Transmission Line Losses Research Articles

Enhancing efficiency and economy of hydrogen-based integrated energy system: A green dispatch approach based on exergy analysis

Hydrogen-based integrated energy system holds promise for leveraging the low carbon advantage of hydrogen, but inefficiency of electrolysis hydrogen production leads to significant exergy loss within its operation. Addressing this, this paper focuses on the energy-saving and economic operation of the hydrogen-based integrated energy system, proposes a novel green dispatch approach using loss cost as the objective function and establishes a refined loss cost accounting model based on exergy analysis theory. Firstly, derived from the analogy of exergy loss, the concept and accounting framework of system loss cost are proposed. Secondly, employing exergy analysis and consistent unit exergy cost principle, equipment operation loss cost is calculated through energy, exergy flows analysis and cost allocation. Thirdly, utilizing the total of equipment operation loss cost, wind curtailment penalty cost, and transmission line loss cost as the objective function, a green dispatch model is formulated to minimize overall loss cost while ensuring energy balance and other constraints. Finally, simulations analysis are conducted. The results show that compared to economic dispatch, minimized exergy loss dispatch and multi-objective dispatch methods, proposed approach increases exergy efficiency by 0.54 %, reduces cost by 6.13 % and increases the scale of hydrogen utilization by 3.45 %, respectively.

Social small group optimization algorithm for large-scale economic dispatch problem with valve-point effects and multi-fuel sources

Economic dispatch is an important issue in the management of power systems and is the current focus of specialists. In this paper, a new metaheuristic optimization algorithm is proposed, named Social Small Group Optimization (SSGO), inspired by the psychosocial processes that occur between members of small groups to solve real-life problems. The starting point of the SSGO algorithm is a philosophical conception similar to that of the social group optimization (SGO) algorithm. The novelty lies in the introduction of the small group concept and the modeling of individuals’ evolution based on the social influence between two or more members of the small group. This conceptual framework has been mathematically mapped through a set of heuristics that are used to update the solutions, and the best solutions are retained by employing a greedy selection strategy. SSGO has been applied to solve the economic dispatch problem by considering some practical aspects, such as valve-point loading effects, sources with multiple fuel options, prohibited operating zones, and transmission line losses. The efficiency of the SSGO algorithm was tested on several mathematical functions (unimodal, multimodal, expanded, and composition functions) and on power systems of varying sizes (ranging from 10-units to 1280-units). The SSGO algorithm was compared with SGO and other algorithms belonging to various categories (such as: evolution-based, swarm-based, human behavior-based, hybrid algorithms, etc.), and the results indicated that SSGO outperforms other algorithms applied to solve the economic dispatch problem in terms of quality and stability of the solutions, as well as computation time.

Optimal Placement and Capacity of BESS and PV in EV Integrated Distribution Systems: The Tenth Feeder of Phitsanulok Substation Case Study

Installing a battery energy storage system (BESS) and renewable energy sources can significantly improve distribution network performance in several aspects, especially in electric vehicle (EV)-integrated systems because of high load demands. With the high costs of the BESS and PV, optimal placement and capacity of them must be carefully considered. This work proposes a solution for determining the optimal placement and capacity of a BESS and photovoltaic (PV) in a distribution system by considering EV penetrations. The objective function is to reduce system costs, comprising installation, replacement, and operation and maintenance costs of the BESS and PV. The replacement cost is considered over 20 years, and the maintenance and operation costs incurred in the distribution system include transmission line loss, voltage regulation, and peak demand costs. To solve the problem, two metaheuristic algorithms consisting of particle swarm optimization (PSO) and the African vulture optimization algorithm (AVOA) are utilized. The tenth feeder of Phitsanulok substation 1 (PLA10), Thailand, which is a 91-bus distribution network, is tested to evaluate the performance of the proposed approach. The results obtained from the considered algorithms are compared based on distribution system performance enhancement, payback period, and statistical analysis. It is found from the simulation results that the installation of the BESS and PV could significantly minimize system cost, improve the voltage profile, reduce transmission line loss, and decrease peak demand. The voltage deviation could be reduced by 86%, line loss was reduced by 0.78 MW, and peak demand could be decreased by 5.706 MW compared to the case without BESS and PV installations.

