Energy Waste Research Articles

Multi-objective optimal scheduling of electricity consumption in smart building based on resident classification

By the end of 2021, the urbanization rate of China had reached 64.72 %. Increasing urbanization rates have led to an 80 percent share of carbon emissions in urban areas. Therefore, a load optimal scheduling model of smart buildings is proposed in this paper, which takes into account the cost of carbon emissions. The model aims to minimize the electric cost for building residents and maximize the utilization of distributed energy. The research focuses on the load optimal scheduling for two types of residents, i.e., the working residents and the retired ones, based on their electricity usage patterns and habits. To address the challenges of uneven load distribution, nonlinear behavior, and uncertainties introduced by electric vehicles and photovoltaic energy, the multi-objective beluga whale optimization algorithm with hybrid reverse learning competitive strategies (RCMBWO) is introduced. It utilizes the energy storage and discharge capabilities of electric vehicles to mitigate the uncertainties of photovoltaic energy generation. The simulation results show that load optimal scheduling for both types of residents can lead to significant cost savings for a smart building with 100 households, approximately 29,554 RMB per year. Furthermore, the optimized results can guide the determination of the appropriate size for the photovoltaic energy storage system, reducing energy waste resulting from insufficient energy consumption capability of smart buildings. The research on targeted load optimal scheduling for classified residents presents a viable solution for enhancing the cost-effectiveness and environmental benefits of smart buildings.

Synergy Analysis between Environmental Awareness, Student Participation, and Campus Policies in Waste Reduction and Energy Efficiency at Bina Sarana Informatika University

This research aims to analyze the synergy between three key elements of environmental awareness, student participation, and campus policy in the context of waste reduction and energy efficiency at Bina Sarana Informatika University. The method applied is descriptive observation, where data is collected through field notes in various campus locations as well as in-depth interviews with students. The results indicate that high environmental awareness among students contributes significantly to their active participation in waste management programs and efficient energy use practices. In addition, campus policies that support environmental initiatives were shown to play an important role in increasing student involvement. This synergy between environmental awareness, student participation, and campus policies contributes to the creation of a more sustainable campus environment. The findings also provide strategic recommendations to strengthen environmental education programs and increase student engagement in sustainability-focused campus policies, thereby encouraging more environmentally responsible behavior in the future.

Optimizing Motorcycle Manufacturing Sustainability through the Integration of Waste Heat Recovery and Metal Scrap Recycling: A Process Engineering Approach

The automotive industry manufacturing has experienced rapid growth 2–3 times by 2050, with motorcycles constituting around 30% of vehicles worldwide, but this increase in production has significantly heightened the demand for raw materials and energy. A major challenge arises in managing material waste and waste heat generated during the manufacturing process. This research aims to develop a framework that optimizes the synergy between material waste recycling and waste heat recovery to enhance the sustainability of the motorcycle industry, reduce waste, and lower energy consumption. The design leverages waste heat from the melting process to preheat raw materials, raising temperatures from around 50 °C to 350 °C before melting, thereby reducing additional energy needs, lowering emissions, and decreasing operational costs. Utilizing waste heat for preheating not only mitigates environmental impact and thermal load but also significantly improves energy efficiency, ultimately resulting in cost savings and optimized resource use. Utilizing waste heat directly for preheating raw materials has effectively lowered energy consumption by as much as 30%. This approach not only improves operational efficiency but also decreases production costs and minimizes environmental impact, offering a more sustainable solution for the manufacturing sector.

Thermoelectric Performance in Triplet‐Ground‐State Polymer Intrinsically Boosted by Enhanced Proquinoidal Characteristic

