Energy Flow Research Articles

The development and applications of multidimensional biomolecular spectroscopy illustrated by photosynthetic light harvesting.

The parallel and synergistic developments of atomic resolution structural information, new spectroscopic methods, their underpinning formalism, and the application of sophisticated theoretical methods have led to a step function change in our understanding of photosynthetic light harvesting, the process by which photosynthetic organisms collect solar energy and supply it to their reaction centers to initiate the chemistry of photosynthesis. The new spectroscopic methods, in particular multidimensional spectroscopies, have enabled a transition from recording rates of processes to focusing on mechanism. We discuss two ultrafast spectroscopies - two-dimensional electronic spectroscopy and two-dimensional electronic-vibrational spectroscopy - and illustrate their development through the lens of photosynthetic light harvesting. Both spectroscopies provide enhanced spectral resolution and, in different ways, reveal pathways of energy flow and coherent oscillations which relate to the quantum mechanical mixing of, for example, electronic excitations (excitons) and nuclear motions. The new types of information present in these spectra provoked the application of sophisticated quantum dynamical theories to describe the temporal evolution of the spectra and provide new questions for experimental investigation. While multidimensional spectroscopies have applications in many other areas of science, we feel that the investigation of photosynthetic light harvesting has had the largest influence on the development of spectroscopic and theoretical methods for the study of quantum dynamics in biology, hence the focus of this review. We conclude with key questions for the next decade of this review.

Methane fueled lake pelagic food webs in a Cretaceous greenhouse world

Methane (CH4) is a potent greenhouse gas but also an important carbon and energy substrate for some lake food webs. Understanding how CH4 incorporates into food webs is, therefore, crucial for unraveling CH4 cycling and its impacts on climate and ecosystems. However, CH4-fueled lake food webs from pre-Holocene intervals, particularly during greenhouse climates in Earth history, have received relatively little attention. Here, we present a long-term record of CH4-fueled pelagic food webs across the Cretaceous Oceanic Anoxic Event 1a (~120 Mya) that serves as a geological analog to future warming. We show an exceptionally strong expansion of both methanogens and CH4-oxidizing bacteria (up to 87% of hopanoid-producing bacteria) during this Event. Grazing on CH4-oxidizing bacteria by zooplankton (up to 47% of ciliate diets) within the chemocline transferred substantial CH4-derived carbon to the higher trophic levels, representing an important CH4 sink in the water column. Our findings suggest that as Earth warms, microbial CH4 cycling could restructure food webs and fundamentally alter carbon and energy flows and trophic pathways in lake ecosystems.

Analysis of Impact of Control Strategies on Integrated Electric Propulsion System Performance During Icebreaking Process

Developing an efficient power system is an important way for icebreakers to respond to high maneuverability and strong fluctuation loads under icebreaking conditions. The performance of power systems under short-period, regularly fluctuating load-sea conditions has been intensively studied. However, the performance of the power system in the face of a long-period, stochastic multi-frequency fluctuation icebreaking process has not been fully explored, especially the parameter uncertainty and battery cycle life. In this study, an integrated electric propulsion system with an optimal control strategy is suggested for improving the power system’s dynamic performance and battery cycle life. First, an energy flow model with a diesel–electric unit as the main body and coupled energy storage system/hybrid energy storage system has been constructed. A comparative analysis of rule-based and optimization-based energy management strategies has been performed, and an optimized strategy with dynamic programming as global regulation at the upper level and model predictive control at the lower level is suggested to integrate the slow and fast dynamic powers and achieve adaptability to strong fluctuation loads. In this control strategy, the uncertainties of energy storage system/hybrid energy storage system parameters have been introduced to eliminate their impact on the system performance. Then, the icebreaking process with multi-frequency fluctuation has been simulated, and the hybrid energy storage system with battery and supercapacitor is recommended to reach multi-objective with the lowest power fluctuation of diesel–electric unit, highest efficiency, and the minimum battery degradation. Finally, the fuel oil consumption and emissions of the hybrid energy storage system have been discussed, and the optimized strategy can save fuel oil by up to 5.33% and reduce the CO2 emission by 22% during the icebreaking process, exhibiting great potential in the environmental friendliness and significant advantages in terms of low fuel oil consumption.

