Energy Sector Research Articles

Examining the Environmental Kuznets Curve Hypothesis in Energy, Agriculture, and Industry Sectors: The Case of Kazakhstan

Examining the Environmental Kuznets Curve Hypothesis in Energy, Agriculture, and Industry Sectors: The Case of Kazakhstan

Calculation of electrical energy losses in distribution networks for power supply using oil and vacuum circuit breakers

A method for approximate estimation of load losses in distribution networks from 6 to 10 kV, as well as for lower voltage networks, has been proposed. The main advantage of this method is that the root mean square current is calculated only once for a series of calculations. This approach significantly reduces the time required for calculations and improves their accuracy, as it eliminates the need for multiple determinations of the root mean square current for each individual calculation. The proposed approach contributes to a better understanding of the influence of various factors on load losses, which allows for more effective planning and management of distribution networks. This is particularly important in the context of increasing loads on electrical networks and higher demands for their reliability and efficiency. In the calculation of electrical energy losses in distribution networks from 6 to 10 kV, methods that use generalized coefficients of electrical circuits and operating modes in the form of regression equations are widely applied. The most significant and independent factors, such as the input of active energy, total line length, number of line sections, total number of transformers, and their total installed capacity, must be taken into account and are included in the calculation equation. Additionally, the components used and their regular maintenance play an important role in electrical energy losses in electrical networks. The main direction of research is the optimization of distribution network parameters, taking into account the latest technologies and materials, as well as the implementation of automated monitoring and control systems that will allow timely detection and elimination of problems associated with electrical energy losses. The proposed method for estimating load losses in distribution networks is a promising direction for the development of the energy sector, which will contribute to improving the efficiency and reliability of electrical networks, as well as reducing the costs of their operation and maintenance.

Effects of Graphene Reinforcement on Static Bending, Free Vibration, and Torsion of Wind Turbine Blades.

Renewable energy markets, particularly wind energy, have experienced remarkable growth, predominantly driven by the urgent need for decarbonization in the face of accelerating global warming. As the wind energy sector expands and turbines increase in size, there is a growing demand for advanced composite materials that offer both high strength and low density. Among these materials, graphene stands out for its excellent mechanical properties and low density. Incorporating graphene reinforcement into wind turbine blades has the potential to enhance generation efficiency and reduce the construction costs of foundation structures. As a pilot study of graphene reinforcement on wind turbine blades, this study aims to investigate the variations of mechanical characteristics and weights between traditional fiberglass-based blades and those reinforced with graphene platelets (GPLs). A finite element model of the SNL 61.5 m horizontal wind turbine blade is used and validated by comparing the analysis results with those presented in the existing literature. Case studies are conducted to explore the effects of graphene reinforcement on wind turbine blades in terms of mechanical characteristics, such as free vibration, bending, and torsional deformation. Furthermore, the masses and fabrication costs are compared among fiberglass, CNTRC, and GPLRC-based wind turbine blades. Finally, the results obtained from this study demonstrate the effectiveness of graphene reinforcement on wind turbine blades in terms of both their mechanical performance and weight reduction.

Calculation of electrical energy losses in distribution networks for power supply using oil and vacuum circuit breakers

A method for approximate estimation of load losses in distribution networks from 6 to 10 kV, as well as for lower voltage networks, has been proposed. The main advantage of this method is that the root mean square current is calculated only once for a series of calculations. This approach significantly reduces the time required for calculations and improves their accuracy, as it eliminates the need for multiple determinations of the root mean square current for each individual calculation. The proposed approach contributes to a better understanding of the influence of various factors on load losses, which allows for more effective planning and management of distribution networks. This is particularly important in the context of increasing loads on electrical networks and higher demands for their reliability and efficiency. In the calculation of electrical energy losses in distribution networks from 6 to 10 kV, methods that use generalized coefficients of electrical circuits and operating modes in the form of regression equations are widely applied. The most significant and independent factors, such as the input of active energy, total line length, number of line sections, total number of transformers, and their total installed capacity, must be taken into account and are included in the calculation equation. Additionally, the components used and their regular maintenance play an important role in electrical energy losses in electrical networks. The main direction of research is the optimization of distribution network parameters, taking into account the latest technologies and materials, as well as the implementation of automated monitoring and control systems that will allow timely detection and elimination of problems associated with electrical energy losses. The proposed method for estimating load losses in distribution networks is a promising direction for the development of the energy sector, which will contribute to improving the efficiency and reliability of electrical networks, as well as reducing the costs of their operation and maintenance.

