Line Losses Research Articles

A Robust Distributed Algorithm for Solving the Economic Dispatch Problem with the Penetration of Renewables and Battery Systems

In the field of energy networks, for their effective functioning, it is necessary to distribute the required load between all online generating units in a proper way to cover the demand. The load schedule is obtained by solving the so-called Economic Dispatch Problem (EDP). The EDP can be solved in many ways, resulting in a power distribution plan between online generating units in the network so that the resulting price per unit of energy is minimal. This article focuses on designing a distributed gradient algorithm for solving EDP, supplemented by models of renewable sources, Battery Energy Storage System (BESS), variable fuel prices, and consideration of multiple uncertainties at once. Specifically, these are: time-variable transport delays, noisy gradient calculation, line losses, and drop-off packet representations. The algorithm can thus be denoted as robust, which can work even in unfavorable conditions commonly found in real applications. The capabilities of the presented algorithm will be demonstrated and evaluated on six examples.

Power supply reliability assessment for a multistate electrical power network with line loss rates

Power supply reliability assessment for a multistate electrical power network with line loss rates

Low-Voltage Distribution Network Loss-Reduction Method Based on Load-Timing Characteristics and Adjustment Capabilities

The primary contributors to elevated line losses in low-voltage distribution networks are three-phase load imbalances and variations in load peak–valley differentials. The conventional manual phase sequence adjustment fails to capitalize on the temporal characteristics of the load, and the proliferation of smart homes has opened up new scheduling possibilities for managing the load. Consequently, this paper introduces a loss-reduction method for low-voltage distribution networks that leverages load-timing characteristics and adjustment capabilities. This method combines dynamic and static methods to reduce energy consumption from different time scales. To commence, this paper introduced a hierarchical fuzzy C-means algorithm (H-FCM), taking into account the distance and similarity of load curves. Subsequently, a phase sequence adjustment method, grounded in load-timing characteristics, was developed. The typical user load curve, derived from the classification of user loads, serves as the foundation for constructing a long-term commutation model, therefore mitigating the impact of load fluctuations on artificial commutation. Following this, this paper addressed the interruptible and transferable characteristics of various smart homes. This paper proposed a multi-objective transferable load (TL) optimal timing task adjustment model and a peak-shaving control strategy specifically designed for maximum sustainable power reduction of temperature-controlled loads (TCL). These strategies aim to achieve real-time load adjustment, correct static commutation errors, and reduce peak-to-valley differences. Finally, a simulation verification model was established in MATLAB (R2022a). The results show that the proposed method mainly solves the problems of three-phase imbalance and large load peak–valley difference in low-voltage distribution networks and reduces the line loss of low-voltage distribution networks through manual commutation and load adjustment.

Design of optical fiber delay line with large delay range and low insertion loss

For the application of continuously adjustable optical fiber delay lines, a large delay range can increase the instrument’s measurement range. Increased insertion loss of components will reduce the signal-to-noise ratio of the collected signal, ultimately limiting the measurement accuracy of the instrument. In order to take into account both large delay range and low insertion loss in design, a spatial light transmission and fiber coupling model based on scalar diffraction theory was established and the insertion loss was equivalently calculated through the coupling efficiency of the coupling lens. Then, we analyze the impact of optical fiber delay line’s structural parameters and adjustment errors on coupling efficiency. By optimizing lens group parameters and limiting adjustment tolerances, we can reduce the insertion loss of optical fiber delay lines in a large delay range and conduct experimental verification. Considering various influencing factors, we use a lens group with a focal length of 12 mm, achieving a coupling efficiency of no less than 92.7% within the delay range of 0–1 m. This theoretical model provides a new quantitative analysis method for improving the performance of the optical fiber delay line.