Non-Foliar Photosynthesis in Pea (Pisum sativum L.) Plants: Beyond the Leaves to Inside the Seeds

In addition to leaves, photosynthesis can occur in other green plant organs, including developing seeds of many crops. While the majority of studies examining photosynthesis are concentrated on the leaf level, the role of other green tissues in the production of total photoassimilates has been largely overlooked. The present work studies the photosynthetic behavior of leaves and non-foliar (pericarps, coats, and cotyledons) organs of pea (Pisum sativum L.) plants at the middle stage of seed maturation. The Chl a fluorescence transient was examined based on OJIP kinetics using the FluorPen FP 110. A discrepancy was observed between the performance index (PIABS) for foliar and non-foliar plant tissues, with the highest level noted in the leaves. The number of absorbed photons (ABS) and captured energy flow (TRo) per reaction center (RC) were elevated in the non-foliar tissues, which resulted in a faster reduction in QA. Conversely, the energy dissipation flux per RC (DIo/RC and PHI_Do) indicated an increase in the overall dissipation potential of active reaction centers of photosystem II. This phenomenon was attributed to the presence of a higher number of inactive RCs in tissues that had developed under low light intensity. Furthermore, the expression of genes associated with proteins and enzymes that regulate ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCo) activity was observed, including chaperonins Cpn60α and Cpn60β, RuBisCO activase, as well as phosphoribulokinase. The expression of these genes was found to differ between foliar and non-foliar tissues, indicating that the activation state of RuBisCO may be modified in response to light intensity. Overall, the present study provides insights into the mechanisms by which non-foliar green tissues of plants adapt to efficient light capture and utilization under low light conditions.

Periodically asymmetric responses of deep chlorophyll maximum to light and thermocline in a clear monomictic lake: Insights from monthly and diel scale observations

Deep chlorophyll maximum (DCM), a chlorophyll peak in the water column, has important implications for biogeochemical cycles, energy flow and water surface algal blooms in deep lakes. However, how an observed periodically asymmetric DCM response to environmental variables remains unclear, limiting our in-depth understanding and effective eco-environmental management of deep lakes. Based on both monthly field investigations in 2021 and diel continuous observations in 2021–2023 in clear, monomictic Lake Fuxian, Southwest China, the temporal dynamics and drivers of DCM were examined and periodic features of DCM were found, with a formation period (FP, February–July) and a weakening period (WP, August–December). On the monthly scale, although DCM dynamics were partly attributed to thermocline structures, the role of light penetration depths varied with period. In the FP, the influence of light on DCM was direct, i.e., increased depth and thickness but decreased magnitude. Differently, the influence of light mainly occurred by affecting thermocline structures in the WP, where water quality was another important driver. On the diel scale, light was a major reason for a thicker and lower (magnitude) DCM during day than at night, and the response of DCM to environmental factors between the FP and WP differed also more during day. This periodically asymmetric response of daytime DCM not only being caused by light but possibly also related to other physical factors such as lake surface water temperature, wind speed and precipitation. Bayesian network modelling suggested that water darkening and stratification intensification may promote a shallower, thinner and larger (magnitude) DCM in both FP and WP, but achieving such changes in DCM requires different light and thermocline thresholds. Our findings provide new information valuable for modelling DCM and for predicting the related surface algal blooms in deep lakes under climate change and eutrophication.

Probing Spatial Energy Flow in Plasmonic Catalysts from Charge Excitation to Heating: Nonhomogeneous Energy Distribution as a Fundamental Feature of Plasmonic Chemistry.

