Decrease Power Loss Research Articles

Power loss transition of stable ZnO varistor ceramics: Role of oxygen adsorption on the stability of interface states at the grain boundary

Highly stable ZnO varistor ceramics with steadily decreasing power loss have been put into applications in electrical and electronic systems for overvoltage protections, even with the absence of general understandings on their aging behaviors. In this paper, we investigated their aging nature via conducting comparative dc aging experiments both in air and in nitrogen, during which variations of electrical properties and interface properties were measured and analyzed. Notably, continuously increasing power loss with severe electrical degradation was observed for the sample aged in nitrogen. The power loss transition was discovered to be closely related to the consumption of oxygen absorption at the grain boundary, which could, however, remain constant for the sample aged in air. The density of interface states, which is crucial for pinning the potential barrier, was proved to decrease in nitrogen, but keep stable in air. Therefore, it is concluded that the oxygen absorption at the grain boundary is significant for the stability of interface states, which further correlates to the long-term stability of modern stable ZnO varistor ceramics.

Optimizing structure and properties of Al/Cu laminated conductors via severe shear strain

The study is focused on determining the relations between electric properties and structural features within newly designed laminated Al/Cu conductors manufactured via rotary swaging at room temperature and subjected to two post-process heat treatments. Structure analyses were performed via scanning and transmission electron microscopy, mechanical properties were investigated via microhardness measurements, and electric properties during direct and alternating current transfers were both experimentally examined and numerically simulated. Fabrication of the laminate via rotary swaging introduced advantageous combinations of electric and mechanical properties, the design of the laminate had favourable effect on decreasing power losses during alternating current transfer, too. Specific electric resistivity was affected particularly by structural features, such as grain size, grain boundaries and twinning, and texture orientations and intensity. The lowest specific electric resistivity (22.7 Ωm×10−9) was measured for the swaged laminate heat treated at 350 °C featuring structure restoration. Annealing at 250 °C imparted partial structure restoration resulting in bimodal grain size distribution and substantial deterioration of the electric properties.

ANALISIS PENAMBAHAN JURUSAN GARDU DISTRIBUSI I.598 PADA PENYULANG APEL PT.PLN RAYON RIVAI PALEMBANG

The final report discusses replenishment plan of distribution substation I.598 major at apel feeder in PT. PLN Rival Rayon Palembang to decreases overload fault, drop voltage, and power losses conductor. According to the discussion on the final report, obtained replenishment plan of distribution substation major is able to decreases one of major’s loading which has the biggest load, namely B major from 65,61% is decreased to 21,95%, decreases drop voltage of B major’s conductors from 7,5% is decreased to 1% on phase R, 4,3% is decreased to 1,4% on phase S and 6% is decreased to 1,9% on phase T and also decreases power losses of B major’s conductors from 1,6 kW is decreased to 0,04 kW on phase R, 0,6 kW on decreased to 0,09 kW on phase S and 1,2 kW is decreased to 0,19 kW on phase T. These conditions are occurred by replenishment of conductor and dividing B major’s load to new majors, namely C and D major so that they influence loading, current load, and conductor length will be decreased. Therefore overload fault, drop voltage, and power losses conductor will be minimized.
 Key words : Replenishment of Substation Major, Overload, Drop Voltage, Power Losses

Applications of Novel Heuristic Algorithms in Design Optimization of Energy-Efficient Distribution Transformer

Transformers are one of the crucial and expensive assets of a power grid. Reducing power losses in power and distribution transformers is important because it increases the efficiency of the transformer, which in turn reduces costs for the utility company and consumers. Losses in the transformer generate heat, which can reduce the lifespan of the transformer and require additional cooling. Additionally, reducing losses can help to decrease greenhouse gas emissions associated with the generation of electricity. This study presents an optimization method for transformer design problem using variables that have a great impact on the performance of a transformer. Due to the non-convex nature of the transformer design problems, the empirical methods fail to find the optimal solution and the design process is very tedious and time-consuming. Considering No Free Lunch (NFL) theorem, the design problem is solved using four novel heuristic optimization algorithms, the Firefly Optimization Algorithm (FA), Arithmetic Optimization Algorithm (AOA), Grey Wolf Optimization Algorithm (GWO), and Artificial Gorilla Troops Optimizer Algorithm (GTO) and the results are compared to an already manufactured 1000 kVA eco-friendly distribution transformer using the empirical methods. The outcome of the optimization shows that the suggested method along with the algorithms mentioned leads to a notable decrease in power losses by up to 3.5%, and a reduction in transformer weight by up to 8.3%. This leads to an increase in efficiency, decreased costs for materials, longer lifespan and a reduction in emissions. The developed model is capable of optimally designing oil-immersed distribution transformers with different power ratings and voltage levels.

