System Bus Research Articles

Application on ac station service system for gathering station based on roof photovoltaic system

Abstract With the increasingly severe global energy crisis and environmental pollution, it is imperative to develop and utilize clean and renewable energy. In order to achieve carbon peak and carbon neutrality as soon as possible, and reduce the proportion of fossil energy generation, decarbonization in the power industry is imperative. This article focuses on the design of rooftop photovoltaic systems at gathering stations. By installing solar photovoltaic panels on the roof of the gathering station building, a photovoltaic power generation system is constructed to convert solar energy radiated into electricity. The DC power generated by the solar photovoltaic power generation system is converted by an inverter and connected to the 380V bus of the station power system as a supplementary power supply for the station load, thereby increasing the proportion of green electricity consumption in the collection station and achieving the goal of carbon reduction

Harmonic State Estimation in Power Systems Using the Jaya Algorithm

The increasing use of nonlinear loads in power systems introduces voltage and current components at non-fundamental frequencies, leading to harmonic distortion, which negatively impacts electrical and electronic devices. A common mitigation strategy involves identifying harmonic sources and installing filters nearby. However, due to the high cost of power quality (PQ) meters, comprehensive harmonic level monitoring across the entire power system is impractical. To address this, various methodologies for Harmonic State Estimation (HSE) have been developed, which estimate distortion levels on unmonitored system buses using data from a minimal set of monitored ones. Many HSE techniques rely on optimization algorithms with numerous tuning parameters, complicating their application. This paper proposes a novel methodology for fundamental frequency power flow and harmonic state estimation using the Jaya algorithm, which is characterized by fewer tuning parameters for easier adjustment. It also introduces a strategy to determine the minimal number of buses that need monitoring to achieve system observability. The methodology is validated on the IEEE-14 and IEEE-30 bus systems, demonstrating its effectiveness. The results of the proposed methodology are compared with those obtained using Evolutionary Strategies (ESs), highlighting its enhanced accuracy and computational efficiency.

Optimization of the intake system for the Setra NS 913 bus

Abstract The paper presents the implementation on buses of a dynamic air transfer system (SDTA) brand Air by Corneliu. That system is the subject of a patent entitled Dynamic Air Transfer Device RO 200900028. At the initiative of the Alba Iulia public Transport society, with a fleet of about 100 buses, we started a study on the efficiency of air intake in the internal combustion engine by implementing an SDTA. Since the air filter location on this bus model, Setra NS 913, is behind the rear axle wheels, the filter is exposed to dust, water and other particles thrown by the drive wheels, which leads to premature clogging and blockage of the filtration area, in the context in which the bus runs mainly on asphalt-free roads. The gas-dynamic resistance (filter permissiveness) would increase considerably, resulting in a severe reduction in the degree of filling of the engine cylinders. In order to eliminate the disadvantages mentioned above, respectively to increase the life of the air filter with implications on the performance of the engine, we have designed a dynamic system consisting of the following components: the air collector, located on the top of the bus; the grid housing, located on the suction grid; tubing, connecting element between the air collector and the grid housing. In order to realize the 3D model of SDTA, the specialized software VISI - CAD / CAM was used.

Composite Accessibility Index: A Novel and Holistic Measure for Evaluating Transit Accessibility

The accessibility of public transport is a vital factor for the overall success of transit operations. It determines whether people choose to use and rely on public transport by assessing the ease of accessing opportunities. Accessibility, as a measure of the system’s performance, encompasses various travel segments and can be evaluated from different perspectives. Evaluating transit accessibility in data-constrained environments, particularly in developing countries, requires an optimal framework. The present study proposed a framework by modifying available accessibility measurement indices and trying to encompass all affecting variables in a single composite index. The integrated transit system comprising the bus rapid transit system and city bus in Surat city, India, is selected to demonstrate the proposed framework. The results of the ranked-based correlation coefficient test exhibit the comprehensive assessment capabilities of the proposed composite index in evaluating transit performance. Surat city’s transit network shows better coverage based on the gravity model theory, that is, moderate performance in local coverage offered capacity per population. However, it exhibits poor accessibility with respect to reaching destinations, resulting in below-average transit accessibility. Except for the city center and eastern part, 65% of the city area experiences inadequate accessibility of public transport. These findings align with the city’s low transit mode share of 2.5% and stagnant daily ridership of 0.25–0.28 million passengers in the last half decade. The composite index map serves as a planning tool for optimizing the utilization of available resources and guiding future policy implementations.

