Energy Waste Research Articles

Transformasi Energi Rumah Tangga: Otomatisasi Beban Listrik dengan IoT

This study aims to develop an Internet of Things (IoT)-based electrical load control system that can improve energy consumption efficiency in households. The system utilizes the Blynk application connected to relays and current sensors to monitor and control electricity usage in real-time. The research compares the system with and without the use of a repeater to assess its impact on response time. The results show that the use of a repeater reduced the communication response time between the devices and the application from 4.2 seconds to 2.8 seconds. This reduction in response time allows the system to optimize load management more quickly and efficiently. Additionally, the system has the potential to reduce energy waste, lower electricity costs, and support efforts to reduce carbon emissions through better energy management. However, challenges include the initial investment costs, device compatibility, and data security issues, which need to be addressed for wider implementation in Indonesia. With further development, this system holds great potential in supporting energy sustainability and household efficiency.

Green Practices: Way to Sustain with Small-Scale Enterprises

Environmental sustainability, once primarily associated with large corporations, is now a growing focus for small-scale enterprises (SSEs). These businesses are vital to global economic development, contributing around 40% to GDP in emerging economies and generating more than 50% of employment opportunities, according to the International Finance Corporation (IFC). However, despite their economic significance, the environmental impact of SSEs cannot be overlooked. Collectively, they contribute to issues such as high energy consumption, waste generation, and improper resource utilization. Adopting green practices offers SSEs an opportunity to address these challenges while unlocking significant benefits. Sustainable operations can lead to cost savings through reduced resource usage, improved brand reputation among eco-conscious consumers, and enhanced compliance with increasingly stringent environmental regulations. Furthermore, green initiatives align businesses with global sustainability goals and prepare them for future resource and market demands. This chapter delves into how small-scale businesses can effectively incorporate sustainable practices into their operations. It examines the specific challenges they face, such as financial constraints and lack of awareness, and offers practical strategies to overcome these hurdles. Ultimately, it underscores the importance of sustainability as a strategic imperative for long-term success in the evolving global marketplace. Keywords: Green Practices, Small-Scale Enterprises, Sustainability.

Unlocking landfill biogas potential: a feasibility study on sustainable energy in the UAE

Abstract Landfill biogas (LFB) projects present a promising solution for sustainable energy generation, yet their feasibility in arid climates remains largely unexplored. This study investigates the feasibility of generating biogas from landfill waste in the UAE, focusing on energy generation potential, economic viability, and environmental benefits. The study evaluates landfill biogas production using internal combustion engine and gas turbine technologies across three scenarios with varying methane content (40%, 50%, and 60% by volume). The results indicate that internal combustion engine technology demonstrates greater economic feasibility compared to the gas turbine technology, yielding a net present value of up to $83 million. Additionally, implementing landfill biogas to energy projects has the potential to power between 68,412 and 136,824 households while cutting greenhouse gas emissions by up to 66% compared to existing waste management practices. However, the relatively high levelized cost of energy underscores the need for policy interventions and financial incentives to enhance project viability. By addressing this critical knowledge gap, the study provides a replicable framework for optimizing waste-to-energy (WTE) systems in arid environments and contributes actionable insights to global renewable energy efforts.

Application of simulated annealing algorithm in multi-objective cooperative scheduling of load and storage of source network for load side of new power system

To improve the adaptability of grid load collaborative scheduling, a multi-objective collaborative scheduling method based on a simulated annealing algorithm for the load storage of grid loads on the load side of a new power system is proposed. Local bus transmission technology is adopted to collect the dynamic parameters of energy network load energy storage on the load side of the new power system. The collected load dynamic parameters are fused with energy distribution state parameters to extract the state characteristics of energy network load storage. The simulated annealing algorithm is adopted to realize the load characteristics fusion and adaptive scheduling processing of energy network on the load side of the power system, and the spectral characteristics of the load dynamic parameters are extracted. The dynamic scheduling method of simulated annealing is used to realize the multi-objective optimization of dynamic load of energy network. Based on the co-optimization results of simulated annealing, the optimization application of the simulated annealing algorithm in the multi-objective co-scheduling of loads and energy storage in a new power system is realized. The experimental results show that after 400 iterations, the control convergence accuracy of the proposed method reaches 0.980, which is significantly better than that of the comparison method, and performs well in terms of scheduling efficiency improvement, load scheduling stability, scheduling time and energy waste ratio, proving that the method has good multi-objective integration and strong optimization ability in the scheduling process, and improves the load balanced scheduling and adaptive control ability of the power system.