A Novel Radiality Maintenance Algorithm for the Metaheuristic Based Co-Optimization of Network Reconfiguration With Battery Storage

Network reconfiguration (NR) is a well-accepted technique to decrease power losses and enhance the voltage profile of the distribution network. The practical challenges in solving the NP-hard NR problem using metaheuristics are to randomly generate and, in each iteration, check and repair non-radial distribution network configurations without compromising on solution space in the least amount of time. Inefficient handling of non-radial configurations results in large computational time and high standard deviation. This paper mitigates the aforementioned challenges by proposing a novel radiality maintenance algorithm (RMA) that involves the novel concept of junction nodes and a selection set to produce only radial configurations. The proposed approach can potentially improve the standard deviation and computational efficiency of metaheuristics in solving the NR problem. The proposed RMA is generic, model-independent, and scalable, as it can be seamlessly integrated into any metaheuristic approach to solve the NR problem involving feeders of different sizes. The proposed RMA, combined with the accelerated particle swarm optimization, is implemented to solve: 1) the standard snapshot NR problem; and 2) the multiperiod co-optimization problem that simultaneously computes optimal network configuration and control setpoints of the photovoltaic system and battery energy storage system. Simulation results suggest a 27.3% standard deviation reduction in achieving the best results reported in the literature on NR-based power loss reduction within a comparable timeframe of 1.6 seconds. The effectiveness and reliability of the proposed algorithm are demonstrated on IEEE 33-bus test system.

Distribution network topology planning and optimization: A brief review

This article investigates distribution network topologies, with an emphasis on Mesh, Radial, and Ring designs, within the context of smart grids. With the primary goal of decreasing power losses using optimization techniques. The ZIP model is used to precisely capture load behaviour in load flow. This research adds to our understanding of topology selection, optimization approaches, and load behaviour modelling, improving in this way increases the efficiency and reliability of electrical distribution networks.

Optimized Network Reconfiguration with Integrated Generation Using Tangent Golden Flower Algorithm

The importance of integrating distributed generation (DG) units into the distribution network (DN) recently developed. To decrease power losses (PL), this article presents a meta-heuristic population-based tangent golden flower pollination algorithm (TGFPA) as an optimization technique for selecting the ideal site for DG. Furthermore, the proposed algorithm also finds the optimal routing configuration for power flow. TGFPA requires very few tuning parameters and is comprised of a golden section and a tangent flight algorithm (TFA). Hence, it is easy to update these parameters to obtain the best values, which provide highly reliable results compared to other existing techniques. In different case studies, the TGFPA’s performance was assessed on four test bus systems: IEEE 33-bus, IEEE 69-bus, IEEE 119-bus, and Indian-52 bus. According to simulation results, TGFPA computes the optimal reconfigured DN embedded along with DG, achieving the goal of minimal power loss.

A Novel Design Methodology and Numerical Simulation of BLDC Motor for Power Loss Reduction

In recent decades, there has been a growing interest in the design and development of power loss reduction in electric drive systems. To realize the full potential of the Brushless DC motor (BLDCM), the design methodology of an effective intelligent controller is vital. On the other hand, the Landsman converter is used in a bridgeless configuration to enhance the power factor and minimize the power loss of the BLDCM. In addition, BLDCM utilizes the different intelligent controllers that are used to decrease power loss. The performance of the Landsman converter and CSC converter is analyzed concerning various configurations/stages, and the numerical MATLAB 2016a simulation results are discussed to arrive at the suitable intelligent controller for the BLDC motor, and comparison results are presented. The proposed converter is designed and validated using hardware implementation by minimizing power loss. Effectiveness can be tested and valued for the proposed controller for the various intelligent controllers of BLDCM.

