Aggregate Energy Research Articles

The effects of green technology and globalization on energy demand in emerging economies

Preserving energy security and promoting sustainable development in the face of globalization constitute essential challenges. Hence, this study focuses on how green technology innovation (GRTI) and globalization (GLOB) influence renewable (RE) and non-renewable (NRE) energy demand, employing panel data from 15 emerging nations from 1990 to 2023. The study discloses major insights employing several panel data approaches to tackle cross-sectional dependency, slope heterogeneity, and structural breaks in cointegration. The results indicate that a 1% change in GRTI leads to a 0.13% rise in REN at a 1% significance level, whereas its impact on NRE is negligible, reducing it by 0.01% in the long run. Conversely, a 1% increase in GLOB leads to an insignificant 2.62% rise in REN and a significant 1.02% increase in NRE at the 5% significance level. Besides, in terms of aggregate energy consumption, GRTI has an unfavorable impact, whereas GLOB holds a positive impact. Notably, the interaction between regulatory quality (REQ) and IVA implies a substantial fall, although the interaction between GLOB and REQ remains promising for aggregate energy demand. Finally, the COVID-19 epidemic markedly enhanced environmental awareness and energy-saving behaviors beyond the explanatory variables. Policies should encourage green technology innovation and prudent globalization to conserve energy demand.

Technological Progress as a Catalyst for Energy Efficiency: A Sustainable Technology Perspective

Enhancing energy efficiency through sustainable technological progress is imperative for pursuing sustainable development, particularly in developing countries where economic growth is strongly linked to higher energy consumption. In Tunisia, an open and developing economy, fossil energy consumption can be reduced without compromising economic growth by focusing on diminishing energy intensity. This study investigates the effects of technological progress on the overall energy intensity in Tunisia from 1980 to 2019, examining the role that technological advancements may play in attaining sustainable development goals. This study is based on a growth accounting model that uses time-series analysis and a cointegration estimation approach. Our empirical results suggest the presence of a long-term connection between the variables. The attainment of enhanced energy efficiency is contingent on the growth rate of technological progress, which should exceed capital and labor productivity. The results reveal that the net impact of technological advancements is estimated at -0.0163, which signifies that aggregate energy intensity tends to decrease by an annual average of 1.63% in the long term. These findings underscore the need for developing economies to restructure their energy policies and support sustainable technological initiatives and green entrepreneurship. Developing countries can reduce their energy intensity while boosting their economic growth by fostering technological innovation. This study demonstrates how technological progress and green entrepreneurship can be leveraged to enhance energy efficiency and drive sustainable development in developing nations.

A structural rationale for reversible vs irreversible amyloid fibril formation from a single protein.

Reversible and irreversible amyloids are two diverging cases of protein (mis)folding associated with the cross-β motif in the protein folding and aggregation energy landscape. Yet, the molecular origins responsible for the formation of reversible vs irreversible amyloids have remained unknown. Here we provide evidence at the atomic level of distinct folding motifs for irreversible and reversible amyloids derived from a single protein sequence: human lysozyme. We compare the 2.8 Å structure of irreversible amyloid fibrils determined by cryo-electron microscopy helical reconstructions with molecular insights gained by solid-state NMR spectroscopy on reversible amyloids. We observe a canonical cross-β-sheet structure in irreversible amyloids, whereas in reversible amyloids, there is a less-ordered coexistence of β-sheet and helical secondary structures that originate from a partially unfolded lysozyme, thus carrying a "memory" of the original folded protein precursor. We also report the structure of hen egg-white lysozyme irreversible amyloids at 3.2 Å resolution, revealing another canonical amyloid fold, and reaffirming that irreversible amyloids undergo a complete conversion of the native protein into the cross-β structure. By combining atomic force microscopy, cryo-electron microscopy and solid-state NMR, we show that a full unfolding of the native protein precursor is a requirement for establishing irreversible amyloid fibrils.