Plasmonic catalysts use light to drive chemical reactions. One critical question is how light energy moves at nanoscales in these complex systems, leading to chemical transformations. In this contribution, we map out this energy flow by developing approaches to measure spatial temperature distributions in heterogeneous plasmonic catalysts, consisting of three-dimensional networks of plasmonic nanoparticles anchored on an oxide support. We survey the local temperatures of molecules adsorbed on catalytically active plasmonic nanoparticles, the nanoparticles themselves, and the catalyst support, under steady-state continuous-wave illumination. We reveal the existence of large temperature gradients, in which the local temperatures of the molecules, nanoparticles, and the surrounding environment can vary greatly. We show that these temperature gradients are a natural consequence of plasmon relaxation, involving the interconversion between electromagnetic light energy, electronic excitations, and heating of various entities as these electronic excitations relax. The presence of these gradients is a fundamental and unique feature of gas-phase plasmonic catalysis.

An elucidation on productivity, energetics, and carbon footprint of different forage land-use systems in semi-arid tropics of Karnataka, India

Forages are rapid biomass-generating crops that often demand intensive management. They necessitate a clear understanding of energy flow and carbon (C) footprinting which in turn helps in optimization of production resources and environmental impact assessment. Therefore, a field experiment was conducted for five consecutive years (2019–2023) to ascertain eight forage crops’ productivity, energetics, and C footprint. The crops under the annual monoculture system were maize and cowpea. While, Napier, Guinea, Rhodes, Green panic, Anjan grass, and Signal grasses were under perennial monoculture system. The results revealed that, the Napier grass was superior in biological productivity by recording 28%–50% higher green fodder yield over other forages. The energy analysis indicated that the Guinea grass consumed the highest energy (61,719 MJ ha−1 Year−1) during production, while Napier grass showed the highest energy output (32,5991 MJ ha−1 Year−1). Further, Napier grass outperformed the rest in terms of energy use efficiency (5.49), energy productivity (2.39 kg MJ−1), net energy gain (266,641 MJ ha−1 Year−1), energy profitability (4.49), nutrient energy ratio (14.7), and human energy profitability (558). Similar to energy input, Guinea grass production showed the highest C input (970 kg-CE ha−1 Year−1). Whereas, highest C output was observed with Napier grass (56,694 kg-CE ha−1 Year−1) due to its substantial C gain (55,805 kg-CE ha−1), C-efficiency ratio (63.79), and C-stability index (0.98). Consequently, Napier grass can be adopted as a productive, energy profitable, and C-efficient forage crop in semi-arid tropical conditions.

Study on the structure and energy flow of the salt marsh wetland ecosystem in Liaohe Estuary based on the Ecopath model

Salt marshes are one of the three blue carbon ecosystems recognized by the Intergovernmental Panel on Climate Change (IPCC). However, coastal salt marshes in China are facing the risk of degradation. To reveal the status of the salt marsh wetland ecosystem in Liaohe Estuary, an Ecopath model composed of 14 functional groups was constructed based on the 2019 ecological survey data. A comprehensive analysis of the system’s food web structure, energy flow processes, and overall ecosystem characteristics was conducted. The results show that the energy flow in the Liaohe Estuary salt marsh wetland ecosystem is mainly distributed in three integrated trophic levels. The utilization rates of trophic levels II and III are low, easily causing blockages in the lower trophic levels of the ecosystem’s energy flow. The total system throughput of the Liaohe Estuary salt marsh wetland ecosystem is 49,099.039 t·km²·a−1;. The system connectivity index and the system omnivory index are 0.207 and 0.109, respectively. Compared with other wetland systems, the ecosystem has a larger scale, but the overall ecosystem characteristic index reveals lower stability and complexity of the Liaohe Estuary salt marsh wetland system.