Enhancement of transmission line parameters for the supply of energy in the Rivers state local government area of Obio Akpor

Efficient energy transmission is crucial for meeting the growing demand for electricity, particularly in urban and rural areas. In the Rivers State Local Government Area of Obio Akpor, Nigeria, ensuring reliable power supply is essential for supporting economic development and improving quality of life. However, challenges such as transmission line losses, voltage fluctuations, and inadequate infrastructure hinder the effective distribution of energy in the region. This article presents a comprehensive study on enhancing transmission line parameters to improve energy supply in Obio Akpor. Through field measurements, data analysis, and simulation studies, the performance of existing transmission lines is evaluated, and strategies for enhancing efficiency and reliability are proposed. The literature review explores previous research on transmission line optimization, emphasizing factors such as conductor material, line design, and insulation to minimize losses and maximize power transfer capability. Materials and methods encompass data collection, including impedance measurements, voltage profiles, and load characteristics, followed by computer simulations to assess proposed enhancements.

PI-based simulation modeling for performance testing of the power transmission line

The transmission line is one vital component of electrical power system. It determines some fundamental characteristics such as transmission efficiencies, voltage drops and line losses which are important matters to be considered in system planning, design and maintaining. The so-called PI-based modeling refers to using basic PI (proportional and integral) elements as well as other basic elements to implement one specific simulation. Grounded on the distributed-element model and addressing complex-element modeling, one PI-based simulation method is introduced in this study for teaching purposes and applied to modeling and simulation for performance testing of the power transmission line. The proposed method is demonstrated in the Simulink simulation environment and verified by performance testing of the power transmission line including complex-element-based equivalent distributed-element modeling for (short, medium and long) transmission lines, load flow analysis, short circuit test, open circuit test and the “Ferranti-effect” phenomenon, SIL (surge impedance loading) and series and shunt compensation simulation. Results indicate workability of the proposed method that it provides one convenient and vivid way for complex-element-based simulation modeling and solving numerical solutions as well. The proposed PI-based method for complex-element modeling and its Simulink-based simulation approach may be useful for related electrical engineering simulations and testing.

Effects of Non-Gaussian Surface Roughness on Conductor Loss in High-Frequency Transmission Lines

Effects of Non-Gaussian Surface Roughness on Conductor Loss in High-Frequency Transmission Lines

Experimental and theoretical study on the influence of bundle number on corona loss characteristics of ultra high voltage corona cage positive/negative DC conductors at high altitude

The corona loss generated by the conductor is one of the important factors in the design of ultra-high voltage (UHV) direct current transmission lines. This article is based on the high-altitude (2200 m) ultra-high voltage corona cage experimental platform built in Xining City, Qinghai Province. For the LGJ400-35 conductor used in the typical ± 800 kV DC transmission lines from Qinghai to Henan Province, positive and negative polarity corona experiments were conducted on LGJ400-35 conductors with 4, 6, 8, and 10 bundle under surface field strength conditions of 14–22 kV/cm. For the first time, corona loss data of bundle conductors in positive/negative polarity ultra-high voltage DC transmission lines were obtained, Fit the prediction formula for corona loss of transmission lines under different bundle numbers and surface electric field strengths of wires. And build a model in COMSOL Multiphysics software for simulation analysis, fitting the correction factor for the impact of wind speed on wire corona loss. The research results in the article can provide data reference and support for the construction of ultra-high voltage direct current transmission lines in high-altitude areas.

