Sustainability Of Energy Sector Research Articles

A novel interdisciplinary model for optimizing coalbed methane recovery and carbon dioxide sequestration: Fracture dynamics, gas mechanics, and its application

The Carbon Dioxide Enhanced Coalbed Methane (CO2-ECBM) technique significantly enhances clean energy extraction and mitigates climate change. Central to this process is the dynamic evolution of rough fracture networks within coal seams, influencing the migration of CO2 and natural gas. However, existing research lacks a comprehensive, quantitative approach to examining the micro-evolution of these fractures, including fracture roughness, fracture density, fracture touristy, and fracture size, particularly under thermo-hydro-mechanical effects. Addressing this gap, our study introduces an innovative, fractal model for quantitative analysis. This model intricately characterizes fracture networks in terms of number, tortuosity, length, and roughness, integrating them with fluid dynamics affected by external disturbances in CO2-ECBM projects. Upon rigorous validation, the finite element method analysis reveals significant impacts of micro-parameters on permeability and natural gas extraction. For instance, increasing CO2 injection pressure from 4 to 6 MPa changes fracture network density by up to 6.4%. A decrease in fracture density (Df) from 1.6 to 1.5 raises residual gas pressure by 2.7% and coal seam stress by 9.5%, indicating crucial considerations for project stability. Applying the proposed interdisciplinary model to assess CO2 emissions in Australia, it is can be obtained that when Df decreases from 1.6 to 1.5, the total amount of CO2 storage reduces by 17.71%–18.04%. Our results demonstrate the substantial influence of micro-fracture behaviors on CO2-ECBM projects, offering a ground-breaking solution for efficient greenhouse gas reduction and clean energy extraction, with practical implications for the energy sector's sustainability.

Predicting the Production and Depletion of Rare Earth Elements and Their Influence on Energy Sector Sustainability through the Utilization of Multilevel Linear Prediction Mixed-Effects Models with R Software

For many years, rare earth elements (REEs) have been part of a wide range of applications (from cell phones and batteries to electric vehicles and wind turbines) needed for daily life all over the world. Moreover, they are often declared to be part of “green technology”. Therefore, the data obtained from the United States Geological Survey (USGS) on the reserve and production of rare earth elements underwent treatment using the multivariate imputation by chained equations (MICE) algorithm to recover missing data. Initially, a simple linear regression model was chosen, which only considered fixed effects (β) and ignored random effects (Ui). However, recognizing the importance of accounting for random effects, the study subsequently employed the multilevel Linear Mixed-Effects (LME) model. This model allows for the simultaneous estimation of both fixed effects and random effects, followed by the estimation of variance parameters (γ, ρ, and σ2). The study demonstrated that the adjusted values closely align with the actual values, as indicated by the p-values being less than 0.05. Moreover, this model effectively captures the sample’s error, fixed, and random components. Also, in this range, the findings indicated two standard deviation measurements for fixed and random effects, along with a variance measurement, which exhibits significant predictive capabilities. Furthermore, within this timeframe, the study provided predictions for world reserves of rare earth elements in various countries until 2053, as well as world production forecasts through 2051. Notably, China is expected to maintain its dominant position in both reserve and production, with an estimated production volume of 101,985.246 tons, followed by the USA with a production volume of 15,850.642 tons. This study also highlights the periodic nature of production, with a specific scale, as well as periodicity in reserve. These insights can be utilized to define and quantify sustainability and to mitigate environmental hazards associated with the use of rare earth materials in the energy industry. Additionally, they can aid in making informed decisions regarding at-risk rare earth reserves, considering potential future trends in electric vehicle (EV) production up to the year 2050.

Understanding expectations from and capabilities of climate-economy models for measuring the impact of crises on sustainability

The multi-faceted emergencies of our time (recession, pandemics, and international conflict) can disrupt progress towards sustainable development goals (SDGs). While climate-economy models can show pathways out of these disruptions, numerous stakeholder-informed enhancements are required to navigate through the interconnected SDG landscape. We introduce a novel Fuzzy Cognitive Maps (FCMs) approach that integrates Monte Carlo simulations, aiming to capture and understand the differences among modellers' and experts' perceptions of the impacts of such crises on broader sustainability, considering models’ existing/planned capacity and uncertainty over perceived magnitude and propagation of impacts across SDGs. Our application shows that expert stakeholders appeared more concerned over the implications of these crises for sustainable development than modellers, but expectations were considerably constrained by model capabilities. SDGs 8 (growth), 7 (energy-sector sustainability), and 13 (climate action) were robustly found as most prone to examined shocks. Our proposed Monte Carlo Fuzzy Cognitive Mapping (MCFCM) approach also highlighted potentially important propagation effects as well as gaps in integrated assessment model capabilities to holistically study the SDG spectrum.

