Main Power System Research Articles

Design considerations of implementing process bus and PTP along an IEC 61850-based main line traction power system

Design considerations of implementing process bus and PTP along an IEC 61850-based main line traction power system

Capacitor Bank Panel Design to Improve Industrial Power System Efficiency and Safety

Industrial loads generally use control equipment and power electronics that use semiconductor materials that are very sensitive to voltage fluctuations. As reactive power compensation, industries usually use capacitor banks to increase power factor, reduce losses and increase line capacity. But it turns out that the use of capacitor banks also causes problems related to capacitor bank switching during the energizing process. During the energizing process, transient voltages and currents will be generated which can potentially damage control equipment, power electronic equipment, switching equipment and the capacitor bank itself. The Capacitor Bank panel assembly process involves the preparation of components such as MCB (Miniature Circuit Breaker), MCCB (Molded Case Circuit Breaker), Capacitor Bank, and other components. After that, these components are carefully assembled according to the pre-prepared design. Next, the installation of the Capacitor Bank panel involves mounting the panel to the location according to the plan and connecting it to the building's main power system. Accurate wiring and meticulous testing are required to ensure that the panels function properly. Therefore, a good understanding of the assembly and installation process of Capacitor Bank panels is essential to ensure efficient, and safety.

Enhanced proportional integral controller for DSTATCOM with particle swarm optimization algorithm in power system

Power system expansion planning is supported by using distributed generation (DG) instead of installing new main power system generators. The portability and autonomous operation of the DG make it capable of integrating into the distribution system. Power electronics devices for home loads, mainly electric vehicles, mobile phones, and laptops, introduce harmonics and related power quality issues to the distribution system. This load creates power quality issues like an increase in total harmonic distortion (THD) and a reduction in power factor. This paper uses the DG to supply important power electronics devices for the mitigation of power quality problems in distributed systems with non-linear loads, such as electric vehicles, called the “distributed static compensator (DSTATCOM)”. Wind and photovoltaic (PV) generators supply power to a common DC source. To improve power quality D-STATCOM powered by PV and wind energy systems at the DC link is incorporated. The direct axis/quadrature axis method (DQ method) controls the real and reactive components of the power. Proportional integral (PI) and particle swarm optimization (PSO) based PI controller parameter estimation are developed, and results are compared for power quality performance. In terms of improving power quality, the PSO-based parameter estimate of the PI controller performs better than the traditional PI controller.<br /><div class="extension_reset_css AnnotateNet_widget AnnotateReviewNotesButton" style="display: none; z-index: 2147483644;" data-id="ExtensionWidget"><div class="extension_reset_css AnnotateNet_widget annotateclickable" style="z-index: 8; display: none;" title="Resize" data-id="Widget"> </div></div>

Analysis of Remote Islanding Detection Methods for Distributed Resources

Penetration of distributed generation in the power grid is increasing. This situation leads to new possibilities but also new issues, such as anti-islanding protection. During a loss-of-mains or islanding situation, distributed generation (DG) units remain feeding a part of the electrical network without connection to the main power system. Currently, DG units have to be disconnected from the grid during islanding as soon as possible, due to potential risks for repair crews and components, poor power quality in the island and reclosing problems. A fast and reliable islanding detection method could avoid mentioned issues. Among the many existing methods, remote schemes could meet these requirements. Hence, this paper presents the operating principles of remote islanding detection methods, as well as the current state of development of communication-based remote islanding detection methods to be applied in distributed power generation systems.

Enhanced Randomized Harris Hawk Optimization of PI controller for power flow control in the microgrid with the PV-wind-battery system

