Line Capacity Research Articles

ZNF623 contributes to breast carcinoma progress by recruiting CtBP1 to regulate NF-κB pathway

BackgroundBreast cancer ranks among the most prevalent tumor types worldwide. Copy number amplification of chromosome 8q24 is frequently detected in breast cancer. ZNF623 is a relatively unexplored gene mapped to 8q24. Here, we explore the expression profile, prognostic significance, and biological action of ZNF623 in breast carcinogenesis. MethodsTo evaluate the mRNA expression pattern and prognostic relevance of ZNF623 across different cancer types, we conducted bioinformatic analyses. The expression of the gene was suppressed using ZNF623 shRNAs/siRNAs and augmented through transfection with plasmids containing ZNF623 cDNA. Cell viability assay, clonogenic assay, and transwell migration assay were utilized to assess the proliferation, viability, and invasion capacity of breast cancer cell lines. Luciferase reporter assay served as a pivotal tool to ascertain the transcriptional activity of ZNF623. IP-MS and co-IP were employed to validate that ZNF623 interacted with CtBP1. ChIP analysis and ChIP-qPCR were conducted to assess the genes targeted by ZNF623/CtBP1 complex. Flow cytometry was conducted to evaluate the phosphorylation status of p65. ResultsZNF623 expression was notably elevated in breast cancer (BC). Prognostic analysis indicated higher expression of ZNF623 indicated worse survival. Functional experiments discovered that the upregulation of ZNF623 significantly enhanced both the proliferative and migratory capacities of breast cancer cells. Luciferase reporter assay indicated that ZNF623 was a transcription repressor. Immunoprecipitation coupled mass spectrometry analysis revealed a physical association between ZNF623 and CtBP1 in the interaction group. The conjoint analysis of ChIP-seq and TCGA DEG analysis revealed that the ZNF623/CtBP1 complex repressed a series of genes, such as negative regulation of the NF-kappaB signaling pathway. Flow cytometry analysis discovered that knockdown of ZNF623 decreased the phosphorylation level of p65, indicating that ZNF623 could regulate the activity of the NF-κB pathway. ConclusionZNF623 predicts poor prognosis of BC and enhances breast cancer growth and metastasis. By recruiting CtBP1, ZNF623 could suppress NF-κB inhibitors, including COMMD1, NFKBIL1, PYCARD, and BRMS1, expression from the transcription level.

Optimal Power Flow of Power System with Unified Power Flow Controller Using Moth Flame Optimization with Locational Marginal Price

Consideration of transmission line capacity and the optimal power flow (OPF) determines the locational marginal price (LMP), which in turn determines the performance and profitability of a producing unit. Reducing the total cost of the generators can lead to a drop in the market price of electricity. It is recommended to use numerical and repetition-based approaches for solving power flow equations due to their nonlinear nature. In order to achieve the ideal power flow at an affordable price, this paper employs a Moth Flame Optimization (MFO) to solve the equations. We then enhance the MFO’s structure to make it more effective at performing the simultaneous calculations of power passing through transmission lines. Flexible AC transmission systems (FACTS) tool that has been utilized to overcome this problem is the Unified Power Flow Controller (UPFC). Lastly, the proposed MFO algorithm would include the following parameters in its output: bus voltages, line losses, generated power, total generating expenditures, and generator profits. In this work, the proposed method is tested on the IEEE 57-bus network also shows that it improves upon the OPF problem.

Discussion on multi-condition load capacity evaluation algorithm of transmission line based on fusion algorithm

ABSTRACT High temperature, strong wind, ice cover and other problems may lead to transmission line breakage, tripping, tower toppling and so on. In order to reduce the probability of such problems, it is necessary to predict the load capacity of transmission line in multiple working conditions. In order to improve the accuracy of load capacity prediction of transmission lines under multiple working conditions and reduce the occurrence of bad transmission line problems, Particle Swarm Optimisation-Back Propagation neural network algorithm is used to simulate the prediction of transmission lines under different working conditions with different accuracy. The results show that the error of the optimised fusion algorithm is smaller than that of the pre-optimised algorithm. Combined with the prediction error results of the traditional neural network, it is found that the fusion algorithm can improve the prediction effect of transmission lines, has strong robustness, and can be popularised in practice.