Modified Social Group Optimization to Solve the Problem of Economic Emission Dispatch with the Incorporation of Wind Power

Economic dispatch, emission dispatch, or their combination (EcD, EmD, EED) are essential issues in power systems optimization that focus on optimizing the efficient and sustainable use of energy resources to meet power demand. A new algorithm is proposed in this article to solve the dispatch problems with/without considering wind units. It is based on the Social Group Optimization (SGO) algorithm, but some features related to the selection and update of heuristics used to generate new solutions are changed. By applying the highly disruptive polynomial operator (HDP) and by generating sequences of random and chaotic numbers, the perturbation of the vectors composing the heuristics is achieved in our Modified Social Group Optimization (MSGO). Its effectiveness was investigated in 10-unit and 40-unit power systems, considering valve-point effects, transmission line losses, and inclusion of wind-based sources, implemented in four case studies. The results obtained for the 10-unit system indicate a very good MSGO performance, in terms of cost and emissions. The average cost reduction of MSGO compared to SGO is 368.1 $/h, 416.7 $/h, and 525.0 $/h for the 40-unit systems. The inclusion of wind units leads to 10% reduction in cost and 45% in emissions. Our modifications to MSGO lead to better convergence and higher-quality solutions than SGO or other competing algorithms.

Optimal dispatch of combined heat and power generating units with prohibited operating zones using improved heap‐based optimizer

AbstractIn the present market scenario, energy cost has been increased and also restrictions have been faced in fossil fuels energy sources. This leads to evolvement of combined heat and power generating units having higher efficiency as compared to the existing systems. The optimal dispatch of CGUs involves a number of intricate constraints, making it a practical optimization problem. So, an improved heap‐based optimizer algorithm has been implemented in this work for solving optimal dispatch problem by accomplishing a proper balance between initial and final stages of global search and convergence, respectively. This problem provides optimal scheduling of heat and power generating units and seeks to minimize the overall fuel cost supply of combined units considering their operational limits. Here, three test systems, that is, 7‐units, 24‐units and 48 units system have been taken into consideration to verify the performance of proposed IHBO algorithm. The impact of prohibited zones on power dispatch has been analysed for both the system in an electricity market. In addition, the valve‐point loading effect, mutual dependency of produced heat and power of combined units and also transmission power losses in transmission lines have been studied. Comparisons among different methods have been made based on their respective solutions obtained and from that it manifests the robustness and superior performance of the proposed technique. Verification studies showed that impact of prohibited zones on generating units, increases the production cost with respect to without prohibited zones. However the proposed technique yields least production cost among other techniques.

Distributed Generation in Electric Power Systems: An Overview and Important Issues

This paper discusses distributed generation (DG) in electric power systems. Various popular DG technologies that are currently used are also described, along with brief explanations of their working principles. It has been acknowledged that the integration of DG with renewable energy sources in power systems is increasing and will grow further. The main reason for this growth is the rising cost and environmental concerns of non-renewable energy sources (fossil fuels). Furthermore, DG offers some advantages, such as reducing power losses in transmission and distribution lines and improving power supply security. However, the increasing DG penetration brings technical implications for the power system to which the DG is connected. These critical issues are also highlighted in the present paper.

IoT-assisted energy cooperation in adjacent buildings with interrupted utility

Facing severe power outages primarily due to generation shortfalls and transmission line losses, Pakistan is seeing an overwhelming shift in renewable energy sources both in residential and industrial buildings. Motivated by the same, efficient load sensing and management techniques – already available in the literature – are being adopted in modern construction their efficiency in terms of cost-savings, however, is still questionable. In this work, an Internet-of-Things (IoT) assisted energy cooperation scheme for adjacent buildings equipped with renewable energy sources is proposed for enhanced efficiency in energy management, with additional generators to cater for the power outages. The IoT network consists of a combination of local and global aggregators; while each building is equipped with a local aggregator to determine the current state of electricity, heating and cooling consumption and generation, the global aggregator, on the other hand, acts as an intelligent hub for energy cooperation. The latter determines the amount of energy to be shared among the buildings to minimize the overall energy cost. For theoretical realization of the proposed scheme, a comprehensive energy cooperative mathematical model is developed, whose objective function is presented as a nonlinear optimization problem – linearized using McCormick’s Envelopes. Our simulation results reveal that the proposed framework promises increased efficiency in terms of energy cost-savings; we support our claims with a detailed quantitative analysis.

