Minimum Energy Loss Research Articles

The optimal control law of the power supplied to the wheeled vehicle in case of curvilinear movement

INTRODUCTION: Highly mobile wheeled vehicles are designed to move on roads and terrain in various road and soil conditions, which is accompanied by frequent and significant changes in traction forces and rolling resistance forces. In this regard, in order to maintain vehicle mobility and ensure low energy costs when performing transport tasks, it is necessary to continuously change the operating mode during movement from completely locked to differential in the case of a mechanical transmission. At the same time, the transmission operating mode selected by the driver is not always rational. Thus, the development of a law for controlling the power supplied to the propulsion system, ensuring minimal energy losses while maintaining vehicle mobility in widely varying road conditions, is an urgent task. PURPOSE OF THE STUDY: Increasing the energy efficiency of highly mobile wheeled vehicles by applying a control law for the power supplied to the propulsion system, adaptive to driving conditions. METHODOLOGY AND METHODS: Increasing the energy efficiency of movement can be achieved by reducing losses due to wheel slipping by controlling the power supplied to the propulsion unit. It is advisable to obtain the control law as a result of solving an optimization problem, where the loss power is chosen as the objective function, and the traction forces developed on each of the wheels are chosen as the varied values. At the same time, in order to maintain the possibility of vehicle movement, it is necessary to take into account that the total traction force on all wheels must be determined by external conditions and provided by the power plant. To solve the optimization problem, the Lagrange multiplier method was used. RESULTS AND SCIENTIFIC NOVELTY: The studies carried out made it possible to obtain in analytical form a unified law of adaptive control of the power supplied to the propulsors, applicable in a wide range of road conditions in both straight and curved motion, providing a close to optimal distribution of moments across the driving wheels of the machine, obtained as a result of numerical optimization. PRACTICAL SIGNIFICANCE: The application of the developed law for controlling the power supplied to the propulsors, based on the use in the process of movement of information only about the longitudinal and vertical forces, rotational speeds and angles of rotation of the wheels (trajectory radius), will improve the efficiency of performing transport tasks when moving a vehicle in continuously changing road conditions due to reducing the load on the driver in terms of controlling differential locks in comparison with a manual transmission both in straight and curved motion.

Ionic covalent organic framework based quasi-solid-state electrolyte for high-performance lithium metal battery

Lithium metal solid-state batteries are promising as rechargeable energy storage devices due to their non-combustible nature, resistance to high temperatures, and non-corrosive properties. However, their widespread application is hindered by low lithium-ion conductivity and poor compatibility at the electrode/electrolyte interface. To address these challenges, two covalent organic frameworks (COFs), one with functional imidazolium groups (Dha-COFim) and one without (Dha-COF), were synthesized. Ionic liquids (ILs) were then incorporated into these COFs to create quasi-solid-state electrolytes (Dha-COFim-IL and Dha-COF-IL). The Dha-COFim, with its ordered porous structure, forms interconnected ion channels that enable fast lithium-ion transport and enhance lithium salt dissociation, achieving excellent thermal stability, high ionic conductivity (1.74 × 10⁻³ S cm⁻1), and a wide electrochemical window at room temperature. Density functional theory (DFT) calculations showed that the fixed imidazolium groups in Dha-COFim enhance interactions with TFSI⁻ anions, improving lithium salt dissociation. This allows free lithium ions to move quickly through the channels with minimal energy loss. Additionally, the formation of a stable SEI layer rich in LiF and Li3N at the lithium metal/electrolyte interface accelerates Li⁺transport, ensuring uniform lithium deposition and superior battery performance. When combined with a LiFePO4 cathode, the LiFePO4‖Dha-COFim-IL‖Li cell delivers high discharge capacity and excellent cycling stability, providing a new strategy for designing quasi-solid-state electrolytes for high-energy-density lithium batteries.

Fluorinated and Methylated ortho-Benzodipyrrole-Based Acceptors Suppressing Charge Recombination and Minimizing Energy Loss in Organic Photovoltaics

Fluorinated and Methylated <i>ortho</i>-Benzodipyrrole-Based Acceptors Suppressing Charge Recombination and Minimizing Energy Loss in Organic Photovoltaics

High-Performance Shear Mode Ultrasonic Transducer Operating at Ultrahigh Temperature Fabricated with Bi12SiO20 Piezoelectric Crystal.