Microgrids, characterized by their ability to work individually or in combination with the main power system, play a pivotal role in addressing the growing demand for reliable and sustainable energy solutions. This work concentrates on the integration of sustainable energy sources, specifically photovoltaic (PV), and wind generation and a battery storage system within a microgrid framework. Additionally, a power flow control strategy is implemented to enhance the dynamic behaviour and stability of the microgrid. The proportional-integral (PI) controller is a fundamental component in regulating the microgrid’s power flow, ensuring optimal performance under varying operating conditions. However, tuning the PI controller parameters is a difficult task because of the dynamic and nonlinear nature of renewable energy sources. In this work, the application of the Enhanced Randomized Harris Hawk Optimization (ERHHO) to fine-tune the PI controller is proposed, using the algorithm’s ability to mimic the hunting behaviour of hawks in finding optimal solutions. The PV-Wind-Battery microgrid system is modelled, and the proposed algorithm is employed to optimize the PI controller parameters for efficient energy management. The ERHHO algorithm’s exploration-exploitation balance is harnessed to navigate the complex solution space and converge to optimal PI controller settings, thereby enhancing the microgrid’s stability and performance. The study evaluates the effectiveness of the proposed ERHHO-based PI controller tuning through comprehensive simulations. Performance metrics such as transient response, overshoot, settling time, and steady-state error are analysed to validate the robustness and efficiency of the proposed method. Compared to its nearest optimization algorithm, with the proposed algorithm rise time is reduced by 50%, overshoot is reduced by 75%, settling time is reduced by 66%, and finally, a percentage of reduction of steady-state error is 45%. The outcomes of this research contribute to the advancement of microgrid control strategies, offering a novel approach to PI controller tuning in the context of diverse renewable energy sources. The integration of the Harris Hawk Optimization algorithm provides a promising avenue for enhancing the operational efficiency and reliability of microgrids, paving the way for sustainable and resilient energy systems in the aspect of growing energy landscapes.

Effects of a Self-Pressurized Injection Strategy on the Formation of a Stratified Mixture and the Combustion of an Aviation Kerosene Piston Engine

Abstract The aviation kerosene piston engine (AKPE) is the main power system for small- and medium-sized unmanned aerial vehicles (UAVs). Conventional AKPEs use carburetors or port fuel injection (PFI) as fuel supply, resulting in poor cold start performance and difficulty in forming an economically efficient stratified mixture. In addition, two-stroke AKPEs using carburetors or PFI have serious scavenging losses. These reasons lead to the poor economic performance of conventional AKPEs. Direct injection (DI) can be controlled through precise injection timing to form a stratified mixture. The combustion of stratified mixtures in engines can effectively improve the fuel economy and endurance flight time characteristics of UAVs. As a special DI injector, self-pressurized injectors have great potential in the power field of UAVs. To effectively apply self-pressurized injectors on UAV engines and improve the economy, an engine model and a self-pressurized injector spray model are established and verified in this paper. The single injection strategy and segmented injection strategy for forming stratified mixtures are explored, and the combustion performance is studied. The main conclusions are as follows: the optimal installation angle of the injector is 15 deg, which yields excellent results in the formation of the mixture at this angle. When the fuel injection quantity is small, utilizing a single injection strategy combined with delaying the end of the injection phase (EOIP) can form a stratified mixture. Reducing the angle difference between the EOIP and the ignition timing can improve the power and economy. As the fuel injection quantity is large, a stratified mixture can be formed through two-stage injection. When the fuel injection ratio is 4:1, the uniformity of the mixture distribution in the combustion chamber is significantly improved. Adjusting the second EOIP between a 35 deg crank angle (CA) before top dead center (BTDC) and a 30 deg CA BTDC can achieve a stratified mixture with good economy and power performance.

Impact of Automation on Enhancing Energy Quality in Grid-Connected Photovoltaic Systems

Rapid growth in the integration of new consumers into the electricity sector, particularly in the industrial sector, has necessitated better control of the electricity supply and of the users’ op-erating conditions to guarantee an adequate quality of service as well as the unregulated dis-turbances that have been generated in the electrical network that can cause significant failures, breakdowns and interruptions, causing considerable expenses and economic losses. This research examines the characteristics of electrical variations in equipment within a company in the industrial sector, analyzes the impact generated within the electrical system according to the need for operation in manufacturing systems, and proposes a new solution through automation of the regulation elements to maintain an optimal system quality and prevent damage and equipment failures while offering a cost-effective model. The proposed solution is evaluated through a reliable simulation in ETAP (Energy Systems Modeling, Analysis and Optimization) software, which emulates the interaction of control elements and simulates the design of electric flow equipment operation. The results demonstrate an improvement in system performance in the presence of disturbances when two automation schemes are applied as well as the exclusive operation of the capacitor bank, which improves the total system current fluctuations and improves the power factor from 85.83% to 93.42%. Such a scheme also improves the waveform in the main power system; another improvement result is when simultaneously operating the voltage and current filter together with the PV system, further improving the current fluctuations, improving the power factor from 85.83% to 94.81%, achieving better stability and improving the quality of the waveform in the main power grid.