Comprehensive exergy, exergoeconomic, exergoenvironmental and energy audit assessment in a textile factory

In the industry, the discussion of energy and exergy analysis has gained increasing importance due to human needs from the past to the present. In the textile industry, this analysis has only been implemented in a limited manner and in isolated units. Specifically, in the dyeing, printing, and finishing units, steam and hot oil energy is utilized for heating processes. This heating requirement is met by steam boilers and hot oil boilers, which are essential for the operation of an integrated system. Identifying factors of energy loss and pollutant production, along with applying energy improvement techniques in textile factories, can significantly reduce the problems associated with fossil fuels. To identify potential energy and environmental improvements, an energy audit was conducted throughout the Borujerd Textile Factory in Iran, which goes beyond previous fragmented and isolated assessments to provide a comprehensive review of the entire system. This audit integrated thermography and flue gas analysis to enhance the accuracy and effectiveness of performance evaluation. By performing exergy, exergoeconomic, and exergoenvironmental (4E) analyses, the performance of the existing system was evaluated, providing a comprehensive overview of efficiency and the potential for improvements and optimizations. Environmental impact analysis was conducted using life cycle assessment in SimaPro for different sections of the plant. The results indicate that the most significant exergy destruction occurs in steam boilers and hot oil boilers, totaling 33.5 MW and 91%, respectively, as well as the washing after printing machine in the dyeing department, accounting for 3% of total exergy destruction due to high energy wastage and low efficiency in these devices. The cost rate of overall exergy destruction is estimated at $61.1 per hour. The highest environmental impacts were observed for steam boilers and the pad steam machine in the dyeing department, primarily due to the equipment's structure and the use of polluting materials that contribute to emissions from these devices. After the energy audit, the most effective solutions to the identified problems were proposed. It was also determined that the most significant heat loss occurs in pad steam machines, washing after printing, and bleaching washing machines.

Chemical Composition and Methane Production Potential of Agricultural Residues: Olive Pomace, Cottonseed Meal and Red Pepper Processing Waste

Biogas is a renewable energy source produced through the anaerobic digestion of organic materials such as agricultural residues, manure, sewage, and food waste. This process involves the breakdown of these materials by microorganisms in the absence of oxygen, resulting in the production of a mixture of gases, primarily methane (CH4) and carbon dioxide (CO2), along with trace amounts of other gases like hydrogen sulfide (H2S) and ammonia (NH3). Biogas production from agricultural residues like olive pomace (OLV), cottonseed meal (CTM), and red pepper processing (RPP) waste holds promise for sustainable energy generation and waste management. This study investigates the chemical composition and methane production potential of these residues, emphasizing their protein, fat content, and Acid Detergent Fiber (ADF)/Neutral Detergent Fiber (NDF) ratios. Chemical analyses revealed significant variations among the materials, with cotton waste exhibiting the highest dry matter, organic matter, protein, and fat content, while pepper waste showed the highest ash content, and olive waste had the highest fiber (ADF and NDF) content. Methane production ranged from 0.34 to 0.45 m³ kg-1 of organic dry matter (ODM), with cotton displaying the highest methane yield. Biogas production ranged from 0.61 to 0.78 m³ kg-1 ODM, with cotton again yielding the highest biogas production. Methane content in biogas varied between 54.64% and 57.72%, with cotton also showing the highest methane content. At the end of the study, the dry matter (DM) and organic dry matter (ODM), ash, protein, fat, ADF, and NDF ratios of the materials were determined to be 85.51%-94.09%, 87.91%-92.92%, 7.08%-12.09%, 7.49%-15.93%, 3.76%-8.01%, 52.16%-71.07%, and 34.49%-55.58%, respectively. The materials showed chemical differences. Research highlights include the significant bioenergy potential of olive waste and cottonseed meals, alongside the environmental benefits of utilizing olive pomace for biogas production. Experimental findings reveal varying methane and biogas yields across materials, influenced by their nutrient compositions. The study underscores the viability of integrating these agricultural residues into biogas production systems, contributing to renewable energy initiatives and sustainable agricultural waste management practices.