Shear mode ultrasonic waves are in high demand for structural health monitoring (SHM) applications owing to their nondispersive characteristics, singular mode, and minimal energy loss, especially in harsh environments. However, the generation and detection of a pure shear wave using conventional piezoelectric materials present substantial challenges because of their complex piezoelectric response, involving multiple modes. Herein, we introduce a high-quality piezoelectric crystal Bi12SiO20 (BSO), exhibiting a robust piezoelectric response (d14 = 45.1 pC/N) and a pure vibration mode. Thereafter, we developed a BSO-based shear mode ultrasonic transducer and conducted finite element simulations and experiments. Results indicated that the proposed transducer excels in exciting and receiving pure shear waves with a high signal-to-noise ratio across a wide operating frequency range. Remarkably, the proposed transducer demonstrates efficacy ranging from 25 to 800 °C, which exhibits an exceptionally high operating temperature. These excellent attributes, coupled with cost-effectiveness, render this crystal highly promising for practical SHM applications.

On the Optical response of all-dielectric metasurface in the exceptional point

All-dielectric nanophotonics leverages high-refractive-index dielectric materials to manipulate light at the nanoscale with minimal energy loss, offering strong electric and magnetic resonances. These properties make all-dielectric structures ideal for a range of advanced photonic applications, from ultra-thin lenses to sensors. In this study, we explore the multipole response of all-dielectric metasurfaces when operating near an exceptional point (EP), a singularity in non-Hermitian systems where eigenmodes coalesce. Numerical simulations reveal that at the EP, the metasurface’s resonance splits, with significant contributions from magnetic dipole (MD) and electric quadrupole (EQ) modes. These findings enhance our understanding of EPs in metasurface physics and highlight the potential of this geometry for applications in photonic devices.

Thermal Optimalization with CFD Analysis and Real-Time Performance Identification in Briquette Ovens Using Modbus-Based Communication

Briquette ovens that utilize biomass energy frequently face obstacles in achieving consistent heat distribution, resulting in ineffective energy usage and varying product quality. This study tackles these challenges by merging Computational Fluid Dynamics (CFD) analysis, performed with Cradle software, alongside a Modbus-based temperature data acquisition system to significantly boost energy efficiency and temperature regulation. A total of 32 K-type thermocouples were meticulously positioned within the oven to gather real-time temperature data, which was processed through LabVIEW. CFD simulations revealed irregular heat distribution patterns, especially at the rear of the oven. The temperature data obtained via Modbus corroborated these observations, allowing for strategic modifications to enhance heat distribution and minimize energy loss. The system achieved an impressive accuracy rate of 98.89%, with a mere error margin of 1.11%, substantially elevating the oven’s energy efficiency and briquette drying capabilities. This research clearly illustrates that the integration of CFD modeling with real-time data acquisition constitutes a powerful method for optimizing the functionality of industrial heating systems.

Curvature-Specific Coupling Electrode Design for a Stretchable Three-Dimensional Inorganic Piezoelectric Nanogenerator.

Structures such as 3D buckling have been widely used to impart stretchability to devices. However, these structures have limitations when applied to piezoelectric devices due to the uneven distribution of internal strain during deformation. When strains with opposite directions simultaneously affect piezoelectric materials, the electric output can decrease due to cancellation. Here, we report an electrode design tailored to the direction of strain and a circuit configuration that prevents electric output cancellation. These designs not only provide stretchability to piezoelectric nanogenerators (PENGs) but also effectively minimize electric output loss, achieving stretchable PENGs with minimal energy loss. These improvements were demonstrated using an inorganic piezoelectric material (PZT thin film) with a high piezoelectric coefficient, achieving a substantial maximum output power of 8.34 mW/cm3. Theoretical modeling of the coupling between mechanical and electrical properties demonstrates the dynamics of energy harvesting, emphasizing the electrode design. In vitro and in vivo experiments validate the device's effectiveness in biomechanical energy harvesting. These results represent a significant advancement in stretchable PENGs, offering robust and efficient solutions for wearable electronics and biomedical devices.