Safety assessment of masonry undamaged and damaged arches subjected to gravitational loads and horizontal forces. A numeric procedure to identify the optimal thrust line

In 2019 the authors formulated a numerical procedure for assessing the safety of masonry arches based on their geometry and the shape of the thrust line. The thrust line is calculated to be nearest to the geometric axis of the arch, because it is that corresponding to the optimal inner stress state. The original procedure, which focused on the safety analysis of undamaged fixed arches subject to gravitational loads, is reformulated here to also consider arches on pinned supports as well as damaged arches, i.e. one- and two-hinged arches. The procedure is further extended to also assess safety against horizontal actions, such as those resulting from an earthquake. Finally, safety is evaluated by identifying the domain of admissible thrust lines within the thickness of the arch and by computing the degree of safety in terms of the capacity of the thrust line to be moved vertically within the domain. The reformulation and extension of the procedure exploits the technique of partitioned matrices to enable automation and easy implementation in structural calculation software.

Revolutionizing energy infrastructure: Automated route planning for underground transmission lines in Phnom Penh

The capacity of conventional overhead transmission lines (OTL) has been exceeded by the energy consumption of Cambodia's flourishing cities. Underground transmission lines (UTL) provide a unique solution due to their technical and environmental advantages. However, engineers must contend with high UTL costs and the need for effective conduit cable installation. This study presents a solution that automates the shortest route method for determining the optimal path for routing UTL power supply cables between any two substations. Multiple algorithms are evaluated to identify the most effective solution to this design's inherent shortest-path problem. Using Geographic Information System (GIS) data, potential UTL network routes in Phnom Penh, Cambodia can be investigated. The ultimate product is an automated route planning support tool that has the potential to revolutionize energy project planning by generating optimal routes for UTL. This will increase efficiency and lower costs, making UTL a more viable option for meeting the energy demands of modern infrastructure. This study contributes significantly to the field of energy infrastructure planning and has the potential to be replicated in cities around the world.

Planning Service Protocols for Extra-Long Trains with Transfers

This paper presents a modeling framework for optimizing operational protocols of extra-long trains (XLTs) in metro systems (i.e., trains longer than station platforms). With the rising travel demand in megacities, metro systems face challenges such as overcrowded stations, delays, and passenger anxieties. XLTs have been proposed as a promising solution to increase metro line capacity without additional infrastructure construction. The study explores the trade-offs between the additional capacity gained through complex protocols, the potential benefits of protocols with inline transfers, and the importance of effective passenger information systems from both passengers’ and operators’ perspectives. Mathematical programs are proposed to optimize protocols for a given demand distribution and to estimate the maximum line capacity of an XLT system. The benefits of implementing XLTs are evaluated in hypothetical and real-world cases with varying demand distributions and network sizes. The results demonstrate significant capacity increases ranging from 24% to 126% as compared with regular train operations, depending on system parameters and demand distribution. These findings demonstrate promise for using such systems to improve metro line capacity in the real world. History: This paper has been accepted for the Transportation Science Special Issue on ISTTT 25 Conference. Funding: The work was supported in part by the University of Illinois, Urbana Champaign [Grant Grainger STII Seed Fund] and the Zhejiang University-University of Illinois Urbana-Champaign Institute [Grant DREMES-202001]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/trsc.2024.0527 .

Proposal of a Transport Planning Model for the Removal of Quarry Stone Using a Simulation

This article describes a transport planning model which applies a simulation to support decision-making in quarry operations. The analysis of the transport system was used as input for creating the model and the subsequent research. There are five loading points in the quarry from which, according to the plan, the quarry stone is transported to the crusher, where it proceeds for further processing. The required daily capacity of the downstream technological line is 3800 t/day. Based on the analysis, it was found that it was impossible to fulfill this requirement from the two loading points which were the furthest from the unloading point. For this reason, two simulation models of the transport system were created. The first simulation model is a transport system (loading, removal and dumping of quarry stone) from one loading point. Simulation experiments were performed on this model for all loading points. The findings from the analysis confirmed the results of the simulation experiments. Subsequently, a model of the combined quarry stone removal from two loading points was proposed. The model was designed for two variants of dividing the work shift into two work sections. In the model, which had a tabular form, the combinations of loading points and values of the minimum number of unloaded cars for stone removal were suitable to ensure its necessary daily capacity. The last part of this research was expanding the original model with an additional loading point. Several experiments were performed on this model. The aim of these experiments was to verify the combinations of loading points presented in the proposed model and the combinations of unsatisfactory loading points. Based on the research results, the transport planning model and simulation models are suitable additional tools for the decision-making process in removing quarry stone.