Streamlining latent spaces in machine learning using moment pooling

Many machine learning applications involve learning a latent representation of data, which is often high-dimensional and difficult to directly interpret. In this work, we propose “moment pooling,” a natural extension of deep sets networks which drastically decreases the latent space dimensionality of these networks while maintaining or even improving performance. Moment pooling generalizes the summation in deep sets to arbitrary multivariate moments, which enables the model to achieve a much higher effective latent dimensionality for a fixed learned latent space dimension. We demonstrate moment pooling on the collider physics task of quark/gluon jet classification by extending energy flow networks (EFNs) to moment EFNs. We find that moment EFNs with latent dimensions as small as 1 perform similarly to ordinary EFNs with higher latent dimension. This small latent dimension allows for the internal representation to be directly visualized and interpreted, which in turn enables the learned internal jet representation to be extracted in closed form. Published by the American Physical Society 2024

An Ultra‐High Voltage AC/DC Isolated Matrix Converter Applied to V2G Electric Vehicle Charging Piles

ABSTRACTIn recent years, in order to alleviate global environmental problems, renewable energy power generation and the electric vehicle industry have been vigorously promoted by many countries. During this background, many scholars have proposed the development of vehicle‐to‐grid (V2G) systems to alleviate the impact of renewable energy generation on grid quality, and electric vehicle charging piles are the core part of realizing V2G systems. This article proposes an ultra‐high voltage AC/DC isolated matrix converter applied to V2G electric vehicle charging piles, which can achieve bidirectional flow of energy, and proposes the control strategy that can reduce the current stress of the device. In addition, the ultra‐high voltage module of the proposed topology can provide wide voltage range and high voltage charging power for different types of electric vehicles. The proposed topology and control strategy are verified by simulation.

Emergy-Based Evaluation of Xiaolangdi Reservoir’s Impact on the Ecosystem Health and Services of the Lower Yellow River

The disturbance in river ecosystems caused by reservoirs and dams has become a critical topic, attracting increasing attention. However, the extent to which reservoir and dam construction and operation impact downstream river ecosystem health and ecosystem service functions is not fully understood. This research examines the Xiaolangdi Reservoir and the Lower Yellow River (LYR) ecosystem in China as a case study. We analyzed the complex material and energy flows in the LYR ecosystem using emergy theory and developed a set of emergy-based indicators for the quantitative assessment of river ecosystem health and services under reservoir operation interference. The results indicate that the total natural capital and environmental endowments of the LYR ecosystem have remained relatively stable after the operation of the Xiaolangdi Reservoir, with an increase in renewable emergy input. The ecosystem’s vigor decreased slightly, while the biomass emergy diversity index remained stable. However, the total emergy inputs increased significantly, with external feedback inputs becoming the most important emergy source for the LYR ecosystem. The resilience of the LYR ecosystem improved, with a significant increase in emergy density and a decrease in the emergy sustainability index. These findings suggest that although the river ecosystem continues to provide supporting services to human society, the extent of these services has diminished compared to pre-perturbation levels. In this research, a methodology for analyzing the impact of key reservoir operations on the ecosystem health and services of a large river is proposed to provide support for large river sustainable development studies.

Analysis of Energy Transfer in the Ignition System for High-Speed Combustion Engines

In order to produce reliable and reproducible ignition of lean fuel–air mixtures and highly stratified mixtures, it is necessary to ensure a high concentration of spark discharge energy and to provide a strong energy impulse for the triggering of chain processes of chemical decomposition of fuel molecules. For this reason, studies have been undertaken on the flow of electrical energy from the ignition system to the spark plug and on the formation of an electric discharge arc with a high concentration of thermal energy. The experimental results were obtained using an ignition coil energy test stand and a constant volume chamber with high-speed spark discharge recording capability. It was confirmed that increasing the charging time of the ignition coil from 0.5 ms to 5.0 ms increases the energy delivered to the coil from 9.5 mJ to 330 mJ. In the same range, the energy generated by the coil was recorded to range from 4.2 mJ to 70 mJ. The coil’s efficiency was found to decrease with increasing charging time from 45% up to 20.5%. Further energy losses were presented when the spark discharge energy was analyzed. In the paper, the results of investigations concerning electric discharge arc development have been presented, illustrated by a few exemplary photos, and discussed. The mathematical interpretation of the electrical energy flux in the ignition system resulting from the energy of the discharge arc has been conducted and illustrated by some functional independences and relationships.