Suppressing Exciton–Vibration Coupling via Intramolecular Noncovalent Interactions for Low‐Energy‐Loss Organic Solar Cells

AbstractMinimizing energy loss is crucial for breaking through the efficiency bottleneck of organic solar cells (OSCs). The main mechanism of energy loss can be attributed to non‐radiative recombination energy loss (ΔEnr) that occurs due to exciton–vibration coupling. To tackle this challenge, tuning intramolecular noncovalent interactions is strategically utilized to tailor novel fused ring electron acceptors (FREAs). Upon comprehensive analysis of both theoretical and experimental results, this approach can effectively enhance molecular rigidity, suppress structural relaxation, reduce exciton reorganization energy, and weakens exciton–vibration coupling strength. Consequently, the binary OSC device based on Y‐SeSe, which features dual strong intramolecular Se ⋅ ⋅ ⋅ O noncovalent interactions, achieves an outstanding power conversion efficiency (PCE) of 19.49 %, accompanied by an extremely small ΔEnr of 0.184 eV, much lower than those of Y‐SS and Y‐SSe based devices with weaker intramolecular noncovalent interactions. These achievements not only set an efficiency record for selenium‐containing OSCs, but also mark the lowest reported ΔEnr value among high‐performance binary devices. Furthermore, the ternary blend device showcases a remarkable PCE of 20.51 %, one of the highest PCEs for single‐junction OSCs. This work demonstrates the effectiveness of intramolecular noncovalent interactions in suppressing exciton–vibration coupling, thereby achieving low‐energy‐loss and high‐efficiency OSCs.

Suppressing Exciton-Vibration Coupling via Intramolecular Noncovalent Interactions for Low-Energy-Loss Organic Solar Cells.

Minimizing energy loss is crucial for breaking through the efficiency bottleneck of organic solar cells (OSCs). The main mechanism of energy loss can be attributed to non-radiative recombination energy loss (ΔEnr) that occurs due to exciton-vibration coupling. To tackle this challenge, tuning intramolecular noncovalent interactions is strategically utilized to tailor novel fused ring electron acceptors (FREAs). Upon comprehensive analysis of both theoretical and experimental results, this approach can effectively enhance molecular rigidity, suppress structural relaxation, reduce exciton reorganization energy, and weakens exciton-vibration coupling strength. Consequently, the binary OSC device based on Y-SeSe, which features dual strong intramolecular Se ⋅ ⋅ ⋅ O noncovalent interactions, achieves an outstanding power conversion efficiency (PCE) of 19.49 %, accompanied by an extremely small ΔEnr of 0.184 eV, much lower than those of Y-SS and Y-SSe based devices with weaker intramolecular noncovalent interactions. These achievements not only set an efficiency record for selenium-containing OSCs, but also mark the lowest reported ΔEnr value among high-performance binary devices. Furthermore, the ternary blend device showcases a remarkable PCE of 20.51 %, one of the highest PCEs for single-junction OSCs. This work demonstrates the effectiveness of intramolecular noncovalent interactions in suppressing exciton-vibration coupling, thereby achieving low-energy-loss and high-efficiency OSCs.

Simulation and Experimental Research on the Energy Loss of Confluence Pipelines

Compared with T- and Y-shaped confluence pipelines, arc confluence pipelines have a smaller energy loss coefficient. In the study presented herein, numerical simulation analyses of the flow fields of T-shaped, Y-shaped, bifurcated, and arc confluence pipelines were carried out. An experimental system was designed to study the energy loss coefficient of the arc confluence pipeline by using five different pipe diameters and nine different radii with water as the working fluid and analyze the influence of pipe diameter, radius, and Reynolds number on the energy loss of the arc confluence pipeline. As the radius of the arc confluence pipeline increases, the energy loss coefficient of confluence first decreases and then increases, and the minimum energy loss corresponds to a radius of 65 mm; with an increase in Reynolds number, the energy loss coefficient of confluence first decreases gradually and tends to a certain value. With an increase in diameter, the energy loss coefficient of confluence decreases gradually.