Superhydrophobic and Thermally Conductive Coating for Restraining Corona Loss and Audible Noise of High-Voltage Transmission Lines

In recent years, the number of high-voltage transmission lines has sharply increased with the rapid development of modern industry. However, a corona discharge phenomenon often occurs on the exposed high-voltage transmission lines, leading to energy loss and noise pollution. Herein, we have proposed a facile spraying method to prepare a superhydrophobic and thermally conductive coating to restrain the corona discharge phenomenon of high-voltage transmission lines, with vinyl silicone oil and hydrogen silicone oil as the main materials and modified boron nitride (BN) as a thermal conductive filler. The obtained composite coating exhibited superhydrophobicity, with a high water contact angle of 162°. In addition, the coating also showed a good self-cleaning capability, non-adhesion capability, mechanical stability, and chemical stability. Owing to the construction of the thermally conductive pathways with BN, the thermal conductivity of the coating reached 1.05 W/m·K, which was beneficial to quickly dissipating the heat generated by the current heating effect. Moreover, the corona losses of the positive and negative electrodes under simulated rainy conditions were decreased by 7.43% and 8.05%, respectively. The findings of our work have provided a new strategy to effectively restrain the corona discharge phenomenon of transmission lines, showing great application potential in the field of high-voltage power networks.

Water consumption of electric power system in China: from electricity generation to consumption.

Understanding the water requirement of electricity generation is critical to the development of both electricity and water systems, while the water consumption of the whole electric power system remains unrevealed. Here, we examine the water consumption driven by electricity generation, transmission, and consumption in China, finding that 14 billion m3 of freshwater is consumed by electricity generation in 2019 and that 2.5 billion m3 of freshwater was virtually transferred via electricity transmission. Nationally, the freshwater consumption per unit of electricity generation was 1.9 m3/MWh. Based on the state-of-the-art electricity transmission data, we find that 59% of the transported electric power was from water-scarce provinces and 0.7 billion m3 of freshwater was lost due to the electricity loss in transmission lines in China. It is essential to link water resources with the whole electric power system (production, transmission, and consumption) rather than only part of the power system as in previous research.

ПОКАЗНИКИ ЯКОСТІ ЕЛЕКТРОЕНЕРГІЇ ТА ЇХНЄ ПОЛІПШЕННЯ АКТИВНИМИ ФІЛЬТРАМИ

This article discusses power quality and the role of active filters in improving power quality. The characteristic of this article discusses power quality and the role of active filters in improving power quality. Power quality characteristics, including voltage non-sinusoidality, voltage unbalance, input current harmonic distortion and the ratio of active to full power, are considered. Various technical means of compensating reactive power and improving current and voltage spectra, including active filters, and current standards governing their requirements are considered. The benefits of active filters, such as reduced energy losses, suppression of higher harmonics, power factor correction and flicker re-duction, are described. A correct definition of apparent power is presented to justify an energy efficient control strategy for a shunt active filter to minimize power losses in the transmission line. To facilitate the distributed compensation of unbalance power, the corresponding current vector is represented by four orthogonal components, which produce separate contributions to the transmission line loss power. The use of active filters in power systems can improve power quality and ensure efficient use of electrical equipment. Ref. 14. Keywords: power quality, efficiency, technical means, active harmonic filters, nonlinear load.

Performance Analysis of Marine-Predator-Algorithm-Based Optimum PI Controller with Unified Power Flow Controller for Loss Reduction in Wind–Solar Integrated System

