Power Loss Research Articles

Optimizing Network Reconfiguration to Reduce Power Loss and Improve the Voltage Profile in the Distribution System: A practical Case Study

The electricity provider incurs a high costs and investments to transfer the electrical power to customers in the distribution network. Hence, the reliability of the distribution network (DN) is particularly important in the lives of customers. A distribution system faces many issues due to its direct impact of the voltage profile (VP) and power losses (PL) problems. The aim of this study is to provide an effective scheme to address the of VP and PL problems. In this research, a Selective Particle Swarm Optimization (SPSO) algorithm was used to find combination of switches to enhance VP and reduce PL. The proposed method has been tested in the distribution network system, 125-buses Sigeri-Makassar Indonesia. There are three kinds of considered load scenarios, namely: nominal load; active power load increase; active and reactive power load increase. The research results indicated that the VP of the system can increased from 0.918 pu to be 0.922 pu and decreased PL from 0.6482 MW to be 0.6052 MW; the VP can increased from 0.895 pu to be 0.901 pu and reduced PL from 1.0469 MW to be 0.97532 MW, the VP can increased from 0.895 pu to be 0.900 pu and reduced PL from 1.1929 MW to be 1.0758 MW, for scenarios 1, 2 and 3, respectively. The simulation results showed that the proposed method provides optimal solution, which can enhance the VP and reduce PL. This is indicated that the proposed method is an effective strategy for enhancing voltage stability and solve PL problem.

Electric vehicle and photovoltaic advanced roles in enhancing the financial performance of a manufacturing and commercial setup

Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network.

Enhancing power conversion efficiency in five-level multilevel inverters using reduced switch topology

This paper presents extensive research on improving the power conversion efficiency of five-level multilevel inverters (MLIs) by utilizing a reduced switch topology. MLIs have received an abundance of focus because of their ability to generate high-quality output waveforms and have better harmonic outcomes than traditional two-level inverters. The high number of switches in MLIs, on the other hand, can result in increased power losses and lower overall efficiency. In this paper, a novel reduced switch topology for five-level MLIs, which is having five switches is proposed with the aim of minimizing power losses while preserving superior performance due to lesser number of switches. To achieve efficient power conversion, the proposed topology employs advanced pulse width modulation control strategies and optimized switching patterns. The simulation results show that the minimized switch topology improves the power conversion efficiency of the five-level MLI, resulting in lower losses and better overall system performance. The total harmonic distortion (THD) value of the output current has been reduced to 7.12% and the efficiency has been achieved to 96.92%. The findings of this investigation help to advance MLI technology, allowing for more efficient and reliable power conversion in a variety of applications such as renewable energy systems, electric vehicles, and industrial drives.

A bidirectional power converter connecting electric vehicle battery and DC microgrid

One way to increase electric vehicle (EV) battery utilization is to connect it to a dc microgrid. The EV battery can assume the role of an energy storage from the grid point of view. A bidirectional DC-DC converter will be needed to transfer power between them back and forth. This paper proposes the converter design considering its functional objective, including interleaved phase number determination. Efficiency performance evaluation is presented by power loss analysis with the parasitic-parameters consideration of the components. Finding optimum switching frequency based on power loss analysis is performed independently between input and output sides of the converter. Finally, experiments using a scaled-down prototype are shown to verify the analytical analysis of the converter. The experimental results properly validate the power loss analytic analysis carried out in this paper with a maximum error of 2.04% at 1131-watt, 60 V battery voltage, and 140 V grid voltage. Maximum efficiency 96.97% is obtained at 301-watt, 130 V battery voltage, and 151 V grid voltage. Overall, the converter has a simple structure, capable to be operated in various levels of input and output voltages with a minimum battery side current ripple.