Assessment of the Solar Energy Potential over South America Estimated by CMIP6 Models in the Present and Future Climate

Developing the renewable energy matrix of South America (SA) is fundamental for sustainable socioeconomic growth and mitigating climate change's adverse effects. Thus, this study estimates changes in SA's solar irradiance and solar power potential using data from eight global climate models (GCMs) belonging to the Coupled Model Intercomparison Project—Phase 6 (CMIP6). Applying statistical downscaling and bias correction with the Quantile Delta Mapping (QDM) technique, we evaluate projected changes in the Concentrated Solar Power (CSP) and Photovoltaic Power (PVP) outputs under different future climate scenarios (SSP2-4.5 and SSP5-8.5). Historical simulations (1995–2014) are validated using ERA5 reanalysis and CLARA-A3 satellite observations. The QDM method reduces the models' systematic biases, decreasing the ensemble's errors by 50% across SA throughout the year. Regarding future decades (2020–2099), the CMIP6 ensemble shows spatial and seasonal variability in solar generation. For CSP, estimates suggest that regions traditionally favorable to solar energy generation (such as the Brazilian Northeast and portions of Chile) will maintain their suitable conditions during the 21st century, projecting a potential 1–6% increase (particularly under the SSP5-8.5 scenario in southern Chile and most of Brazil). Concerning PVP generation, the CMIP6 ensemble projects a rise of 1–4% (mainly under the SSP5-8.5 scenario in the Amazonia, Midwest, and Southeast Brazilian sectors). Moreover, trend analyses projected individually by the CMIP6 GCMs converge on an increasing PVP, mainly in Brazil's Amazonia and Midwest regions. In contrast, for South Brazil, approximately 84% of the projections show a negative trend (or no trend), evidencing unfavorable or uncertain conditions for solar generation development in the region. Despite the data and processes' inherent limitations, this study yields a first analysis of statistically downscaled projections from CMIP6 for solar power generation in South America, providing valuable information for energy sector decision-makers.

Solar energy generation from residential buildings, transition of the energy sector from fossils to carbon-free energy and meeting UN SDG

Purpose This study aims to focus on the transition of Kosovo’s energy generation sector from fossil fuels (94%), to renewable sources. The installation of 10 kW photovoltaic (PV) panels in individual houses will mitigate CO2 emissions from electrical energy generation and contribute meeting the sustainable development goals (SDGs; 7, 11 and 13) set by United Nations General Assembly. This study case is based on the installation of PV panels on the roofs, and where possible on the facades of the private residential buildings in seven, the most populated towns of Kosovo (Prishtina, Prizren, Mitrovica, Peja, Gjakova, Ferizaj and Gjilan). Design/methodology/approach This study used the data, in regard to direct normal irradiation, altitude, coordinates, PV system configurations, specific PV power output and optimum tilt of PV panels specific for the selected locations,retrieved from Global Solar Atlas, which is a web-based-tool, as provided by “Solargis,”a company that provides online and commercial solar data resources, selected by The World Bank and the International Finance Corporation. The second software was RETScreen Expert, which is more sophisticated and allows input of more variables with regard to the proposed 10 kW PV system. With the use of RETScreen Expert software, the financial viability of the project, the equity payback period, and the reduction in greenhouse gas (GHG) emissions compared to the base case were assessed. Based on the gained data, the feasibility and outcome of the study case were assessed in terms of power generation, cost and comparison with the present PV installed capacities in Kosovo. Findings Small-scale solar energy generated from individual buildings can make great impact of country’s policies toward lowering CO2 emission as one most influential greenhouse gas in rising average global temperature, improving air quality in towns by lowering emission of harmful gases and particulate matter (PM). As the study foresees installation of 10 kW of PV in residential houses, the calculated yearly energy generation would be around 15 MWh, which is twice of the average of real consumption of a household in Kosovo. This calculated energy generation from private houses is equal in capacity with generation of present PV parks that are connected on grid as reported from Transmission, System and Market Operator of the Republic of Kosovo. This proves that, if implemented, the study outcome would make Kosovo to meet the goal for a carbon free energy and meeting targets of at least three out of 17 SDG set by UNSC. Originality/value This paper’s model provides a ground for a transition of national energy sector from 90% fossils dependence to renewable energy sources (RES). Despite of some barriers such as cost of initial investment, energy storage, lack of government’s incentives and legislative base for households to become prosumer or at best energy self-sufficient buildings, this solution will make Kosovo harness its unused RES and meet targets of Paris Climate Agreement for net zero CO2 emissions from energy production by 2050 and SDG targets.