Operational properties of cement-free concrete with porous aggregate

The article presents the results of technology development and research on the operational properties of porous aggregate and cement-free concretes based on it. The purpose of the work is to study lightweight concretes containing a liquid–glass porous aggregate for resistance to various aggressive influences. The porous granular aggregate was obtained by firing a mixture of liquid glass with the ash of thermal power plants and an ash aluminosilicate microsphere. Binders based on caustic magnesite and liquid glass with the addition of thermal energy waste were used to produce coarse-pored concretes. The choice of cement-free binders is due to the high adhesion to the filler. The behavior of the developed concretes in various aggressive environments, under the influence of low and elevated temperatures, has been studied. The resistance of magnesia concrete to the effects of water and salt solutions has been revealed. The technological and operational advantages of liquid-glazed concrete are shown, featuring increased thermal insulation ability, satisfactory resistance to aggressive media and resistance to low and high-temperature fluctuations. The developed concretes can be used in the enclosing structures of objects for various purposes.

Reducing Carbon Footprint by Optimizing IOT Device Usage

The project improves the energy efficiency in the IoT system with reduction of carbon footprint. It so does by real-time monitoring and processing of data, device's control given the development through Flask, and handling of the front-end process using modern web technologies. The datasets are given in this analysis of the usage pattern of energy, thus highlighting its inefficiencies and allows for prediction in maintenance and adaptive optimisation strategies. This movement is devoid of waste of energy unnecessarily; thus, it brings about sustainability so far as it gives common-sensical understanding on how the IoT system can efficiently and effectively be operated. Thus, it goes hand-in-hand with global campaigns aimed at countering change efforts in climate by an IoT technology-a tool for reducing environmental impacts by the connected system using data analytics and software solutions. Keywords- Carbon Footprint, IoT, Machine Learning, Energy Optimization, Smart Cities, Sustainability, Predictive modeling.

Life Cycle Assessment of Methanol Production from Municipal Solid Waste: Environmental Comparison with Landfilling and Incineration

Inadequate waste management strategies play a significant role in exacerbating environmental challenges, such as increased greenhouse gas emissions, resource depletion, and other adverse ecological impacts. These issues are aggravated by the global rise in municipal solid waste (MSW) generation, surpassing the rate of population growth. Simultaneously, there is an urgent demand for sustainable energy solutions to combat climate change and its wide-ranging impacts. In response, this study addresses a critical question: is methanol production from MSW, a waste-to-chemical (WtC) alternative based on circular economy principles, a more environmentally sustainable approach compared to traditional waste-to-energy (WtE) methods like landfilling with biogas recovery and incineration? To answer this, this study evaluates the environmental performance of MSW-to-methanol technologies using life cycle assessment (LCA), focusing on key indicators such as global warming potential, resource depletion, and impacts on human health and ecosystem quality. The results reveal that methanol production from MSW significantly reduces global warming potential (GWP) by 87% compared to landfilling and 56% compared to incineration. Additionally, the process demonstrates high energy efficiency in electricity generation, achieving 80% of the output of incineration. These findings position MSW-to-methanol as a promising alternative for advancing sustainable waste management and renewable energy transitions. While the technology is still in its developmental stages, this research highlights the need for further advancements and policy support to enhance feasibility and scalability. By providing a comparative environmental analysis, this study contributes to identifying innovative pathways for addressing pressing waste management and energy sustainability challenges.

