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- A Green Supply Chain Model for Decaying Items with Learning and Inflation
Under the Strategy of Trade Credit and Preservation Technology-
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Abstract: Abstract The present paper discusses an EOQ model with the help of inflation for strategy of trade credit as well carbon emission under the preservation technology for deteriorating greening items. As we know, the quality of greening items day by day reduces on account of deterioration. The preservation technology is an alternative idea for the preservation of deteriorating greening items. In the present paper, the retailer supplies the green deteriorating items to the purchaser with the policy of permissible delay in payment. The buyer packs the green deteriorating items for controlling the value of green decaying items. The buyer preserves these green deteriorating items with the help of preservation technology. Some inventory costs regarding environmental issues such as carbon emission cost, packing cost, and development cost have been included. Supply chain model, preservation technology, and trade credit policy are more effective inventory tools, and recently, decision-makers are using these policies in their business policy. Flipkart, Amazon, and other online markets are using these policies and taking more profit. In the end, we have minimized the total cost with respect to inventory cycle time. Numerical example has been shown for validation of the present scenario. The observation study has been presented for the managerial insight and application in industries. PubDate: 2024-08-05
- Analysis of Multi-renewable Energy Potential Sites in India Using Spatial
Characteristics: A GIS and Hybrid MCDM Approach-
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Abstract: Abstract Land use and site selection are critical factors in the sustainable installation of large-scale renewable energy projects at a significant scale to accomplish the global goals of promoting renewable energy adoption and fostering a cleaner and more sustainable future. To systematically investigate, the present study developed a geographical information system (GIS)–multi-criteria decision making (MCDM) comprehensive framework to evaluate the spatial characteristics of suitable sites in India. Subsequently, the study identified prominent potential sites and states with abundant renewable resources and assessed the pre-feasibility of renewable power projects. Utilizing the developed framework and analysis, the study identified eight solar sites and seven wind sites as prominent potential locations. Furthermore, Rajasthan, Gujarat, Andhra Pradesh, Karnataka, and Tamil Nadu were identified as states with substantial renewable energy potential, and their renewable energy policies were discussed. The study also conducted case studies on two notable sites, Virudhunagar (S26) and Tirunelveli (W34), in Tamil Nadu, evaluating their technological and economic viability. The levelized cost of energy for solar and wind energy at these sites was determined to be $0.035/kWh and $0.039/kWh, respectively, which is comparable to, and lower than, the costs associated with existing projects. The study emphasizes the significance of incorporating spatial characteristics of suitable sites and evaluating their techno-economic repercussions to ascertain the triumph of the endeavor. PubDate: 2024-08-05
- Assessing the Smartness Required of Electricity Metres for Affordable,
Inclusive, and Sustainable Electricity Access in the Global South-
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Abstract: Abstract Increased use of smart technology is seen as a solution to providing equitable and reliable energy access. Consequently, there has been a global push for smart metreing. There is a range of smart metres available with differing features and functionality. This work discusses an approach for rating the degree of smartness of an electric metre to assess whether it can help provide equitable and affordable electricity access to the Global South. Analytic hierarchy process (AHP), the multicriteria decision-making tool, is employed for obtaining a framework for evaluating smartness. India is the country chosen in this paper as a case representing the Global South. Expert opinion is used as input to provide a weightage to various criteria that make up smartness. A survey was conducted to collect data for the AHP in which experts from both industry and academia participated. Based on their inputs, 2 AHP frameworks were created. The data obtained and the AHP results show that there is an agreement between both sets of experts on what constitutes a smart metre for a developing country such as India. Using the expert-agreed AHP framework, a smartness score was then calculated for any given metre. As a case study, few commercially available Indian electricity metres are considered for smartness assessment and affordability, and the results are discussed. It is demonstrated that the new framework allows decision makers to choose economical smart metres that aid in achieving efficient electricity access. Additionally, it is noted that both sets of experts seem to favour similar metres with regard to smartness. PubDate: 2024-08-03