Enabling direct seawater electrolysis by redox-inactive amphiphilic amines via chloride sequestration

Sustainable hydrogen production requires large amounts of treated freshwater and precious metals. Direct electrolysis of seawater without additional electrolytes can be a practical approach to address these limitations, however, it usually suffers from kinetically favored chlorine evolution reaction (CER), which is detrimental to an electrolysis system. We report that organocatalytic amphiphilic diamines play a crucial role in preventing the generation of chlorine gas. The feasibility of direct seawater electrolysis was demonstrated with pH-responsive organic amines, which can self-assemble under neutral and acidic conditions. Electrochemical analysis of our electrolysis in saline solutions revealed that (electro)chemical stability of amphiphilic diamines was responsible for preventing CER and hypochlorite formation. Our findings may have significant implications for the chemical industry and energy sectors as the world transitions towards renewable energy sources.

A three-dimensional finite strain volumetric cohesive XFEM-based model for ductile fracture

The verification/prediction by numerical simulation of the resistance of large-scale metal structures subjected to extreme loading (e.g. accidental mechanical overload) that can lead to failure constitutes a major issue in the transport, energy, and defense sectors. This work aims to develop a three-dimensional numerical methodology (i) capable of macroscopically accounting for the various dissipative mechanisms of plasticity and damage until failure, (ii) formulated within the framework of large deformation, (iii) implemented in a commercial computation code, and (iv) mesh-objective. The commercial computational code is ABAQUS-std, and the methodology is implemented as a user finite element (UEL). Geometric non-linearities are treated within the framework of an updated Lagrangian formulation (ULF). The more or less diffuse damage phase is described by the Gurson–Tvergaard–Needleman (GTN) microporous plasticity model with standard finite element (FE). The micro-void coalescence phase-induced dilation/shear band is described using an original volumetric cohesive extended finite element method approach (VCZM-XFEM). The progressive loss of cohesion leading to ultimate cracking is treated with extended finite element method (XFEM). Particular attention is paid to transition criteria (damage to localization, localization to cracking), to the orientation of the localization plane (especially in Mode II), to the cohesive zone model and to techniques for overcoming numerical difficulties (volumetric locking, numerical integration). The so-built 3D-FS-GTN-VCZM-XFEM unified methodology is capable of reproducing the degradation mechanisms, and, the failure surface shape and orientation in large elasto-plastic deformation of structures typical of laboratory tests, even for fairly coarse meshes.

Efficiency rankings of economic sectors: a focus on sustainability and circularity objectives

Purpose Waste generation poses a significant environmental challenge in the United Arab Emirates due to the rapid urbanization, population growth and industrialization witnessed in recent decades. As a result, there has been a substantial surge in waste production. To fulfil its sustainability and circular economy aspirations in various economic domains, the UAE must prioritize efficient waste management. The purpose of this study is to assess the environmental and energy efficiency of the UAE’s economic sectors particularly within its vital energy sectors, which encompass crude oil, natural gas and mining, manufacturing and electricity, by gauging their adherence to sustainability and circularity objectives. Design/methodology/approach The authors used the data envelopment analysis input–output model to identify sectors that exhibit strong performance as well as those that are falling behind. Findings Based on this study, the agriculture, the crude oil, natural gas and mining sectors and financial services and banking were found to be the most efficient. The results of this study concluded that the UAE is making progress toward achieving its sustainability and circularity objectives; however, the findings suggest that more effort is needed to fully realize these goals. Originality/value By identifying high-performing and underperforming sectors, decision-makers can prioritize efforts to enhance sustainability and circularity in area of greatest need in the economy.