AbstractOver the past decade, polymer thermoelectric materials featuring flexibility, lightness, and bio‐friendliness have been paid increasing attention as promising candidates for waste heat recovery and energy generation. For a long time, the dominant approach to optimizing the thermoelectric performance of most organic materials is chemical doping, which, however, is not always ideal for practical applications due to its tendency to involve intricate processing procedure and trigger material and device instability. Currently, the pursuit of single‐component neutral thermoelectric materials without exogenous doping presents a compelling alternative. In this work, we designed and synthesized a high‐spin polymer material, PBBT‐TT, by simultaneously employing thieno[3,4‐b]thiophene (TbT) and benzo[1,2‐c : 4,5‐c′]bis[1,2,5]thiadiazole (BBT) units with pronounced proquinoidal characteristics, its analogue, PBBT‐T to demonstrate the effect of the TbT unit was also synthesized. The results indicate that because of the enhanced quinoidal resonance, increased spin density and strong intermolecular antiferromagnetic coupling, PBBT‐TT exhibits high intrinsic electrical conductivity and Seebeck coefficient, which showcases an outstanding power factor of 26.1 μW m−1 K−2 without doping. This achievement surpasses other neutral organic conjugated polymer and radical conductors, and is even comparable to some typical early‐stage doped polymers. Notably, PBBT‐TT exhibits remarkable ambient stability, retaining its initial thermoelectric performance over a 120‐day period. Our finding demonstrates that modulating the intermolecular spin interactions in open‐shell polymers through the introduction of strong proquinoidal units is an effective strategy for the development of doping‐free, intrinsically high‐performance polymer thermoelectric materials.

Thermoelectric Performance in Triplet-Ground-State Polymer Intrinsically Boosted by Enhanced Proquinoidal Characteristic.

Over the past decade, polymer thermoelectric materials featuring flexibility, lightness, and bio-friendliness have been paid increasing attention as promising candidates for waste heat recovery and energy generation. For a long time, the dominant approach to optimizing the thermoelectric performance of most organic materials is chemical doping, which, however, is not always ideal for practical applications due to its tendency to involve intricate processing procedure and trigger material and device instability. Currently, the pursuit of single-component neutral thermoelectric materials without exogenous doping presents a compelling alternative. In this work, we designed and synthesized a high-spin polymer material, PBBT-TT, by simultaneously employing thieno[3,4-b]thiophene (TbT) and benzo[1,2-c : 4,5-c']bis[1,2,5]thiadiazole (BBT) units with pronounced proquinoidal characteristics, its analogue, PBBT-T to demonstrate the effect of the TbT unit was also synthesized. The results indicate that because of the enhanced quinoidal resonance, increased spin density and strong intermolecular antiferromagnetic coupling, PBBT-TT exhibits high intrinsic electrical conductivity and Seebeck coefficient, which showcases an outstanding power factor of 26.1 μW m-1 K-2 without doping. This achievement surpasses other neutral organic conjugated polymer and radical conductors, and is even comparable to some typical early-stage doped polymers. Notably, PBBT-TT exhibits remarkable ambient stability, retaining its initial thermoelectric performance over a 120-day period. Our finding demonstrates that modulating the intermolecular spin interactions in open-shell polymers through the introduction of strong proquinoidal units is an effective strategy for the development of doping-free, intrinsically high-performance polymer thermoelectric materials.

Metaheuristic optimizing energy recovery from plastic waste in a gasification-based system for waste conversion and management

In an era where sustainable waste management and clean energy production are paramount, this study presents an innovative integration of plastic waste gasification with solid oxide fuel cell (SOFC) technology, optimized through metaheuristic particle swarm optimization (PSO). The research explores the conversion of polypropylene (PP) waste into syngas via gasification, which is then utilized as a fuel for SOFCs to generate electricity. The optimization process focuses on maximizing power and heating outputs while minimizing carbon dioxide emissions. The study's findings demonstrate the potential of integrating gasification and SOFC technologies to create a sustainable energy system that addresses the challenges of plastic waste. Key findings from the metaheuristic PSO multi-objective optimization reveal that optimal power production, approximately 360 kW, is achieved at temperatures exceeding 1140 K, irrespective of the steam/PP waste ratio. Heating production peaks at 1000 kW with temperatures above 1120 K and utilization factors over 0.765, while the minimum heating output is 700 kW. Emission analysis indicates a significant reduction in carbon dioxide emissions with increased temperatures and utilization factors, achieving a minimum of 700 kg/MWh at temperatures above 1120 K. The study's results demonstrate the effectiveness of the PSO optimization in fine-tuning the operational parameters of the integrated system, leading to improved energy efficiency and reduced environmental impact. Power production of 366.37 kW, a significant heating rate of 995.20 g/s, and emissions of 714.06 kg/MWh are the optimum performances. The research provides valuable insights into the potential of plastic waste-to-energy technologies as sustainable solutions for energy production and waste management.