Typhoon-induced failure analysis of electricity transmission tower-line system incorporating microtopography

Safety of electricity transmission tower-line systems is always at risk from various natural hazards, especially typhoons, which have the potential to cause significant damage and disruption. However, previous studies have predominantly focused on typhoons occurring in open-flat terrains, disregarding the impact of actual terrains. To address this research gap, this paper comprehensively examines the typhoon-induced responses of an electricity transmission tower-line system while considering the influence of microtopography. Specifically, a virtual wind tunnel is first established to simulate the typhoon within a specific microtopography. The wind characteristics of the typhoon considering the influence of microtopography are then studied in terms of the average wind speed, gust factor, and turbulence intensity, and compared to those at open-flat terrains. Finally, the influences of microtopography on the typhoon-induced responses and collapse of the electricity transmission tower-line system are investigated. The results demonstrate that the introduction of microtopography can obviously increase local wind speed and enhance fluctuation of wind, resulting in large responses and collapse risk of electricity transmission tower-line systems. This paper could provide a valuable reference for assessing the wind-resistant capacity of electricity transmission lines located in complex terrains, e.g., mountains and valleys.

Quality Improvement Project Selection Using Fuzzy AHP and TOPSIS to Support Lean Six Sigma at PT ABC

This research aims to improve project quality at PT ABC by integrating the Fuzzy Analytical Hierarchy Process (F-AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) within the Lean Six Sigma framework. This method assesses and selects quality improvement projects by considering uncertainty and complexity in decision-making. The Fuzzy AHP approach is used to flexibly assign criteria weights, while TOPSIS is used to rank projects based on performance scores relative to the ideal solution. This research aims to select the most suitable Lean Six Sigma project using the MCDM fuzzy AHP and TOPSIS approaches at PT ABC. There are three alternative quality improvement projects and three assessment criteria. The data processing results using Fuzzy AHP and TOPSIS showed that the most influential criterion was the impact criterion, with a value of 0.665. Overall, the order of influencing criteria is cost (0.260) and time (0.075). Based on a review of all criteria, the project to increase the drive plate production line (A) capacity was ranked first with a value of 0.772. Second place is the project to increase capacity and consolidate rear axle assemblies A and B with a value of 0.5529. Finally, the third is the process innovation and integrated manufacturing project to strengthen the business with a value of 0.4053.

Discovery and characterization of novel FGFR1 inhibitors in triple-negative breast cancer via hybrid virtual screening and molecular dynamics simulations

The overexpression of FGFR1 is thought to significantly contribute to the progression of triple-negative breast cancer (TNBC), impacting aspects such as tumorigenesis, growth, metastasis, and drug resistance. Consequently, the pursuit of effective inhibitors for FGFR1 is a key area of research interest. In response to this need, our study developed a hybrid virtual screening method. Utilizing KarmaDock, an innovative algorithm that blends deep learning with molecular docking, alongside Schrödinger’s Residue Scanning. This strategy led us to identify compound 6, which demonstrated promising FGFR1 inhibitory activity, evidenced by an IC50 value of approximately 0.24 nM in the HTRF bioassay. Further evaluation revealed that this compound also inhibits the FGFR1 V561M variant with an IC50 value around 1.24 nM. Our subsequent investigations demonstrate that Compound 6 robustly suppresses the migration and invasion capacities of TNBC cell lines, through the downregulation of p-FGFR1 and modulation of EMT markers, highlighting its promise as a potent anti-metastatic therapeutic agent. Additionally, our use of molecular dynamics simulations provided a deeper understanding of the compound’s specific binding interactions with FGFR1.

