Multiple-criteria decision analysis to substantiate the prospects of industrial and solid municipal wastes as slurry fuel components

This article investigates the recovery of typical wastes (coal slime, sawdust, cardboard and tire pyrolysis residue) as part of high-moisture slurry fuels. Using a laboratory furnace, the ignition and combustion characteristics of fuels as well as NO_x and SO_x emissions were determined. Using multiple-criteria decision-making (MCDM) methods and experimental results, we access the performance of four different slurry fuels in comparison with bituminous coal. The novelty of the study is based on the following features: we consider a unique set of parameters of the fuels (economic, environmental, safety and energy indicators), as well as three countries for their potential use (the USA, India and Russia); three different methods for calculating the efficiency indicator of each fuel were used. Despite rather low energy performance, the summarizing efficiency indicator of waste-based slurries was 53-93% higher than that of coal. The use of cardboard in the composition of a fuel blend showed the best complex result (the increase in the efficiency indicator was 80-93% relative to coal). The least promising additive was the pyrolysis residue of automobile tires. Its addition resulted in a 10-15% decrease in overall efficiency relative to a slurry without additives. The research results are useful for optimizing the component composition of waste-based slurries, technical and economic development of projects for the incineration of various wastes in the form of high-moisture fuel slurries.

Strategies for risk management in adopting Industry 4.0 concept in manufacturing industries

Purpose

This paper aims to concentrate on classifying and analyzing the risks associated with the Industry 4.0 (I4.0) concept in manufacturing industries and developing strategies for managing risks.

Design/methodology/approach

In this research paper, risks categories and their sub-components associated with the I4.0 concept are identified by performing a systematic literature survey of peer-reviewed journal articles and taking inputs from industry experts and academicians. Then, the importance of the identified risks and causal relations among risks are analyzed by using decision-making trial and evaluation laboratory (DEMATEL) method. Finally, the strategies are developed to mitigate the identified risks.

Findings

From the literature survey, 6 risk categories and their 19 sub-components associated with the I4.0 concept are identified. The DEMATEL method resulted in economic risks and technical risks as the top two risk categories in the I4.0 concept. Ecological risks and legal and political risks are relatively low-ranked risk categories.

Research limitations/implications

Causal relations and ranking among risk categories and their sub-components are obtained by analyzing responses received through questionnaires. There are other methods also available for risk analysis, which are beyond this study.

Practical implications

This research paper will help the industrialists to effectively manage the risks involved in adopting I4.0 concept in manufacturing industries by adopting strategies.

Originality/value

This research paper gives an idea about risks associated with the implementation of the I4.0 concept in manufacturing industries. Also, this paper uses the DEMATEL method for ranking the identified risk categories and their sub-components.

Fuzzy Ensemble of Multi-Criteria Decision Making Methods for Heating Energy Transition in Danish Households

More than 110 countries, including 500 cities worldwide, have set the goal of reaching carbon neutrality. Heating contributes to most of the residential energy consumption and carbon emissions. The green energy transition of fossil-based heating systems is needed to reach the emission goals. However, heating systems vary in energy source, heating technology, equipment location, and these complexities make it challenging for households to compare heating systems and make decisions. Hence, a decision support tool that provides a generalized ranking of individual heating alternatives is proposed for households as decision makers to identify the optimal choice. This paper presents an analysis of 13 heating alternatives and 19 quantitative criteria in technological, environmental, and financial aspects, combines ideal solution-based multi-criteria decision making with 6 weighting methods and 4 normalization methods, and introduces ensemble learning with a fuzzy membership function derived from Cauchy distribution to finalize the ultimate ranking. The robustness of the proposed method is verified by three sensitive analyses from different aspects. Air-to-water heat pump, solar heating and direct district heating are the top three rankings in the final result under Danish national average data. A framework is designed to guide decision makers to apply this ranking guideline with their practical, feasible situations.