Real-time transient stability early warning system using Graph Attention Networks

In this paper, a classifier based early warning system is designed, trained and tested based on time-series of Phasor Measurement Unit (PMU) measurements at all buses in a power system. The classifier is based on a novel combination of Graph Attention Networks and Long Short-Term memories, and is trained to label power system data in the form of captured windows of PMU measurements. These labels are then used to provide early warning for transient instability. The classifier is trained and tested data from simulations of the Nordic44 test system, and includes extensive topological variations under two different load levels. It is found that accurate early warnings can be provided, but the quality of prediction is highly dependent on specific power system characteristics, such as how quickly the power system responds to transient disturbances.

Complex frequency divider

This work presents the Complex Frequency Divider Formula (CFDF), an explicit equation for the complex frequencies (CFs) of the voltage of every bus of a power system in terms of a linear combination of the CFs of the currents injected by the devices connected to the network. The coefficients of this linear combination depend on the topology of the system, voltages and currents. The CFDF carries valuable information on the impact of every device on the dynamic of the voltage and frequency of any particular bus of the system. The formulation is exact, as it does not require any simplification of the dynamic model of the system. The CFDF is implemented in two benchmark systems to show its potential in static and dynamic analysis in different scenarios. Finally, relevant notes on the applications of the proposed formula are outlined.

Challenges and facilitating factors in interorganizational knowledge acquisition: evidence from the Orange Line Metro Train System and Sustainable Bus Rapid Transit Corridor

Purpose This paper aims to identify challenges and facilitating factors in interorganizational knowledge acquisition. For this purpose, the interorganizational settings of the Orange Line Metro Train System and Sustainable bus rapid transit (BRT) Corridor in Pakistan are examined. Design/methodology/approach This study uses an exploratory multiple case study approach. The empirical data encompasses semi-structured interviews and archival documents. Within and cross-case analyses are used for analyzing the data. Findings The findings identify challenges such as time pressure, knowledge hiding, finding credible information sources, organizational red tape and facilitating factors such as clear objectives, individual interest and personal commitment, and revisiting the organizational culture and environment in which interorganizational knowledge acquisition takes place. Originality/value By examining knowledge acquisition in interorganizational projects, this study contributes to the literature on knowledge-based theory.

Pandemic insights: analysing public transport with logit models

The impact of the Covid-19 pandemic on public transportation usage in Bursa, Turkey, was examined in this work. The usage of major transit systems (buses, trams and light rail) before and during the pandemic were assessed. Changes in public transportation behaviour were captured through an online survey of 767 participants from key activity centres. Using two ordinal logit models, the factors influencing preferences were identified. It was found that age, gender and home-to-work distance were influential before the pandemic, while educational status and distance became crucial during the pandemic. The research further explored the tendency to walk, cycle or use an e-scooter if safe, separated non-motorised transportation routes had been provided, considering various scenarios of home–workplace distance. The results of this study will help decision makers make sustainable transportation plans by taking into account catastrophic periods such as the Covid-19 pandemic.

Improvement of Voltage profile by Integrating Renewable Generation Units at weak bus locations of the System

The Grid consists of higher rating sources and transmission system that supports local loads. The grid operates at voltages in the range of 66kV-132kV and transmits power in MW to smaller or longer distance locations. Due to higher rating power system the power quality issues are also more. For our consideration an IEEE 14 bus interconnected system is represented as grid operating at higher rated values. The weak bus of the interconnected system is determined by Fast voltage stability index (FVSI) and load flow analysis using Newton-Raphson method available in MATLAB software. The weak buses are integrated with renewable power generation units like PV plant and wind farm improving the bus characteristics. This paper presents a comparative analysis with and without the RGUs in the system. Improvisation of the parameters like power loss, reduced conventional power consumption, power factor and voltage magnitudes are validated through time domain simulations.