Lyapunov-derived fuzzy temperature control for thermoelectric cooling system using dynamic updating law

In this paper, an intelligent temperature control strategy is proposed for thermoelectric cooling systems. The Lyapunov-based control method allows a dynamic updating law to be employed in the fuzzy logic system to improve the system performance in the presence of unmodeled dynamics. A new smooth function is also integrated into the control loop to limit input voltage, effectively addressing potential energy waste issue. Furthermore, the controller design challenges posed by even-power input are resolved using the adaptive fuzzy control method and Lagrange’s mean value theorem. Performance analysis indicates that the control function and state signals of the refrigeration system are bounded under our proposed method. Compared with the traditional intelligent control strategy, we only need to design a dynamic update law, which effectively reduces the complexity of the algorithm and is favorable for implementation. Finally, simulation and experimental results demonstrate the effectiveness of the method proposed in this paper. Compared to the traditional PID method, our control method reduces the maximum error by 29.4% and the setting time by 35.7% in the experiment.

Quantitative simulation and validation of energy carbon emission efficiency changes in Chinese urban agglomerations

In the context of the global energy dilemma, enhancing energy efficiency has inevitably become a pivotal strategy for mitigating energy waste and promoting sustainable development. Urban agglomerations, as growth poles leading high-quality regional economic development, play a significant role in this process. Within these urban agglomerations, the aggregation of various factors and the substitution of energy resources substantially influence the energy carbon emission efficiency (ECEE) of surrounding cities during their development and maturation phases. This study initially employs a three-stage Data Envelopment Analysis (DEA) to quantitatively analyze the ECEE values of 19 urban agglomerations from 2006 to 2020. It then establishes a methodology for calculating the joint intensity (JI) and joint threshold (JT) of ECEE within these urban agglomerations. Finally, a validation process is executed using MATLAB simulation and verification methodology to fit and authenticate the evolutionary patterns of ECEE in Chinese urban agglomerations. The primary objective of this research is to model the evolution of ECEE, thereby exploring the sustainable development pathways for urban agglomerations in China. The research findings indicate that: (1) The results from the three-stage DEA demonstrate that, after removing the influences of external environmental factors and random errors, the comprehensive technical efficiency (TE) of energy carbon emissions for the 19 urban agglomerations in China experienced a wave-like increase, rising from 0.410 to 0.506 between 2006 and 2020. (2) The calculation results of the constructed JI model indicate that the JT values of ECEE for national-level, regional-level, and local-level urban agglomerations are 1006.92, 226.60, and 160.14, respectively. The national-level urban agglomerations have significantly higher JT values and JI than the other two levels of urban agglomerations. (3) The results of the Matlab simulation verification show that 16 urban agglomerations fit well with the wave-like ascending evolutionary pattern. However, four urban agglomerations exhibit an opposite fitting effect due to the influence of their pillar industries or the small number of cities within these accumulations, making them unrepresentative. Consequently, the evolutionary curve of ECEE in Chinese urban agglomerations generally exhibits a wave-like upward trend over time.

Numerical optimization and experimental study of helically coiled tube heat exchanger based on Entransy degeneration theory

Heat exchangers are the most frequent energy transfer equipment in energy-consuming sectors, and their design and optimization are critical for reducing environmental impact and energy waste. In this study, a thermodynamic model of a spiral coil heat exchanger is reconstructed, and the use of Entrancy degradation theory is reviewed. The idea of layered modeling of helically coiled tube heat exchanger and the double-layer cycle model with simultaneous optimization of structural parameters and flow conditions are proposed, and experiments are performed to verify the reliability of the numerical model through. Multi-objective genetic algorithm is adopted for optimization with Entransy degeneration number (NgHE), Performance Evaluation Criteria (PEC) and Field Synergy Number (Fc) as optimization criteria to achieve multi-layer structure, multi-layer cycle and multi-objective optimization. The correlation equations for flow and heat transfer in the tube and shell sides of the heat exchanger are obtained, which are explored and verified. The results show that the heat exchanger thermodynamic modification model and the derived Entransy degeneration optimization criterion for the heat exchanger can reduce the overall useful energy loss by 11.2 % ∼ 15.2 %. When the minimum NgHE is taken as the optimization criterion, the NgHE is reduced by 13.6 % compared to the PEC and by 12.2 % compared to the Fc.