Studies on the development and performance of natural dye-sensitised solar cell

ABSTRACT Dye-sensitised solar cells (DSSCs) have gained popularity as a cost-effective alternative to silicon-based solar cells. The present study, provides a unique approach for the construction of DSSCs using anatase titanium dioxide (TiO2) as the photoelectrode material and natural fruit extracts (blackcurrent and pomegranate) as photosensitisers. To generate a compact and homogenous TiO2 anatase layer, nanoparticles are deposited onto a transparent conducting fluorine-doped tin oxide glass. Subsequently, natural fruit extracts were added to the TiO2 anatase film, functioning as photosensitisers to absorb sunlight and start the electron transfer process. Each fruit extract unique chemical makeup adds to the absorption of various wavelengths, widening the DSSC's light absorption spectrum. A thin graphite coating was applied to a conducting material for the generation of a counter electrode, which completes the DSSC structure. The sensitised TiO2 anatase layer and counter electrode are joined together, with a redox electrolyte filling the gap between them. Current–voltage measurements used to characterise the manufactured DSSC during simulated solar irradiation. The DSSC's efficiency was calculated as 0.4–18% based on the produced photocurrent and incident light intensity. The study’s finding shows that a DSSC can be successfully fabricated because of its low manufacturing cost and low harmful. It has wide applicability in renewable energy sectors.

Quantifying Fiscal Multipliers in South Africa: A Structural Var Approach

Fiscal multipliers have deteriorated in South Africa since the global financial crisis in 2008 and 2009. Weakening fiscal multipliers to a record low of zero has constrained the government’s ability to use fiscal policy measures to stimulate the economy, particularly in the aftermath of the COVID-19 pandemic and recent geopolitical risks affecting the global economy. The current paper quantifies fiscal multipliers in South Africa. The study employed the structural vector autoregressive to quantify government spending and government tax revenue fiscal multipliers in South Africa over the period 2000M01–2023M10. The control variables for the study are government total spending, total government tax revenue, and the production index as a proxy variable for economic activity. This is the first study to employ high-frequency monthly data, which increases the number of observations, thus yielding significant and robust results. The accumulated government expenditure and government tax revenue multipliers are 0.4 and 0.1, respectively. The empirical results are consistent with the Keynesian view that government spending, particularly investment spending, fosters economic growth. Structural reforms in logistics, the energy sector, and education to boost economic growth and improve fiscal multipliers that are currently less than one in South Africa must be adopted as a policy response.

A Novel Function of a Research Process Based on a Power Internet of Things Architecture Intended for Smart Grid Demand Schemes

The global energy sector is currently undergoing a significant transformation to address sustainability, energy efficiency, and grid resilience. Smart grids, leveraging advanced technologies like the power internet of things (PIoT), play a crucial role in this transformation. This research focuses on enhancing the efficiency, reliability, and sustainability of electricity distribution through IoT technologies. It envisions a system where interconnected devices, sensors, and data analytics optimize energy consumption, monitor grid conditions, and manage demand response scenarios. Central to this effort is the integration of PIoT into the smart grid infrastructure, particularly in implementing dynamic pricing strategies for demand response. Leveraging power line communication (PLC) techniques, this innovative approach facilitates real-time communication between grid components and consumers. The results demonstrate improved grid stability through dynamic load management, effectively responding to demand fluctuations, and minimizing disruptions. The deployment of dynamic pricing methods using PLC-driven schemes empowers customers by offering access to real-time energy use data. This access incentivizes energy-efficient behavior. leading to a 30% increase in the adoption of energy-saving techniques among consumers. A utility company pilot study claimed a 12% drop in peak demand after adopting time-of-use charges, with an accuracy rate of 98.87% in total.

Mergers and acquisitions, knowledge base and technological trajectories. An exploratory study in the wind energy sector

ABSTRACT The wind energy sector has increased its technological complexity for the last 20 years, with new technological and convergent domains like advanced materials, complex simulation, and artificial intelligence. In this context, mergers, and acquisitions (M&A) have become a key channel for companies in the sector to absorb new knowledge and develop complementary capabilities. The aim of this article is to trace the recent trajectory of the sector’s knowledge base and to analyze the role of M&A, specially of New Technology Based Firms in the generation of new capabilities through knowledge recombination. Using co-occurrence networks on a unique database of 1,299 companies in the wind sector and their acquired companies, we developed a methodological approach to investigate the trajectory of the wind sector at a global level. The empirical analysis verifies that acquisitions belonging to ‘unrelated’ sectors contribute significantly to the diversification and complexification of the sector’s knowledge base over time.