A Quasi-Binomial Regression Model for Hurricane-Induced Power Outages during Early Warning

A Quasi-Binomial Regression Model for Hurricane-Induced Power Outages during Early Warning

Frequency Stabilizing and Reducing Power Outages of The Islanded Power ‎Network Using a ‎Load Shedding Method in The Presence of Renewable Energy ‎Resources

Frequency Stabilizing and Reducing Power Outages of The Islanded Power ‎Network Using a ‎Load Shedding Method in The Presence of Renewable Energy ‎Resources

High-reliability uninterruptible power supply manager for critical virtualization cluster

Information technology servers are complex, delicate, and expensive systems; power grid interruption is one of the possible causes that can lead to hardware damage or logical disk structure damage, with severe consequences. Moreover, a power grid drop causes a sudden interruption of the services managed by a server. Uninterruptible power supplies (UPS) provide backup power when the regular power grid source drops. UPSs can only maintain a server for a short time. Therefore, it is necessary to introduce a blackout manager who can correctly shut down the server activities. Moreover, the manager must be able to restore the servers' status when the electrical grid power returns to its normal state. This paper proposes a possible UPS power manager able to manage servers during a prolonged electrical blackout. The UPS power manager identifies the blackout and keeps the servers safe by saving their state and shutting them down properly. Following the power grid restoration, the UPS power manager restarts the servers and restores their state. The proposed approach has been evaluated on a virtualization cluster used for critical activities at the Politecnico di Torino.

Selection of Power Semiconductor Devices for a Standalone System based on Power Loss Analysis

Selection of Power Semiconductor Devices for a Standalone System based on Power Loss Analysis

Design of higher gain linearly polarized 2×2 microstrip patch array antenna for wireless communication

The fifth-generation technology is popular and best as far as data rates are concerned for wireless applications. To meet the increased demand of the modern world for faithful communication, this research work is carried out. In this approach, a single patch, 1×2 array, and 2×2 array are designed using a low-cost FR4 dielectric substrate ( =4.4) covering the 3.3–3.8 GHz frequency band. Due to the lack of gain from arrays in the present research, an attempt is made to achieve excellent gain from arrays with a minimum number of patches. First, the gain of a single inset-fed antenna is compared with another normal single patch of the same thickness but with an additional air dielectric medium. Next, the second single patch is extended to obtain a rectangular 1×2 array and a 2×2 array antenna. A second single patch measuring 50×32.5×0.8 mm is designed assuming an infinite ground plane. It has 3mm air gap between the patch strip and the ground. Air acts as a second dielectric layer that reduces power loss. This allows a maximum gain of 15.2 dB with a return loss of -22 dB. Also, antenna efficiency and bandwidth are 91% and 267.69 MHz, respectively.

Barium titanate–silicon elastomer based body coupled antenna for wearable microwave head imaging applications

This paper presents a flexible monopole antenna fed by a coplanar waveguide (CPW) feeding line with a barium titanate (BaTiO3) silicon-elastomer impedance matching layer for microwave head imaging applications. The operating frequency bandwidth of the proposed antenna is 614 MHz which is from 0.475 GHz to 1.089 GHz. In biomedical microwave sensing and imaging applications, the major challenge is the high power loss due to reflection between the BaTiO3 and the antenna due to impedance mismatch. Therefore, the proposed BaTiO3 silicon-elastomer composite is designed to have dielectric property of 20 which acts as an impedance matching layer for the monopole antenna. The proposed antenna has dimensions of 70×30×6 mm. The flexibility of the antenna is provided by the use of the silicon elastomer. It has been shown that the power radiated into an artificial head phantom improved by almost 160% as compared to antenna without impedance matching layer. Moreover, the SAR level is 0.0286 W/kg when 1 mW of power is transmitted, which is well below the limit set by the regulation. This makes the antenna suitable for wearable biomedical applications due to its wideband characteristic and improved power penetration into human head.

A modified chess knight reconfiguration approach for mitigating power losses in PV systems

Partial shading is a prevalent phenomenon that diminishes the power output of solar Photovoltaic (PV) systems. Reconfiguring the connections of a PV array has been proven to be effective in mitigating the negative impact of partial shading. This paper proposes a modified chess knight reconfiguration approach that improves power generation capability under different shadow footprints. The proposed method is validated experimentally and in MATLAB Simulink under different shading footprints such as, short, or narrow wide, short, or narrow long, corners, symmetrical and asymmetrical shadows. Five recently proposed dynamic and static reconfiguration techniques i.e., Row index, Sudoku, Particle Swarm Optimisation (PSO), Chess knight, and Total Cross Tied (TCT) have been used for analysis of all shadow footprints. The proposed technique is more effective in reducing output power losses, smoothing characteristic curves, and requires fewer switches. The effectiveness of the proposed technique is evaluated via performance analysis based on energy, cost savings and profit. The study found that the proposed technique mitigates power loss by 71% and increases profit by 13.5%. A generalized conceptual switching matrix scheme is also proposed, allowing the PV system to be reconfigured using any scheme reported in the literature.