Aggregator control of battery energy storage in wind power stations to maximize availability of regulation service

Battery energy storage systems can produce very fast bi-directional power flows, which makes them suitable for providing wind power regulation and frequency control services. Though battery systems can provide fast regulation services, their energy storage capacities are quite low in comparison to other generation sources, so regulation responses from them should be optimized to maximize availability of service. This paper proposes an aggregator that optimizes frequency control responses from battery energy storage systems to maximize service availability. The frequency control response from the aggregated system is defined by a single frequency-droop characteristic. This provides the predictability of response required to comply with grid codes and allows the aggregated system to participate in frequency control markets as a single entity. The method of implementation is fail-safe as failure to receive an optimized order from the aggregator does not prevent the battery energy storage systems from responding to frequency events. This mitigates stability concerns relating to communication delays between the aggregator and battery energy storage systems. Battery systems that provide multiple functions, such as frequency control system services and wind power regulation, can participate in the aggregator scheme by assigning a proportion of the battery’s capacity to the aggregator scheme. Simulations performed in DIgSILENT PowerFactory show that the aggregator successfully extends the duration of full regulation service from the battery systems during frequency excursion events.

The Impact of Human Capital on Energy Consumption in Vietnam

The paper studied the impact of human capital on energy consumption in Vietnam using the ARDL model during the period from 1986 to 2019. The results showed that there exists a long-term positive relationship between human capital and aggregate energy consumption, fossil energy consumption, average renewable energy consumption. Besides, the study also revealed the impact of economic growth on fossil energy consumption in the short term. These findings helped proposing a number of recommendations for the government such as improving the quality of human capital, using more renewable energy and the need to fund research and development.

Low-cost, all-organic, hydrogen-bonded thin-film composite membranes for CO2 capture: Experiments and molecular dynamic simulations

Despite the excellent separation performance of organic-inorganic hybrid membranes, such as mixed-matrix membranes, their commercial application remains challenging due to difficulties in uniformly dispersing inorganic fillers and achieving good interfacial contact over large areas. In this paper, we present high-performance, thin-film composite (TFC) membranes made from low-cost, all-organic materials using a commercially attractive and straightforward process for CO2 capture. The TFC membranes were prepared on a porous polysulfone support using 2,4,6-triaminopyrimidine (TAP) dispersed in comb-shaped polymerized poly(oxyethylene methacrylate) (PPOEM), synthesized through a free radical polymerization process. The organic filler TAP functioned as a hydrogen bond inducer, controlling the free volume and reducing gas diffusivity, thereby enhancing CO2 selectivity over larger gases such as N2 and CH4. Incorporating 2 wt% TAP significantly improved separation performance by primarily reducing N2 and CH4 permeances, achieving a CO2 permeance of 1140 GPU, with CO2/N2 and CO2/CH4 selectivities of 43.3 and 15.0, respectively. The achieved performance significantly surpassed that of Pebax-based membranes and successfully met the target criteria for post-combustion CO2 capture. Variations in free volume, molecule aggregation, hydrogen bonding, and interaction energies between gases and membranes were thoroughly investigated via molecular dynamic (MD) simulations. This high-performance TFC membrane, created through simple and facile methods using entirely organic materials, achieves commercial standards for post-combustion CO2 capture.

Enhancing energy efficiency in Asia-Pacific: Comprehensive energy policy analysis

The Asia-Pacific (APAC) region has undergone remarkable economic growth over the past three decades, significantly reducing poverty levels. However, the concurrent rise in energy consumption and its environmental impact necessitate the development of a sustainable energy system to sustain and accelerate this progress. Recognizing the critical role of energy efficiency, governments in the region have increasingly formulated and implemented energy policies, encompassing laws, regulations, and action plans. However, understanding the precise influence of these policies on energy efficiency remains a challenge. This study employs an endogenous stochastic frontier analysis (SFA) model using data from the Asia Pacific Energy Portal Policy database covering 23 emerging economies from 2000 to 2017 to assess how energy policies affect energy efficiency in the APAC region. The findings indicate that implementing energy policies correlates with an average increase in energy efficiency by 0.158%. However, the impact varies depending on whether the policies are laws, regulations, or strategies. Though the region's average energy efficiency standing is at 0.34, there has been a consistent upward trend observed from 2000 to 2017. Furthermore, optimizing aggregate energy policies has resulted in substantial energy savings, averaging 0.15 quadrillion Btu. In light of these results, we proposed some policy actions.