A systems thinking approach to address sustainability challenges to the energy sector

The energy sector is an intrinsically dynamic and complex system, and therefore its behaviour is not solely controlled by constituent components. Rather, it is a consequence of dynamic interactions among them. To properly manage such a system in a sustainable manner, it is necessary to understand the underlying dynamics of component interactions. Despite this, the interconnections between components of the energy sector in research and policy have received little attention. Here, we outline crucial limitations of previous efforts and emphasize the importance of using systems thinking in addressing the energy sector's sustainability challenges. We demonstrate this by a case study of the Australian energy sector, which has experienced emerging sustainability issues. Research findings show that current policies promoting energy development in the country are likely to be ‘fixes that fail’ that ultimately undermine sustainability. To achieve in building a sustainable energy sector, the policy must focus on implementing long-term solutions and avoid short-term quick fixes.

Biomass woodchip tracking by image analysis in a model of a fixed bed combustor

Energy sector sustainability is one of the main concerns in the recent years. Biomass, in form of woodchips, is interesting for direct combustion in external combustion cycles (e.g. supercritical CO2 Brayton cycles) due to the opportunity of using low quality and low environmental impact fuels. In this study, a direct combustion system working with biomass woodchips is investigated by means of an image analysis technique. The system is made up by a screw conveyor and a fixed bed, where the woodchips are processed. The analysed device operates in cold-condition, and woodchips are partially coloured according to their dimensional class to be traced once these reached the bed surface. A proper algorithm was developed to identify the particles size, define and detect macroparticles centres, and evaluate the main particles motion pattern by comparing the centre positions during time. The results were particularly useful to understand potential inefficiencies of the combustion system due to an uneven woodchips distribution. In addition, the results achieved with the proposed test rig and the adopted methodology can also be used to validate results from Discrete Element Modelling (DEM) simulations.

Multi-criteria decision analysis methods for energy sector's sustainability assessment: Robustness analysis through criteria weight change

Well-optimized decision-making is a prerequisite for effective energy planning, and this requires several criteria to be considered. The multi-criteria decision analysis (MCDA) methods underpin this decision-making process through different techniques. A MCDA method can provide a reliable methodology that helps to organize the most optimized result in the presence of many different opportunities, parameters, and constraints. The selection of an effective MCDA method in the energy sector is challenging. Particularly, sustainability assessment of the electricity generation sector using a MCDA method is difficult as it is necessary to consider at least three different criteria (economic, environmental, and social) with many indicators. This work compares the robustness, with respect to criteria weight change, of seven MCDA methods that are employed to assess the sustainability of electricity generation technologies through a case study. This case study underpins conducting an effective comparison between the employed methods and conclusions drawn. Robustness is defined cumulatively, counting the number of ranking changes while varying the criteria weights by 5%, 15% and 50%. The methods considered are Weighted Sum Method (WSM), Weighted Product Method (WPM), VIKOR, Technique for Order Preference by Similarity to Ideal Solutions (TOPSIS), Performance Ranking Organization Method for Enrichment of Evaluations (PROMETHEE), Analytical Hierarchy Process (AHP), and COmplex PRoportional ASsessment (COPRAS). The analysis revealed that COPRAS is the most robust MCDA method, followed by WPM. The least robust one is found to be TOPSIS. Both AHP and WSM ranked third in the robustness measure.

Corporate Social Responsibility and Corruption: Implications for the Sustainable Energy Sector