Two-stage robust optimization of unified power quality conditioner (UPQC) siting and sizing in active distribution networks considering uncertainty of loads and renewable generators

This paper proposes a robust optimization siting and sizing strategy for the unified power quality conditioner (UPQC) in the active distribution network (ADN) integrated with renewable energy generators. The optimization objectives including investment cost, line loss, and voltage deviation are integrated into an overall cost for both the planning and operating stages. A novel UPQC equivalent power injection model is proposed based on the auxiliary branch method. A set of linear and second-order conic (SOC) constraints are employed to accurately describe the steady-state operation of UPQC. An improved branch current flow model is developed to incorporate radial distribution networks with UPQCs. The UPQC siting and sizing planning is formulated as a mixed integer second-order conic programming (MISOCP) problem. Accounting for the uncertainty in loads and distributed generators, a two-stage robust optimization model is established to address worst-case operational scenarios. A solving strategy is developed based on the strong duality theory and the column-and-constraint generation (C&CG) algorithm, and then commercial solvers can solve the problem accurately and efficiently. Case studies on an IEEE 33-node distribution network demonstrate this strategy's robustness in dealing with loads and renewable energy uncertainties, making it applicable across different UPQC topologies and operation modes. The proposed method has superior performance over the representative meta-heuristic approaches in terms of global optimality as well as an over 7.5 times faster computation speed. This work has significance in enhancing the quality and efficiency of modern power systems highly integrated with renewable energy.

Photovoltaic power generation prediction and optimization configuration model based on GPR and improved PSO algorithm

As the growing demand for energy as well as the strengthening of environmental awareness, photovoltaic power generation, as a clean and renewable energy source, has gradually attracted people's attention and attention. To facilitate the dispatching and planning of power system, this study uses historical data and meteorological data to build a photovoltaic power generation prediction and configuration optimization model on the ground of Gaussian process regression and improved particle swarm optimization algorithm. The simulation results show that the regression prediction curve of the Gaussian process regression prediction model is the closest to the real curve, and the prediction curve is stable and not easily disturbed by noise data. The Root-mean-square deviation and the average absolute proportional error of the model are small, and the disparity in the predicted value and the true value of the model is small; The integration of multi factor data has improved the accuracy of prediction data, and the regression prediction effect is good. The improved Particle swarm optimization algorithm could continuously enhance in the search for the optimal solution, and the Rate of convergence is fast. The Pareto solution can provide different solutions suitable for photovoltaic power generation optimization. Reasonable optimization configuration can effectively reduce active power line loss and voltage deviation, with the maximum reduction values reaching 132kW and 0.028, respectively. The research and design of predictive models and optimized configuration models can promote the formation of smart grids.

Navigating Power Paths: Assessing Line Losses in the IEEE 14-Bus System amidst Electric Vehicle and Renewable Energy Integration

Purpose: This study thoroughly investigates the impacts of Electric Vehicles (EVs) and Renewable Energy Sources (RES) on line losses within the IEEE 14-Bus System, with a particular emphasis on addressing challenges and optimizing power system planning. The primary purpose of this study is to assess and understand the intricate relationships between EVs, RES, and line losses within the IEEE 14-Bus System. The research aims to provide insights that contribute to the development of tailored strategies in power system planning, addressing challenges posed by EV adoption and RES integration. By exploring the impact on grid efficiency, sustainability, and reliability, the study aims to guide future power system planners in optimizing the integration of EVs and RES.
 Materials and Methods: The study utilizes load flow analysis, specifically the Newton-Raphson method, to model and simulate scenarios reflecting EV charging and discharging dynamics alongside intermittent RES integration within the IEEE 14-Bus System. A 24-hour dynamic load flow analysis is conducted to capture the diverse and dynamic impacts under varying load conditions. This comprehensive approach allows for a detailed assessment of line losses in the presence of EVs and RES.
 Findings: The study reveals nuanced impacts, indicating higher EV adoption and increased RES integration result in notable escalations in line losses. This highlights challenges associated with grid efficiency, emphasizing the need for tailored strategies in power system planning.
 Implications to Theory, Practice and Policy: The study advances theoretical understanding of dynamic interactions between EVs, RES, and power systems. In practice, it underscores the importance of adaptive control mechanisms and optimized strategies for accommodating EVs and RES while minimizing line losses. On a policy level, the findings suggest the need for regulatory frameworks incentivizing sustainable energy practices and technological research to mitigate challenges posed by EV adoption and RES integration.