Suppressing Exciton–Vibration Coupling and Reducing Nonradiative Energy Loss in Conjugated Polymers Through Fluorine Substitution in Side Chains

Fluorine (F) substitution in polymers modulates both molecular energy levels and film morphology; however, its impact on exciton–vibrational coupling and molecular reorganization energy is often neglected. Herein, we systematically investigated F‐modified polymers (PBTA‐PSF, PBDB‐PSF) and their nonfluorinated counterparts (PBTA‐PS, PBDB‐PS) through simulations and experiments. We found that F atoms effectively lower the vibrational frequency of the molecular skeleton and suppress exciton–vibration coupling, thereby reducing the nonradiative decay rate. Moreover, introducing F atoms significantly decreases the reorganization energy for the S0 → S1 and S0 → cation transitions while increasing the reorganization energy for the S1 → S0 and cation → S0 transitions. These changes facilitate exciton dissociation and reduce the energy loss caused by dissociation and nonradiative recombination of excitons. Additionally, introducing F atoms into polymers enhances the π–π stacking strength and the crystal coherence length in both neat and blended films, ultimately resulting in improvements in the power conversion efficiency of PBTA‐PSF:L8‐BO and PBDB‐PSF:L8‐BO are 16.51% and 17.59%, respectively. This study provides valuable insights for designing organic semiconductor materials to minimize energy loss and achieve a higher power conversion efficiency.

Simulation study of the effects of different materials used in the core of a TSV inductor on its behavior when integrated into a DC/DC converter

This research focuses on the design and modeling of a Through-Silicon via (TSV) inductor, tailored for integration within an interleaved boost converter. The TSV inductor features a winding structure designed with vertical TSVs linked to horizontal rectangular connections, creating an efficient topology. A comprehensive electrical model has been developed to account for all parasitic effects arising from the various physical components of the TSV inductor. MATLAB software was employed to analyze the influence of different materials used in the construction of the TSV inductor, with the goal of optimizing its inductance values and quality factor. This approach involved selecting materials that minimize energy losses, thereby enhancing the overall performance of the inductor. To validate the electrical parameters derived from the physical characteristics and material properties, the TINA simulation software was used. It simulated the interleaved boost converter circuit incorporating the TSV inductor’s equivalent electrical circuit for accuracy verification.

Highly Sensitive T-Shaped Quartz Tuning Fork Based CH4-Light-Induced Thermoelastic Spectroscopy Sensor with Hydrogen and Helium Enhanced Technique.

In this paper, a highly sensitive methane (CH4) sensor based on light-induced thermoelastic spectroscopy (LITES) and a T-shaped quartz tuning fork (QTF) with hydrogen (H2) and helium (He) enhancement techniques are reported for the first time. The low resonant frequency self-designed T-shaped QTF was exploited for improving the energy accumulation time. H2 and He were utilized as surrounding gases for the T-shaped QTF to minimize energy loss, thereby enhancing the sensitivity of the LITES sensor. Additionally, a fiber-coupled multi-pass cell (FC-MPC) with a 40 m optical length was utilized to improve the optical absorption of CH4. The frequency response of the T-shaped QTF with different concentrations of H2 and He was investigated, and the Q factor in the H2 and He environment increased significantly. Compared to operating QTF in a nitrogen (N2) environment, the signal amplitude was enhanced by 2.9 times and 1.9 times in pure H2 and He environments, respectively. This enhancement corresponded to a minimum detection limit (MDL) of 80.3 ppb and 113.6 ppb. Under different CH4 concentrations, the T-shaped QTF-based H2-enhanced CH4-LITES sensor showed an excellent linear response. Furthermore, through Allan deviation analysis, the MDL of the T-shaped QTF-based H2-enhanced CH4-LITES can reach 38 ppb with an 800 s integration time.

Impact of structural changes of Ge–Sb–Se chalcogenide glasses on their acousto‐optic properties

AbstractAcousto‐optic (AO) devices are known for their high parallel processing capabilities and efficient transduction, essential for real‐time processing systems. As a vital AO medium, chalcogenide glasses exhibit high AO figures of merit (M2), yet high M2 is often coupled with high acoustic attenuation (α). Thus, to obtain the trade‐off between M2 and α, a series of xGeSe2−(100−x)Sb2Se3 (40 ≤ x ≤ 85) is investigated for their AO properties. When GeSe2 content reaches 50%, a stable network of [GeSe4] and [Se2Sb–Se–SbSe2] units forms, minimizing energy loss and α while maintaining a high M2. Compared with conventional AO materials, this composition achieves an exceptional equilibrium between high M2 and reduced α, offering a distinct advantage in optimizing performance. This unique composition balance provides valuable insights for developing advanced chalcogenide glasses in AO applications.