Local and Remote Cooperative Control of Hybrid Distribution Transformers Integrating Photovoltaics in Active Distribution Networks

This paper proposes a hybrid distribution transformer integrating photovoltaics (HDT-PV) with local and remote cooperative control in an active distribution network (ADN). HDT-PVs, regarded as promising devices with high reliability and easy engineering in ADNs, can not only realize the on-site maximum utilization of distributed solar energy but also solve the various power quality problems that follow. Moreover, the reactive power flow in the ADN can be optimized through remote cooperative control of multiple HDT-PVs. In this situation, the two objectives of voltage regulation and network power loss decrease are achieved in the ADN. If the power electronic device in the HDT-PV fails, the HDT-PV is able to work as a conventional distribution transformer by cutting off all power electronic devices and PV systems. Even when a small number of HDT-PVs malfunction, the system can still run stably. Finally, the simulation and experimental results demonstrate the effectiveness of the proposed scheme.

CFD-Predicted Rotordynamic Characteristics for High-Temperature Water Liquid Seal Considering Tooth Deformation

With the development of high-temperature centrifugal pump, the temperature of the medium in the pump must be higher than the normal water temperature. It is particularly important to study the rotordynamic characteristics of the seal at high temperature due to it being the core component of the rotor system. This paper takes the high temperature water liquid seal as a research object to study its rotordynamic characteristics based on the fluid-solid-thermal coupling, the deformation of seal teeth under thermal and dynamic loads was calculated. Based on the test rig, the leakage flow rate and drag power loss of water liquid seal at 20 °C, 50 °C, and 86 °C temperatures were tested and compared with the CFD (Computational Fluid Dynamics) calculation. Meanwhile, the DEFINE-CG-MOTION and DEFINE-PROFILE control macro were used to establish the rotor whirling equation, the frequency-independent rotordynamic coefficients (K, k, C, c) and frequency-dependent rotordynamic coefficients (Keff,Ceff) were evaluated by transient CFD method. This analysis was done at three different pressure drops (2.08, 4.12, and 8.25 bar) and three rotational speeds (2000, 4000, and 6000 r/min). The results show that with the increase of water temperature, both the leakage flow rate and drag power loss decrease, indicating the 86 °C water seal has a better sealing capacity. From the rotordynamic perspective, with the increase of water temperature, the direct stiffness coefficient decreases, and the effective stiffness coefficient Keff for 20 °C water seal possesses a better stiffness capability than the other two temperature seals. The effective damping coefficient Ceff for 20 °C water seal is larger than the other two temperature seals, which means it is more stable for the rotor system.

Swimming near substrates: Stingray self-propelled undulatory simulations

Fish movement investigations typically assume motion through unbound fluids. However, benthic organisms experience ground effects when moving near substrates. To identify the internal ground-effect mechanisms on self-propelled stingrays, simulations applying an in-house developed fluid-structure interaction algorithm were performed. A geometric model was developed from three-dimensional (3D) laser-scan data of a live freshwater stingray. The ratios of distances between the stingray and solid boundary to its disc width and unbounded fluid were investigated at two swimming frequencies: 2.385 and 3.384 Hz. Velocity fluctuation amplitude during one cycle near a substrate was approximately 30% less than that in unbounded fluid. The two peaks of the force coefficient in one cycle decreased and increased, respectively, with decreased power loss near the substrate; this is related to the pressure and wake distributions on the lower stingray surface at two typical instances. Pressure regions on the front and rear lower wing-crest surfaces decreased when approaching the substrate at the first typical instance, whereas that of the wing trough increased for the second typical instance. The vortex size on the lower wing surface decreased near the substrate for both instances.

A Simple SVM Technique on Three-Phase MPUC7 Inverter for Solar Photovoltaic System