Integrating Floating Photovoltaics with Hydroelectricity

The transition process from fossil fuels to environmentally friendly renewable energy sources carries the risk of creating new environmental damages. Photovoltaic technology represents one of the alternatives with the least risk of harmful environmental impact. However, this technology has two important drawbacks: the significant land occupation for the installation of PV systems and the uncontrollability of production. By constructing floating photovoltaic plants on hydroelectric reservoirs, both of these problems can be reduced to an acceptable level. Some artificial reservoirs, originally built for hydroelectric power plants, have acquired a significant secondary function as recreational areas and fish breeding sites. Therefore, there is justified resistance from the local community to change the existing appearance and purpose of such reservoirs. This paper proposes a completely new concept of integrating the interests of the local community into such objects. In addition to preserving existing uses, the concept also offers new features. This can make the entire system environmentally friendly and sustainable. This paper details the technology behind the construction of floating photovoltaic power plants on artificial reservoirs and emphasizes their various advantages. These benefits include the non-utilization of cultivable land, the ease of assembly and construction, integration into existing power grids, and the potential to address electricity storage issues. For instance, Buško Lake, covering an area of 55.8 km2, may host 2.93 km2 of installed floating photovoltaic (FPV) facilities, enabling a total installed capacity of 240 MW. With an average of 5.5 h of daily sunshine, this totals 2007 annual hours, equivalent to a 55 MW thermal power plant. An analysis showed that, with losses of 18.2%, the average annual production stands at 302 GWh, translating to an annual production value of 18 million € at 60 €/MWh. The integration of this production into an existing hydroelectric power plant featuring an artificial reservoir might boost its output by 91%. The available transmission line capacity of 237 MW is shared between the hydroelectric power plant (HPP) and FPV; hence during the FPV maximum power generation time, the HPP halts its production. HPP Orlovac operates a small number of hours annually at full capacity (1489 h); therefore in combination with the FPV, this number can be increased to 2852 h. This integration maintains the lake’s functions in tourism and fishing while expanding its capabilities without environmental harm.

Dynamic Thermal Rating in Diverse Climatic Conditions: Uncertainty Analysis and Fuzzy Logic Approach

Abstract: In recent times, there has been a significant rise in the need for electricity, a trend expected to continue. This surge in demand has resulted in transmission lines operating at much higher capacities, which in turn exposes them to increased thermal and mechanical stress, ultimately impacting the reliability of the transmission network. In this paper presents a comprehensive analysis of the static thermal rating (STR) and dynamic thermal rating (DTR) of power lines across varied climatic conditions. The study encompasses a thorough investigation into the thermal behavior of power lines during both summer and winter seasons over a 24-hour period. Through rigorous computational simulations and empirical data collection, the STR and DTR profiles are determined to assess the real-time capacity of power lines under changing environmental conditions. Furthermore, the research introduces a novel approach utilizing fuzzy logic to model the dynamic thermal rating (FDTR) based on the IEEE 738 standard, in regions characterized by diverse climatic patterns. By integrating fuzzy logic with meteorological data, the FDTR model offers enhanced accuracy in predicting the thermal performance of power lines, considering factors such as ambient temperature, wind speed, and solar radiation. The proposed methodology aims to provide utilities and grid operators with a reliable tool for optimizing power transmission capacity, mitigating the risk of overheating, and ensuring grid reliability in regions with complex and fluctuating weather conditions. This study contributes to the advancement of smart grid technology and facilitates efficient energy management in diverse climate zones

Fuzzy Logic-Based Dynamic Thermal Rating Assessment for Adaptive Grid Operations

Abstract: In recent times, there has been a notable increase in electricity demand, which is expected to continue rising. This uptick in demand has led to transmission lines operating at higher capacities, exposing them to greater thermal and mechanical stress and affecting the reliability of the transmission network. This paper presents an in-depth analysis of the static thermal rating (STR) and dynamic thermal rating (DTR) of power lines across various climatic conditions. The study investigates the thermal behavior of power lines during both summer and winter seasons over a 24-hour period. Through computational simulations and empirical data collection, the study determines the STR and DTR profiles to evaluate the real-time capacity of power lines under changing environmental conditions. Additionally, the research introduces a novel approach using fuzzy logic to model the dynamic thermal rating (FDTR) based on the IEEE 738 standard, particularly in regions with diverse climatic patterns. By integrating fuzzy logic with meteorological data, the FDTR model improves accuracy in predicting the thermal performance of power lines, considering factors like ambient temperature, wind speed, and solar radiation. This methodology aims to offer utilities and grid operators a reliable tool for optimizing power transmission capacity, reducing the risk of overheating, and ensuring grid reliability in areas with complex and fluctuating weather conditions. The study contributes to the advancement of smart grid technology and facilitates efficient energy management in diverse climate zones.