Probing-aided spectrum sensing-based hybrid access strategy for energy harvesting CRNs

To address the issues of energy supply and spectrum scarcity in Internet of Things (IoT), energy harvesting (EH) and cognitive radio (CR) technologies have been proposed and widely applied. In EH-CR networks (EH-CRNs), miss detection causes significant energy and time wastage of IoT devices, especially secondary users (SUs), and causes serious interference to primary users (PUs). To alleviate this concern, we propose a probing-aided spectrum sensing (PaSS) model for EH-CRNs, where M pairs of PUs and one pair of SUs coexist. The secondary transmitter (ST) harvests energy from the radio frequency (RF) signals of PUs for opportunistic spectrum access. In the PaSS model, probing operation is employed to further confirm the real state of the spectrum that has been sensed as free in order to avoid the waste of time and energy resulting from miss detection. Based on the PaSS model, we propose a novel hybrid access strategy, where the ST’s actions (i.e., sensing, probing, EH, underlay/overlay transmission mode) depend on the belief vector of M channels, energy state and data buffer state of the ST. By developing an adjusted double deep Q-network (ADDQN) reinforcement learning algorithm, we aim to find the optimal strategy that minimizes the long-term average number of packet losses (ANPL) and the ANPL minimization problem is an integer programming problem. Simulation results validate the ANPL performance of the ST in the ADDQN-PaSS model, and reveal impacts of network parameters on the performance of the ST, and find that at least 7.9% reduction of ANPL is achieved by using the ADDQN-PaSS model.

Sustainable Transformation: A Case Study of an Engineering-to-Order Additive Manufacturing Firm

Purpose: Addressing sustainability challenges in additive manufacturing (AM) is critical due to high energy consumption and waste. Optimising AM operations is vital for sustainability. However, the existing literature lacks practical examples for AM companies on how to enhance sustainability. To address this gap, a case study within an AM firm was conducted. Design approach: Using the analytical hierarchy process (AHP), sustainability key performance indicators (KPIs) were identified, aligned with the firm’s strategic objectives. Sustainable value stream mapping (Sus-VSM) analysed the production process for sustainability performance. A sustainability strategy map (SSM) was created based on the five perspectives of the 4th generation balanced scorecard (BSC) approach and the results from the case study. Findings: The research identified optimisation areas in the multi-jet-fusion (MJF) process, crafted tailored sustainability KPIs, and developed a SSM to seamlessly integrate sustainability initiatives into the company’s vision. Value: This contribution provides a structured methodology for selecting KPIs and offers a holistic approach to implementing Sus-VSM within the AM industry. The manuscript emphasises the need to incorporate a fifth perspective into the BSC and proposes a framework for developing a SSM. This study aims to guide AM companies toward a more environmentally responsible and socially conscious approach to manufacturing.

Advances in bimetallic metal organic frameworks (BMOFs) based photocatalytic materials for energy production and waste water treatment

Advances in bimetallic metal organic frameworks (BMOFs) based photocatalytic materials for energy production and waste water treatment

Parametrical Choice of the Optimized Fusion System for a FFHR

Fusion–fission hybrid reactors are concepts of subcritical reactors based on the coupling of fusion and fission devices. In this case, the fusion reactor would work as an external neutron supplier for the fission core of the machine. Such systems could, in principle, operate as multi-purpose machines, such as energy generators, breeders and waste burners. The large availability of fusion and fission technologies makes the choice of devices to couple quite chaotic. In fact, most of the concepts proposed in the literature are based on attempts without real optimization. The purpose of this paper is to propose a parameter which could provide practical information regarding the choice or the design of the fusion system of an FFHR. An engineering approach based on the estimation of the energy efficiency of FFHRs was used. An evaluation of the parameter and some of its possible practical applications are shown. Obtained results indicate that, from a geometrical point of view, compact machines would need lower Q-values to reach high neutron source performance.

Facile synthesis of nitrogen-containing multiwalled carbon nanotubes as a worth metal-free electrocatalyst for hydrogen evolution reaction and semicarbazide oxidation