This paper focuses on the concept of Corporate Social Responsibility (CSR) and its relationship with sustainability. The authors investigate the linkages between CSR and sustainability at both enterprise and country levels. The main focus of this study is the energy sector due to its importance in terms of economic, environmental, and social impacts. There are some doubts as to whether a socially responsible business meets public welfare expectations and fosters the country’s social and economic development, as well as the successful achievement of sustainable development objectives. However, it becomes apparent that the development of corporate social responsibility in the energy sector faces a plethora of challenges. Corruption is one of the most important challenges of sustainable energy development. The study analyzes the main areas of CSR policies where energy companies are expected to make a positive contribution to sustainable energy development: mitigation of environmental impact, economic and social development, and good governance. The authors argue that the corruption risks represent a very important issue that is hampering sustainable energy development, and CSR can be applied to mitigate these risks in the energy sector. In addition, government policies might be necessary to create a favorable environment for corruption risk mitigation. The study analyzes the main tools of corporate social responsibility in the energy sector and addresses the impact of CSR on the sustainability of energy sector and corruption risk mitigation. The study analyzes a corruption risk mitigation model in the energy sector and provides recommendations for strengthening corporate social responsibility and mitigating corruption risk. Our results show that CSR can play a vital role in dealing with corruption in the energy sector at the enterprise level. It becomes apparent that anti-corruption standards represent the main supporting means for achieving other CSR goals and principles. Therefore, mitigation of corruption risks should become a priority for socially responsible companies that are operating in the energy sector.

To Study the Performance and Emissions Characteristics of Butanol Blended Gasoline Fuel Single Cylinder Spark Ignition Engine

As our country has vast resources including molasses, bagasse, rice husk and wheat husk for production of butanol, utilization of butanol in spark ignition engine will enhance sustainability of energy sector. Butanol is a carbon neutral fuel and octane booster of gasoline. This study is aimed at study of performance and emission characteristics of a spark ignition engine for different butanol-gasoline blends. In the first phase, experimental work was conducted on the spark ignition engine with butanol which volume in gasoline was varied from 10% to 30%. The compression ratio of the engine was maintained as 6.5:1. CO and HC emissions decreased with increase the butanol content in gasoline. This is due to increase in oxygen %age in the fuel. However, NOx emission increased with higher percentage of butanol in gasoline blend. It is observed from this experimental study that latent heat of vaporization of butanol dominates the NOx at lower load resulting to lower NOx where as high temperature due to oxygen content of butanol influences at higher load that results in higher NOx emission. In the second phase, in order to improve the performance and emission reduction of the engine, its compression ratio was increased from 6.5:1 to 8.7:1 by modification of the engine cylinder head. The results indicate the beneficial of the higher compression ratio in terms of performance and all emissions except NOx emission. HC emissions decreased drastically from 115 ppm with B0 to 74 ppm with B20 and CO decreases from 7.62% for B0 to 4.4% for B20.NOx emission is lesser at lower load and conversely it is higher at higher load. It is vary from 107 ppm with zero load to 1013 ppm with B30 at 1500W load. The optimum value of butanol percentage in gasoline is chosen as based on NOx emission.

Efficiency of Energy Consumption as a Base for Sustainable Energy Sector

Lithuania, as many other EU countries, encounters key challenges in three energy sector fields: energy independence, energy sector competitiveness and sustainable energy sector development. Such situation is determined by historical and political conditions, as well as by limited internal energy resources. In such context an importance of energy consumption efficiency pursuing country energy sector sustainability is highlighted. By implementing the long-term goals and tasks a country may seek to increase the efficiency of energy production, distribution and consumption, as well as to increase energy production from renewable and waste energy sources. The main objective of the paper is to analyze the efficiency of energy consumption, the factors influencing energy sector competitiveness and sustainability, and to assess the development soundness of the use of renewable energy sources in Lithuania. The paper discusses the main EU legal documents and their provisions regulating energy sector, analyze energy production and consumption efficiency data in Lithuania and reveal the economic effect of the use of renewable energy sources in Lithuania.

Assessment of Biogas Station Impact on Material Productivity of Agricultural Complex

In search of alternatives for replacing fossil sources with renewable ones, intensive construction of biogas cogeneration power plants started in Latvia in 2008. Maize silage and manure are the most popular substrates used, yet, other alternatives are searched for and tested. It has to be assessed how the energy sector sustainability strategy can impact resource management in the agriculture sector. The aim of this paper is to determine how the introduction of the biogas station in typical agricultural complex consisting of farm and arable land has affected its material productivity. In this paper the biogas production impact on material flows and productivity were evaluated by applying material flow analysis to the case study object which is a traditional intensive farm in Latvia but now reoriented towards the production of electrical and thermal energy. The case study showed that introduction of the biogas station into the traditional farm caused materialization of this economic system, because eco-efficiency (economic output divided by material input) decreased by 41%. The main conclusion is that the biogas production from the biomass is favourable from energetic point of view but current renewable-energy policy in some cases can cause inefficient use of materials putting pressure on surrounding environmental systems and resource depletion.

Negative externalities and sustainability of energy sector

Negative externalities and sustainability of energy sector