Multicriteria Decision-Making to Determine the Optimal Energy Management Strategy of Hybrid PV–Diesel Battery-Based Desalination System

This paper identifies the best energy management strategy of hybrid photovoltaic–diesel battery-based water desalination systems in isolated regions using technical, economic and techno–economic criteria. The employed procedures include Criteria Importance Through Intercriteria Correlation (CRITIC) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) as tools for the solution. Twelve alternatives, containing three–four energy management strategies; four energy management strategies, load following (LF), cycle charging (CC), combined LF–CC, and predictive strategy; and three different sizes of brackish water reverse osmosis (BWRO) water desalination units, BWRO-150, BWRO-250, and BWRO-500, are investigated with capacity of 150, 250, and 500 m3/day, respectively. Eight attributes comprising different technical and economic metrics are considered during the evaluation procedure. HOMER Pro® software is utilized to perform the simulation and optimization. The main findings confirmed that the best energy management strategies are predictive strategies and the reverse osmosis (RO) unit’s optimal size is RO-250. For such an option, the annual operating cost and initial costs are $4590 and $78,435, respectively, whereas the cost of energy is $0.156/kWh. The excess energy and unmet loads are 27,532 kWh and 20.3 kWh, respectively. The breakeven grid extension distance and the amount of CO2 are 6.02 km and 14,289 kg per year, respectively. Compared with CC–RO-150, the amount of CO2 has been sharply decreased by 61.2%.

A Systematic Literature Review of Multi-Criteria Decision-Making Methods for Sustainable Selection of Insulation Materials in Buildings

The European Commission has recently adopted the Renovation Wave Strategy, aiming at the improvement of the energy performance of buildings. The strategy aims to at least double renovation rates in the next ten years and make sure that renovations lead to higher energy and resource efficiency. The choice of appropriate thermal insulation materials is one of the simplest and, at the same time, the most popular strategies that effectively reduce the energy demand of buildings. Today, the spectrum of insulation materials is quite wide, and each material has its own specific characteristics. It is recognized that the selection of materials is one of the most challenging and difficult steps of a building project. This paper aims to give an in-depth view of existing multi-criteria decision-making (MCDM) applications for the selection of insulation materials and to provide major insights in order to simplify the process of methods and criteria selection for future research. A systematic literature review is performed based on the Search, Appraisal, Synthesis and Analysis (SALSA) framework and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. In order to determine which MCDM method is the most appropriate for different questions, the main advantages and disadvantages of different methods are provided.

Multi-Criteria Efficiency Analysis of Using Waste-Based Fuel Mixtures in the Power Industries of China, Japan, and Russia

This paper presents the results of analyzing the efficiency of the following five fuel types: dry coal, wet coal processing waste, coal–water slurry, and two waste-derived slurries. In the calculations, we employed 16 criteria related to the energy industry, economy, social aspects, safety at plants, and environmental protection. We used the experimental data, obtained from the combustion of the fuels under study at three heating temperatures (700 °C, 800 °C, and 900 °C). Three countries were analyzed, where all of them have a high share of using fossil fuels in the energy industry: Japan, China, and Russia. The total performance indicator was calculated using three multiple-criteria decision analysis techniques (weighted sum method, weighted product method, and analytic hierarchy process). The choice of weight coefficients was confirmed for each method. We found that coal and coal–water slurry had the lowest integral efficiency indicators (0.016–0.535 and 0.045–0.566, respectively). The maximum effect was achieved when using waste-derived slurry with used turbine oil (0.190–0.800) and coal processing waste (0.535–0.907). There were, on average, 3%–60% differences in the integral efficiency indicator for the same fuel in different countries. The difference in the efficiency indicator of the same fuel in different countries was on average 3%–60%; with changes in temperature, the difference in efficiency was 5%–20%; and when changing the calculation procedure, the difference was 10%–90%.

Multi-Criteria Decision-Making (MCDM) for the Assessment of Renewable Energy Technologies in a Household: A Review

Different power generation technologies have different advantages and disadvantages. However, if compared to traditional energy sources, renewable energy sources provide a possibility to solve the climate change and economic decarbonization issues that are so relevant today. Therefore, the analysis and evaluation of renewable energy technologies has been receiving increasing attention in the politics of different countries and the scientific literature. The household sector consumes almost one third of all energy produced, thus studies on the evaluation of renewable energy production technologies in households are very important. This article reviews the scientific literature that have used multiple-criteria decision-making (MCDM) methods as a key tool to evaluate renewable energy technologies in households. The findings of the conducted research are categorized according to the objectives pursued and the criteria on which the evaluation was based are discussed. The article also provides an overview and in-depth analysis of MCDM methods and distinguishes the main advantages and disadvantages of using them to evaluate technologies in households.