Network Reconfiguration Framework for CO2 Emission Reduction and Line Loss Minimization in Distribution Networks Using Swarm Optimization Algorithms

This paper presents the development of a generic active distribution network (ADN) operation simulation framework that incorporates selected swarm optimization algorithms (SOAs) for the purpose of reducing CO2 emissions and line loss minimization through network reconfiguration (NR). The framework has been implemented in the ADN of Taipower. Network data, provided by the Distribution Mapping Management System and Distribution Dispatch Control Center (DDCC) of Taipower, were converted into an OpenDSS script to create ADN models. The SOA is integrated into the framework and utilized to determine the statuses of both four-way and two-way switches in the planning and operating stages, in accordance with the proposed multi-objective function and operational constraints. The weightings for these decisions can be customized by distribution operators to meet their specific requirements. In this paper, the weighting for line loss reduction is set to one for minimizing CO2 emissions. The numerical results demonstrate that the proposed ADN framework can recommend a feeder switching scheme to distribution operators, aiming to balance feeder loading and minimize the neutral line current. Finally, this approach leads to reduced line losses and minimizes CO2 emissions. In contrast to relying solely on historical operational experience, this generic ADN reconfiguration framework offers a systematic approach that can significantly contribute to reducing CO2 emissions and enhancing the operational efficiency of ADNs.

Optimal Reactive Power Flow of AC-DC Power System with Shunt Capacitors Using Backtracking Search Algorithm

In this paper, it is proposed that a two-terminal high voltage direct current (HVDC) be integrated into the power system. Line-commutated converter (LCC)-HVDC is used because of its ability to reduce line losses, which improves overall system efficiency. Shunt capacitors also aid in voltage maintenance by compensating for the reactive power demand. In essence, limiting voltage drops in electrical networks promotes a more efficient power transmission and distribution by lowering resistive losses. In power system investigations, it was discovered that the HVDC link and SCB exist separately. So, for the first time, the backtracking search algorithm (BSA) is used to solve the optimal reactive power flow (ORPF) of a power system with a HVDC link and shunt capacitor banks (SCB). Although BSA simulations on a modified IEEE 30 bus yielded successful results, ABC was also utilized for comparing the outcomes of different methods. Overall, three separate cases of the modified IEEE 30 bus system were examined. When the acquired results are compared to other methods, the suggested algorithm is found to be better at concerning effectiveness as well as performance.

Multi-objective reactive power optimization for low voltage distribution networks based on improved marine predator algorithm

A large number of distributed photovoltaic generators are constructed in the 0.4 kV distribution network, which causes the distribution network’s power flow and voltage amplitude to change, and brings new challenges to the reactive voltage control. Firstly, a reactive power adjustment model is invented, and the objective of the optimization is to minimize the distribution network line losses and node voltage shifts. Secondly, the standard marine predator algorithm is improved by using Bernoulli mapping, nonlinear attenuation weight function, and elite replacement strategy, and the model is solved by the improved algorithm. The results of the example optimization of a 21-node low-voltage distribution network show that the presented reactive power adjustment method can control the voltage point within a reasonable range and reduce the line loss rate. The improved marine predator algorithm has better global optimality finding and faster convergence than traditional intelligent algorithms.

Evaluation of the ionization of noble gases under the effect of an electric field for the generation of useful energy

This work originated from the demand presented by an electric power transmission company and addresses a possible solution for the sector by exploring alternatives to extend the flight time of drones in the inspection of transmission lines. This original article demonstrates the use of the electromagnetic field of a transmission line to generate useful electrical power at the terminals of a bulb containing argon gas. It is an unprecedented application in power transmission. In this work, the tests based on a proof of concept are documented, where the results obtained were satisfactory and still allowed to connect an LED through the constructed arrangement. It is observed that the continuity of this research can provide scalability for applications whose main source of ion excitation is given from the energy dissipated as electric field loss in high-voltage lines.

Research on relay protection technology of high temperature superconducting cable system

High-temperature superconducting cables have many advantages such as low line loss, large transmission capacity, small space occupation, and environmental friendliness, which provide a highly efficient, compact, reliable, and green way of power transmission for power grids, and have great potential for application in large-capacity power transmission and urban power grid expansion and reconstruction. However, high-temperature superconducting cables have a complex structure, which is quite different from traditional cable lines in terms of operating conditions and fault mechanisms, and the requirements for the secondary system are also more stringent. Relying on the project of China Power Grid, “Research and Demonstration Application of Superconducting Transmission Technology in Urban Distribution Networks”, the thesis carries out an in-depth research on relay protection technology adapted to the access of high-temperature superconducting cables.