- Optimal Power Flow of Multi-objective Combined Heat and Power with
Wind-Solar-Electric Vehicle-Tidal Using Hybrid Evolutionary Approach-
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Abstract: Abstract Determining effective power generation while reducing emissions, voltage deviations, and preserving transmission line voltage stability is the goal of the proposed effort. In this presentation, the combined heat and power of economic dispatch (CHPED) system is implemented in the IEEE-30 bus to assure the best possible power flow in the transmission line while fulfilling the load demand. As the source of fossil fuel is improvising day by day it is an important aspect to combine renewable energy sources for effective power generation. Renewable energy sources including wind, solar, electric vehicles, and tidal are integrated with proposed systems to lessen the need for fossil fuels in the production of electricity. The system became more complex as a result of the presence of wind uncertainty, valve point impact, and transmission losses. To enhance system performance in dealing with non-linearity, the multi-trial vector-based monkey king evolution technique uses training-based optimization to guide control choices. To improve the search capability of the proposed technique, the suggested method mixes chaotic-op-positional-based learning (COL) with MMKE (COMMKE). The suggested COMMKE algorithm has been tested for three distinct test systems for a proposed system with and without renewable sources. In terms of convergence rate and best possible solution to the objective functions, the proposed algorithm outperforms other optimization techniques. The robustness of the recommended optimization technique has been evaluated by statistical analysis. To make this scrutiny in a rigorous manner such that the robustness of the proposed technique can be judged more reliably, an analysis of variance (ANOVA) test is employed. To address the superiority of the intended method, a comparison with tried-and-true optimization strategies has been made. PubDate: 2024-07-15
- Developing Resilient Peer-to-Peer Energy Sharing Scheme Using
“N-1” Contingency-
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Abstract: Abstract A peer-to-peer energy sharing system, aiming to achieve emissions reduction by generating and sharing renewable energy among participants, has emerged as an appealing solution for addressing carbon emissions attributed to energy consumption. However, the resiliency of the peer-to-peer energy sharing system, particularly in addressing the risks of disruptions, has yet to be studied thoroughly in existing literature. Hence, this work aims to design an optimal peer-to-peer energy sharing scheme that can reduce electrical costs, while ensuring the carbon emissions reduction goal can be achieved even in the presence of disruptive risks. The concept of N-1 contingency has been incorporated into the proposed methodology. With the proposed approach, the minimum renewable capacity requirement of each player can be determined to ensure the fulfillment of energy demand and emissions reduction goal even when any of the players are unexpectedly shut down. Generally, by expanding the size of the solar panel, the remaining players are able to share extra renewables to fulfill its energy demand while achieving the emissions reduction goal. To demonstrate the effectiveness of the proposed methodology, an illustrative case study with three energy players is introduced. The result shows that if N-1 contingency is not applied, both energy cost and total emissions have at least increased by 35,054.49 RM/month (10.81%) and 46,218.34 kg/month (19.47%), respectively, assuming one of the players is experiencing disruptions. In short, this work reveals the potential of applying N-1 contingency to enhance the robustness of peer-to-peer system while ensuring its stability and performance even under challenging conditions. PubDate: 2024-07-12
- Evaluation Method of Multi-energy Sustainable Development Potential Based
on Distributed Model-
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Abstract: Abstract Distributed power equipment is a type of power supply equipment that is completely based on the idea of energy cascade utilization. To address electricity and environmental issues, it is necessary to sustainably increase the allocated resources. Starting from the basic elements and operational needs of distributed distribution networks, this article constructs a set of comparative indicators for their power efficiency. And guiding planning and architectural tips were proposed when evaluating the effectiveness of existing distribution networks. The experimental results show that compared with typical intensity systems, the multi-intensity mechanical system based solely on the allocation of human body models reduces gasoline consumption by 17.2%. The operating cost of a multi-motor system based solely on the allocation of human models is reduced by 17.5% compared to a regular force system. And the initial investment cost of a multi-power device mainly based on the allocated body model is 1.83 times that of a regular force system. Compared with conventional power systems, the carbon dioxide emissions of multi-intensity small tools based solely on human models have been reduced by 15.98%. The experimental results confirm the effectiveness of this method. PubDate: 2024-07-11