Impact of string connection and contact defects on electrical current distribution in solar cells and modules: A model validated by magnetic field imaging

AbstractModeling of solar modules and their components is essential to quantify geometrical, optical, and electrical losses and to improve the designs and technologies in terms of performance. In most loss analysis models, the current share among the busbars of the solar cell is assumed to be equal since a symmetrical distribution of the metallization is given. The impact of string terminal connection on the current distribution among the ribbons and the resulting changes in ohmic losses has not been studied yet. In this study, a MATLAB model is developed to consider the impact of the string connector terminal position on the current distribution and the ohmic losses in the ribbons and in string connector. The model allows for the analysis of the impact of contact defects scenarios in ribbons and string connectors on the current distribution. Results show that the highest current flows at the closest busbar to the string connector terminal while the current decreases at the busbars farther away from the terminal due to higher ohmic resistance of the current path. The higher the ohmic resistance of the string connector, the more inhomogeneous the current share at busbars. Simulating a 9 busbar M6 half‐cell with 1 × 0.08 mm2 string connector, positioning the string connector terminal at the leftmost or rightmost ribbon results in 0.4 W less power compared to center connection configuration, where the string connector terminal is positioned at the center ribbon. Furthermore, simulation results show that inhomogeneity of current causes about 2.1% reduction in module power compared to the case of evenly distributed cell current, considering a 120‐haf‐cell module with the same string connector. Regarding contact defect analysis, exemplary simulations show the impact of the position of detached ribbons on the power or efficiency loss. Considering left or right connection configuration, detaching the leftmost or rightmost ribbon results in higher power loss compared to other ribbons. Detaching one cell ribbon completely from the string connector results in about 0.2%abs decrease in cell efficiency, while detaching the outer ribbon along all strings of a 120‐half‐cell module results in power loss of about 0.8%. The developed model is validated by performing magnetic field imaging (MFI) measurements, in which the magnetic flux density induced by the current carried by the ribbons is measured.

Analysis of heating defects in extension rods of extra-high voltage direct current overhead transmission lines

This paper studies the overheating defect of an extension rod in a ± 800 kV extra-high voltage direct current overhead transmission line, and proposes various factors that affect the overheating of the extension rod. Establish an equivalent model of an extra high voltage DC transmission line based on equipotential point and line parameter analysis, and calculate the model parameters. The proposed model can also be applied to ultra-high voltage DC overhead transmission lines such as ± 500 kV, and has strong universality. Simulation experiments show that if the equivalent resistance value of the split wire side is reduced by 0.01Ω, the power loss on the extension tie rod can be increased to 380.951 W; if the equivalent resistance value of the jumper side is increased by 0.01Ω, the power loss on the extension tie rod can be increased to 273.41 W. Combined with theoretical analysis and simulation verification, it is concluded that the main factor affecting the overheating of the extension rod is the change in the resistance value on the jumper side caused by the increase in contact resistance. A systematic troubleshooting plan for related defect problems is proposed, which has important reference and guidance significance for such line fault problems.

A Multi-Objective Approach for Optimal Sizing and Placement of Distributed Generators and Distribution Static Compensators in a Distribution Network Using the Black Widow Optimization Algorithm

This paper presents a new optimization technique for the locations and sizes of Distributed Generators (DGs) and distribution static compensators (DSTATCOMs) in a radial system of a distribution network based on a multi-objective approach. It uses black widow optimization to improve voltage profile and power loss reduction. The black widow optimization simulates the mating behaviour of black widow spiders. The optimum size and placement of DGs and DSTATCOMs are deemed to be decision variables that are defined by using black widow optimization. The proposed technique is implemented in selected IEEE bus systems to evaluate its performance. The simulation results indicate reduced power losses and voltage profile enhancement as sizes and locations of integrated DGs and DSTATCOMs are adjusted based on optimization. The number of DGs and DSTATCOMs required to achieve the objectives is reduced. Furthermore, the results of the black widow algorithm are compared to existing techniques in the literature.