Redesign of Virtual Power Plant-led Electricity Demand Response Program

As the scale of renewable energy on the demand side continues to grow, a new demand response program (DRP), the virtual power plant (VPP), pays a rebate to the consumer and purchases his rooftop solar electricity. This electricity is dispatched to areas of electricity shortages, which is vital in balancing electricity loads and avoiding energy waste. However, the new DRP differs from the traditional DRP in terms of paying rebates. The traditional DRP requires consumers to respond above a specified baseline to receive a rebate. In contrast, in the new DRP, consumers can receive a rebate even if their response is small (i.e., no baseline). There is no research that addresses this divergence. Therefore, we construct a supply chain consisting of a consumer and a VPP for this novel DRP and analyze the strategic interactions between them in two situations where a baseline is not set/set. Our results show room for improvement in the DRP that dispatches electricity generated from rooftop solar. If the consumer generates more electricity from rooftop solar, the baseline, rather than frustrating the consumer, motivates the consumer to be more responsive. While the baseline also discourages the demand response process, it reduces the emissions generated from the consumer’s over-responsiveness. Additionally, our study suggests that a baseline, whether it facilitates or hinders the DRP, could benefit the VPP, depending on the business model of the VPP. In addition, we add several extensions to demonstrate the robustness of our model.

High-Performance Thermoelectric Composite of Bi2Te3 Nanosheets and Carbon Aerogel for Harvesting of Environmental Electromagnetic Energy.

Intensifying the severity of electromagnetic (EM) pollution in the environment represents a significant threat to human health and results in considerable energy wastage. Here, we provide a strategy for electricity generation from heat generated by electromagnetic wave radiation captured from the surrounding environment that can reduce the level of electromagnetic pollution while alleviating the energy crisis. We prepared a porous, elastomeric, and lightweight Bi2Te3/carbon aerogel (CN@Bi2Te3) by a simple strategy of induced in situ growth of Bi2Te3 nanosheets with three-dimensional (3D) carbon structure, realizing the coupling of electromagnetic wave absorption (EMA) and thermoelectric (TE) properties. With ultra-low thermal conductivity (0.07 W m-1 K-1), the CN@Bi2Te3 composites achieved a minimum reflection loss (RL) of 51.30 dB and an effective absorption bandwidth (EAB) of 6.20 GHz at an optimal thickness of 2.8 mm. Additionally, under a temperature gradient of 80 K, the flexible thermoelectric generator (FTEG) system generates a maximum output power of 42.2 μW. By absorbing 2.45 GHz microwaves to build the temperature difference, the EMA-TE-coupled device achieves an optimal Uoc of 38.4 mV, a short-circuit current of 1.03 mA, and an output power of 9.87 μW upon a radiation time of 50 s. This work establishes a potential pathway for further recycling electromagnetic energy in the environment, which is also promising for the preparation of large-area flexible EM to electrical energy conversion devices.

Progress in palladium-based bimetallic catalysts for lean methane combustion: Towards harsh industrial applications

<p>Significant volumes of lean methane (0.1–1.0 vol%) are released untreated into the atmosphere during industrial operations, contributing to the greenhouse effect and energy wastage. Catalytic methane combustion presents a promising avenue to mitigate these emissions. Depending on their active components, catalytic systems are predominantly categorized into noble metal-based and non-noble metal-based catalysts, with palladium (Pd)-based catalysts recognized for their superior low-temperature oxidation activity. Nevertheless, enhancing the thermal stability of Pd remains challenging, complicated by impurities such as H<sub>2</sub>O, SO<sub>2</sub> and H<sub>2</sub>S in the lean methane stream, which can cause catalyst poisoning and deactivation. Recent research has focused on the design of Pd-based bimetallic catalysts, offering improved stability, activity, and resistance to poisoning in harsh industrial conditions. This review examines advancements in improving the deactivation resistance of Pd-based bimetallic catalysts for lean methane combustion, covering active site characterization, dispersion and metal-support interactions, the role of auxiliary metals, and structural modulation strategies. It also investigates the impact of harsh industrial environments on Pd-based catalyst performance, focusing on deactivation mechanisms and mitigation strategies. Ultimately, this review identifies current research trends and challenges for Pd-based catalysts in demanding applications. By providing insights into the design of Pd-based catalysts with enhanced stability, activity, and resistance to poisoning, this review aims to guide the development of catalysts that meet industrial demands.</p>

Municipal solid waste management strategy selection: Multi-criteria decision making under uncertainty