- Vehicle Routing Problem in Sustainable Horticulture Supply Chain for Food
Security Enhancement: a Case Study-
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Abstract: Abstract The horticulture industry has a special role in the health of society due to its direct impact on the food security in society, so it is one of the important industries that affect the lives of all people. Also, due to the increase in the growth of the world population, the need for food is increasing day by day, so it is necessary to pay special attention to the horticulture industry to reduce the rate of hunger in the world, which causes various problems. This study focuses on the routing of vehicles to carry different kinds of horticultural products considering their shelf life to keep the stability and quality of these products at the highest level. This aim has been achieved through presenting a comprehensive multi-period MILP model for different types of horticultural products and various types of vehicles in the horticultural supply chain. A case study in European Union is also presented to analyze the efficacy of model. The outcome of this research could be proliferative for managers, decision makers, and policy designers of horticulture supply chain since it proffers avenues of sustainable production enhancement. PubDate: 2024-07-09
- Analyzing the Enablers of Circular Economy: A Sustainable Manufacturing
Perspective-
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Abstract: Abstract In light of the growing usage of scarce resources, heightened consumerism, and ballooning emissions, the spike in consumer demand for products precipitates an upswing in production. This, thus, encourages the deterioration of the ecosystem. The obligatory adoption of sustainable development becomes important for maintaining ecosystems and preserving natural resources. Attaining the goals of sustainable development compels firms to adopt a circular economy (CE) strategy, focusing emphasis on sustainable manufacturing processes. Nevertheless, the adoption and expansion of CE are impeded by several obstacles, including the considerable upfront expenses, the intricate nature of the supply chain, the lack of collaboration between businesses, insufficient information, shortages in skills, the need to compromise on quality, and the extended time required for disassembly. The study identifies 15 enablers of the adoption of circular economy (CE) in a developing economy. The fuzzy decision-making trial and evaluation (Fuzzy-DEMATEL) method was used to prioritize and categorize these enablers. The findings reveal that “Top Management Commitment” is the most significant enabler of circular economy (CE). Other CE enablers include an increase of profit, infrastructure and technology, environmental laws and regulations, economic benefits, strategic planning, training and education for employee and, reduction of cost. Understanding these enablers’ underlying causes is just as important as identifying them as it will inform the development of strategic imperatives that may help these enablers and promote the expansion of circular economy (CE). PubDate: 2024-07-03
- Pinch Analysis for Land-Constrained Agriculture Sector Planning
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Abstract: Abstract Agriculture is an essential economic sector as it plays an important role in providing growing populations with sufficient food. Thus, it is imperative for policymakers to plan sufficient food stockpiles based on consumption requirements while ensuring lands are used in an efficient manner for producing a range of crops. Land is a limited resource and should be utilised efficiently to meet crop/food production demands. Thus, this work presents land use pinch analysis (LUPA), to aid planning of crop based on land footprint. LUPA is a novel application that allows the decision maker to determine the minimum amount of low land footprint crop required to achieve reductions in land usage and to meet food product demands. To illustrate LUPA, this work provides a numerical case study intended to highlight the benefits and features of the methodology. The case study aims to determine the amount of low land footprint oil crop (e.g., palm oil) that could replace other oil crops to meet a given edible oil demand and achieve reductions in land footprint. Results from the case study suggest that policymakers can opt for around 1 million hectares of low land footprint oil crop to meet the specified edible oil demand and replacing about 8 million hectares of a higher land footprint oil crop in the process. The case study is revisited analyse the impact of crop yield on the planning. This evidently shows that LUPA can be used as a means for strategising land allocation and land use reductions to meet edible oil demands. PubDate: 2024-07-01