Optimal power dispatch in hybrid power system for medium- and large-scale practical power systems using self-adaptive bonobo optimizer algorithm

Incorporating renewable energy sources (RESs) introduces a notable amount of uncertainty in the optimal planning and operation of electrical power grids. Under these circumstances, this paper proposes the application of a recently introduced metaheuristic optimization technique to solve the stochastic optimal power flow (OPF) problem involving wind and solar power sources. The self-adaptive bonobo optimizer (SaBO) is used to minimize three distinct objective functions: (i) Total generation cost (TGC) minimization, including both thermal and wind/solar generation costs, (ii) Power loss minimization, (iii) Combined generation cost and emissions effect minimization. The costs associated with the stochastic generation of wind and solar power included direct costs, reserves and penalty costs from the overestimation and underestimation of available wind and solar power, respectively. The performance of the proposed algorithm is evaluated on two power systems: the modified IEEE 30-bus and the Algerian DZA 114-bus test systems. To demonstrate the efficacy of the SaBO, the obtained results have been compared with those obtained from the Kepler optimization algorithm (KOA) and other recently published optimizers under the same case studies and constraints. The comparative results clearly show the superiority of the SaBO algorithm over all other well-known optimization algorithms provided in the literature for solving the OPF problem. This is evidenced by minimizing total generation costs of 781.2363 $/h for the modified IEEE 30-bus and 16,706.1630 $/h for the Algerian DZA-114-bus system. Furthermore, the integration of RES led to a notable 2.33% and 11.67% reduction in total generation cost for the IEEE 30-bus and Algerian DZA 114-bus systems, respectively, compared to their initial configurations without RESs. The promising findings highlight the powerful of the optimizer to solve non-linear and complex optimization problems in power systems.

Improved mountain gazelle optimizer based interactive distributed strategy to solving large scale OPF

This paper focuses on solving the multi-objective optimal power flow of large-scale power systems under critical loading margin stability with accuracy using a novel improved mountain gazelle optimizer (IMGO)-based flexible distributed strategy. Multi-shunt compensator-based flexible alternative current transmission systems (FACTS), such as SVC and STATCOM devices, are integrated at specified locations to exchange reactive power with the network. Several metaheuristic methods can solve the standard OPF related to small and medium test systems. However, by considering large-scale electric systems based on FACTS devices and renewable energy and by considering the operation under loading margin stability, the majority of these techniques fail to achieve a near-global solution because of the high dimension and nonlinearity of the problem to be solved. This study proposes the Multi-Objective OPF-Based Distributed Strategy (MO-OPFDS), a new planning strategy that optimizes individually and simultaneously various objective functions, in particular the total power loss (T∆P), and the total voltage deviation (T∆V). Standard MGO search is enhanced by automatically balancing exploration and exploitation throughout the search. The robustness of the proposed variant was validated on a large electric test system, the IEEE 118-Bus, and on the Algerian Network 114-Bus under normal conditions and at critical loading margin stability. The obtained results compared with several recent techniques clearly confirm the high performance of the proposed method in terms of solution accuracy and convergence behavior.

Deep learning model for enhanced power loss prediction in the frequency domain for magnetic materials

AbstractThis paper outlines the methodology for predicting power loss in magnetic materials. It starts by introducing the concept of core loss and the complexity of modelling it. Steinmetz's equation is presented to calculate power loss based on frequency and magnetic flux density, but its limitations are highlighted. As an alternative, a neural network‐based method is introduced. The proposed methodology adopts a long short‐term memory network, expressing the core loss as a function of magnetic flux density, frequency, temperature, and wave classification. Fast Fourier transform was implemented to reduce the data points of the sampled flux density waveform while preserving its characteristics. Analyzing in the frequency domain enabled streamlining the training of the model. The input features were arranged as required, and the network architecture was designed with appropriate layers and optimal activation functions. Through extensive training using the datasets, the model assimilated intricate relationships between input variables and known power loss. Evaluation and validation metrics were subsequently employed to gauge the performance of the trained network. This innovative methodology aims to significantly augment the precision of power loss predictions, providing valuable insights into the nuanced behaviour of magnetic materials.