Transmission line losses are a crucial and essential issue in stable power system operation. Numerous methodologies and techniques prevail for minimizing losses. Subsequently, Flexible Alternating Current Transmission Systems (FACTSs) efficiently reduce transmission losses, and the Unified Power Flow Controller (UPFC) is a reactive power compensation controller. The parameter strength of the proportional–integral (PI) controller was calibrated with the Marine Predator Algorithm (MPA), a recent metaheuristic algorithm. An MPA-based optimum PI controller with a UPFC evaluates the optimal location of the UPFC and PI controller parameters to accomplish the desired research objective. The power rating of the UPFC was determined depending on the voltage collapse rating and power loss and an evaluated performance analysis of the MPA–PI-controlled UPFC on a modified IEEE-30 bus transmission network in MATLAB Simulink code. The Newton–Raphson method was used to perform the load flow analysis. Hence, the proposed MPA–PI controller was examined in contrast to preferred heuristic algorithms, the Artificial Bee Colony (ABC) and Moth Flame Optimization algorithms (MFO); the results showed that the MPA–PI controller exhibited better performance with an improved voltage profile and surpasses active power losses with the optimal placement of the UPFC device under different loading conditions. The active power loss, considering a UPFC with the proposed algorithm, reduced from 0.0622 p.u to 0.0301 p.u; consequently, the voltage profile was improved in the respective buses, and the loss percentage reduction during a 100% base load was 68.39%, which was comparatively better than the ABC and MFO algorithms.

Steady state Contingency Analysis of IEEE-39 Bus system Using PSS/E

Nowadays the stable, secure and reliable power system operation is the main objective of anyelectric power utility. The Power system is vulnerable to any contingency i.e. loss of Transmission line,Transformer, Generating unit etc. The power system control engineer should have detail analysis of at leastthe most probable and sever contingencies of the system and accordingly devise the remedial action plan.Thus, Power system contingency analysis and evaluation play vital role in ensuring power system stabilityand reliability. Keeping in view the importance of contingency analysis in power system operation andcontrol, this research focuses on steady state Contingency analysis of IEEE-39 bus system using newtonRaphson method. PSS/E is used for the analysis, different contingencies are evaluated and ranked basedupon the Power flow (Overloading), Voltage and phase angle deviation. Once the ranking is performed, thePV and QV analysis is performed for most severe contingencies. Remedial Actions is proposed for themost severe contingencies and this research could be applied to any real time network.

Deep learning techniques for transmission line fault classification – A comparative study

Despite advancements in technology, power system faults leading to electric power interruption remain a significant issue. Efficient restoration of the power system relies on the swift classification and clearance of faults. Among the various types of faults in transmission lines, open circuit and short circuit faults are commonly encountered. This study specifically focuses on the analysis of five types of short circuit faults: line-to-line, line-to-ground, double line-to-ground, triple line, and triple line-to-ground faults. Faults can cause both power failure and power loss in transmission lines. Once a fault occurs, it is crucial to restore electricity supply promptly to prevent further losses. Therefore, the development of a system capable of accurately and swiftly detecting and removing faults is essential. Traditionally, categorizing transmission line faults required sophisticated mathematical modeling, intricate signal processing techniques, and expert knowledge to interpret the output signals. In this paper, an alternative approach is proposed, utilizing deep learning techniques for transmission line fault classification. Specifically, the paper employs techniques such as artificial neural network (ANN), long short-term memory (LSTM), with and without window regression (WR). By implementing these deep learning techniques, automatic feature extraction and signal processing are achieved, streamlining the fault classification process. The experimental results obtained from this study demonstrate an accuracy of 42.98% for ANN, 99.98% for LSTM, and 99.99% for LSTM-WR. These outcomes underscore the effectiveness of the deep learning techniques employed in accurately classifying transmission line faults, with LSTM and LSTM-WR outperforming ANN in terms of accuracy.

Congestion Management Using an Optimized Deep Convolution Neural Network in Deregulated Environment