Analysis of aggregated load consumption forecasting in short, medium and long term horizons using Dynamic Mode Decomposition

In response to the growing need for precise energy demand forecasting in distribution grids, this study examines the effectiveness of the Dynamic Mode Decomposition (DMD) algorithm for short, medium, and long-term demand forecasting in distribution grids, leveraging diverse time series energy consumption data. The DMD algorithm, a data-driven approach renowned for its capacity to discern frequencies and trends, will be compared against established forecasting techniques, including XGBoosting Regressor, Long Short-Term Memory, and PROPHET. The research is conducted through a comprehensive case study comprising three distinct phases: study on pattern capturing of DMD, comparison in Long term horizon with all models studied and robustness study of DMD. It recalls upon real aggregated hourly energy consumption data sourced from a Spanish distribution grid. The practical applications and benefits of DMD in time series forecasting are examined carefully in order to show its comparative advantages over alternative forecasting models. To ensure a rigorous assessment of the findings, the analysis will employ four key statistical metrics: Root Mean Square Error (RMSE), Mean Squared Error (MSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE). The results obtained with the case studies showed a 75% reduction on computational waste compared to other models and the results are closer to classical models, obtaining an improvement in the best case study of 44% comparing RMSE with Prophet. The insights gained can help future applications and research in the field.

Hierarchical transactive home energy management system groups coordination through multi-level consensus sharing-based distributed ADMM

Coordinating residential building groups requires a hierarchical structure in which aggregate objectives and coupled constraints are incorporated into decision-making processes at different layers of the electric distribution system. Failure to handle these matters can raise issues, such as rebound peaks and contingencies. This paper proposes a Hierarchical Transactive Coordination Mechanism (HTCM) capable of dealing with residential consumers’ objectives/constraints and local and grid coordinators’ shared objectives/coupled constraints under a bottom-up strategy. Particularly, the proposed multi-level framework distributes local and grid coordinators’ shared objectives among consumers to flatten the aggregate consumption profile and minimize the aggregate energy cost at each level. The suggested scheme is enhanced by developing two additional operations. A gain-sharing technique is designed to fairly divide the total gain acquired by the grid coordinator across the hierarchy from higher to lower levels, successively. Besides, a coupled constraint-sharing method is devised to link these levels and fulfill the coupled constraints by revising consumers’ decisions. The proposed approach is applied to a society of buildings comprising Home Energy Management System (HEMS) groups with demand response-enabled electric Baseboard Heaters (BHs), and its effectiveness is investigated through different case studies. The results demonstrate that the recommended HTCM is able to improve the society’s aggregate power profile load factor by 89%, from 0.45 up to 0.85, and decreases its overall electricity cost by 6.2%.

Emergy-Theory-Based Evaluation of Typhoon Disaster Risk in China’s Coastal Zone

The evaluation of typhoon disaster risk is a widely discussed global topic. Currently, the index system method has become a common approach for the evaluation of typhoon disaster risk. However, the indices within the system are calculated independently, and subjective human factors significantly influence the assignment of index weights. The existing studies lack purely quantitative assessment methods, which makes the studies less precise and more difficult for other researchers to replicate. To bridge this gap, this study employs emergy analysis methods based on thermodynamics to develop a typhoon disaster risk evaluation index system for China’s coastal zone. Without the interference of weights and other human factors, the system contains various quantitative indices, including aggregate impelling energy, typhoon intensity emergy, adaptability emergy, the vulnerability index, and the integrated typhoon hazard index. Subsequently, these indices and socio-economic data were spatialized, and the evaluation of typhoon disaster risk was conducted at the city grid level in the coastal zone of China. The findings reveal that the high-risk areas for typhoon disasters in China are concentrated in prefecture-level cities along the southeast coast. The typhoon disaster risk index is higher in the southern region compared to the northern region, with a decreasing trend in the distribution of the integrated typhoon hazard index from coastal to inland areas. The aim of this study is to use a new quantitative evaluation method (emergy) to evaluate typhoon disasters. It also serves as a theoretical foundation and technical support for national and local governments in the formulation of policies for disaster prevention and reduction.

Mesoscopic model of cycling trip energy expenditure based on operating modes

Cyclist physical exertion is largely ignored in quantitative travel analysis, partly due to a lack of appropriate tools. Microscopic models of second-by-second energy expenditure based on equations of motion are data intensive and cannot be applied to hypothetical routes (such as needed for route choice modelling). Macroscopic models of aggregate energy expenditure based on a fixed assumed energy intensity are insensitive to traveller, trip, and contextual factors that are relevant for behavioural research and policy analysis (such as bicycle type or trip purpose). Building on concepts from motor vehicle emissions analysis, this paper proposes a mesoscopic approach to model cycling trip energy expenditure based on the distribution of travel time across discrete states of motion (“operating modes”) for different classes of traveller and trip (“model segments”). We aim to answer two key questions for model implementation: 1) which variables most effectively classify trips into model segments and 2) what operating mode definition most consistently characterizes cycling energy expenditure within model segments? We also evaluate the precision of the mesoscopic model relative to cycling energy estimates from microscopic and macroscopic models. Applied to a dataset of naturalistic cycling trips in Vancouver, Canada, the proposed mesoscopic model with six model segments based on 3 segmenting variables (rider gender, electric-assist bicycle, and high or low speed tier) explains up to 28 % of the variance in trip-level energy estimates from the microscopic model (within around 35 W of the microscopic estimates, on average). Further research to develop cycling trip energy models for general application is discussed.