Application of a Multi-Criterion Decision-Making Method for Solving the Multi-Objective Optimization of a Two-Stage Helical Gearbox

This paper provides a novel application of a multi-criterion decision-making (MCDM) method to the multi-objective optimization problem of designing a two-stage helical gearbox. This study’s goal is to identify the ideal primary design elements that increase gearbox efficiency while reducing the gearbox cross-section area. In this work, three primary design parameters were selected for investigation: the gear ratio of the first stage and the coefficients of wheel face width (CWFW) of the first and second stages. The multi-objective optimization problem was further split into two phases: phase 1 solved the single-objective optimization problem of minimizing the gap between the variable levels, and phase 2 solved the multi-objective optimization issue of identifying the ideal key design factors. Moreover, the multi-objective optimization problem was handled by the SAW method as an MCDM approach, and the weight criteria were computed using the entropy approach. This study’s significant characteristics are as follows: First, a multi-objective optimization problem was successfully solved using the MCDM approach (SAW technique) for the first time. Second, the power losses in idle motion were investigated in this work in order to determine the efficiency of a two-stage helical gearbox. From this study’s findings, the ideal values for three major design parameters can be determined for the design of a two-stage helical gearbox.

Analysis of Load Imbalance in Tarakan Distribution Transformer of PT PLN (Persero) Sukarami Customer Service Unit

Load imbalance in an electric power distribution system always occurs and the cause of this imbalance is unbalanced single-phase loads on low voltage network customers. As a result of this load imbalance, a current arises in the neutral of the transformer, which can cause power losses. The aim of the research is to analyse the load imbalance of the Distribution Transformer PC0044, PC0074, PC0088, PC0129, PC1319 on the Tarakan Feeder of PT PLN (Persero) Sukarami Customer Service Unit. The results of the research show that the highest peak load percentage occurs on the PC1319 Distribution Transformer, namely 93.0874%, and based on PLN ED Decree No. 0017.E/DIR/2014, transformer loading. The largest percentage of load imbalance occurs in the PC0044 Distribution Transformer, namely 38.0952%, and based on PLN ED Decree No. 0017.E/DIR/2014, the current imbalance between phases is included in the bad category because the load imbalance is ≥ 25%. The largest percentage of power losses due to neutral current in the transformer neutral conductor occurs in the PC0044 Distribution Transformer, namely 2.6737%, and based on PLN ED Decree No. 0017.E/DIR/2014, the neutral current TR is included in the good category because the power losses due to the neutral current in the transformer neutral conductor are <10%. The largest percentage of power losses due to neutral current flowing to the ground occurs in the PC0044 Distribution Transformer, namely 5.0784%.

A hybrid optimization approach for strategically placing electric vehicle charging stations in a radial distribution IEEE-33 bus system

Abstract The main objective of this study is to demonstrate the effectiveness of using Hybrid Particle Swarm Optimization (HPSO), a unique methodology, to optimize an IEEE-33 bus system for optimal placement of electric vehicles. This methodology has been specifically designed to effectively regulate voltage fluctuations while reducing power dissipation. The exploration capabilities of PSO and the exploitation capabilities of SA make HPSO a robust algorithm for a specific objective function. HPSO has shown superior performance compared to current traditional methods after careful study. Simulation results illustrate power loss reductions ranging from 1.01% to 8.21% compared to various metaheuristic methodologies. The inclusion of this approach demonstrates that combining the capabilities of PSO and SA facilitates the development of a highly efficient optimization framework by combining their stochastic search and fast convergence capabilities. This methodology not only sets innovative benchmarks for power system development, but also represents a significant paradigm shift in managing and improving durable and efficient electrical networks.