Multiple-Zone Synchronous Voltage Regulation and Loss Reduction Optimization of Distribution Networks Based on a Dual Rotary Phase-Shifting Transformer

For the problem in which accessing a high proportion of renewable energy results in exceeding the limit in distribution network voltage, the existing regulating method experiences difficulty in considering the two-way voltage regulation and loss reduction optimization function. This study proposes a series-type dual rotary phase-shifting transformer (DRPST) based on the principle of phase volume synthesis. This transformer exhibits bidirectional voltage regulation, high reliability, and low cost. First, the topology, operating principle, and equivalent circuit of DRPST are introduced, and its simplified circuit model is established. On the basis of this model, the causes of voltage exceeding the limits are analyzed and the active distribution network model that contains DRPST is constructed. A real-time rolling two-layer optimization strategy based on DRPST is proposed. The inner layer model is solved using the multi-objective particle swarm optimization algorithm with the objective of minimizing voltage deviation and line loss. The optimal compromise solution of the Pareto solution set of the inner layer model is determined using the fuzzy subordinate degree function method. The outer model is based on the optimal compromise solution of the inner model, and the DRPST output rotor angle is controlled without deviation through double closed-loop proportional–integral regulation. Finally, the correctness and effectiveness of the proposed topology and control method are verified via simulation and experimental analysis.

Calculation of excessive losses in low voltage line caused by computers

This work estimates excessive losses in low voltage line caused by nonlinear loads. Typical examples of nowadays nonlinear loads are computers, which numbers is especially increased in different types of companies as well as universities. In the case study the excessive losses in low voltage lines caused by the old and new computers are evaluated. The results presented show that the new technologies applied in the new generations of computers increased level of excessive losses in low voltage lines.

Machine learning-based optimal distributed generation and electric vehicle load management

The load profile of radial distribution networks (RDNs) is significantly impacted when plug-in electric vehicles (PEVs) are connected to them in large numbers. The disturbances in the load profile may lead to increased power losses in distribution lines and deterioration of the network voltage profile. The provision of distributed generation at strategic locations in the distribution network can help to compensate for the impact on the electrical network due to PEV loads. This paper proposes the use of machine learning (ML)-based models for determining the optimal location of distributed generators (DGs) in an RDN. The proposed method considered time-varying load in addition to PEV load. The suggested method determines optimal placement of DGs based on the power loss reduction index and voltage deviation index reduction index. Four distinct types of ML models were used in the proposed approach using synthesised data on the Institute of Electrical and Electronics Engineers' 33-bus RDN. The performance of the ML models was evaluated with respect to mean squared error and mean absolute percentage error and, for the ML models considered, the random forest ML model gave the best performance.

Impact of Compact Fluorescent Lamps on the Excessive Transmission Line Losses

The proposed paper deals with the calculation of the excessive transmission line losses caused by the compact fluorescent lamps. The number of the installed compact fluorescent lamps is rapidly increased, nowadays. Since such a lamps have large impact on the power factor as well as on the voltage and current total harmonic distortion their inclusion to the low voltage electrical grid should be fully investigated. In the paper the numerical model, with nonlinear characteristics of compact fluorescent lamps inclusion, is dealt. The numerically analysis is performed for four different compact fluorescent lamps available on the Slovenian market.

Optimal generation expansion planning model for solar PV generation on Run of River-based hydro-based power system using binary genetic algorithm

Abstract This paper presents a binary genetic algorithm approach developed to solve the optimal generation expansion planning problem for solar photo-voltaic (PV) based Run of River (ROR) hydro generation systems. The results show that the methodology effectively solves mixed-integer, constrained nonlinear generation expansion problems. The model is then used to optimize the generation expansion problem for the electricity grid in the eastern region of Nepal, considering the under construction and planned solar PV and ROR-based hydropower plants. The optimal problem is formulated to determine the optimal number, location and type of power plant to fulfill the demand for the electricity grid of the eastern zone grid of Nepal. Results show that the total generation from the optimal sites combining hydro and solar sites is found to be about 26% of that of total energy in the Nepalese grid. However, the total demand in the system under consideration for the year is about 1352 GWh. With eliminating line losses, a surplus generation of about 1377 GWh has been found. This surplus can be used as power pooling with neighboring countries. The system has a surplus during the wet season but needs to be improved during the dry season. Hence, appropriate policies can be formulated for power banking and pooling to balance the demand–supply in the system.