A techno-economic scheduling of distribution system including multi-microgrids considering system reconfiguration and bus selector switches

The Microgrid (MG) as an alternative energy system, would reduce power loss, enhance energy consumption efficiency, and improve the system reliability for a sustainable city. Energy scheduling of distribution systems (DSs) including multi-microgrids (MMGs), would result in a multi-objective problem from DS operators’ point of view for a techno-economic operation. In this regard, a multi-objective model for operation scheduling of DS and connected MGs, is proposed in this paper, which also considers the system management solutions such as reconfiguration and determination of the energy trading points for MGs connection. The proposed model is applied to a modified IEEE 33-bus distribution system including 4 MGs. Simulation results and analysis based on the fuzzy satisfying method indicate that the simultaneous consideration of distribution system reconfiguration and Bus Selector Switches (BSSs) for MGs can improve the social welfare function by 4.58 % and reduces the energy losses by 15.82 %.

An Experimental Study on BLE 5 Mesh Applied to Public Transportation

Today, In-Vehicle Wireless Sensor Networks (IVWSNs) are being used by car manufacturers because it saves time in the assembling process; saves costs in the harness and after-sales; and makes vehicles lighter, which helps lessen fuel consumption. There is no definition for wireless solution technology for IVWSNs, because each one has its own characteristics, and probably this is one of the reasons for its smooth usage in the automotive industry. A gap identified in wireless sensor networks for the automotive domain is that the related literature focuses only on ordinary cars with a star topology and few of them with mesh topology. This article aims to cover this gap by presenting an experimental study performed on verifying the new Bluetooth 5 technology working in a mesh topology applied to public transportation systems (buses). To perform this evaluation, a setup to emulate an IVWSN was deployed in a working city bus. Measuring the network metrics, the bus was placed in a variety of conditions during its trajectory to determine the influence of the passengers and the whole environment on the data transmission. The results suggest that Bluetooth 5 in a mesh topology is a promising candidate for IVWSNs because it shows the robustness of losing only 0.16% packets in the worst test, as well as its ability to cover a wider range compared to its previous version, indeed a better RSSI and jitter, with lower transmission power, compared to a star topology. The round trip time results can support the analysis for time-critical applications.

A tight compact quadratically constrained convex relaxation of the Optimal Power Flow problem

In this paper, we consider the Optimal Power Flow (OPF) problem which consists in determining the power production at each bus of an electric network by minimizing the production cost. Our contribution is an exact solution algorithm for the OPF problem. It consists in a spatial branch-and-bound algorithm based on a compact quadratically-constrained convex relaxation. It is computed by solving the semidefinite rank relaxation of OPF once at the root node of the algorithm. An important result is that the optimal value of our compact relaxation is equal to the rank relaxation value. Then, at every sub-nodes of our branch-and-bound, the lower bound is obtained by solving a quadratic convex problem instead of an SDP. Another contribution is that we add only O(n+m) variables that model the squares of the initial variables, where n is the number of buses in the power system and m the number of transmission lines, to construct our relaxation. Then, since the relations between the initial and auxiliary variables are non-convex, we relax them to get a quadratic convex relaxation. Finally, in our branch-and-bound algorithm, we only have to force a reduced number of equalities to prove global optimality. This quadratic convex relaxation approach is here tailored to the OPF problem, but it can address any application whose formulation is a quadratic optimization problem subject to quadratic equalities and ring constraints. Our first experiments on instances of the OPF problem show that our new algorithm Compact OPF (COPF) is more efficient than the standard solvers and other quadratic convex relaxation based methods we compare it with.

Multi-objective optimization of reactive power dispatch problem using fuzzy tuned mayfly algorithm

The recent multi-objective optimization problems are very complex which require an effective and robust evolutionary method for obtaining a global Pareto-optimal solutions. Most of these multi-objective evolutionary techniques are population-based methods which usually work on random search approaches and often trapped into local minima during their execution. A new fuzzy tuned mayfly algorithm (FTMA) is presented in this paper, to obtain the Pareto-optimal solutions for any complex multi-objective power system problem. It has a self-adapting global exploration capability to get the best Pareto-optimal solutions by varying two crucial parameters i.e., crossover (Pc) and mutation Pm probabilities. Moreover, a model of Pareto-dominance is employed to rank non-dominating solutions to maintain the diversity within the populations. The proposed evolutionary approach is examined on a standard ZDT benchmark test suite and its algorithmic performance is statistically compared with a few of the recent optimization techniques such as NSGA-II, NSGA-III, MMODE, MOAVOA and MMA algorithm. It is further applied to minimize two distinct objective functions (i.e., total transmission loss and voltage stability index) for IEEE-118 bus system and IEEE-24 bus RTS. A comprehensive statistical analysis is presented for the obtained numerical results, which proves that proposed FTMA has better convergence with better solution diversity in comparison to the other competing algorithms. A comprehensive analysis based on statistical results reveal that the proposed FTMA is superior for obtaining better non-dominating pareto-fronts as compared to other competing methods.