Seasonal Distribution of Key Small-Sized Fish in the South Inshore of Zhejiang, China

Small-sized fish are a vital food source for large predatory commercial fish and play a key role in marine food webs, bridging lower and higher trophic levels. They are indispensable in maintaining the energy flow and material cycling within aquatic ecosystems. This study utilized bottom-trawl survey data from 2017 to 2020 along the south inshore of Zhejiang, China, complemented by concurrent environmental data, to examine the influence of environmental factors on the resource density and seasonal distribution patterns of four dominant small-sized fish species. The research findings indicated that SSH (sea surface height) and Chl (chlorophyll-a concentration) emerged as the key environmental factors influencing resource densities, with all four species exhibiting similar preferences toward these variables. However, significant disparities were observed in their preferences for SST (sea surface temperature), SSS (sea surface salinity), and DO (dissolved oxygen). The various species’ resource density and distribution patterns underwent significant seasonal variations. Additionally, the seasons and regions with the highest resource densities consistently aligned, occurring predominantly in autumn within the northern waters of the study area. This research further elucidated the environmental predilections and seasonal spatial distribution traits of small-sized fish in the south inshore of Zhejiang, an important feeding ground for economic fish species in the East China Sea. This provides scientific backing for forecasting alterations in coastal fishery resources under environmental and climate change scenarios and supports ecosystem-based fisheries management strategies.

Research on Large Hybrid Electric Aircraft Based on Battery and Turbine-Electric

Hybrid electric aircraft use traditional engine and electric propulsion combinations to optimize aircraft architecture, improve propulsion efficiency, and reduce fuel consumption. As a new technology, the fuel and energy consumption calculation of hybrid electric aircraft is more complicated than traditional aircraft due to the usage of different energy forms. The purpose of this paper is to develop the analytical method for fuel and energy consumption for hybrid electric aircraft. This paper summarizes the working principle of hybrid electric aircraft, including the system architecture and power conversion mechanism. The calculation of fuel and energy consumption for hybrid electric aircraft is carried out in detail. In order to evaluate large hybrid electric aircraft, the architecture, based on energy flow, is established, and turbofan engine, electrical system, electric duct fan, and aerodynamic model characteristics are established. With a single-aisle aircraft as an example, the fuel and energy consumption under the 800 nautical mile range is performed. It shows that fuel consumption can be reduced by 10% and energy consumption by 4.7% compared with a traditional aircraft. The effects of different range and battery ratios are analyzed. The payload range for the hybrid electric aircraft is analyzed. The results show that even though the hybrid electric aircraft reduces the payload and range, it can significantly reduce fuel and energy consumption.

Continuous cropping obstacles: Insights from the community composition and the imbalance carbon fluxes within soil nematode food web

Long-term continuouscroppingcan lead to the deterioration of soil environment and the decrease of soil productivity. However, the biological mechanism on the negative effects of long-term continuous cropping has not been extensively explored. Soil nematode food web with multiple trophic levels play critical roles in nutrient cycling and energy flowing in the agroecosystem. Quantifying the carbon flux through different trophic channels within the nematode food web can indicate how continuous cropping influences carbon cycling in the agroecosystem by altering soil biota communities. Therefore, the effects of continuous peanut cropping with different years (1, 5, 20, and 30 years) on soil properties, soil nematode community composition, carbon flux within nematode food web and crop yields were investigated. Results showed that soil pH significantly decreased with increasing continuous cropping years. Differently, soil organic carbon and total nitrogen were the highest in 20-year, and decreased in 30-year of continuous cropping. As continuous cropping years increased, the relative abundance of microbivorous nematodes decreased and that of plant parasites reached as high as 76.11 % and 68.22 % in 20- and 30-year, respectively. Pearson correlation analysis revealed the nematode diversity, the carbon flux uniformity and peanut yield had a significant negative correlation with continuous cropping years. The random forest model indicated that the soil pH and the relative abundance of plant parasites were the key influence factor of the carbon flux uniformity within soil nematode food web. Outbreaks of plant parasites lead to the disruption of carbon flux uniformity within soil nematode food web, which can increase the risk of peanut yield decline after long-term continuous cropping. In conclusion, continuous peanut cropping changed soil properties, reduced soil nematode diversity, and disturbed the multitrophic carbon flux complementarity and uniformity in soil nematode food web, ultimately limiting the crop productivity. This study enhances our understanding of the importance of the resource transfers among soil food web in maintaining sustainable agroecosystem productivity.