Empirical design and comprehensive analysis of multiport converter in distributed generation enabled microgrids

Distributed generation-enabled microgrids are a revolutionary approach for the energy paradigms that will transform the ways of generation, distribution, and utilization. A decentralized approach to energy generation in microgrids results in the robustness and independence of energy networks. Empowerment of the communities to take control of energy requirements with multiport converter-based microgrids promotes sustainability, efficiency, reduced losses, and increased resilience against the evolving trends of the energy sector. In this research, a hybrid energy-integrated multiport converter is designed and analyzed under its various modes of operation. Rapid transitions from one energy source to another are attained within 0.4μs to feed the load at a steady state voltage of 400 V, and within 0.15μs to charge the energy storage system at a steady state voltage of 48 V which indicates the robustness and independence of energy systems via this proposed approach. The resilience of the microgrid is obtained because of this rapid trans Moreover, the proposed converter offers a voltage gain of 8.3 with 96 % efficiency making it sustainable for maximization of renewable energy. In addition, the resilience of the proposed converter is exhibited through high power densities at power losses of not more than 7.5 % making it an innovative candidate for hybrid energy systems as compared to existing technologies. Simulation scenarios are validated through mathematical analysis, proving their effectiveness in distributed generation-enabled microgrids. The proposed research model is effective in a real environment because of the minimal effects of parasitic resistance, reduced total harmonic distortion under different loads, and negligible electromagnetic interferences, demonstrated through simulations.

The challenges for gender diversity and inclusion in the wind energy industry and the ESG perspective of organizations

Context: Gender Diversity and Inclusion (D&I) has been a challenge for the energy and renewable energy industry. The wind energy industry has carried out a series of practices and initiatives to fulfil ESG criteria - environmental, social and governance, however the topic of D&I is still a paradigm for sector organizations. Objective: This paper aims to present how the wind industry can promote D&I to meet ESG criteria, specifically, mapping industry challenges to promote D&I practices. Method: The research methodology is a qualitative case study with 10 semi-structured interviews from different executive and managerial positions in organizations in the wind energy sector. Results: The results demonstrated that there are a series of challenges and some ongoing practices, but the gap between these practices and initiatives and the culture of organizations is still a sectoral bottleneck. Contribution: The scientific and practical contribution of the research lies in presenting a kaleidoscope with 5 main challenges for continuing the discussion of D&I in companies, as well as 10 practices reported by interviewees that unfold into a roadmap for the global wind sector.

Discourse and transformation

Abstract This paper sets out to investigate the representation of energy in China’s diplomatic discourse in a context where power structures within and among nation-states are shifting and energy is becoming more politicized. To do this, this research adopts corpus-assisted discourse-historical analysis to examine discursive strategies and investigates the way energy is constructed in China’s diplomacy. Results show a dichotomy of an active ingroup and an indifferent outgroup, revealing a reversal of power in the fierce competition of discourse in the international energy sector, which serves as a catalyst for the creation of demand for new energy sources and the development of new energy industries. The analysis of grounded linguistic evidences also signifies that discourse is the site where power is not only enacted and performed, but also negotiated and contested.

Extreme Weather Events and the Energy Sector in 2021

Abstract In 2021, the energy sector was put at risk by extreme weather in many different ways: North America and Spain suffered heavy winter storms that led to the collapse of the electricity network; California specifically experienced heavy droughts and heat-wave conditions, causing the operations of hydropower stations to halt; floods caused substantial damage to energy infrastructure in central Europe, Australia, and China throughout the year, and unusual wind drought conditions decreased wind power production in the United Kingdom by almost 40% during summer. The total economic impacts of these extreme weather events are estimated at billions of U.S. dollars. Here we review and assess in some detail the main extreme weather events that impacted the energy sector in 2021 worldwide, discussing some of the most relevant case studies and the meteorological conditions that led to them. We provide a perspective on their impacts on electricity generation, transmission, and consumption, and summarize estimations of economic losses.

