System Power Loss Research Articles

Review article: Research on coupled vibration of multi-engine multi-gearbox marine gearing

Abstract. The type and working principle of multi-engine multi-gearbox gearing are introduced. The global dynamic modeling method, based on the generalized finite element theory, and the layered dynamic modeling method, based on the idea of whole first and then partial are proposed, and the dynamic models of three operation modes in the four engines with two shafts are established. The effects of coupling, rotation speed, configuration and power loss on the dynamic response of the system are studied by using the dynamic model. The research results show that the coupling vibration of multi-engine multi-gearbox gearing is obvious at low speed, and the coupling vibration weakens with the increase in speed. Reducing the coupling stiffness can weaken the coupling vibration of the system. The symmetrical structure of the transmission system has the same dynamic response at the symmetrical position. Meshing friction has little effect on the dynamic response of the system. The more power flowing through the cross-connect gearbox, the greater the system power loss. This research provides theoretical support for the low-vibration design of multi-engine multi-gearbox marine gearing and has a positive significance for understanding the coupled vibration characteristics of complex gear systems.

Optimal Capacitor Location and Sizing for Reducing the Power Loss on the Power Distribution Systems due to the Dynamic Load of the Electric Buses Charging System using the Artificial Bee Colony Algorithm

The modern power distribution system is connected to many loads, affecting the power system reliability and causing more power loss. One of the new loads is the battery charging station for electric vehicles or electric buses. The charging load will have a charge that varies with the operating time of each vehicle. Therefore, this article focuses on optimal capacitor location and sizing for reducing the power loss on the power distribution systems due to the dynamic load of the electric bus system using the artificial bee colony algorithm. The dynamic charging load of 3 types of electric bus systems was applied: Plug-in charging, Pantograph charging, and Battery swapping charging. The simulation results show that the installation of 0.3167 MVar capacitors for Plug-in electric bus systems reduced the power loss by 0.5465 MWh. In comparison, the installation of 0.2893 MVar capacitors for the Pantograph electric bus systems reduces the power loss by 0.5459 MWh. The installation of 0.2922 MVar capacitors for the Battery swapping systems reduces the power loss of 0.5517 MWh. The installation of shunt capacitors can reduce the power distribution system's power loss and the benefit of capacitors installing 1,501.27, 1,443.76, and 1,474.02 USD/year, respectively.

WITHDRAWN: Optimal deployment of UPFC based on critical bus ranking using an effective PSO algorithm

This paper presents critical bus ranking based on load approach for optimal deployment of UPFC device in grid network. An effective PSO is programmed for optimal deployment of UPFC based on proposed critical bus ranking to enhance voltage stability of system. The deployment of UPFC at critical bus location can increase the stability of system by decreasing power loss of the grid system. Further the fuel cost can be minimized improving economic criteria. IEEE 14-bus network is programmed in MATLAB and results shows efficacy of proposed method .

Aggregator units allocation in low voltage distribution networks with penetration of photovoltaic systems

The aggregator units are essential in implementing smart grids since they are responsible for connecting smart meters installed on the consumers and ensuring exchanging information with the utility control centers. This paper presents a methodology to allocate these aggregators in low voltage distribution systems with solar photovoltaic generation. The proposed method is composed of two stages. In the first one, the aggregators are allocated considering the minimization of the distance to the remote terminal unit and their installation costs using a method based on Particle Swarm Optimization. In the second stage, the smart meters are connected to each allocated aggregator using a graph method. These connections are performed, taking into account a function, which depends on the distance between the meters and the load density within the aggregator coverage area. The proposed methodology was tested using a 400 V low voltage distribution system with 45 residential loads and 12 photovoltaic generators. The results showed that the proposal allocates aggregators at points where the consumer groups' load curves into the aggregator coverage area are better characterized. The values of the average voltage profile and the system's power losses in each aggregator coverage area presented an excellent match with values obtained with the test system without installing aggregators. From this characterization, it is possible to get useful information for operational planning and expansion planning of low voltage networks with photovoltaic generators by aggregation areas.