The technical issue of congestion, which is predominantly found in deregulated power systems, is caused by the failure of transmission networks to satisfy load power demands. This failure is primarily caused due to an increase in loads or loss of transmission lines or generators in modern restructured power networks. This work introduces a CM approach using Deep Convolution Neural Network (DCNN) for minimizing congestion and supporting Independent System Operators (ISOs). The purpose of the work is to generate enhanced prediction outputs for congestion management with reduced error values. These objectives were achieved through the actual power rescheduling of generators. The proposed work adopts DCNN which is optimized using an Improved Lion Algorithm (LA) and aids in providing significant outcomes for congestion management with reduced error. By implementing customized IEEE 57-bus, IEEE 30-bus, and IEEE 118-bus test systems, the suggested approach has been successfully verified for its performance on test systems of varied sizes. This analysis incorporates restrictions such as line loads, bus voltage influence, generator, line limits, etc. The most important results for the test system indicating convergence profile, congestion cost, and change in real-power and voltage magnitude are obtained by the simulation in MATLAB, and on the basis of the obtained simulation outcomes, it is evident that the proposed Improved Lion Algorithm optimized Deep Convolution Neural Network displays phenomenal computation performance in minimizing congestion losses at minimum congestion costs. When compared to several contemporary optimization techniques, the suggested technique performs better in terms of congestion cost and losses by generating improved prediction outputs with reduced errors.

Study of a solid-state transmitting device with a phase correction system, which increases the summing efficiency

Modern radar is a complex system, built on the basis of almost all the achievements of such areas as radio electronics, computer engineering and, of course, microwave devices. One of the most important units of radar, which determines the potential characteristics of the system as a whole, is the transmitting device. Nowadays the task of signal transmission with minimal losses in transmission lines and obtaining required power levels at the output of the transmitting device is relevant. However, existing methods may be insufficient to accomplish this task. In this regard, it may be necessary to improve or develop new systems and methods using the latest advances in microwave and antenna technology, radio and microelectronics, the totality of which will provide devices with these parameters. One such way to increase the stacking efficiency and output power of the transmitting device is to correct the phase of the amplification channels of the transmitting device in the range of operating frequencies. In this article the advantages of using solid-state transmitting devices in radar stations over electric-vacuum amplifying devices are considered. The most common ways of summation the power of microwave devices are described. An algorithm of the phase correction system is presented. The results of an experimental study of the system of gain channel phase correction for a transmitting device with eight gain channels, operating in a relatively wide frequency range, are presented. The proposed amplification channel phase correction system compensates the existing difference in the electrical lengths of the elements of the divider-adder path and amplifying modules in accordance with the algorithm, by means of controlled phase shifters (integrated into each amplifying module). The change in the phases of the microwave signal in (n-1) amplification channels is performed based on the calculated phase corrections obtained on the basis of successive estimates of the total output power of the reference amplifying module with each of the (n - 1) modules, where n is the total number of amplifying modules (channels amplification) in the transmitter. The output power is estimated by the ADC according to the level of the microwave power envelope at the lower, middle and upper frequencies of the operating range, taken from the adder output by a directional coupler. The performance of the phase correction algorithm is ensured by the control device of the amplifying module, the control and monitoring device of the transmitting device, the automatic monitoring and control system from the processing and indication system, as well as the appropriate interface at the operator's workplace. The proposed algorithm corrects the phases of the amplification channels according to the values obtained by the calculation method based on the data measured in the process of phase correction, which made it possible to reduce the maximum required number of phase shifter adjustments to 3 for each of n and each frequency, thereby ensuring a threefold increase in device performance. It was experimentally confirmed that the application of the proposed technical solution increases the efficiency of power summation of the considered transmitter from 70% to 94% - 99% (excluding active losses in the divider-adder and RMSD of the output powers of the amplifying modules) and an increase in the output power of the transmitter by 30% was achieved. The obtained results can be used to improve the algorithmic-software support of developed or modernized transmitting devices of radar stations.

Enhancing power system security using soft computing and machine learning

Purpose. To guarantee proper operation of the system, the suggested method infers the loss of a single transmission line in order to calculate a contingency rating. Methods. The proposed mathematical model with the machine learning with particle swarm optimization algorithm has been used to observe the stability analysis with and without the unified power flow controller and interline power flow controller, as well as the associated costs. This allows for rapid prediction of the most affected transmission line and the location for compensation. Results. Many contingency conditions, such as the failure of a single transmission line and change in the load, are built into the power system. The single transmission line outage and load fluctuation used to determine the contingency ranking are the primary emphasis of this work. Practical value. In order to set up a safe transmission power system, the suggested stability analysis has been quite helpful.