Resilience-oriented placement of multi-carrier microgrids in power systems with switchable transmission lines

Extreme events such as floods, hurricanes, earthquakes, and wildfires pose significant threats to the uninterrupted supply of electricity to consumers, as they can cause the failure of numerous power system components. The resilience of a power system is defined by its ability to withstand extreme events and continue meeting demand. While the placement of multi-carrier microgrids (MGs) in power systems can impact resilience, the literature lacks research on resilience-oriented placement. This paper aims to address this gap by proposing a resilience-oriented placement strategy for multi-carrier MGs, utilizing switchable transmission lines to enhance the resilience of power systems. The study focuses on a heat-power-hydrogen MG that obtains gas from a gas network, exchanges power with the main power system, and incorporates combined heat and power (CHP), electrolyzer, and thermal storage. The developed model employs a stochastic mixed-integer linear programming (MILP) approach, ensuring the attainment of the global optimum. Resilience is evaluated using the metric of expected load not supplied (ELNS). The results demonstrate that when the bus connected to the MG is isolated, the MG generates electricity through its CHP unit to meet local demand, reducing the total demand shed in the power system and improving system resilience. Specifically, the MG reduces ELNS from 4955.48 MWh to 2356.64 MWh, indicating a remarkable 52% improvement in ELNS. Furthermore, the study shows that transmission line switching further decreases ELNS from 2356.64 MWh to 848.68 MWh. Several experiments are conducted to analyze the sensitivity of power system resilience to the number of MGs, the MG-power system exchange limit, and the limit on gas import from the gas network.

Energy Router Applications in the Electric Power System

Energy router is being investigated to replace conventional transformer in the electric grid. Improvement so far observed in use of converter makes possible the intelligent integration between systems with different characteristics’ in terms of frequency and voltage levels as well as exploitation of generation sources and storage systems typically operating in DC. Consequently, it is believed that Energy Router is able to interconnect different portions of electrical networks and at different voltage levels and types. The Energy Router is an assembly of converters isolated by a medium or high frequency transformer. In its design, different voltage levels and types are made available to achieve high results in terms of system integration, efficiency and flexibility. This paper evaluates the main potentials of this technology if widely introduced in the main power system. Starting from the single component description, a couple of possible applications are presented and discussed.

Dynamic and quantitative risk assessment of Cruise ship pod propulsion system failure: An integrated Type-2 Fuzzy-Bayesian approach

Azipod propulsion has revolutionized the future of ship propulsion and maneuvering operations with over 20 years of experience, eventually improving ship safety, reliability, energy efficiency, and overall vessel performance. However, it consists of technically complex machinery systems; its breakdown can result in many potential failures with severe repercussions. In this work, an accident-based dynamic risk assessment study of the Cruise ship pod propulsion system has been carried out. It is based on the real-ship accident of the Norwegian Star, which resulted in the loss of ship propulsion. When historical accident statistics are limited, traditional methods fail to address the uncertainty, dynamic environment, and quantitative risk assessment problems. The goals include avoiding worst-case scenarios by illustrating the progression of dynamic change in risk and establishing the Bayesian network framework for dealing with uncertainty more effectively. Interval type-2 Fuzzy expert system is integrated with the dynamic Bayesian network and bow-tie model for quantitative risk assessment, which laid the groundwork for the subsequent hazard identification and quantitative risk assessment. This accident network summarizes how pod machinery operational failures can cause accidents. The estimated sensitive machinery nodes such as Main motor failure, propulsion system, and power system failure are the leading causes of pod propulsion system failures on board cruise vessels. Risk analysts and decision-makers in the marine and offshore engineering industry can use the suggested model as a decision support tool to considerably reduce and eliminate potential failures, improving the ship's safety and system reliability.