For decades, due to the increasing generation of waste and its negative environmental impacts, efficient municipal solid waste management (MSWM) has become a major concern of sustainable development. On the other hand, selecting an appropriate strategy remains a critical issue for municipal authorities without applying a multi-criteria decision-making (MCDM) approach. This study aims to select the best MSWM strategy from five potential MSW management strategies under various factors that influence waste strategy selection, such as economic, social, technical, and environmental factors. This study used three fuzzy integrated MCDM methods, namely the Decision-Making Trail and Evaluation Laboratory (DMATEL), the Analytic Network Process (ANP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to select best MSWM strategies. The study used data from a survey of experts who had knowledge of waste management. The survey data was then analyzed using the DMATEL, ANP and TOPSIS methods under a fuzzy environment. The Fuzzy DEMATEL method is used to identify the causal relationships among the criteria and sub-criteria, while ANP is applied to determine the relative weights of MSWM strategy selection sub-criterion. Finally, TOPSIS is used to rank the waste management strategies depending on established sub-criteria. The result of fuzzy TOPSIS demonstrated that recycling of municipal solid waste is the best alternative which has the highest closeness coefficient followed by reuse. Thus, the result of this study revealed that MSWM strategies are ranked as: waste recycling (A1), reuse (A2), reduce (A1), energy recovery (A4), and disposal (A5), with closeness coefficient values of 0.80, 0.61, 0.60, 0.47, and 0.17, respectively.

Sustainable strategies for water, energy, and food waste management in India

Sustainable strategies for water, energy, and food waste management in India

The impact of China's green technology transfer on energy intensity in countries along the Belt and Road.

To assess the influence of China's green technology transfer on the energy intensity of Belt and Road Initiative (BRI) regions, we first constructed an index of green technology transfer using nearly 80,000 international green patent families from 2002 to 2020. This paper further quantified its association with the energy intensity of BRI regions and tested the possible energy rebound effect. The results revealed an increase in the number of green patent transfers from 2002 to 2015, followed by a decrease between 2016 and 2020, possibly due to increasing technological maturity. Among them, more than 50% of green technology patents were for alternative energy production, and 66% of green patents were transferred to developing countries. Moreover, green technology transfer and its subcategories can decrease the energy intensity of BRI countries, with the transfer of alternative energy production and waste management patents having the greatest effect. This inhibitory effect is more prominent in developing regions than in developed ones. Finally, we found that green technology transfer induced the energy rebound effect in the host country. Further analysis showed that green technology transfer can significantly inhibit energy consumption in developing regions by affecting the industrial structure and energy price. The conclusions drawn in this paper offer valuable insights for the promotion and implementation of green technology.

A novel post-combustion CO2 capture process for natural gas combined cycle power plant based on waste energy utilization and absorption heat transformer

A novel post-combustion CO2 capture process for natural gas combined cycle power plant based on waste energy utilization and absorption heat transformer

IoT Enabled Motor Drive Vehicle for the Early Fault Detection in New Energy Conservation

The key areas of interest in respect of which analyses are provided within the context of the paper are sustainable business practices that can help drive the change towards a low carbon economy. The study focuses on advanced techniques for managing businesses to advance the link between economic development and environmental conservation to optimize economic and environmental performance. Furthermore, based on the features, discussed in the paper, it is possible to identify the meaning of the concepts making the organizations introduce sustainability factors, as well as the possible effect these decisions may have on their future performance. This paper explores the role of machine learning (ML) and data-driven business strategies in promoting sustainable business development within smart cities. By integrating ML models across various sectors such as energy management, transportation, waste management, water usage, public safety, and urban planning, cities can optimize resources, reduce environmental impact, and enhance overall efficiency. Results from implementing these strategies in a smart city context show a 10% reduction in energy consumption (from 200,000 kWh to 180,000 kWh), a 50% increase in renewable energy share (from 20% to 30%), and a 40% decrease in CO2 emissions (from 500 tons to 300 tons) due to the use of autonomous electric vehicles. In transportation, average traffic speed improved by 16.67% (from 30 km/h to 35 km/h), and public transport efficiency increased by 21.43% (from 70% to 85%). In waste management, waste collection costs were reduced by 20% (from $50,000 to $40,000), and the recycling rate increased by 40% (from 25% to 35%). Water usage efficiency rose by 12.5% (from 80% to 90%), while water leak incidents decreased by 60% (from 50 to 20). Additionally, predictive policing reduced crime rates by 40% (from 5 to 3 per 1,000 residents), and emergency response times improved by 33.33% (from 15 minutes to 10 minutes). Finally, urban planning efficiency increased by 25% (from 60% to 75%) in land use, and green space area expanded by 40% (from 50 to 70 square kilometers).