The crosslinking sites and molecular conformation of gelatin hydrogel modified by transglutaminase

This work aimed to investigate the covalent crosslinking sites induced by transglutaminase (TGase, EC 2.3.2.13) in gelatin hydrogel and their impact on the gelatin molecular conformation. LC-MS/MS results demonstrated that Lys644 and Gln1351 of α1 chain and Gln19 of α2 chain were the main sites. The results of molecular dynamic (MD) simulation indicated that at the moderate degree of covalent crosslinking (13.55%), Radius of gyration (Rg) values decreased from 11.5 to 10.0 nm at 4 °C and led to a more compact structure, therefore enhancing structural tightness and gel strength. As the degree of crosslinking rose, the number of crosslinking sites gradually increased, with a predominant distribution in the C-terminal pro-peptide of gelatin chain. At the high crosslinking degree (37.48%), Rg value decreased at 100 °C and gelatin chains were connected through a “head to tail” linkage configuration, resulting in a significant reduction in the triple helix-like structure. The structure maintained the gel-forming ability at high temperature while lowering the aggregation energy of water molecules from −2.359 × 105 to −2.455 × 105 kJ/mol, leading to thermal irreversibility of gelatin hydrogel.

Pulsed Electric Field Treatment of Oat and Barley Flour: Influence on Enzymes, Non-starch Polysaccharides, Dough Rheological Properties, and Application in Flat Bread

AbstractThis study examined the effects of pulsed electric field (PEF) treatment on enzymes, non-starch polysaccharides, and bread-making potential of oat and barley flour. Enzyme activity, microstructure, β-glucan extractability, molecular weight (Mw) and structure of non-starch polysaccharides, dough rheology, and flat bread properties were determined. An exponential decay model explained better the residual activity of oat β-glucanase across electric field intensity than barley β-glucanase. PEF treatment of flour at 12 kV/cm for 162 ms significantly reduced β-glucanase activity (40.2–76.5%) while increasing the concentration of total β-glucans (33.5%) and water-extractable arabinoxylans (36–41%). Mw of linear β-d-glucans decreased (9%) while Mw of branched arabinoxylans increased (6–33%). Scanning electron microscopy showed changes in microstructure of barley proteins. Blending wheat flour (70%) with oat or barley flour (30% weight) after PEF treatment enhanced gluten aggregation energy (29–19%) and breakdown viscosity (18–43%) of dough, as well as increased β-glucan content (21–32%) but reduced specific volume (11–24%). The findings of this study provide a comprehensive insight into the PEF’s potential for retarding enzymatic reactions and preserving integrity of cereal non-starch polysaccharides.

Plasmon assisted synthesis of TiN-supported single-atom nickel catalysts

We report the deposition of single atom nickel catalyst on refractory plasmonic titanium nitride (TiN) nanomaterials supports using the wet synthesis method under visible light irradiation. TiN nanoparticles efficiently absorb visible light to generate photoexcited electrons and holes. Photoexcited electrons reduce nickel precursor to deposit Ni atoms on TiN nanoparticles’ surface. The generated hot holes are scavenged by the methanol. We studied the Ni deposition on TiN nanoparticles by varying light intensity, light exposure time, and metal precursor concentration. These studies confirmed the photodeposition method is driven by hot electrons and helped us to find optimum synthesis conditions for single atoms deposition. We characterized the nanocatalysts using high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM), energy dispersive X-ray spectroscopy (EDX), and X-ray photoelectron spectroscopy (XPS). We used density functional theory (DFT) calculations to predict favorable deposition sites and aggregation energy of Ni atoms on TiN. Surface defect sites of TiN are most favorable for single nickel atoms depositions. Interestingly, the oxygen sites on native surface oxide layer of TiN also exhibit strong binding with the single Ni atoms. Plasmon enhanced synthesis method can facilitate photodeposition of single atom catalysts on a wide class of metallic supports with plasmonic properties.