In This paper, a simple single-dimension Space Vector Modulation (SVM) technique is introduced to implement on three-phase thirteen-level Modified Packed U-Cell (MPUC) inverter for photovoltaic system in which many DC sources are available. The three-phase thirteen-level converter consists of three single-phase seven-level MPUCs that each phase has six switches and two isolated DC sources. One major advantage of proposed method is to produce an output voltage with nearly constant amplitude in desired range in case of input DC voltage fluctuations, which is common in renewable sources like Photovoltaic Systems (PV). On the other hand, the conventional Pulse Width Modulation (PWM) strategies do not have such capability. Thus, the converter behavior is investigated for the proposed control method and Level Shift PWM (LS-PWM) and it is shown that the LS-PWM method does not function properly when the DC voltage varies. In order to produce an output voltage with seven equal levels, which results in reduction of the switching losses and Total Harmonic Distortion (THD), it is necessary to trigger switches in proper way. Consequently, two switching patterns are introduced and the significant decrease in power loss due to the second switching pattern is shown. Furthermore, it is investigated that in three-phase mode, the 3rd order line-voltage harmonics are eliminated well and the voltage and current THD are further improved by the proposed method. To validate the proposed SVM technique, MATLAB Simulink simulation results are presented and a comparative analysis is done between the proposed method and LS-PWM.

Single- and Multi-Objective Modified Aquila Optimizer for Optimal Multiple Renewable Energy Resources in Distribution Network

Nowadays, the electrical power system has become a more complex, interconnected network that is expanding every day. Hence, the power system faces many problems such as increasing power losses, voltage deviation, line overloads, etc. The optimization of real and reactive power due to the installation of energy resources at appropriate buses can minimize the losses and improve the voltage profile, especially for congested networks. As a result, the optimal distributed generation allocation (ODGA) problem is considered a more proper tool for the processes of planning and operation of power systems due to the power grid changes expeditiously based on the type and penetration level of renewable energy sources (RESs). This paper modifies the AO using a quasi-oppositional-based learning operator to address this problem and reduce the burden on the primary grid, making the grid more resilient. To demonstrate the effectiveness of the MAO, the authors first test the algorithm performance on twenty-three competitions on evolutionary computation benchmark functions, considering different dimensions. In addition, the modified Aquila optimizer (MAO) is applied to tackle the optimal distributed generation allocation (ODGA) problem. The proposed ODGA methodology presented in this paper has a multi-objective function that comprises decreasing power loss and total voltage deviation in a distribution system while keeping the system operating and security restrictions in mind. Many publications investigated the effect of expanding the number of DGs, whereas others found out the influence of DG types. Here, this paper examines the effects of different types and capacities of DG units at the same time. The proposed approach is tested on the IEEE 33-bus in different cases with several multiple DG types, including multi-objectives. The obtained simulation results are compared to the Aquila optimizer, particle swarm optimization algorithm, and trader-inspired algorithm. According to the comparison, the suggested approach provides a superior solution for the ODGA problem with faster convergence in the DNs.

Overmodulation Operation of Hybrid Modular Multilevel Converter With Reduced Energy Storage Requirement

The hybrid modular multilevel converter (MMC) has the advantages of dc fault blocking and overmodulation capability as the promising candidate in future multiport HVdc systems. Especially, the overmodulation ability could increase the modulation index higher than 1 without voltage distortions on the ac side. However, the hybrid MMC under the overmodulation operations could suffer from the voltage deviations between the half-bridge submodule (HBSM) and full-bridge submodule (FBSM) capacitors. In this article, the structure of the self-balancing branches (SBBs) is introduced into the hybrid MMC to eliminate the aforementioned voltage deviations. As a result, the energy storage requirement (ESR) of the hybrid MMC under the overmodulation operations could be greatly reduced compared with the conventional hybrid MMC without SBBs. Besides, the voltage balancing strategy is improved to avoid the impulse current in the conduction path of the SBB, by which the current stress of the power devices could be decreased significantly. The simulations and experiments are carried out to verify the effectiveness of the proposed hybrid MMC. It shows that the ESR of the hybrid MMC could be reduced by 30% with decreased power losses under the overmodulation index 1.5 compared with the conventional hybrid MMC.