- Exploring Factors Affecting Sustainable End-of-Life Vehicle Recycling
System: a Structural Equation Modeling Approach-
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Abstract: Abstract Production of automobiles is continuously on the rise in India. This growth in vehicle production increased the generation of end-of-life vehicles. End-of-life vehicle recycling has become a very serious issue in India from environmental, economic, and sustainability perspectives. Hence, it is vital to identify the factors and explore their impact on a sustainable end-of-life vehicle recycling system. The study aims to analyze the relationship among the factors of a sustainable end-of-life vehicle recycling system. This study identified seven factors and developed a conceptual model based on a literature review. A survey of stakeholders in Maharashtra and Gujarat was conducted from February 2022 to October 2022. For this purpose, a questionnaire was distributed online through a Google form link. Structural equation modeling methodology was used to analyze the data of 150 stakeholders and develop the measurement and structural models. The results show a strong relation between the sustainable end-of-life vehicle recycling system and its factors, except those based on the direct impact of government policies and socio-economic measures. The study will help to improve the stakeholders’ understanding of the important measures that need to be taken to develop a sustainable end-of-life recycling system in India. The study will also aid the policy and decision-makers in designing and implementing policies and procedures related to the end-of-life vehicle recycling industry. The research will also help India contribute significantly to the 17 Sustainable Development Goals drafted by the United Nations for all its member nations or ensure a habitable planet for future generations. PubDate: 2024-07-01
- Optimization of Compression Ignition Diesel Engine Combustion, Emission,
and Performance Characteristics at Higher Blends of Biodiesel Using RSM-
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Abstract: Abstract Conventional fuels are exhaustive and produce more emissions. Recent studies have concentrated on discovering and creating clean alternative fuels like biodiesel to reduce harmful emissions and enhance engine performance. In the present work, biodiesel is made from hibiscus cocos nucifera oil by using the transesterification process. Experiments were conducted on a variable compression ratio diesel engine by using input parameters as compression ratios of 15, 16, 17, and 18, loads of 25%, 50%, 75%, and 100%, and blends of B30, B50, B75, and B100. The performance, emission, and combustion characteristics are measured. The results show that brake thermal efficiency, carbon monoxide, hydrocarbons, smoke, and cumulative heat release increase; brake-specific fuel consumption, nitrogen oxide, cylinder pressure, and net heat release decrease. The response surface method is used to optimize the engine variables. The optimized input conditions are the engine load 33%, blend B30, and compression ratio 15. The model is validated by comparing the predicted and confirmed results with an error of less than ± 2%. PubDate: 2024-07-01
- Implementation of the Deep Eutectic Solvent, Choline Urea Chloride (1:2),
to Evaluate the Sustainability of its Application During CO2 Capture-
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Abstract: Green chemistry aims to create chemical products and processes that decrease or eradicate the need for harmful substances. By using green solvents like Deep Eutectic Solvents (DES) it is feasible to devise new processes or modify current that adhere to the principles of circular economy and green chemistry. In this work is presented the potential use of choline urea chloride (1:2) as a solvent; taking the post-combustion capture of carbon dioxide (CO2) as a case study. The results demonstrated that the methodology proposed allows the thermodynamic modeling of DES, obtaining a prediction of data very similar to the experimental trends previously reported. In addition, the use of DES in CO2 capture allowed a 13.97% reduction in environmental impact and required 25.38% less energy than the traditional process based on amine absorption. This led to a reduction in global cost by 32.11% and 19.64% for equipment and services, respectively, and a 21.13% lower cost of operation. Graphical  PubDate: 2024-07-01
- Warehouse Inventory Model for Perishable Items with Hybrid Demand and
Trade Credit Policy-
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Abstract: Abstract The retailer frequently leases an additional warehouse to avoid stockout situations. The mathematical framework for multiple warehouses handling decaying products within a retail setting is presented in this paper. The retailer discounts less-effective products when deterioration begins, encouraging customers to purchase them. This reduces waste and promotes a more sustainable approach towards inventory management. In addition to focusing on sustainable marketing strategies that support environmentally friendly products, the article explores the link between advertising, product pricing, and demand, emphasizing the considerable influence of promotions and price cuts. The study also discusses a trade credit policy, where the supplier grants the retailer a specified credit period for settling the account. The study aims to increase the store’s operational efficiency and minimize overall costs by establishing global optimality for important decision factors such as credit period, storage capacity, and replenishment time. Numerical examples and sensitivity analyses for key factors are provided to explore the impact on the system’s optimal total cost, along with managerial insights. PubDate: 2024-07-01