Optimal and reliable design of stand-alone hybrid renewable energy systems: A multi-objective approach

ABSTRACT This study presents solutions for multi-objective, multi-constraint optimization for both photovoltaic (PV) and photovoltaic/thermal (PV/T) stand-alone hybrid renewable energy systems (SA-HRES). The main objective is to optimize the size and improve the reliability of SA-HRES, which relies exclusively on renewable resources for hydrogen production. To solve the problem, an optimization algorithm based on Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) was proposed and a new power management strategy (PMS) was developed. The reliability index, known as Power Loss Probability Percentage (LPSP), serves as both an objective function and a constraint. The waste energy percentage (PEW) is evaluated as a constraint to ensure that system efficiency remains within specified limits. Among the Pareto optimal solutions that satisfying the constraints of 10% LPSP and 5% PEW, the lowest PEW solutions for PV SA-HRES are $9388.5 with a PEW of 4.32% and LPSP of 6.0%. For PV/T SA-HRES, these values are $9211.6, 3.85%, and 6.9%, respectively. Despite similar annualized cost of system (ACS) values, the PV/T solution, which uses fewer PV/T, has an LPSP with a negligible difference and a lower PEW compared to the PV solution. This suggests the potential benefits of using PV/T instead of PV in HRES, offering improved efficiency and reliability.

Research on Energy Savings through Floating DO Measuring Device in SBR Wastewater Treatment Method

Objectives : The objective of this study is to propose an optimal operational control method to ensure stable effluent water quality and reduce treatment costs in the SBR(Sequencing Batch Reactor) wastewater treatment process. In particular, the study aims to maintain the dissolved oxygen(DO) concentration required for microorganisms while reducing power costs associated with excessive aeration.Methods : To address issues with conventional fixed DO sensors, such as scum formation, inaccuracies caused by bubbles and strong flow velocities during aeration, and reduced reliability due to fluctuating water levels, a floating DO sensor was introduced to measure DO concentrations in real-time. Based on these real-time measurements, the optimal DO concentration required for microbial activity was calculated, and a system was designed to automatically control the airflow rate set value(SV) of the turbo blower.Results and Discussion : The application of a single-variable DO control method effectively reduced the power consumption required for aeration in the SBR aeration tank. This approach prevented energy waste caused by excessive aeration while maintaining the appropriate DO concentration needed for microbial activity. These results demonstrate that the proposed method improves the reliability and efficiency of the system.Conclusion : The real-time DO control method using a floating DO sensor enables energy savings and ensures stable effluent water quality in the SBR process. The proposed method overcomes the limitations of conventional fixed DO sensors, contributing to reduced power costs and improved process efficiency.

Utilizing bio-energy and waste reduction techniques in FDM: Toward sustainable production practices

Additive manufacturing, particularly through fused deposition modeling (FDM), has significantly advanced rapid prototyping and customized production. However, traditional FDM practices raise environmental concerns due to energy use and waste generation. This research explores integrating bio-energy sources and advanced waste reduction techniques within FDM to enhance sustainable production practices. By implementing renewable energy sources and optimizing material usage, this approach aims to lower the carbon footprint associated with FDM. Our study reviews state-of-the-art methods such as biodegradable polymers, energy-efficient hardware, and waste-reducing design algorithms. Experimental results demonstrate that the use of recycled materials can maintain mechanical performance while enhancing sustainability. For instance, recycled PLA achieved a tensile strength of 52.4 MPa and an elongation at break of 6.1%, while recycled PHA showed a tensile strength of 59.4 MPa and an elongation at break of 5.5%. Both materials achieved high material recovery rates, with recycled PLA at 92.7% and recycled PHA at 90.2%, indicating effective closed-loop recovery. These findings indicate substantial reductions in material waste and energy consumption, promoting sustainable practices in both industrial and consumer-level FDM applications. This study contributes to the field of sustainable additive manufacturing by aligning with circular economy principles and addressing the global need for reduced environmental impact.