Steadily Decreasing Power Loss of a Double Schottky Barrier Originating from the Dynamics of Mobile Ions with Stable Interface States

A general aging model of the double Schottky barrier was proposed to unveil the long-term aging behaviors of $\mathrm{Zn}\mathrm{O}$ varistor ceramics, especially for those ones with steadily decreasing power loss. For those samples, the barrier height and electrical properties were even enhanced rather than commonly deteriorated, which were beyond the classic ion migration model. In this paper, inspired by the unique reversible aging of them, interface states are proposed to remain stable in those samples. The major mobile ions, which have been in debate, are further identified to be ${\mathrm{Zn}}_{i}^{\ensuremath{\cdot}}$ ions. Based on these assumptions, a quantitative dynamic ion migration-diffusion model is proposed. The calculated power loss steadily decreases with aging time, which well supported our proposal. When the interface states are not combined with those mobile ions, the formation of a ``U-shape'' ion spatial distribution in depletion layers is found to be responsible for the unique aging phenomena, i.e., a reduction in the depletion layer and interfacial charge, a rise in the depletion layer width, and an increase in the barrier height. However, continuously increasing power loss would be generated if the mobile ions combined with the interface states. Therefore, a general mechanism on the aging of the double Schottky barrier is unveiled that it is a competition process between consumption of the interface states and the dynamics of mobile ions in depletion layers.

Chaotic Particle Swarm Optimization for Solving Reactive Power Optimization Problem

The losses in electrical power systems are a great problem. Multiple methods have been utilized to decrease power losses in transmission lines. The proper adjusting of reactive power resources is one way to minimize the losses in any power system. Reactive Power Optimization (RPO) problem is a nonlinear and complex optimization problem and contains equality and inequality constraints. The RPO is highly essential in the operation and control of power systems. Therefore, the study concentrates on the Optimal Load Flow calculation in solving RPO problems. The Simple Particle Swarm Optimization (PSO) often falls into the local optima solution. To prevent this limitation and speed up the convergence for the Simple PSO algorithm, this study employed an improved hybrid algorithm based on Chaotic theory with PSO, called Chaotic PSO (CPSO) algorithm. Undeniably, this merging of chaotic theory in PSO algorithm can be an efficient method to slip very easily from local optima compared to Simple PSO algorithm due to remarkable behavior and high ability of the chaos. In this study, the CPSO algorithm was utilized as an optimization tool for solving the RPO problem; the main objective in this study is to decrease the power loss and enhance the voltage profile in the power system. The presented algorithm was tested on IEEE Node-14 system. The simulation implications for this system reveal that the CPSO algorithm provides the best results. It had a high ability to minimize transmission line losses and improve the system's voltage profile compared to the Simple PSO and other approaches in the literature.

Analysis of Optimal Integration of EVs and DGs Into CIGRE’s MV Benchmark Model

In today’s transportation sector, the growing number of electric vehicles (EVs) is progressively replacing petroleum-fueled vehicles, which are also expected to minimize greenhouse gas emissions. The main problem with EVs is the requirement of charging energy, which is fed through distribution network, while simultaneously feeding already connected load. The EV’s integration with the distribution network will overload the network due to EV’s charging load, which will eventually trip the power system protection. In this context, it is necessary to minimize power losses, improve voltage profile with sustainable power supply network. Therefore, optimal placement of EVs is required in the distribution network. Conventionally, researchers have used DGs to minimize power losses and improve voltage profile. In this paper, authors analyzed the effect of EV’s integration with simultaneous placement of distributed generations (DGs). The integration of EVs with higher penetration of DGs is cumbersome due to higher power losses and voltage variances that are outside allowable boundaries. The optimal placement of EVs into the distribution system with higher penetration of DGs is proposed in this paper using a battle royale optimization (BRO) algorithm. Since it is a new problem on CIGRE network which is not discussed before. Hence, the authors compared results with three most famous algorithms namely genetic algorithm (GA), particle swarm optimization (PSO), and accelerated PSO (APSO). The optimization problem is developed as a multi-objective function while decreasing active and reactive power losses, and minimising maximum voltage deviation index. The studied distribution network is the CIGRE 14-bus medium voltage (MV) distribution network. Three case studies are taken in which EVs are integrated in two scenarios with optimally sized and located DGs systems in the CIGRE distribution network using MATLAB. Case-1 includes simple network with DGs integration. Case-2 includes EVs only in the simple network, and case-3 finally includes EVs and DGs for optimal placement with minimum losses. The placement of the EVs results in a decrease in power losses and voltage deviation indices. The bus voltages of case-2, on the other hand, stay unchanged when the EVs are integrated. Case 3 with BRO showed the large reduction in power losses owing to the addition of EVs to the distribution network with DGs (from 19.98 kW, and 19.89 kVar to 2.54 kW, and 3.35 kVar).