Studies of metal-free carbon nanostructures prove effective in energy and environmental applications due to their molecular tunability and vast chemical space. Herein, we synthesize nitrogen-containing multi-walled carbon nanotubes (N-MWCNTs) via. acid-catalysed incorporation of 3, 4-diaminopyridine into multi-walled carbon nanotubes (MWCNTs), and demonstrating their efficacy in electrocatalytic hydrogen evolution reaction (HER) and semicarbazide (SCB) oxidation for energy and environmental waste management, respectively. Successful synthesis is further confirmed by analysis techniques, i.e. Fourier transform infrared (FTIR) spectral analysis shows the diminishing OH frequency around 3250 cm−1 in MWCNTs after functionalization and the formation of an OC–NH bond in N-MWCNTs at 1710 cm−1. X-ray diffraction (XRD) confirms the incorporation of N-species, while Raman spectroscopic analysis indicates an increase in the ID/IG ratio MWCNTs (∼1) to N-MWCNTs (∼1.25), suggesting more defective sites in the N-MWCNTs nanocomposite. X-ray photoelectron spectroscopy (XPS) reveals peaks at 399.38, 400.49, and 402.05 eV, attributed to pyridinic-N, aromatic amide-N, and protonated amine groups, respectively. N₂ adsorption-desorption studies shows a high Brunauer-Emmett-Teller (BET) surface area for N-MWCNTs (119.22 m2/g) compared to MWCNTs (74.94 m2/g). Linear sweep voltammetry (LSV) profiles demonstrate enhanced activity of N-MWCNTs for both HER and SCB oxidation at an ultralow potential of E = −0.55 V vs RHE at 10 mA/cm2, with a lower Tafel slope of 108 mV.dec−1. Moreover, the electrochemical sensing studies indicates on N-MWCNTs were demonstrating an efficient electron transfer to SCB with the lower detection limit of 0.004 μmol. This work provides carbon-based metal-free electrocatalysts for energy harvesting and environmental management.

ENERGY AUTOMATION SUPPORTS ENERGY CONSUMPTION INTENSITY IN CLASSROOMS

Automation of energy use to control energy consumption intensity (IKE) in classrooms is carried out using an Arduino Nano-based system. This system utilizes an IR transmitter to send signals to the air conditioning unit, a servo motor to position the IR transmitter to the appropriate air conditioning unit, a relay to control the lights, and a Real-Time Clock (RTC) module for scheduling based on a specified schedule. The main goal is to prevent energy waste and ensure comfort by turning on and off the air conditioning unit and lights according to a preset schedule. This automatic scheduling includes time setting, transmitter IR control, servo motor, relay control, and LCD. Programmed scheduling ensures that the air conditioner and lights only turn on when needed, while the LCD provides real-time information about the status of the air conditioner and lights. With this automation, the system helps reduce excessive energy consumption, drives significant energy savings, and creates a comfortable and energy-efficient learning environment. The automatic monitoring and regulation system also allows users to focus more on teaching and learning activities without having to worry about manual settings for air conditioning and lights.

Correlation of Water and Energy Parameters in a South of Minas Gerais Water Supply System

Objective: The objective of this study is to investigate the correlation between water and energy parameters in order to obtain water and energy consumption, according to studies by a local water utility. Theoretical Framework: The main theories presented here are the water and energy balances of a water supply network, whose authors can be found throughout the work. Such concepts are fundamental, as they allow correlating the parameters that are the objective of the study. Method: The methodology adopted for this research comprises a literature review to obtain the necessary theoretical basis, as well as data collection carried out through campaigns by the research group throughout its trajectory, in previous works. The processing of the collected data was carried out using water and energy balances, with the consequent correlation of such parameters in relation to water losses in the sector under study. Results and Discussion: The results obtained revealed that losses can reach up to R$249,949.06 in 5 years in the sector under study, reconciling water and energy losses due to the inefficiency of the system under study. Research Implications: This research, due to its approach, can guide measures to increase water and energy efficiency in sanitation companies, resulting in important financial and environmental gains for society by reducing water and energy waste and reducing operating costs, with resulting financial relief for society. Originality/Value: This study contributes to the literature by correlating water and energy parameters in the study of water distribution losses, having revealed the monetary values ​​of the losses and their impacts on society.

Pharmaceutical Wastewater and Sludge Valorization: A Review on Innovative Strategies for Energy Recovery and Waste Treatment

Currently, a large amount of pharmaceutical waste (PW) and its derivatives are being produced and, in some cases, inadequate management or treatment practices are applied. In this regard, this research explores the adoption of several alternatives to deal with these problems, including biocarbon within the framework of the circular economy. Photocatalytic nanomaterials have been also extensively discussed as a feasible way to remove pharmaceutical compounds in wastewater. Although there are existing reports in this area, this document provides a detailed study of the synthesis process, experimental conditions, the integration of photocatalysts, and their impact on enhancing photocatalytic efficiency. Additionally, the low cost and ease of fabrication of lab-scale microbial fuel cells (MFCs) are thoroughly examined. This innovative technology not only facilitates the degradation of hazardous compounds in wastewater but also harnesses their energy to generate electricity simultaneously. The aforementioned approaches are covered and discussed in detail by documenting interesting recently published research and case studies worldwide. Furthermore, this research is of significant importance because it addresses the valorization of PW by generating valuable by-products, such as H2 and O2, which can occur simultaneously during the photodegradation process, contributing to more sustainable industrial practices and clean energy technologies.

