable resources, 30 geo‐environmental criteria were identified to prioritize FGP. Quantitative values for each criterion were then calculated for all SWs. The Principal Component Analysis (PCA) was employed to reduce the FGP conditioning criteria. Next, using the decision matrix based on the selected criteria, three GT algorithms and BWM were applied, and the SWs were prioritized accordingly. FGP maps were then created using all four approaches, with results categorized into five classes, namely, very low, low, moderate, high, and very high. Finally, the prioritization patterns from the MCDM approaches were compared against observed discharge data from all 18 SWs to select the optimal method. The results from all four MCDM approaches indicated that SW5 had the highest potential for flood generation. The BWM approach classified about 56% of the study watershed as having low or very low FGP. In contrast, GT identified only 45% of the area in this category, with approximately 39% of SWs classified with high or very high FGP. The comparison of means using the One‐Way ANOVA test revealed insignificant differences between the MCDM approaches and the observed discharge data. However, the similarities between the results of the Condorcet, Borda scoring, Fallback bargaining, and BWM approaches, compared with the observed discharge data, were 27.78%, 27.78%, 33.33%, and 44.44%, respectively. Accordingly, the BWM approach with the highest similarity was chosen as the optimal model. The summary indicated that the BWM approach outperformed the GT algorithms in mapping flood generation compared to the observed flood discharge data.

Given the ambitious targets of carbon emission reduction set for the very near future, it is now expected that retrofitting operations on existing buildings aim both at reducing their operational energy consumption and at improving their seismic performance. Indeed, it is now well acknowledged that, if a sole energy efficiency upgrade is provided to a given building, in case of an earthquake occurrence, double economic and environmental losses will be experienced due to both the lost investment for energy retrofitting and the repair and retrofitting activities for post-earthquake damage. Moreover, social losses may also be experienced in terms of casualties, injured or homeless due to the seismic and structural deficiencies of the existing structure. To aid thus the process of a coupled seismic/energy renovation of the existing building stock, several multi-criteria decision-making (MCDM) approaches have been developed for the identification of optimal retrofitting solutions for buildings. Such procedures typically consider a range of economic, social, technical, and, more recently, environmental aspects that are assumed to be of interest to decision makers (e.g., installation cost, duration of works, architectural impact, need for specialised workers, etc.). The present study demonstrates the application to a case-study school building of two different MCDM approaches, which account for seismic vulnerability and energy efficiency, as well as related environmental impacts of buildings. The main differences between the two procedures are explored in terms of considered decision-making parameters and corresponding weights, rankings of retrofitting options and identification of the optimal retrofitting strategies.

Accident-prone road section (APRS) treatment is the most effective strategy for accident reduction. Because use of multicriteria decision making (MCDM) in the decision process improves the quality of the decision, especially in problems involving multiple criteria, MCDM approach may be the appropriate approach for APRS determination. In this study, an MCDM-based methodology was developed for the determination of APRSs. Weighted linear combination method was used to combine criteria. Because use of experts' opinion for criteria weight determination in MCDM studies may bring subjective results, all possible criteria weight combinations (with some simplifications) were tried to determine the best weight combination. “Relative risk” was used as common unit for criteria standardization and past accident data is utilized to express the “relative risk”. The methodology was tested on D850 State Highway, Tokat, Turkey. Five criteria (horizontal alignment, vertical alignment, intersections, significant places, shoulder width) were used in the process. At the end, although 63 out of 94 sections (67.02%) were labeled as “accident prone”, 173 out of 206 accidents (83.98%) take place in these sections. Therefore, the methodology can be used for APRS determination. Also, the effect of any change in the road properties on the accident-proneness can be simulated by simply changing the criterion values.

Transportation of petroleum-based products is a complex and hazardous logistics process. Selecting the appropriate transportation vehicles for this process is crucial for ensuring safety and efficiency. Therefore, prioritizing selection criteria and choosing the most suitable fuel tanker is essential in reducing potential risks and improving overall fleet operations. Given the many types of tankers available for petroleum product transportation, decision-makers should employ a multi-criteria decision-making (MCDM) approach to identify the best option for their specific needs. This study introduces a novel MCDM approach that combines the Weighted Aggregated Sum Product Assessment (WASPAS) and the Criteria Importance through Intercriteria Correlation (CRITIC) in a Fermatean fuzzy (FF) environment, addressing five main criteria and evaluating five fuel tanker alternatives. Using this approach, the research identified and prioritized key criteria for selecting an appropriate tanker model by providing insights into 24 sub-criteria. The results reveal that tanker price emerges as the most important sub-criterion, leading us to determine the M3 tanker model as the most suitable fuel tanker after carefully evaluating all 24 different sub-criteria. The findings can significantly assist petroleum firms in making informed decisions when choosing fuel tankers by considering various technical, operational, comfort, environmental, and economic factors. The results can also be used to inform policy on fuel distribution.