- RSM-Based Empirical Modeling and Thermodynamic Analysis of a Solar Flat
Plate Collector with Diverse Nanofluids-
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Abstract: Abstract As the energy demand for household applications is increasing, the utilization of solar energy becomes important in fulfilling the energy needs of electrical and thermal appliances. Harvesting the energy from solar through solar thermal energy systems will be effectively used in household and industrial heating applications where the consumption of electrical energy is predominant. Solar thermal energy is harvested through simple devices like flat plate collectors but involves many challenges. Solar flat plate collectors’ thermal efficiency is improved by increasing the heat transfer rate by replacing the regular fluids with nanofluids due to their superior thermo-physical properties. Investigators are driven to find novel energy and exergy analysis by the challenges in effective heat transfer and conservation by improving it by including gold, alumina, and copper oxide nanoparticles. To investigate the energy efficiency characteristics of solar flat plate collectors (FPC), the experiments are carried out by considering the different nanofluids (nanofluids with nanomaterials such as gold (Au) and aluminum oxide (Al2O3) as well as copper oxide (CuO) as thermal transport media), flow rates of nanofluids (0.016 kg/s, 0.033 kg/s, and 0.05 kg/s), and with mass fraction of nanoparticles (0%, 0.1%, 0.2%, 0.3%, and 0.4%) in nanofluids as variables, such that the energy efficiency, exergy destruction, second law efficiency, entropy generation, and pressure drop performance indicators. The maximum exergy efficiencies are found with \(Au\) nanofluids 31.55% and 28.78% at 0.4% mass concentration, which has the enhanced second law efficiency compared to water and other nanofluids. At the same time, exergy destruction is found to be minimum (1183.41 W) for \(Au\) nanoparticle with 0.4% mass fraction and 0.016 kg/min flow rate. The maximum exergy destruction (1509.95 W) was found in the water with 0% concentration at 0.05 kg/min due to the minimum temperature and base fluid heat flow. The energy efficiency and second law efficiencies are well increased with a slight increase in the pressure drop for the 0.4% mass fraction of Au with Al2O3 and CuO nanoparticles. The DoE-based statistical method, the Box-Behnken method, is employed as an experimental design matrix to develop prediction models for exergy responses and pressure drop characteristics. The models are validated through ANOVA results and verified for the R2 and R2adj values (> 0.95), and the results are obtained from the models. The results of prediction models are found to have a good correlation with experimental results, and the maximum error between the prediction results and the experimental results is less than 5%. As a future scope, the models are suggested for optimizing the process variables to improve energy efficiency, exergy destruction, and pressure drop objectives. PubDate: 2024-07-01
- A reverse Logistics Inventory Model with Consideration of Carbon Tax
Policy, Imperfect Production, and Partial Backlogging Under a Sustainable Supply Chain-
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Abstract: Abstract The awareness of consumers for reused or recycled items and environmentally friendly practices has grown over the past few decades, which has encouraged businesses to integrate sustainability development into their operations. As a result, industry’s supply chains are focusing on product recycling, waste reduction initiatives, and proper disposal of expired products. Sustainable development has benefited a variety of industries, including inventory management; it helps to sustain the environment as well as the economy. In this study, the effect of carbon emission on a reverse logistics inventory model is investigated when manufacturing and remanufacturing with multiple retailers are taken into account. In an effort to minimize the carbon emission, many countries are imposing strict limits on carbon emitters. Carbon tax policy is one of the laws that has been successfully implemented in many countries. In this paper, carbon emissions are released from various supply chain activities like product manufacturing, remanufacturing, storage, waste disposal, transportation, and deterioration. To control the excess release of carbon emission, carbon tax regulation is incorporated. During remanufacturing, due to some error, the machine switches from being “in