A whale optimization algorithm-based multivariate exponential smoothing grey-holt model for electricity price forecasting

Accurately forecasting electricity prices is essential for a variety of stakeholders in the energy sector, including market investors, policymakers, and consumers. However, existing forecasting techniques are often limited by complex parametric estimates and strict restrictions on input variables. This paper proposes a Whale Optimization Algorithm (WOA)-based multivariate exponential smoothing Grey-Holt (GMHES) model for electricity price forecasting. The proposed WOA-GMHES(1,N) model uses historical data to learn the underlying trends and patterns of electricity prices. The WOA algorithm is used to optimize the model parameters, which are adaptively adjusted to reflect the changing dynamics of the electricity market. The proposed model is evaluated on real high- and low-voltage electricity price data from Cameroon. The results show that the novel WOA-GMHES(1,N) model outperforms competing models, achieving RMSE and SMAPE scores of 0.1359 and 0.61%, respectively. This novel model is also computationally efficient, requiring less than 1.3 s to generate a forecast. The proposed WOA-GMHES(1,N) model is a promising novel approach for electricity price forecasting. The model is accurate, efficient, and flexible, making it a valuable tool for a variety of stakeholders in the energy sector.

Exploring the Application of Digital Twin Technology in the Energy Sector using MEREC and MAIRCA Methods

Smart city sustainability initiatives prioritize creating environmentally, economically, and socially sustainable urban environments. Digital Twin (DT) technology creates precise digital replicas of physical assets, systems, or processes. These digital twins play a crucial role in advancing the goals of smart city sustainability. This paper explores the development and application of DT technology for integrated regional energy systems in smart cities, emphasizing its potential to optimize energy consumption, reduce costs, and enhance overall system performance. The CloudIEPS platform, an energy internet planning platform based on digital twin technology, is a great example of how digital twin technology can be applied in practice, helping optimize energy efficiency and reduce costs. Integrating digital twin technology with the Multi-Criteria Decision-Making (MCDM) methods offers a novel approach to managing and optimizing energy systems in smart cities. The paper aims to create a consistent and robust approach to determining the best digital twin solution for energy systems in smart cities. The paper identifies critical factors for decision-making and establishes a method for assessing the significance of criteria using Triangular Neutrosophic Sets (TNS) through the MEthod based on Removal Effects of Criteria (MEREC) and the Multi-Attributive Ideal Real Comparative Analysis (MAIRCA) approach. These methods are used to evaluate and prioritize multiple criteria in decision-making processes. Furthermore, the methods are combined with Triangular Neutrosophic Sets (TNS) to support decision-making for smart cities' energy systems, better accounting for the complex and uncertain nature of energy systems. A case study is conducted to apply and validate the developed methodology and perform a sensitivity analysis of the experimental results. The research outcomes indicated that the proposed methodology is robust and effective in handling the uncertainty and complexity inherent in smart cities' energy systems. The sensitivity analysis further confirms the stability and adaptability of the proposed methodology across different scenarios, making it a valuable tool for policymakers and stakeholders in the energy sector.

Trading mechanism for social welfare maximization in integrated electricity and heat systems with multiple self-interested stakeholders

Cooperation across multiple energy sectors is capable of maximizing social welfare as revealed by existing research, but such holistic dispatch can be hardly implemented in a reality where energy sectors are run by different stakeholders respectively. To fill this gap, energy trading among multiple self-interested stakeholders is investigated in this paper. To maximize the social welfare of the trading results, an effective pricing method, referred to as network-constrained generalized locational marginal prices, is proposed. A trading mechanism is then carefully designed to encourage stakeholders to trade at network-constrained generalized locational marginal prices, while economic properties of the resultant generalized Nash equilibrium are analyzed in depth. The effectiveness of the mechanism is validated in two integrated electricity and heat systems with different scales. Numerical comparison demonstrates that existing non-cooperative mechanisms may result in undesirable deadweight losses, while surplus sharing is a tricky issue in cooperative mechanisms, making the cooperation unstable and infeasible. On the contrary, each stakeholder may optimize its subsystem in a self-interested manner in the proposed mechanism, but the overall outcome strikingly coincides with social welfare maximization.