Optimal Siting and Sizing of Distributed Generators by Strawberry Plant Propagation Algorithm

Increasing the unplanned penetration of Distributed Generators (DGs) has spurred active and reactive power losses in the distribution system. This article suggests using a novel Strawberry Plant Propagation Algorithm (SPPA) for planning the placement of the DGs with the aim of reducing the network (active) power losses and improving the overall voltage profile. The proposed method (SPPA) has been tested on 33 and 69 node radial systems in MATLAB. A cost analysis was also performed and compared with other contemporary methods. The results for the considered variables show the significance of the proposed method in comparison to various other counterparts, including the Mine Blast Algorithm and Particle Swarm Optimization.

Design and Analysis of Single-Inductor Power Converter for Both Battery Balancing and Voltage Regulation

In this article, a highly efficient battery-balancing circuit with output voltage regulation for mobile applications is proposed and analyzed. The proposed circuit performs a cell-balancing operation for series-connected multiple-battery cells and voltage regulation operation simultaneously without additional power conversion stages. Therefore, it can be integrated into a battery pack with maximized power density and efficiency. These features are essential for recent low-power applications with multiple batteries, such as wireless/smart speakers, drones, and electronic point-of-sale, that require high power density. The operational principle, electrical modeling, and tradeoff relationship between the system power losses and balancing characteristics are derived, and the optimal design candidates of the proposed topology are discussed in terms of Pareto optimization. The effectiveness of the proposed system is verified with a prototype board using GaN switches, and 96.05% efficiency is achieved with a 1.8 V, 0.5 A load.

Appraisal of Aggregate Technical, Commercial and Collection Losses in Nigerian Electricity Distribution System

From a practical point of view, no power system is free of losses. Power system losses, especially in distribution systems are usually high and result in increasing the cost of operations to the electric utilities and the price tag of electricity to the consumers. Aggregate Technical, Commercial and Collection (ATC&C) losses is a reliable parameter that reveals the true energy and revenue loss conditions of distribution systems. In this paper, mathematical models were developed for the determination of billing efficiency, collection efficiency, and ATC&C losses using Life Camp Area Office’s network of Abuja Electricity Distribution Company Plc Nigeria, as a case study. The average billing efficiency, collection efficiency and ATC&C losses for the period under review were found to be 89.73%,84.80%, and 23.79% respectively. An understanding of appraisal of these losses is important to the power system Engineers, energy policy makers, and the power firms as it enables areas of high losses in the network to be identified, which will give room for credible investment plans and subsequent monitoring of the losses.
 Keywords: ATC&C losses, billing, energy, distribution system, revenue

Optimal placement of facts devices to reduce power system losses using evolutionary algorithm

<p>The rapid and enormous growths of the power electronics industries have made the flexible AC transmission system (FACTS) devices efficient and viable for utility application to increase power system operation controllability as well as flexibility. This research work presents the application of an evolutionary algorithm namely differential evolution (DE) approach to optimize the location and size of three main types of FACTS devices in order to minimize the power system losses as well as improving the network voltage profile. The utilized system has been reactively loaded beginning from the base to 150% and the system performance is analyzed with and without FACTS devices in order to confirm its importance within the power system. Thyristor controlled series capacitor (TCSC), unified power flow controller (UPFC) and static var compensator (SVC) are used in this research work to monitor the active and reactive power of the carried out system. The adopted algorithm has been examined on IEEE 30-bus test system. The obtained research findings are given with appropriate discussion and considered as quite encouraging that will be valuable in electrical grid restructuring.</p>

Two-stage fuzzy-logic-based for optimal energy management strategy for SOFC/PV/TEG hybrid polygeneration system with electric charging and hydrogen fueling stations