Neurodynamics-based distributed model predictive control of a low-speed two-stroke marine main engine power system

This article studies a steady operation optimization problem of a low-speed two-stroke marine main engine (LTMME) power system including a cooling water subsystem, a fuel oil subsystem and a main engine subsystem with input and state constraints. Firstly, a distributed model with coupling inputs and states is established for the LTMME power system according to laws of thermodynamics and kinetics. Further, an optimization problem of the LTMME power system is formulated to ensure the system to operate steadily, subjected to constraint conditions of the distributed model and the input and state bounds. Moreover, the optimization problem is rewritten as a quadratic programming problem, and an iterative distributed model predictive control (DMPC) scheme based on a primal–dual neural network (PDNN) method is used to obtain the optimal inputs within the constrained range. Finally, based on the actual data from an underway ocean vessel named Mingzhou 501 with an LTMME power system, a group of simulations are carried out to verify the effectiveness of the proposed approach.

Data-driven multi-layered intelligent energy management system for domestic decentralized power distribution systems

Energy management techniques have been immensely adopted in residential, industrial, and commercial sectors to meritoriously flatten the load profile of consumers. In this article, a cutting-edge intelligent energy management system is proposed to analytically monitor and regulate the load demand of a residential area to meritoriously address the load balancing and scheduling optimization problem with an aim to design an autonomous domestic complex, less reliant on the focal power grid. To do so, single- and multi- objective functions are defined for the presented double-layered framework. In the first layer, a day-ahead scheduling problem is evaluated to achieve the mutual revenue of electricity utilities and consumers, while in the second layer, a real-time coordination scheme for robust energy transactions among appliances, multiple microgrids, and the main power system is examined. Herein, a 0−1 multiple knapsack problem incorporated with the mixed-integer linear programming method is used to formulate the system mathematical model. To evaluate the intended system model, three heuristic algorithms (genetic algorithm, wind-driven optimization, and their hybrid) are modified. Furthermore, the Monte–Carlo simulations are performed to mitigate the impact of randomness and avoid pre-convergence. From the results of extensive simulations, it is corroborated that the proposed methodology is robust, reliable, and eco-social compared to prior schemes. This article reveals that the hybrid approach outperformed the other two strategies in terms of energy consumption, electricity cost, peak-to-average ratio, and user comfort level.

The Method of Calculating the Frequency of the Initiating Event in a Dual-Unit Site with the Example of LOOP Events

In a nuclear power plant, the consequences of a multi-unit event occurring concurrently are more serious than those of a single-unit event. The first step in the probabilistic safety analysis of multi-units is to analyze the initiating events and calculate the frequency of initiating events for simultaneous events of multiple units. The difficulty in using the fault tree model is that the known data are all frequency data from a single unit and cannot be logically multiplied. In this paper, taking a dual unit as an example, we used the formula to convert the probability of failure of the second unit within 72 h and then build a fault tree model. After analyzing the results of the dual unit, the most frequent cut set was the common cause of failure of the main transformer and of the switching failure of the main and auxiliary external power. The final calculation of the frequency of simultaneous loss of off-site power events for the dual units within 72 h was 3.22 × 10−4/year. After comparing with the single-unit results, it was found that the common cause failure of each unit’s independent equipment was the main reason for the occurrence of a loss of off-site power. Shared equipment in a single unit was ranked low in all the cut sets (such as the stability of the external grid for the main and auxiliary power systems) but was ranked high in multiple units. The calculation results of the frequency of initiating events of double units were two orders of magnitude lower than those of a single unit. However, the consequences of simultaneous events of multiple units were higher than those of single reactors. Therefore, attention should be paid to the risk of a simultaneous loss of off-site power event of multiple units.

Accident analysis of 220, 500 kV overhead lines of the main power systems network

The statistical analysis of overhead lines (OHL) of the unified national power grid (UNPG) of the Central European part of the country for the previous 15 years is subjected to statistical analysis. The structure of the failure flow parameter (failure frequency) of 220 and 500 kV overhead lines with a total length of 17.6 and 8.5 thousand kilometers, respectively, is compared. It is shown that the last decade is characterized by the most favorable reliability characteristics. At the same time, a tendency was detected, when the parameter of overhead line failure flow became insignificantly dependent on the nominal voltage of the network. This fact makes us doubt the existing belief of specialists, according to which the specific (per 100 km) failure rate of overhead transmission lines decreases with the increase of the nominal voltage of the network. The above trend once again demonstrates the objective possibility of purposeful management of electric networks reliability.