Optimized Proportional Integral Derivative Based Power System Stabilizer Using Jaya Algorithm for Angular Stability Enhancement

This study presents an optimized Proportional Integral Derivative Based Power System Stabilizer (PIDPSS) using Jaya Algorithm for angular stability enhancement. Jaya algorithm introduced by Rao, is an optimization technique with few control parameters which is used to minimize the objective function F(K). The modeling and simulation were done using Matlab /Simulink software version R2021b on IEEE 14-Bus system and Single Machine Infinite Bus (SMIB). A three-phase fault was introduced into the network at system runtime of 5s with a fault clearing time of 0.1s. The result of the simulation of the IEEE 14 Bus system showed a 74% and 24% reduction in overshoot time of speed deviation for generators 1 and 2, with settling times of 2.5s and 4s, respectively, in the presence of PIDPSS. The load angle experienced a 14% and 19% reduction in overshoot with settling times of 2s and 2.5s, respectively in the presence of PIDPSS for generators 1 and 2, respectively. The Electrical Power result showed 27% and 6% reduction in overshoot time as well as settling times of 2.5s and 4s, respectively, for generator 1 and 2 in the presence of PIDPSS. The result of the simulation of SMIB system also showed a 25% reduction in overshoot time in relation to deviation speed at a settling time of 4s in the presence of PIDPSS. The Load Angle showed- a 13% decrease in overshoot time at 2s settling time in the presence of PIDPSS. Also, the Electrical Power result highlighted a 15% drop-in overshoot time and settles within 2s. These results affirms that the PIDPSS introduced improved overall system stability.

Analysis of large scale distribution network using Whale Optimization Algorithm

In this study, we use a loop matrix to describe the reorganisation of the RDN's formulation. Calculation time is increased when an optimum reorganisation is determined analytically. More network buses means more time to calculate. Therefore, a technique of optimisation is required to determine the best reorganisation of the radial distribution system. The optimum reorganisation aims to reduce network losses to a minimum and the voltage profile is enhanced. Loop matrices are used to describe the re-formulation of the radial distribution system. The analytical technique of identifying optimum reconfiguration involves additional calculation time. The computational complexity grows as the system's bus count rises. Therefore, a search for the best possible radial distribution system reconfiguration necessitates an optimization technique. The ideal reconfiguration focuses mostly on reducing the system's overall loss. The genetic algorithm (GA), particle swarm optimization (PSO), and whale optimization algorithm (WOA) are the optimization methods used in this paper. Two test systems consisting of 119 buses, and 135 buses are used to evaluate the effectiveness of various optimization strategies. The outcomes are then compared with one another.

Comprehensive Review of Energy Storage Systems Characteristics and Models for Automotive Applications

Currently, the electrification of transport networks is one of the initiatives being performed to reduce greenhouse gas emissions. Despite the rapid advancement of power electronic systems for electrified transportation systems, their integration into the AC power grid generates a variety of quality issues in the electrical distribution system. Among the possible solutions to this challenge is the inclusion of continuous storage systems, which can be located either onboard or offboard. The rapid development of energy storage devices has enabled the creation of numerous solutions that are leading to ever-increasing energy consumption efficiency, particularly when two or more of these storage systems are linked in a cascade and a hybrid mode. The various energy storage systems that can be integrated into vehicle charging systems (cars, buses, and trains) are investigated in this study, as are their electrical models and the various hybrid storage systems that are available.

Assessment of photovoltaic generation penetration effect on the maximum loadability of the system