Integration between supplies for stationary power and vehicles is potentially useful for increasing the efficiency and the reliability of energy generation systems. Solid oxide fuel cell is one matured technology, which is suitable for a polygeneration system and provides an integration of supply for stationary power and vehicles. However, a combination of solid oxide fuel cell with photovoltaic thermal and thermoelectric generation increases the complexity of a polygeneration system. The system needs a management strategy for dispatching the energies produced. Therefore, in this work, a fuzzy energy management strategy was applied for this polygeneration system by considering two different configurations: an off-grid system with electric vehicle supply and an on-grid system with hydrogen vehicle supply. A two-stage fuzzy energy management strategy considering optimization and management of multi-parameters of the polygeneration components was considered. The evaluation of the optimum fuzzy was analyzed based on energy, economic, and environmental criteria. From the results obtained, the optimal strategy increased the reliability, energy, and system cost savings by 22.05%, 22.4%, and 32.58%, respectively. Moreover, the optimum management reduced the power loss of the polygeneration system by about 48.82%, which was achieved by the configuration with electric vehicles supply and off-grid connection.

Finding Radial Network Configuration of Distribution System Based on Modified Symbiotic Organisms Search

Network reconfiguration (NR) is one of the most effective methods to reduce line power loss in the distribution system, which causes higher losses than the other parts of the power system. This paper proposes a modified symbiotic organisms search (MSOS) algorithm to solve the NR problem. For the purpose of enhancing the effectiveness of MSOS, the mutualism and parasitism strategies of the original symbiotic organisms search (SOS) have been modified to create better new solutions. In the mutualism strategy, the so-far best solution is updated immediately as soon as new solutions are created. In the parasitism strategy, the update is only implemented for the first half of control variables, whereas another half still remains unchanged. The comparison results between MSOS and SOS on twenty-five benchmark functions and different scales of test distribution systems with 14, 33, 69, and 119 nodes show that the improvement level of MSOS over SOS is significant with higher success rates and better quality of gained solutions. Similarly, MSOS also reaches better results than other methods in the literature. Consequently, MSOS can be a favorable method for determining the most appropriate configurations for the distribution systems.

Harris hawks optimization algorithm based power loss minimization in micro grid incorporated with distributed generation

In this paper, Harris hawks optimization algorithm is used to solve the distributed generation placement problem in the micro grid. Distributed generation will effectively mitigate the loss of a real power system and improve the voltage profile. Thus, reducing actual power loss is viewed as a fitness function to optimally locate and rate the distributed generation in the micro grid. The method presented is applied in the IEEE test systems, such as the 33-bus and 69-bus micro grids. Simulation analyses are performed in MATLAB simulation software and simulation results are compared with existing PSO and ES-PSO algorithms. The results show the superiority and consistency of the Harris hawks optimization algorithm in terms of power loss minimization, voltage profile, and execution time.

Transmission congestion management considering voltage stability margin

This paper presents a solution for the transmission congestion management considering voltage stability issues using optimal generation rescheduling. While practicing congestion management using optimization techniques, the control variables remain under their upper or lower limits but it may lead to the lowered level of voltage security after optimization. To counterbalance this adverse effect, a modified objective function has been used. The reactive power generation rescheduling and reactive support from capacitors have been incorporated along with active power generation rescheduling to manage congestion as well as to improve the network voltage stability margin. The Random Inertia Weight Particle Swarm Optimization (RANDIW-PSO) algorithm has been employed in this paper to obtain optimized solutions. The proposed methodology is tested on the New-England test system for different realistic scenarios. The results confirm a noteworthy decline in congestion cost along with the improvement in network voltage stability margin. Moreover, system performance has been improved in terms of system power losses, increased reactive power reserve at generators and voltage profile.

Minimum reactive power loss optimization of power grid systems based on improved differential evolution algorithm

With the expansion of power system scale, the operation of the power grid system has been greatly challenged. Reactive power optimization can make the power system operate safely and economically. In this paper, an improved differential evolutionary algorithm is applied to reactive power optimization of power system. We take the minimum power system loss as the objective function, the power balance condition as the equality constraint, the control variables and state variables as the inequality constraint conditions to establish the system model. Finally, IEEE30 bus and IEEE33 bus power system are selected to verify the effectiveness of the proposed algorithm.