Assessment of Geothermal Fields in the South Pannonian Basin System Using a Multi-Criteria Decision-Making Tool

This paper analyses potential geothermal sites in North-East Croatia which is part of the Pannonian Basin System where a substantial geothermal potential was discovered during hydrocarbon exploration using the Multi-Criteria Decision-Making Tool specially developed for the purposes of the Horizon 2020 project: Multidisciplinary and multi-context demonstration of EGS exploration and Exploitation Techniques and potentials (H2020 MEET). Most of these sites use available geothermal energy potential for commercial purposes, mainly for balneology and more recently for agriculture and electricity generation. The case study involves five different geothermal locations chosen according to their geothermal potential, the current state of production and possible future development, including one oil field that is at the very end of its production life. Three potential final users’ types; agriculture demand, electricity generation demand and district heating have been evaluated for each of the five chosen geothermal sites. The conducted analysis should be of great benefit for further analyses which will be carried out using the aforementioned Multi-Criteria Decision-Making Tool. The performed study showed high consistency of obtained results and actual usage of five geothermal fields.

Inter-Criteria Dependencies-Based Decision Support in the Sustainable wind Energy Management

Decision problems related to the wind energy require considering many, often interrelated and dependent on each other, criteria. To solve such problems, decision systems based on Multi-Criteria Decision Analysis (MCDA) methods are usually used. Unfortunately, most methods assume independence between the criteria, therefore, their application in decision problems related to the wind energy is debatable. This paper presents the use of the Analytic Network Process (ANP) method to solve a decision problem consisting in selecting the location and design of a wind farm. The use of the ANP method allows capturing the complexity of the decision problem by taking into consideration dependencies between criteria. As part of the verification of the solution, the results of the ANP method were compared with those of the Analytic Hierarchy Process (AHP) method, which uses only hierarchical dependencies between criteria. The conducted verification showed that the inter-criteria dependencies may have a significant influence on the obtained solution. On the basis of the conducted sensitivity analysis and the research into robustness of the rankings to the rank reversal phenomenon, it has been found out that the ranking obtained with the use of the ANP is characterized by a higher quality than by means of the AHP.

The Concept of Risk and Possibilities of Application of Mathematical Methods in Supporting Decision Making for Sustainable Energy Development

This study is devoted to presentation of the concept of risk, and the possibility of applying mathematical methods in supporting decision making in the energy sector to promote sustainable energy development. The problem with risk assessment in the energy sector arises mainly due to the difficulty of expressing risk in numerical terms. To avoid risk, it is necessary to set the criteria and objectives of measurement before making decisions in the energy sector. The aim of this study is to try to fill in this gap by means of comparing decisions under risk conditions within models supporting energy decisions. The authors’ focus is on the problem of risk in supporting decision making towards sustainable energy sector development, which is the main target of the European Union (EU) energy policies. Without the ability to determine the probability of occurrence of certain phenomena and their inclusion into the model, it is not possible to determine how well the solutions resulting from the models are accurate, and what is the probability of their implementation under specific conditions linked to renewable energy development.

A System to Pre-Evaluate the Suitability of Energy-Saving Technology for Green Buildings

Rating systems for green buildings often give assessments from the perspective of the overall performance of a single building or architecture complex but rarely target specific green building technologies. As some of the rating systems are scored according to whether the technologies are used or not, some developers tend to pile up energy-saving technologies blindly just for the sake of certifications without considering their suitability for the application. Such behavior may lead to the failure of achieving the energy goals for green buildings. To solve this problem, a system that pre-evaluates the suitability of green building energy-saving technologies is devised based on modified TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) method, SA (simulated annealing) algorithm and unascertained theory-based data analysis method. By setting indices from technology performance, economy, human satisfaction aspects and by using the building prior information and measured database of technology usage, this system can make a quantifiable and multi-dimensional grading assessment for the target green building energy-saving technologies in the design stage. The system aims at helping the designer choose technologies in the design phase that best enhance the performance of the finished green building. It also helps prevent the sub-optimal performance of unsuitable technologies caused by the “pile up” behavior mentioned earlier. To verify this evaluation system, two building designs which use energy-recovery technology are evaluated, and the predicted performance for both designs matched the actual operation of the technology in the buildings themselves well.