PD-L1 knockdown suppresses vasculogenic mimicry of non-small cell lung cancer by modulating ZEB1-triggered EMT

BackgroundPD-L1 overexpression is commonly observed in various malignancies and is strongly correlated with poor prognoses for cancer patients. Moreover, PD-L1 has been shown to play a significant role in promoting angiogenesis and epithelial-mesenchymal transition (EMT) processes across different cancer types.MethodsThe relationship between PD-L1 and vasculogenic mimicry as well as epithelial-mesenchymal transition (EMT) was explored by bioinformatics approach and immunohistochemistry. The functions of PD-L1 in regulating the expression of ZEB1 and the EMT process were assessed by Western blotting and q-PCR assays. The impact of PD-L1 on the migratory and proliferative capabilities of A549 and H1299 cells was evaluated through wound healing, cell invasion, and CCK8 assays following siRNA-mediated PD-L1 knockdown. Tube formation assay was utilized to evaluate the presence of VM structures.ResultsIn this study, increased PD-L1 expression was observed in A549 and H1299 cells compared to normal lung epithelial cells. Immunohistochemical analysis revealed a higher prevalence of VM structures in the PD-L1-positive group compared to the PD-L1-negative group. Additionally, high PD-L1 expression was also found to be significantly associated with advanced TNM stage and increased metastasis. Following PD-L1 knockdown, NSCLC cells exhibited a notable reduction in their ability to form tube-like structures. Moreover, the levels of key EMT and VM-related markers, including N-cadherin, MMP9, VE-cadherin, and VEGFA, were significantly decreased, while E-cadherin expression was upregulated. In addition, the migration and proliferation capacities of both cell lines were significantly inhibited after PD-L1 or ZEB1 knockdown.ConclusionsKnockdown PD-L1 can inhibit ZEB1-mediated EMT, thereby hindering the formation of VM in NSCLC.

Extracellular matrix markerLAMC2 targets ZEB1 to promote TNBC malignancy via up-regulating CD44/STAT3 signaling pathway.

Triple negative breast cancer (TNBC) is a heterogeneous and aggressive disease characterized by a high risk of mortality and poor prognosis. It has been reported that Laminin γ2 (LAMC2) is highly expressed in a variety of tumors, and its high expression is correlated with cancer development and progression. However, the function and mechanism by which LAMC2 influences TNBC remain unclear. Kaplan-Meier survival analysis and Immunohistochemical (IHC) staining were used to examine the expression level of LAMC2 in TNBC. Subsequently, cell viability assay, wound healing and transwell assay were performed to detect the function of LAMC2 in cell proliferation and migration. A xenograft mouse model was used to assess tumorigenic function of LAMC2 in vivo. Luciferase reporter assay and western blot were performed to unravel the underlying mechanism. In this study, we found that higher expression of LAMC2 significantly correlated with poor survival in the TNBC cohort. Functional characterization showed that LAMC2 promoted cell proliferation and migration capacity of TNBC cell lines via up-regulating CD44. Moreover, LAMC2 exerted oncogenic roles in TNBC through modulating the expression of epithelial-mesenchymal transition (EMT) markers. Luciferasereporterassay verified that LAMC2 targeted ZEB1to promote its transcription.Interestingly, LAMC2 regulated cell migration in TNBC via STAT3 signaling pathway. LAMC2 targeted ZEB1 via activating CD44/STAT3 signaling pathway to promote TNBC proliferation and migration, suggesting that LAMC2 could be a potential therapeutic target in TNBC patients.

Marginal profit maximization estimation of supply chains by waste energy decrement: a case study of the power industry

Economic growth and excessive fossil energy consumption have direct effects on environmental destruction and greenhouse gas increments. The existing appropriate pattern for economic performance increase as well as pollution emissions abatement is a basic issue in industry activities. In this paper, a data envelopment analysis (DEA) model is introduced for estimating the directional marginal profit maximization of supply chain divisions based on wasted energy and power losses. The purpose of this study is to estimate the directional marginal productivity in the supply chain, which enables us to find the optimal direction of efficient divisions on the frontier. This makes the allocation of resources create a marginal profit increase and the pollution emissions be abated simultaneously. Indeed, the proposed model considers the synergistic effects of each input on MP estimation in predetermined directions. The model is able to estimate the marginal profit maximization of desirable output and undesirable output decrease for each input simultaneously. The results suggested that the gas field division of one of the supply chains had fundamental capacities for energy production increments and flare gas decrements. Furthermore, the gas field division of this supply chain also had a considerable structure for the marginal profit maximization of outputs based on flare gas decreases. Additionally, the distribution lines of 0.80% supply chains provided wasted energy reduction by adding one extra unit to the line's capacity in the determined direction. Especially, there were supply chains that had investment opportunities for an acceptable abatement of power losses. This not only enables divisions to respond to fluctuations in demand as they produce more energy in critical situations like climate change but also decreases harmful emissions as wasted energy in supply chain divisions.