Confined liquid crystallization governed by electric field for API crystal polymorphism screening and massive preparation

Active pharmaceutical ingredients (APIs) crystal preparation is a significant issue for the pharmaceutical development attributed to the effect on anti-inflammatory, anti-bacteria, and anti-viral, etc. While, the massive preparation of API crystal with high polymorphism selectivity is still a pendent challenge. Here, we firstly proposed a criterion according to the molecular aggregation, molecular orientation, and hydrogen bond energy between INA molecules from molecular dynamics (MD) simulations, which predicted the hydrogen bond architecture in crystal under different electric fields, hinting the recognition of crystal polymorphism. Then, an electric field governing confined liquid crystallization was constructed to achieve the INA crystal polymorphism screening relying on the criterion. Further, magnifying confined liquid volume by 5000 times from 1.0 μL to 5.0 mL realized the massive preparation of INA crystal with high polymorphic purity (>98.4%), giving a unique pathway for crystal engineering and pharmaceutical industry on the development of innovative and generic API based drugs.

The Application of Rivet, HAP, and Ecotect Programs for the Analysis of Building Envelope Parameters to Optimize Energy Efficiency and Energy Savings: A Case of Baghdad-Iraq

With the growing emphasis on energy conservation and emission reduction in Iraq, there has been a rising focus on the consumption of energy in buildings. This phenomenon is attributable to its substantial contribution to aggregate energy consumption within society. Consequently, the primary focus of energy conservation research has been directed towards this particular domain. There has been a growing emphasis in energy conservation research on public buildings characterized by elevated levels of energy consumption. The examination of energy conservation in expansive public structures carries substantial practical significance and societal value. This study employs a building in Baghdad City - Iraq, as a case study. The research was centred on the execution of experiments pertaining to insulation, the ratio of windows to walls, and the thickness of window glass. A comparative analysis was undertaken through the implementation of simulations that considered the climatic conditions of the Baghdad- Iraq region. In order to evaluate energy efficiency, a variety of software applications were utilized, namely Revit, Ecotect, and Hap. The results showed that when analyzing the climate of Baghdad, it was observed that the total cooling savings ranged from 2.34% to 2.45%. As a result, it was determined that the optimal insulation thickness is 11cm. Additionally, it was observed that the energy savings in cooling remained consistent. The analysis of window-to-wall ratios has shown that the highest level of savings can be achieved by maintaining a window-to- wall ratio of 50%. During the calculation of window glass thickness, it was discovered that in the city of Baghdad, the ideal glass thickness is 2mm. This thickness leads to a 1% reduction in annual energy consumption for cooling purposes. The results of this study are significant as they can significantly contribute to reducing energy consumption. Furthermore, the authors highlight the potential for improving energy efficiency in the buildings situated within the specified study area.

Probabilistic forecast of electric vehicle charging demand: analysis of different aggregation levels and energy procurement

Electric vehicles (EVs) are expected to be vital in transitioning to a low-carbon energy system. However, integrating EVs into the power grid poses significant challenges for grid operators and energy suppliers, especially regarding the uncertainty and variability of EV charging demand. Accurate forecasting of EV charging demand is essential for optimal power system integration, yet previous studies have often only considered point predictions that are inadequate for risk assessment. Therefore, this paper compares different probabilistic forecasting models for the short-term prediction of EV charging demand at various aggregation levels, using a large and novel dataset of over 350,000 charging processes at more than 500 locations across Germany. The performance of both machine learning and deep learning methods is evaluated against a naïve benchmark model, and the impact of data availability on the forecasting models is investigated. Further, the paper examines the effects of forecast accuracy on energy procurement, which has so far received minor attention in the literature. The results show that machine learning methods such as Ada Boosting and Random Forest yield robust results with a normalized root mean square error of 0.42 and 0.41 and a mean absolute scaled error of 0.36 and 0.34 at the highest aggregation level. Furthermore, the results show the influence of different site compositions on the forecast quality and how many charging points are likely to yield a robust forecast. Energy and fleet managers can use the described method to reliably predict the required energy quantities for fleets of sufficient size and procure them at low risk.

Influence of chloride salt erosion on the adhesion of asphalt-aggregate interfaces considering mineral anisotropy: insights from molecular dynamics.