control” to an “out of control” state and generates some imperfect quantities that are instantly inspected and reworked at some cost. Shortages are permitted with partial backlogging, and backlogging rate is constant. The aim of this study is to determine the optimal total cost under a forwards and backwards supply chain system. The model is demonstrated using several numerical examples, followed by a sensitivity analysis that seeks to investigate the impact of key parameters on the optimal solution. Convexity is depicted graphically, and significant features of the results are discussed to extract some management knowledge. The results indicate that the manufacturing cost, remanufacturing cost, and the rate of remanufacturing have a significant impact on the integrated cost of the inventory system. The obtained results also explain that parameters involved in carbon emission activity produce noticeable changes in the total cost. The findings are very managerial and instructive for organizations and businesses seeking environmentally conscious production systems. PubDate: 2024-07-01
- Developing a New Model for Ecological Capability Evaluation of Irrigated
Agriculture Using GIS in Sepidan Township, Iran-
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Abstract: Abstract Agricultural planning is a critical task that requires assessing numerous factors ranging from soil and terrain to socioeconomic markets and infrastructure. Assessing the ecological suitability of land for agricultural cultivation is a complicated procedure. It needs special environmental data and the knowledge of GIS experts to process and evaluate them. To improve the planning and management of irrigated lands, the present study aims to establish a model for the evaluation of ecological capability using a geometric mean approach. The proposed model was tested against several established methods, including the model of Iranian Ecology using Boolean logic, the weighted linear combination (WLC) technique, and the arithmetic average, using the normalized difference vegetation index (NDVI). Results showed the proposed model, calibrated with the geometric mean, was the most accurate (overall accuracy = 71% and kappa coefficient = 0.54) among the methods tested. In contrast, the Iranian ecological model (overall accuracy = 37.5% and kappa coefficient = 0.17) and the arithmetical mean approach (overall accuracy = 57.44% and kappa coefficient = 0.02) showed the least accuracy. The use of geometric mean assessment provides a high degree of flexibility in the identification of areas of agricultural use. Due to its simplicity and high accuracy, this model can serve as a framework for the assessment of ecological capability in other similar regions. In summary, this research highlights the importance of utilizing advanced models and technologies to enhance agricultural planning and management, ultimately leading to better crop production and a sustainable future. PubDate: 2024-07-01
- Synthesis and Optimisation of an Integrated Renewable Energy and
Greenhouse Network-
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Abstract: Abstract This paper presents a study on the synthesis and optimisation of a renewable energy and resource supply chain network (SCN) to satisfy agricultural greenhouse resource and energy demands. This is motivated by the high costs and emissions to run greenhouses due to the resources and energy required for optimal growth conditions. The investigation aims to contribute to the growing area of research on circular practices in the agricultural sector. The SCN includes biomass from agricultural waste transported to a utility hub, consisting of water and carbon dioxide (CO2) as resource supplies, as well as a boiler and steam turbine-generator and solar photovoltaic (PV), as energy conversion technologies. The resources and energy are distributed to greenhouses. The objectives are to minimise both the total annualised costs (TAC) and environmental impact (EI), calculated as CO2 emissions of the integrated network. Multi-periodicity accounts for the monthly and daily variation in constraints on the system, such as feedstock and solar radiation availability and energy limitations. The model is applied to a case study of an agro-industrial zone in Kwa-Zulu Natal (KZN) province, South Africa. The network meets greenhouse demands at a minimum TAC and EI of 8.052 \(\times {10}^{6}\) R/y and 14,370 tCO2e/y, respectively. The biomass supply chain (BSC) contributes most significantly to the TAC at 43.7% while biomass combustion makes up 99.8% of the EI. Additional key results include bagasse and corn stover being selected as the only feedstocks and rail as the transport mode. The 26,560 MWh/y of electricity supplied to the greenhouses is made up by 71.4% from the boiler and turbine-generator with the remainder from solar PV. The potential of solar PV as a clean and low-cost energy source is demonstrated by the model selection at its full capacity. The study confirms that holistic modelling and optimisation of renewable energy SCNs for greenhouses is necessary to meet a trade-off between the network costs and CO2 emissions. PubDate: 2024-07-01