Voltage Profile Enhancement and Loss Minimization Using Optimal Placement and Sizing of Distributed Generation in Reconfigured Network

Power loss and voltage instability are major problems in distribution systems. However, these problems are typically mitigated by efficient network reconfiguration, including the integration of distributed generation (DG) units in the distribution network. In this regard, the optimal placement and sizing of DGs are crucial. Otherwise, the network performance will be degraded. This study is conducted to optimally locate and sizing of DGs into a radial distribution network before and after reconfiguration. A multi-objective particle swarm optimization algorithm is utilized to determine the optimal placement and sizing of the DGs before and after reconfiguration of the radial network. An optimal network configuration with DG coordination in an active distribution network overcomes power losses, uplifts voltage profiles, and improves the system stability, reliability, and efficiency. For considering the actual power system scenarios, a penalty factor is also considered, this penalty factor plays a crucial role in the minimization of total power loss and voltage profile enhancement. The simulation results showed a significant improvement in the percentage power loss reduction (32% and 68.05% before and after reconfiguration, respectively) with the inclusion of DG units in the test system. Similarly, the minimum bus voltage of the system is improved by 4.9% and 6.53% before and after reconfiguration, respectively. The comparative study is performed, and the results showed the effectiveness of the proposed method in reducing the voltage deviation and power loss of the distribution system. The proposed algorithm is evaluated on the IEEE-33 bus radial distribution system, using MATLAB software.

A combination of FA and SRPSO algorithm for Combined Heat and Power Economic Dispatch

This paper represents a hybrid Firefly and Self-Regulating Particle Swarm Optimization (FSRPSO) algorithm to solve optimal Combined Heat and Power Economic Dispatch (CHPED) problem. Valve point effect on fuel cost function of pure generation units, electrical power losses in transmission systems and feasible operating zones are taken into account in the CHPED problem. The CHPED refers to minimize total costs of fuel for electricity and heat generation supply to load demand. The proposed FSRPSO attempts to determine the start of the local search process properly by checking the previous global best. Thus, the FSRPSO is able to exploit strong points of both Firefly Algorithm (FA) and SRPSO mechanisms in order to balance between exploration and exploitation phases. Besides, for the sake of validation the proposed hybrid method, the FSRPSO is examined on 21 well-known benchmarks, and also a real engineering case i.e., two power systems for evaluating its performance compared with the SRPSO, FA, PSO, and other state-of-the-art algorithms. The obtained optimization results show that the proposed FSRPSO provides fast, mature and reliable optimum solutions and outperform other compared algorithms in diverse categories of benchmarks along with the studied CHPED problem.

A Novel Co-Phase Power-Supply System Based on Modular Multilevel Converter for High-Speed Railway AT Traction Power-Supply System

The existing problems of the traction power-supply system (i.e., the existence of the neutral section and the power quality problems) limit the development of railways, especially high-speed railways, which are developing rapidly worldwide. The existence of the neutral section leads to the speed loss and traction loss as well as mechanical failures, all of which threaten the fast and safe operation of the train and the system. Meanwhile, the power quality problems (e.g., the negative sequence current, the reactive power, and the harmonic) can bring a series of problems that cannot be ignored on the three-phase grid side. In response, many researchers have proposed co-phase power-supply schemes to solve these two problems simultaneously. Given that the auto-transformer (AT) power-supply mode has become the main power-supply mode for the high-speed railway traction power-supply system, it has a bright future following the rapid development of the high-speed railway. In addition, there is no co-phase power-supply scheme designed for AT power-supply mode in the existing schemes. Therefore, the main contribution of this paper is to propose a specifically designed power-supply mode more suitable for the AT, as well as to establish the control systems for the rectifier side and the inverter side. In addition, for the proposed scheme, the operation principle is analyzed, the mathematical model is built, and the control system is created, and its functionality is verified by simulation, and its advantages are compared and summarized finally. The result proves that it can meet functional requirements. At the same time, compared with the existing co-phase power-supply scheme, it saves an auto-transformer in terms of topology, reduces the current stress by 10.9% in terms of the current stress of the switching device, and reduces the power loss by 0.25% in terms of the entire system power loss, which will result in a larger amount of electricity being saved. All of this makes it a more suitable co-phase power-supply scheme for the AT power-supply mode.