Analyzing the impact of timetable elements on railway line capacity

Train timetabling poses inherent challenges, prompting the need to enhance existing schedules by extracting valuable insights from the current timetable structure. By such philosophy, this paper studies the impact of timetable elements on the consumed capacity. These elements primarily encompass train operation parameters, including running times and stop plans. Their impact is defined as the deviation of consumed capacity relative to their variations. We initially establish a link between consumed capacity and timetable elements. This relationship is articulated as the signed sum of timetable elements along a designated ”critical path”. Then, the limited impact of any timetable element is clarified, namely changing an element can impact the consumed capacity with its neighbor trains in a combinatorial way. With this knowledge, we analyze the impact of a single element, using stop plans for example. This result is then generalized into analyzing the impact of several dependent and independent stop plans. The findings on capacity calculation and impact analysis of a single element are tested through real-world numerical computations and then extended to analyzing various capacity factors, such as average speed and heterogeneity.

CDKN2A/B Homozygous Deletion Sensitizes IDH-Mutant Glioma to CDK4/6 Inhibition.

Treatment paradigms for isocitrate dehydrogenase (IDH)-mutant gliomas are rapidly evolving. Although typically indolent and responsive to initial treatment, these tumors invariably recur at a higher grade and require salvage treatment. Homozygous deletion of the tumor suppressor gene CDKN2A/B frequently emerges at recurrence in these tumors, driving poor patient outcomes. We investigated the effect of CDK-Rb pathway blockade on IDH-mutant glioma growth in vitro and in vivo using CDK4/6 inhibitors (CDKi). Cell viability, proliferation assays, and flow cytometry were used to examine the pharmacologic effect of two distinct CDKi, palbociclib and abemaciclib, in multiple patient-derived IDH-mutant glioma lines. Isogenic models were used to directly investigate the influence of CDKN2A/B status on CDKi sensitivity. Orthotopic xenograft tumor models were used to examine the efficacy and tolerability of CDKi in vivo. CDKi treatment leads to decreased cell viability and proliferative capacity in patient-derived IDH-mutant glioma lines, coupled with enrichment of cells in the G1 phase. CDKN2A inactivation sensitizes IDH-mutant glioma to CDKi in both endogenous and isogenic models with engineered CDKN2A deletion. CDK4/6 inhibitor administration improves survival in orthotopically implanted IDH-mutant glioma models. IDH-mutant gliomas with deletion of CDKN2A/B are sensitized to CDK4/6 inhibitors. These results support the investigation of the use of these agents in a clinical setting.

Construction of an Adaptive Metric Model for Maximum Access Capacity of Distributed Photovoltaic in Active Distribution Networks

Distributed photovoltaic (PV) access to the active distribution network can easily cause power fluctuation and affect the reasonable setting. The maximum access capacity is constructed as an adaptive metric model. Taking the total installed capacity as the objective function, the maximum access capacity adaptive metering model is constructed. For the constructed model, the constraints of light abandonment constraint, energy storage system constraint, voltage deviation constraint at the common connection point, line limit capacity constraint and distribution transformer capacity constraint are set. The model is solved by using multiple swarm genetic algorithms, output maximum access capacity. The abandonment rate of PV nodes is less than 3%, and the voltage overrun rate and line capacity overrun rate are less than 1%.

ВИЗНАЧЕННЯ ЗАРЯДНОЇ ЄМНОСТІ ПОВІТРЯНИХ ЛІНІЙ ЕЛЕКТРОПЕРЕДАЧІ З УРАХУВАННЯМ ПРОВИСАННЯ ПРОВОДУ

The paper presents the results of studying the effect of wire sagging on the charging capacity of an overhead power line. A refined mathematical model of the overhead line charging capacity is obtained. The results of the study of the error of neglect of wire sagging for typical structures of overhead power lines with voltage from 35 to 750 kV with the arrangement of wires in 2-3 tiers and horizontal arrangement are presented. The influence of changes in the wire sagging boom on the value of the power line charging capacity due to changes in the operating temperature of the wire and due to ice deposits is investigated. It is shown that for 750 kV power lines, such a change can reach 1-1.5%, which, in combination with the long length of the main power lines, can cause a change in the balance of reactive power in the line itself and in adjacent power systems. The possibility of monitoring the wire sagging boom in a run is investigated and the requirements for the accuracy of such measurements are determined. Bibl. 14, fig. 3, table.