Retinal Pigment Epithelial Adenoma: Initial Treatment Outcomes following Episcleral Brachytherapy

Introduction: We aim to explore the safety and efficacy of episcleral brachytherapy as a primary management option for eyes with retinal pigment epithelial (RPE) adenoma. Methods: Retrospective chart review of the demographic, clinical, ancillary, and postoperative outcome data of patients with RPE adenoma in 2 tertiary referral centers. Tumor regression, final visual acuity, and complications were assessed. Results: Five patients (3 females and 2 males) were included. Four of the 5 eyes had peripheral and mid-peripheral lesions, while one tumor was juxtapapillary. Three eyes were treated with ruthenium-106 (100 Gray), and 2 received iodine-125 episcleral plaques (85 Gray). All eyes showed clinical and imaging-based evidence of regression. Four eyes had stable or improved visual acuity, while 1 eye exhibited one line loss of visual acuity due to radiation retinopathy. Local recurrence was not observed in any eye over a median follow-up of 24 (range 6–112) months. Conclusions: Episcleral brachytherapy is an effective management option for select cases of RPE adenoma that is capable of achieving tumor regression while maintaining favorable visual acuity. The initial safety profile of brachytherapy is good without significant vision-compromising complications.

Patent Analysis of the Digital Synchronous Motor Excitation Regulator

A significant part of the devices at enterprises has been in operation since the eighties of the last century. A thyristor exciter is a system designed to control and stabilize the operating processes of engines that are part of devices operating at high speed. The efficiency of operation of such machines as compressors, fans, pumps directly depend on how high-quality exciters are installed in their design. Thyristor exciters are also designed for the generation of low-power hydro and turbo generators, synchronous motors and compensators. In order to increase reliability and ensure uninterrupted operation of a synchronous electric drive with optimal electrical performance, it is necessary to use high speed thyristor exciters, in our case, the digital excitation regulator of a synchronous motor — ANICRON. In comparison with electric machine exciters, thyristor ones require three times less maintenance costs. The improvement of the technical and economic indicators of a synchronous electric drive is carried out by reducing losses in power lines, increasing the reliability of the power electric drive, and additional capabilities of a thyristor-exciter device. To date, the effectiveness of such pathogens has been evaluated by enterprises in the sugar, chemical, energy and other industrial fields. Thyristors are widely used not only in the Russian Federation, but also abroad.

Paper Certificate SMART GRID framework for Pakistan” Perception to practicality

As moving further into the digital age of the 21st century, Pakistan. and rest of the world is becoming increasingly dependent upon electric power. Despite the colossal potential of its energy resources, still Pakistan remains energy deficient. As a consequence, the crucial energy supplies today are not adequate to meet even the present demand. Similarly Line losses are a major issue in Pakistan. We are losing 35 to 40 billion per annum due to inefficiency in power distribution [4], While continuing blackouts or load shedding as it is commonly known, has always been a staple of daily life in Pakistan (figure 1). the dilemma has turned out to be acute since the preceding couple of months. The only way to tackle such colossal plight collectively is to implement smart grid infrastructure into our system. Also integrated use of smart grid would enhance the cooperation between the different sectors of the energy mix to provide an optimal solution in the electrical energy scenario of Pakistan. Smart grid is nothing but a concept/idea needed to run our present day Electrical power system in a more effective, more systematic and less error prone way. To achieve this way of wisdom, we must keep the end or the output required in our mind. Accommodating the present infrastructure with newer and more reliable modern day technologies are also a target of the Smart grid planning. Similarly Clean, green energy structure is an inherent requirement of smart grid development [6].It would provide a long term economic and social benefit to the existing structure of the society.