Energy management in smart distribution networks: Synergizing network reconfiguration, energy storage, and electric vehicles with disjunctive convex hull relaxation

Efficient energy management is critical for modern distribution networks integrating renewable energy, storage systems, and electric vehicles. This paper introduces a novel approach combining network reconfiguration with disjunctive convex hull relaxation to optimize power flow, minimize energy losses, and enhance grid stability. Case studies on 33-node and 84-node networks showcase the model’s effectiveness, reducing energy losses to 0.939 MWh and 7.214 MWh, respectively, outperforming Big-M and McCormick methods. Additionally, the approach achieved a 78 % efficiency improvement, enhanced emissions control, and improved voltage regulation, demonstrating superior renewable energy integration. These results highlight the model's potential to provide a more efficient and sustainable energy management solution, addressing the challenges of modern power grids.

Structural, electronic, magnetic, optical and thermoelectric properties of ferromagnetic double perovskites K2ScCoX6 (X = F, Cl): A first-principles study

To identify a promising alternative to lead-based materials for solar cell application, we investigated the different physical properties of K2ScCoX6 (X = F, Cl) perovskites. Both materials have ferromagnetic ground state. The obtained optimize lattice constants are found to be 8.48 Å and 10.04 Å for K2ScCoF6 and K2ScCoCl6 respectively. Our finding indicate that these materials exhibit excellent structural, mechanical, the thermal stability, as evidenced by their Goldsmith’s tolerance factor, elastic parameters, and negative formation energies. The formation energy is found to be -2.4 and -2.1 eV/atom for K2ScCoF6 and K2ScCoCl6 respectively. The electronic properties reveals that both materials have semiconducting nature. Notably, we observed low direct bandgap of 0.93 eV for K2ScCoF6 and 1.22 eV for K2ScCoCl6, which contrast with the typically large bandgap values reported for most halide double perovskite. The calculated values of Poisson’s and Pugh’s ratios, along with positive Cauchy’s pressure, suggest a ductile nature for these compounds. Additionally, the optical properties show high absorption and optical conductivity, coupled with low reflectivity and minimal energy loss in lower energy ranges. These results suggest that the halogen-based double perovskite materials have significant potential as photovoltaic absorber materials in solar cell applications. Furthermore, their higher Seebeck coefficients, power factors and low thermal conductivity at room temperature underscore their potential for thermoelectric applications.

Optimizing IoT-driven smart grid stability prediction with dipper throated optimization algorithm for gradient boosting hyperparameters

With the surge in global population and economic expansion, there's been a marked increase in electricity demand. This necessitates the efficient distribution of electricity to both residential and industrial sectors to minimize energy loss. Smart Grids (SG) emerge as a promising solution to reduce power dissipation in distribution networks. The application of machine learning and artificial intelligence in SGs has significantly improved the precision of predicting consumer electricity needs. This paper presents a novel approach to improving the stability prediction of Internet of Things (IOT)-driven SGs using different advanced machine learning models. This study explores multiple advanced machine-learning techniques, including Gradient Boosting (GB), K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Neural Networks, and the Decision Tree classifier, focusing on the stability prediction of SGs. This study explores the efficiency of hyperparameter-optimized GB models in predicting SG dynamic stability that encompasses the ability of the system to return to a stable operating point following a disturbance. Focusing on various models, it identifies the Dipper Throated Optimization Algorithm DTO+GB model as the standout, exhibiting unparalleled accuracy and reliability across critical performance metrics such as accuracy (99.32 %), sensitivity (99.16 %), and specificity (99.54 %). Diagnostic and regression analyses further emphasize its better predictive power and the need for hyperparameter optimization to improve the model. This paper highlights the capabilities of advanced machine learning algorithms in conjunction with tactical hyperparameter optimization in enhancing SG stability prediction, introducing a new baseline for future technological and methodological developments in this application.

3, 4-Bis (3-nitrofurazan-4-yl) furoxan (DNTF) and 4-methoxy-1-methyl-3, 5-dinitro-1H-pyrazole (DMDNP) based molten carrier with high energy and low sensitivity: eutectic design and desensitization effect