Asphalt, a polymer mixture composed of various hydrocarbons, is extensively utilized due to its excellent performance. To evaluate the sensitivity of asphalt concrete to chloride salt damage at the nanoscale, considering the anisotropy of aggregate mineral crystal orientation, molecular dynamic simulations were employed to model the interface interactions between asphalt and aggregate mineral components (silica and calcite) under chloride salt exposure. The wetting processes of water droplets and chloride salt droplets on different crystal surfaces of silica and calcite were analyzed. Furthermore, the adhesive energy, decohesion energy, degradation ratio, and energy ratio of the interaction model between asphalt and aggregate mineral interfaces were analyzed to reveal the variations in the interfaces between the two components. The results demonstrated that the anisotropy of the minerals significantly affects the adhesion energy of asphalt and aggregate. Moreover, the surface hydrophilicity of calcite was larger than that of silica. The interfacial adhesion energy of asphalt-calcite was larger than that of asphalt-silica under dry condition and chloride salt attack, and the interfacial adhesion energy of both asphalt and mineral decreased with the increase of chloride salt concentration. The degradation ratio and energy ratio values of asphalt and calcite were larger than those of asphalt and silica, and the anisotropy of the mineral surface affected the degradation ratio and energy ratio values. This study provides a new method and theoretical basis for further research on the damage mechanism and strengthening measures of asphalt-aggregate under chloride salt attack. To investigate the interaction between asphalt and mineral aggregates under chloride salt erosion, models of asphalt, aggregate, and asphalt/aggregate composite systems were constructed using the Amorphous Cell module in Materials Studio 2020 software. Molecular dynamic simulations of the asphalt/aggregate composite system were then conducted using the Forcite module, employing the COMPASS II force field to describe atomic and molecular interactions. Initially, considering the crystal orientation and surface configuration of the aggregate minerals, the impact of mineral anisotropy on the asphalt-aggregate interface model was analyzed. Subsequently, by simulating the contact states of nano water droplets and chloride salt droplets with different mineral surfaces, the wetting characteristics of nano water droplets on silica and calcite surfaces were determined. Lastly, considering the corrosion effect of chloride solution at different concentrations, the adhesion energy, debonding energy, degradation ratio, and energy ratio of the asphalt-aggregate interface interaction model were analyzed.

Effect of phenyl functional groups on the adsorption behaviour of dodecyl anionic emulsifiers on oxides on the aggregate surface

ABSTRACT Emulsified asphalt finds extensive application in pavement repair, addressing issues like road ruts and cracks. While the adsorption behaviour of emulsifiers on oxide surfaces (CaCO3 and SiO2) of aggregates is influenced by the presence of phenyl functional groups, the precise mechanism of this influence remains insufficiently understood. This study employs molecular dynamics models and macroscopic experiments to investigate the mechanism involving emulsifiers, sodium ions, and water at aggregate interfaces, quantifying the role of phenyl functional groups from a molecular perspective. The results reveal the following: strong electrostatic attraction between alkaline aggregates and Na+, leading to substantial Na+ adsorption. The phenyl functional groups reduce diffusion coefficient, adsorption energy, and amounts in alkaline aggregates (−34.6%, −16%, −12.5%), while increasing them in acidic aggregates (+15.9%, + 14.7%, + 27.7%). The phenyl functional groups impact hydrogen bond acceptors, TPSA, and emulsifier complexity, altering adsorption. They enhance emulsifier electrostatic potential, affecting adsorption on different surfaces. In summary, this ongoing research framework aims to fine-tune emulsifiers through the use of phenyl functional groups, enhancing adsorption strength, adsorption amount, and diffusion between emulsifiers and aggregates. This work holds great significance for optimizing emulsifier molecular structures.

Aggregate production planning and energy supply management in steel industry with an onsite energy generation system: A multi-objective robust optimization model

This paper introduces an optimization model developed for the steel industry, the most energy-intensive industrial sector in many countries. New methodologies for both aggregate production planning and energy supply management are developed to maximize profit while minimizing energy consumption and greenhouse gas (GHG) emissions. Moreover, uncertainties are considered, and robustly optimized strategies are identified for a grid-connected steel production company with an onsite energy generation system. The performance of the developed model is evaluated through extensive computational experiments. The results show how energy tariffs affect integrated production planning. Also, the selected production planning time depends on several factors such as electricity, labor, and maintenance costs, and pending orders that need to be fulfilled. The onsite power plant produces electricity when the electricity production cost is lower than the price of electricity provided by the connected grid. Furthermore, the company’s environmental policies influence the choice of energy generation technology. However, implementing an onsite energy generation is a viable policy that benefits both profitability and pollutant reduction. This study helps decision-making in production planning and energy supply management in the iron and steel industry (which can be applied to other industries too), ensuring environmental improvement at the lowest costs.