Systematic photovoltaic system power losses calculation and modeling using computational intelligence techniques

The performance of a photovoltaic (PV) system is highly affected by different types of power losses which are incurred by electrical equipment or altering weather conditions. In this context, an accurate analysis of power losses for a PV system is of significant importance. Hence, the systematic calculation of the PV system power losses based on recorded data of the main electrical and meteorological parameters is investigated in this paper. The proposed approach for power losses calculation investigates both array capture losses (e.g. losses resulted from cell temperature, soiling, low irradiance, snow cover, mismatching, and module quality degradation) and system losses (e.g. losses resulted from cabling, inverter, etc.). Moreover, according to the best of our knowledge, the paper proposes for the first time in the literature the modeling of all types of losses based on computational intelligence techniques. The proposed models can predict the future daily values for each type of loss solely based on the main meteorological parameters. The proposed losses calculation approach is applied to 8 years of recorded data for a 1.44 kWp rooftop PV system located in Denver, CO. Several prediction models are built based on the calculated values of the losses. The models are not only validated on the PV system itself, but also on another PV system with different electrical characteristics in Las Vegas, NV. As the results show, the loss prediction models developed in this paper perform accurately for the main PV system and are also applicable to other PV systems.

Optimal allocation of multiple DGS in RDS using PSO and its impact on system reliability

This article presents the distributed generator (DG) integration in a radial distribution system (RDS). The DG penetration changes the single power source to multiple power sources and bidirectional load flow which enhances the system reliability and reduces system power losses. The particle swarm optimization and gravitational search algorithm are implemented for the optimal siting and sizing of one and three DG units in the RDS to examine its impact on system reliability and loss reduction. The types of DGs considered are Type I (injects real power) and Type IV (injects reactive and real power). The constant power is the chosen load model. The reliability indices taken for the analysis of system reliability are Average Energy Not Supplied, Total Energy Not Supplied and Average System Interruption Duration Index. The efficacy of the proposed method is validated on 33-bus in the presence of single and multiple DGs. The significant decrease in system power losses with the upgraded bus voltage profile, system reliability and remarkable annual loss saving is analyzed for Type IV DG over Type I DG. The results determined are compared to other meta-heuristic approaches as well as analytical techniques to demonstrate the superiority of the proposed methodology. The results are also statistically verified.

A computational intelligence-based technique for the installation of multi-type FACTS devices

As power demand rises, the power system becomes more stressed, potentially leading to an increase in power losses. When compared to lower power losses, higher power losses result in higher power system operating cost. Flexible AC Transmission System (FACTS) devices help to reduce power losses. This paper describes the use of a computational intelligence-based technique, in this case the Artificial Immune System (AIS), to solve the installation of Thyristor Controlled Static Compensator (TCSC) and Static VAR Compensator (SVC) in a power system while ensuring optimal sizing of both devices. The goal of determining the best locations and sizes for the multi-type FACTS devices is to minimize system power loss. Three case studies are presented to investigate the effectiveness of the proposed AIS optimization technique in solving the multi-type FACTS device installation problem under various power system conditions. The optimization results generated by the proposed AIS are beneficial in improving the power system, particularly in terms of system power loss minimization, which also contributes to power system operating cost minimization. As a result, the likelihood of this being sustainable and able to be implemented for an extended period is greater.

Modified whale optimisation-based optimal location of UPQC in distribution system for power quality improvement

A number of researchers has studied the unified power quality conditioner (UPQC) as an eventual solution to enhance the power quality in the electrical distribution system. However, due to the high cost, the location or position of UPQC in distribution system needs to be decided with immense care and must preferably be solved as the optimisation problem. This paper presents a power quality improvement model based on a new modified optimisation algorithm, namely worst solution linked whale optimisation algorithm update (WS-WU). The proposed algorithm finds the optimal location of the UPQC device concerning the power system losses, UPQC cost, and voltage stability index as well. The experimentation is carried out in both IEEE 33 and 69 bus systems. The performance of the proposed model is compared over other conventional methods in terms of performance and convergence analysis, and proves the superiority of the proposed method.