High-frequency vibration analysis of laminated composite plates using energy flow and shear deformation theories

Energy Flow Analysis (EFA) is an efficient approach for characterizing high-frequency vibrations through time-averaged energy density distributions. This study employs EFA to investigate vibroacoustic behavior in laminated composite plates subjected to high-frequency excitation. Governing equations of motion are derived using Classical Plate Theory (CPT), First Order Shear Deformation Theory (FSDT), and Higher Order Shear Deformation Theories (HSDT). Wave propagation parameters like wave number and group velocity are obtained from each theory and compared to assess accuracy. Energy density and intensity formulations are then developed based on classical solutions of the governing equations. EFA analysis indicates that HSDT provides more accurate predictions of wave parameters, especially at very high frequencies where it accounts better for shear deformation effects. Validation against classical energy density solutions shows acceptable accuracy with less than 0.5dB difference in the far-field. Comparisons further demonstrate the superiority of HSDT over FSDT for thicker plates in both classical and EFA analyses. This research establishes the effectiveness of EFA for high-frequency vibration analysis of composite laminates. The main novelty of this research lies in the integration of HSDT into the application of EFA for composite laminates, providing a more precise consideration of shear deformation effects at high frequencies. Specifically, HSDT enhances modeling of critical shear deformation effects at elevated frequencies. EFA delivers computationally efficient solutions while maintaining acceptable accuracy, improving characterization and design of composite structures under high-frequency loading.

Understanding the Level of Integration in Existing Chemical Clusters: Case Study in the Port of Rotterdam

AbstractThe petrochemical industry is composed of several interconnected processes that use fossil-based feedstock for producing chemicals. These processes are typically geographically clustered and often belong to different parties. Reducing the environmental impacts of the petrochemical industry is not straightforward due to, on the one hand, their reliance on fossil fuels for energy and as a feedstock and, on the other hand, the significant level of interconnected energy and material flows among processes. Current methods for analyzing changes to existing processes cannot capture the multitude and level of interactions. The goal of this paper is to create a model of a petrochemical cluster and analyze its physical characteristics and performance. This paper addresses this goal by developing an assessment method that combines process simulations, multiplex graph analysis, and key performance indicators. The method is applied to a case study based on the petrochemical cluster in the Port of Rotterdam, resulting in a uniquely highly detailed model of a petrochemical cluster. The network analysis results show that only some of the processes are very interconnected. From the performance analysis, it can be observed that the olefins process is the most carbon-intense and has high CO2 emissions. Additionally, the results showed the importance of considering existing interconnections when assessing the current performance of existing petrochemical clusters or the performance due to future changes to chemical processes. For instance, some changes would occur to an industrial cluster by introducing alternative carbon sources, such as biomass or CO2.