- Eco-efficiency Evaluation of Thermal Spraying Processes using Data
Envelopment Analysis-
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Abstract: Abstract Eco-efficiency can be used as a useful indicator for decision-making. However, there are several production segments in which studies on eco-efficiency have not been conducted. One example is the thermal spraying production system. To evaluate eco-efficiency in the context of thermal spraying, one must integrate an approach that is able to assess the environmental impacts generated, as well as the costs involved for each step of the process. One technique that can meet this need is the data envelopment analysis (DEA). The overall objective of this work is to evaluate the eco-efficiency of thermal spray processes, through a combination of environmental and economic indicators using DEA. The environmental and economic variables (input and output) to be evaluated in the spraying process were verified. The framework to be employed for eco-efficiency evaluation was defined, and the evaluation was performed using DEA. A total of 33 decision-making units (DMU)s were evaluated, defined by 33 combinations of spraying processes, varying in three types (high-velocity oxy-fuel (HVOF), arc spray, and flame spray). Of the 33 DMUs, 14 presented scores equal to 1, that is, 14 eco-efficient processes present in the three types of TS analyzed. The type of application material used can influence these results, which can cause variation in the process parameters and in the final cost of the product. Companies in the industry can use these results as a basis to analyze their processes from an environmental standpoint concomitantly with the costs involved and increase their competitiveness in the market. PubDate: 2024-07-01
- Energy and Exergy Transfer Diagrams for Visualising Flows in Process
Systems-
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Abstract: Abstract This paper develops a new Exergy Transfer Diagram (ExTD), as an extension of the Energy Transfer Diagram (ETD), to enable the visualisation of both energy and exergy flows within a processing system. Based on Pinch Analysis, the ETD comprises regions in the temperature-enthalpy plot corresponding to the individual heat transfer operations. The position of each operation on the plot provides significant insight into the possible energy savings via retrofit. The ExTD complements the ETD and expresses the exergy flows, enabling the direct targeting of the minimum exergy input to the system and the component-level contributions to total exergy destruction and loss. The ExTD construction uses a Problem Table-based method to provide robust targets for the total exergy destruction of a system. Both the ETD and ExTD tools are demonstrated using an industrial case study of a milk dryer system. Three different utility structures are analysed using the tool including a conventional steam system, a steam system with cogeneration, and a high-temperature heat pump with a supplementary boiler. The results show that the heat pump option achieves the lowest minimum exergy input (4.5 MWx or 1.62 GJx/t) for the system, which represents a 15% reduction in the exergy requirement of the process and, if powered by low GHG-emissions electricity, could achieve a 90% reduction in fossil fuel use and GHG footprint. PubDate: 2024-07-01
- Power System Sustainability Enhancement Through Capacitor Placement
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Abstract: Abstract Sustainability enhancement is one of the optimization problems in the power system to improve system voltage stability and reduce system loss. Numerous well-known advantages of using capacitors in power systems include raising the maximum flow through cables and transformers, improving the system voltage profile and power factor, and lowering losses as a result of compensating the reactive component of power flow. It is a nonlinear integer optimization problem, with sites and sizes of shunt capacitors being discrete values. The purpose of this problem is to determine the optimum location and size of capacitors to be installed in the power system, including numerous constraints such as topology, load requirements, and operational constraints. From long back, the capacitor placement was found to be widespread approach toward sustainable development of power network. Various optimization methods have been developed to solve this issue which include heuristics, metaheuristics, and mathematical algorithms. Each method has its own opportunities as well as obstacles, and opting an appropriate method depends on the intricacy of the problem and the level of accuracy required. This paper describes the state of art of assorted methods of capacitor placement used in power systems with diversified efforts of researchers found to be altering with every upcoming decade. Analysis of these methods shows that still a huge gap needs to be covered to avail all possible benefits of capacitor placement and advanced research planning is required to develop more efficient and effective procedures of capacitor placement in power network. PubDate: 2024-07-01
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