Utilizing insensitive explosives to form a eutectic with 3, 4-bis (3-nitrofurazan-4-yl) furoxan (DNTF) proved to be an effective method for reducing its sensitivity and melting point. In this study, the interaction between DNTF and 4-methoxy-1-methyl-3, 5-dinitro-1H-pyrazole (DMDNP) was simulated using the interaction region indicator (IRI), revealing that the intermolecular forces in the mixture are stronger than those of the individual components. Co-molten mixtures of DNTF-DMDNP with varying compositions were prepared through electrostatic spraying technology, and a binary phase diagram was established using differential scanning calorimetry (DSC). The experimentally extrapolated molar ratio of the DNTF-DMDNP eutectic was determined to be 48.7/51.3, with a eutectic point at approximately 338.2K. Fourier transform infrared spectroscopy (FT-IR) and X-ray diffraction (XRD) tests confirmed that no chemical reactions or crystal transformations occurred during the preparation of the eutectic. The thermal decomposition temperatures at different heating rates and apparent activation energy of the eutectic fell within the range between those of DNTF and DMDNP. Addition of even just 10% DMDNP significantly reduced mechanical sensitivity in co-molten mixtures, resulting in a rapid decrease from 100% to 12% friction sensitivity. The detonation velocity of the DNTF-DMDNP eutectic measured at 8.47kms-1 only experienced a slight decrease by about 0.78kms-1 (8.4%) compared to pure DNTF, indicating efficient desensitization by incorporating DMDNP with minimal energy loss potentiality. Furthermore, adjusting composition allowed for control over detonation performance and sensitivity in melt-cast explosives composed of DNTF-DMDNP.

Optimizing hardware configuration for solar powered energy management in battery ultracapacitor hybrid electric vehicles

The design and construction of an adaptive energy management system incorporating a 12 V–2 Ah battery and a 1F ultracapacitor for solar powered hybrid electric vehicles are presented in this paper. The primary storage battery’s longevity and overall system efficiency are intended to be increased by the EMS’s ability to forecast driving circumstances and lessen the load on it. The method optimizes power distribution among numerous energy storage sources by using sophisticated hardware configurations. Using Arduino Uno software, the EMS continuously modifies power distribution in response to driving circumstances and vehicle energy needs. To conduct a thorough assessment of the system, a mechanical configuration was created to replicate the vehicle’s dynamics. This included situations in which the vehicle moved only by using its moment of inertia and not the accelerator. Testing under diverse operating conditions, such as braking, acceleration, and varying slopes is made possible by this configuration. According to experimental data, peak battery stress is significantly reduced by about 33.33%, resulting in longer battery life. With minimal energy losses of 4.3–4.9%, the system regularly achieves power efficiency ranging from 95.1 to 95.7%. Furthermore, the suggested hardware-based EMS lowers overall energy loss by roughly 10.36%, highlighting its dependability and effectiveness in contrast to traditional techniques. The longevity and efficiency of the system are enhanced by the balanced power distribution between the battery, ultracapacitor, and solar sources, which prevents any one source from being overloaded. Overall, the suggested energy management system is successful in improving energy distribution and extending the lifespan and performance of HEV components.

Stochastic Scheduling of Grid-Connected Smart Energy Hubs Participating in the Day-Ahead Energy, Reactive Power and Reserve Markets

An Energy Hub (EH) is able to manage several types of energy at the same time by aggregating resources, storage devices, and responsive loads. Therefore, it is expected that energy efficiency is high. Hence, the optimal operation for smart EHs in energy (gas, electrical, and thermal) networks is discussed in this study based on their contribution to reactive power, the energy market, and day-ahead reservations. This scheme is presented in a smart bi-level optimization. In the upper level, the equations of linearized optimal power flow are used to minimize energy losses in the presented energy networks. The lower level considers the maximization of profits of smart EHs in the mentioned markets; it is based on the EH operational model of resource, responsive load, and storage devices, as well as the formulation of the reserve and flexible constraints. This paper uses the “Karush–Kuhn–Tucker” method for single-level model extraction. An “unscented transformation technique” is then applied in order to model the uncertainties associated with energy price, renewable energy, load, and energy consumed in mobile storage. The participation of hubs in the mentioned markets to improve their economic status and the technical status of the networks, modeling of the flexibility of the hubs, and using the unscented transformation method to model uncertainties are the innovations of this article. Finally, the extracted numerical results indicate the proposed model’s potential to improve EHs’ economic and flexibility status and the energy network’s performance compared to their load flow studies. As a result, energy loss, voltage, and temperature drop as operation indices are improved by 14.5%, 48.2%, and 46.2% compared to the load flow studies, in the case of 100% EH flexibility and their optimal economic situation extraction.