Evaluation of energy alternatives for sustainable development of energy sector in India: An integrated Shannon’s entropy fuzzy multi-criteria decision approach

An innovation of Renewable Energy (RE) sources promises to bring down costs and starts to deliver a clean energy future without compromising reliability. Renewable energy resource selection comes under the domain of multi-criteria decision making (MCDM) problem as it includes multi-conflicting criteria, namely social, technological, environmental, economic, and political. MCDM methodologies are used in order to select preferred alternative resources because of the presence of complexities in energy planning and energy projects. This paper presents an integrated TOPSIS-Z MCDM method for the selection of optimal RE. The pairwise decision matrix is formed by the decision-makers (DM), which is represented in the Z-number, and weights are evaluated. TOPSIS is used to evaluate and rank suitable RE sources. To validate the efficacy of the proposed methodology, Spearman’s Rank Correlation Coefficient (SRCC) is used and the proposed methodology is compared with various other MCDM methods such as ARAS, VIKOR, and COPRAS.

Renewable energy sources are the most necessitated natural energy to reduce fossil fuels globally. Fossil fuel is the most valuable and limited resource on the planet, but on the other hand, renewable energy creates less pollution. Solar energy is the most effective renewable resource for daily use. Solar power plants are necessary for domestic and daily use. Remote sensing and geographic information technology (GIS) were used for this study to delineate the possible site selection of solar power plants in Kolkata and the surrounding area in West Bengal, India. The analytical hierarchy process (AHP) and the multi-criteria decision-making process (MCDA) were used for each weight calculation and ArcGIS v10.8 was applied for weighted overlay analysis (WOA) for delineation of the result. The site suitability map was developed using a pairwise comparison matrix and the weights were calculated for each criterion. The suitability map was divided into five categories, from not suitable to very highly suitable. A total of 474.21 km2 (10.69%) of the area was classified as very highly suitable whereas 249.54 km2 (5.62%) area was classified as not suitable because of the water area and east Kolkata wetland. A total of 1438.15 km2 (32.43%) of the area was classified as highly suitable for a solar power plant. The Kolkata megacity and water body locations were identified as moderate to not suitable sites. Very high and high-potential sites were identified 2 to 5 km from the central business district (CBD) location, which is Dharmotala. Renewable energy source is needed in the megacity of Kolkata. If solar power plants are contracted then the demand for fossil fuel will be reduced one day, and that will help the environment as well as the society in terms of sustainable development. This study result is helpful for administrators, urban planners, developers, and other stakeholders for the implementation and development of a new solar power plant in the study area.

Background: The search for the use of electrical energy through renewable sources is experiencing significant expansion, particularly at a time when social policies are being implemented with a focus on climate conditions. Solar energy stands out as a renewable energy source with costs that are more accessible than conventional energy sources. Photovoltaic panels for commercial use represent a smart strategy for many companies seeking energy efficiency, cost savings, and sustainability. These systems offer benefits that range from reductions in operational expenses to contributions toward corporate social responsibility goals. Materials and Methods: To conduct this study, two research methods were used: bibliographic research and documentary research. The qualitative approach employed in this article enabled a detailed investment analysis of the elements related to economic engineering applied to solar energy projects. Techniques for economic and financial viability were presented, including Net Present Value (NPV), Internal Rate of Return (IRR), and Payback Period. Results: The findings of the research demonstrated that solar energy is a viable and strategic option for economic growth in Ceará. Considering that Ceará ranks fifth in Brazil for its capacity to generate solar energy, solar power represents a promising investment alternative for the state. The study highlighted the economic and environmental advantages of utilizing solar energy. Conclusion: The research clearly shows that solar energy not only contributes to economic growth but also plays a crucial role in environmental conservation in Ceará. Achieving the objectives reinforces the importance of government policies focused on expanding clean energy sources. These policies will ensure that the benefits of solar energy extend beyond the current scenario, fostering a more sustainable and inclusive future.

Determining the solar radiation for the use of energy generation involves a number of procedures, estimations and calculations using the climatological weather data measurements. The case study was conducted in the Vhembe District area through the nine installed Weather Stations (WS). The analysis determines the minimum and maximum solar radiation equations associated with the local climate patterns in accommodating the theoretical bases and its time period changes. The paper contributes to the main project objectives on renewable (i.e. solar, wind, biomass/biogas and hydro) energy assessment for their potentials and generating at small/ micro scale in the district. These parameters are very important in estimating the solar energy radiation to the area using its extraterrestrial solar radiation per day/ weekly/ monthly and annual periods. The metrology estimations through graphical representations were performed. These provided calculations in which territorial solar energy was determined through climatic conditions and analysis found to be usable.