Thermodynamic and exergo-economic evaluation of biomass-to-X system combined the chemical looping gasification and proton exchange membrane fuel cell

The resource utilization of biomass is of great significance to the adjustment of energy structure. The syngas produced by biomass gasification can be used for power generation and production of green chemical raw materials. In this paper, a biomass-to-X (BtX) system based on the chemical looping gasification and high temperature proton exchange membrane fuel cell (PEMFC) is proposed to produce methanol, electricity, heating and cooling. The heat produced by the BtX system is harnessed for the regeneration of the carbon capture solution, as well as to drive both the organic Rankine cycle and the double-effect absorption chiller, enabling cascade utilization of the energy. The thermodynamic and exergo-economic models are carried out to evaluate system performance. The relationship between the material, energy and cost flow from biomass to products is analyzed. Finally, the influence of key parameters on system performance is studied. The results show that the energy efficiency of the BtX system is 54.0 % and the exergy efficiency is 35.4 %. The yield rate of methanol with 99.2 wt% purity is 6.48 tons/h. The cost of equipment, propanol and biomass accounts for 34.9 %, 28.9 % and 28.1 % of the total investment cost, respectively, while the cost of the PEMFC stack represents 50.4 % of the equipment costs. The unit exergy cost of the electricity and methanol are 0.068 $/kWh and 0.049 $/kWh, respectively. The methanol, carbon capture and cooling costs are most sensitive to the change in the propanol cost, followed by the biomass cost. For every 0.05 increase in the hydrogen fraction to methanol production, the electricity decreases by 3.1 MW and the methanol yield increases by 0.23 kg/s.

Optimizing integrated energy systems at park level: A cooperative game approach with exergy economics

This study presents a comprehensive framework for optimizing energy systems by integrating exergy analysis, energy economics, and game theory. The concept of exergy, which quantifies the usable energy within a system, is employed to evaluate energy efficiency and losses across various energy sources, including thermal, cooling, chemical, and electrical systems. Stoichiometric coefficients, denoted by the factor λ, are utilized to simplify exergy calculations for different energy types and processes. The economic evaluation of energy flows is conducted through energy economics principles, incorporating cost allocation and balance equations. The integration of game theory into the optimization model ensures strategic interactions among energy components, leading to a Nash equilibrium that balances economic performance, efficiency, and environmental sustainability. The model also accounts for emissions and the required proportion of renewable energy. To solve the complex optimization problem, a modified Particle Swarm Optimization (PSO) algorithm is employed, featuring adaptive mechanisms for velocity and inertia updates, enhancing the search process for the optimal solution. The proposed framework is designed to optimize the Integrated Energy System (IES) efficiently, ensuring sustainable and economically viable energy management. The analysis of optimization strategies highlights a trade-off between cost and efficiency. Strategy 1, focused on minimizing cost, achieves the lowest cost at 4069.37 CNY, 25.79 % less than Strategy 2, but with a reduced exergy efficiency of 59.82 %, which is 10.14 % lower than Strategy 2′s 68.47 %. Strategy 3 offers a balanced approach, with a cost of 4970.89 CNY, 9.43 % higher than Strategy 1 but 9.43 % lower than Strategy 2. It achieves an exergy efficiency of 67.87 %, only 0.60 % lower than Strategy 2, thus providing a practical compromise between economic performance and efficiency.

Thermal Integration in Sugar Production Using Pinch Analysis

Objective: the objective of this study is to conceptualize a network of heat exchangers designed to minimize energy waste and enhance the overall efficiency of the sugar production system.Methods: a systematic approach was adopted to analyze energy flows within the plant, identifying key areas for improvement, particularly in heating and evaporation processes. Heat accumulations in cascades and graphical analyses of composite curves were developed using specialized software to optimize heat exchange.Results: the results indicate a significant potential for energy savings, reducing the consumption of cooling and heating utilities in the plant by 7% and 30%, respectively. The developed computational tool allows for energy integration from simple processes to those with hundreds of streams. The pinch technology concept estimated an annual total savings of $464,850.08 in the selected process.Conclusion: this study demonstrates that thermal integration through pinch analysis not only improves energy efficiency in the sugar industry but also contributes to a considerable reduction in operational costs and environmental impact, providing a valuable tool for the industry’s sustainability and competitiveness.