Experimental and numerical investigation of heat transfer modes on pot surfaces in a power range of a cooking porous burner

The investigation of convective and radiative heat transfers to a cooking pot in a porous burner, coupled with an analysis of the pot's bottom and side contributions to total heat transfer, remains an underexplored area of research. In this study, we adopt a comprehensive approach, combining experimental measurements and 3D numerical models, to explore the practical application of a Silicon carbide porous burner fueled with natural gas in cooking pots with power ranging from 12.15 kW to 31.04 kW. Three primary aspects are examined: differentiating between radiative and convective heat transfer contributions, investigating porous mixing characteristics, and analyzing the burner's thermal and combustion efficiencies. To facilitate this investigation, a dedicated test bench is meticulously designed and constructed, equipped with state-of-the-art measuring instruments to effectively monitor the thermal behavior of the heating process. The results reveal that the higher Damköhler number at higher power, driven by the dominance of chemical time over mixing time, accentuates the importance of chemical reactions in heat transfer to the pot. Moreover, increasing the power leads to a reduction in the burner's overall thermal efficiency, from 29.2% to 18.8%, due to a higher energy waste percentage, escalating from 45.12% at P = 12.15 kW to 65.31% at P = 31.04 kW. This increase in power also strengthens the downward movement of the flame and its detachment from the pot surface. The pot's bottom contribution to total heat transfer ranged from 76.7% to 95.5%, with convection alone accounting for over 98% in all cases. Consequently, optimizing the pot bottom geometry for the purpose of enhancing convection presents promising avenues for significantly boosting thermal efficiency. These findings highlight the potential of the investigated porous burner for efficient and clean combustion in cooking appliances.

Efficient risk-based inspection framework: Balancing safety and budgetary constraints

Efficient equipment maintenance is paramount across various industries to mitigate energy wastage and avert potential disasters such as hazardous emissions, fires, and explosions. Within this context, the adoption of risk-based inspection strategies has emerged as a crucial method for assessing equipment integrity. This study integrates the principles of Risk-Based Inspection (RBI) with a novel two-objective mathematical model, resulting in a comprehensive framework for equipment inspection programs. The primary aim of this framework is to reduce overall risk exposure while optimizing inspection expenditures. Unlike conventional approaches, this methodology eliminates the necessity to define threshold risk levels. By integrating inspection costs into the model, the assessment of Failure Consequences, and thereby, the decision-making process has been streamlined. This innovative algorithm effectively balances the reduction of failure likelihood with the minimization of inspection costs, enhancing decision-making capabilities. Importantly, this approach offers significant protection against energy wastage and the occurrence of leaks through robust risk management strategies. The algorithm employs specialized operators to expedite the discovery of optimal solutions. Empirical validation through a case study conducted at a Petrochemical Plant highlights the practicality and effectiveness of the proposed framework.

Identification of optimal waste-to-energy strategies for sustainable development in Iran: SWOT analysis, hybrid MCDM methods, and game theory

The growing global focus on environmental sustainability and the pressing need for efficient waste management and energy crisis mitigation have prompted extensive investigations into sustainable waste management strategies. Given Iran's economic development and population growth, the country faces challenges in energy supply and waste management, making waste-to-energy (WtE) applications a promising solution for sustainable waste management. This study employs a combination of SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis, Multi-Criteria Decision-Making (MCDM) approaches, and game theory to explore WtE technologies and processes, evaluate their applicability within Iran's context, and identify the most effective WtE strategies for the country. Furthermore, game theory and fuzzy Shapley value analysis were utilized to determine the optimal combination of WtE development strategies. The strategy player “SO” held the highest position of power, with a fuzzy Shapley value of (0.391, 1.744, 3.264), resulting in the identification of the optimal strategy combination of SO2ST2WO1WT2, with a value of (0.429, 0.679, 0.893). The recommended combination emphasizes landfill with gas capture, development of incineration power plants, and integrated resource recovery through residue-derived fuel (RDF) implementation. Achieving these objectives necessitates energy policy reforms, pricing adjustments, improvements in the energy subsidy system, and infrastructure and market development.