This paper proposed a method to investigate the effect of increasing PV penetration on the voltage stability of an IEEE 14-bus test system considering maximum PV penetration and system loadability limit. The critical bus of the test system has been decided based on nose curve analysis. The solar PV system is deployed with the most critical bus of the system. The effect of increasing PV penetration on the improvement in the loading capacity of various power system components like transmission lines, transmission line transformers, and generators is investigated over the adopted test system. Based on solar PV penetration up to 100 MW, the maximum loadability limit of the IEEE 14-bus test system increases, as shown by the results. Bus 14 is found to be the most severe bus of the test system using the continuation power flow (CPF) method. However, in some cases, overloading situations develop after a certain limit of PV penetration in the power system. In this condition, the overloading of the power system equipment is improved by the use of a Static Synchronous Compensator (STATCOM) at bus number 14, a double circuit line in the critical line (9–14), and Static Synchronous Series Compensator (SSSC) in the most severe line (9–14) in the system. The maximum loadability of the system gets maximum enhanced from 4.0349 p.u. to 4.5602 p.u. under simultaneous use of solar PV generation, SSSC, and STATCOM at the most critical bus and in most severe line of the system. As evidence, the enhancement in maximum loadability of the system found using the proposed method has been also compared with the existing research. The maximum system loadability has been also enhanced under normal and (N-1) contingency conditions by the use of PV penetration in the system. PSAT/MATLAB software is used for simulation and maximum loadability has been investigated by continuation power flow (CPF) method.

Development of 3-phase fault detection, protection, and automation application with the present of DG in AC power system using GOOSE protocol

In this research work, a protection and automation solution is developed, encompassing SEL751 and SEL751A protection relays that communicate through the IEC-61850 Generic Object-Oriented Substation Event (GOOSE) protocol to deliver high-speed detection and clearance of a 3-phase (3P) fault. The study case is a standard IEEE 13-bus grid including the main system generator (G1), power lines, loads, distributed generation (DG), bus bars, and feeders, equipped with protection relays for detecting over-current faults based on time and current. Two protection relays, B1 in the main system and B2 on the DG side, are integrated with a GOOSE protocol communication system. These settings are configured in such a way that, in the event of the main system breaker being disconnected, the DG cannot be connected to the network, making it a suitable setting for anti-islanding mode (AIM). The efficiency of the relay settings is tested by subjecting the power grid to a 3P fault, by the selected Time-Overcurrent (TOC) U3 inverse curve. Throughout the paper, the descriptions of the study, the grid, assumptions, settings calculations, and analysis of results are systematically presented. For the verification of relay settings, the performance of relays is practically tested and accurately analyzed in detail. The results obtained indicate that the presented strategy is quite effective for the configuration, setting operation, and coordination of relays for fast detection and communication through the GOOSE protocol.

Optimal placement of phasor measurement units using topology transformation method based on Grey Wolf optimization approach

The optimal placement of phasor measurement units (PMUs) requires minimizing both the number of PMUs required and ensure that the whole power system is totally observable. To identify a power system as observable, it is necessary to know the voltages of all the buses in the power system. This paper suggests rules of selection for the topology transformation method, which implies a process of merging a zero injection bus and one of its neighboring buses. The selection of a bus chosen to merge with a zero injection bus will affect the result of the merging process. To determine the most appropriate bus to merge with the zero injection bus, the proposed method will use four rules designed to determine the minimum number of PMUs required to achieve full observability of the power system. The problem is formulated and solved by a grey wolf optimization (GWO) approach. The suggested GWO has been applied to the IEEE 14-bus, 24-bus, and New England 39-bus.

Optimal siting and sizing of custom power system and smart parking lot in the active distribution network

AbstractNon‐linear loads, electrical vehicles (EVs) and power electronics are the sources of harmonic generation in the power system. Harmonics are the reason for the disturbance in the technical constraints and quality of the power system. These disadvantages are formed in the current and the voltage of the system branches and buses. To reduce these harmonics, active and passive power filters are used. Since active power filters (APFs) include electronic power switching devices, they are used to eliminate or reduce current or voltage harmonics. To properly reduce these harmonics and supply consumer demand, private investors (PIs) are considered to enhance the power quality, by investing in the APF units and the distribution network operator (DNO) coordinating and feeding the EVs, by equipping the network with smart parking lots. Total harmonic distortion, bus voltage profile, active power loss and energy not supplied (ENS) are considered problem attributes. Using techniques for order of preference by similarity to the ideal solution (TOPSIS), it is determined how the addition of photovoltaic (PV), energy storage system, and batteries affects the ranking of attributes from the perspectives of both DNO and PI. The best solutions are obtained in the first stage using a genetic algorithm (GA), and the attributes have been prioritized from a utility perspective in the second stage by TOPSIS. To verify the performance of GA and TOPSIS, all of the obtained results are compared with the other algorithms. As seen clearly, active, reactive power loss and ENS in scenarios with the participation PV are reduced. Furthermore, comparing the results of different algorithms confirms the efficiency of GA and TOPSIS.