Development of DSTATCOM Optimal Sizing and Location Technique Based on IA-GA for Power Loss Reduction and Voltage Profile Enhancement in an RDN

The efficiency of electrical distribution systems is being more affected by the increase in voltage drops and power losses. These issues of voltage drop and power loss can be significantly minimized by the incorporation of a Distribution Static Compensator (DSTATCOM) in the distribution network. However, inappropriate positioning and sizing of DSTATCOM can undermine its efficiency. Despite the contributions of many researchers to the optimal placement of DSTATCOM and other compensators in distribution networks, the problems of voltage drop, power losses, and power quality persist, necessitating the need for additional research in this area. In this paper, an innovative technique based on hybridized Immune and Genetic Algorithm (IA-GA) for optimal DSTATCOM placement and sizing for three distinct load levels is proposed. Simulation and analysis of the proposed algorithm were carried out using IEEE-33 bus radial distribution network (RDN) in MATLAB. The simulation results demonstrate a substantial decrease in power loss and a significant improvement in the voltage profile. Evaluation of the proposed method against existing techniques reveals that the proposed technique outperforms IA and PSO in terms of decreasing power loss and enhancement of voltage profiles. A cost-benefit analysis was performed, and it was discovered that the proposed technique yields improved annual cost savings.

Analisis Pengaruh Penambahan Penyulang Dan Pemisahan Beban Terhadap Susut Daya Menggunakan Metode Simple Branch Exchange (Studi Kasus PT PLN ULP Lima Puluh, Sumatera Utara)

AbstractDuring the distribution process there will be a loss of some of the energy that is channeled. This phenomenon is known as losses. This is caused by technical and non-technical factors. In the State Electricity Service (PLN) system, distribution losses or energy losses is calculated by measuring the difference between kWh produced and kWh sell. This kWh difference is the electrical energy lost during the starting process from the generation or secondary side of the Substation to customers’ APP. Cumulatively, the amount of kWh at all base sources is 73,769.524 kWh while the distribution loss that occurs in JTM is 5,835.008 or 7.91%. One way to overcome and minimize distribution losses in the 20 kV Procurement Service Unit (ULP) of Lima Puluh distribution system is to analyze the distribution network system, add new feeders and break the load on the electrical system. The simple branch exchange method is used to separate the network load, which is done by adding a switch by turning the on or off channel and searching for the configuration that produces the smallest power loss and calculating the power loss based on the network load. Based on the simulation results using the ETAP 12.6 software, the results of the energy loss of Procurement Service Unit (ULP) of Lima Puluh is 5,864,112 kWh then decreased after load separation of 4,341,348 kWh. The value of power loss before load separation is 1,955 kW and a decrease in power loss after load separation is 1,484.5 kW. The investment cost incurred for the construction of a new feeder is RP. 22,000,000,000,- with a payback of 9.9 years. Keywords: Feeder, Power Loss, Energy Loss, ETAP 12.6.

Probabilistic Load Flow–Based Optimal Placement and Sizing of Distributed Generators

Distributed generation (DG) is gaining importance as electrical energy demand increases. DG is used to decrease power losses, operating costs, and improve voltage stability. Most DG resources have less environmental impact. In a particular region, the sizing and location of DG resources significantly affect the planned DG integrated distribution network (DN). The voltage profiles of the DN will change or even become excessively increased. An enormous DG active power, inserted into an improper node of the distribution network, may bring a larger current greater than the conductor’s maximum value, resulting in an overcurrent distribution network. Therefore, DG sizing and DG location optimization is required for a systematic DG operation to fully exploit distributed energy and achieve mutual energy harmony across existing distribution networks, which creates an economically viable, secure, stable, and dependable power distribution system. DG needs to access the location and capacity for rational planning. The objective function of this paper is to minimize the sum of investment cost, operation cost, and line loss cost utilizing DG access. The probabilistic power flow calculation technique based on the two-point estimation method is chosen for this paper’s load flow computation. The location and size of the DG distribution network are determined using a genetic algorithm in a MATLAB environment. For the optimum solution, the actual power load is estimated using historical data. The proposed system is based on the China distribution system, and the currency is used in Yuan. After DG access, active and reactive power losses are reduced by 53% and 26%, respectively. The line operating cost and the total annual cost are decreased by 53.7% and 12%, respectively.