POWER QUALITY ANALYIS FOR POWER LED DRIVES

DC micro grids have grown increasingly popular in the energy grid in recent years, as distributed generation has increased. Distributed generation refers to small or large-scale renewable energy that is linked to the main power system. Renewable energy sources like solar and wind power help the local grid, but their output is inherently intermittent and unpredictable, interfering with regular grid operation. Some of these issues can be mitigated by using energy storage in conjunction with renewable energy. Renewable energy is often linked to the grid using power electronic converters. 
 The goal of this research is to simulate and evaluate transmitted emissions in the time and frequency planes using IEEE 1459 to investigate the impacts of DC / DC converters on DC lines, particularly for renewable energy generation. While there are standards and norms for frequencies up to 2 kHz and beginning at 150 kHz, the frequency range 2-150 kHz only has suggested techniques and propagation restrictions. As a result, the emission conveyed in the frequency range of 2-150 kHz is a subject that must be comprehended. The structure of the generation model, as well as the idea of power quality in electricity generating models, will be investigated using data collected through experimental and computer simulations on a medium-scale hybrid network connected to the grid. The technological advances acquired will subsequently be utilized to evaluate the power quality of various DC and AC single/three phase power systems (such as computer servers, airplanes, and so on).

Hierarchical evaluation framework for coupling effect enhancement of renewable energy and thermal power coupling generation system

Renewable energy and thermal power coupling generation system (RETCS) is a special virtual power plant that aggregates renewable energy and thermal power to the main power system through the coupling point. RECTS can coordinate as an integrated system to handle the power fluctuation of renewable energy. Analyzing the interaction of RETCS in resource, economy, and environment comprehensively is the key to improving the coupling effect of the system. This work proposes a coupling coordination degree (CCD) evaluation system to assess and improve the coupling effect of the RETCS. First, CCD evaluation system is established to assess the RETCS using indicators from resource, economy, and environment subsystems in detail. Second, a stochastic RETCS planning model is established to investigate the coordination strategy of the system. Finally, a RETCS case study with different wind power penetration levels and power demand in northeast China is carried out to demonstrate the effectiveness of CCD evaluation system in representing the coupling effect of RETCS and helping to improve the system. Numerical results show that thermal units with deep peak regulation capability can better utilize the ramping and power regulation potential to handle the wind power fluctuation in most cases. An appropriate power source capacities in RETCS can improve the coupling effect of the system under a certain power demand.

Application of an adaptive controller for controlling the rotational velocity of hydrogenerators taking into account the technological state of a Kaplan turbine

The impact of oil leakages in a turbine on the main power system parameters is investigated in reactive hydraulic turbines with adjustable-blade runners (Kaplan turbines) installed at Maynskaya, Nizhne-Bureiskaya and Vilyuyskaya hydroelectric power plants. The main theoretical relations and conclusions were obtained by the methods of mathematical simulation and integral calculations in the MATLAB software environment. A method is proposed for monitoring leakages in the housing of an adjustable-blade runner and smoothing the fluctuations of various parameters (amplitude, rotational velocity, phase angle, active power and generator current) of the power system in the case of oil leak-ages. The control is performed by means of a sensor installed in the runner, a fiber-optic cable and an optical-electrical converter located along the shaft from the runner blades to the oil receiver of the corresponding hydraulic unit. The performed analysis of the obtained mathematical model (frequency response and Nyquist plots were built) relative to the basic parameters of the electrical energy generated by a hydraulic unit showed that the proposed method of monitoring oil leakages contributes to an increase in the operational stability of a hydraulic unit. When constructing the model, the following parameters of the hydraulic unit were taken into account: rotational angle of runner blades and opening angle of hydraulic turbine guide vanes. The developed block diagram can be used to compare variations in the parameters both without oil leakage control and taking into account the automated control system proposed by the authors. It is shown that the obtained logarithmic Nyquist plot can be used to monitor variations in the amplitude, as well as its smoothening, both under normal conditions and taking into account oil leakages in the hydraulic turbine housing.

Study on the fault inversion of large-scale EMT digitalanalog hybrid simulation and test based on ADPSS

The new-typed power electrical system dominated by renewable energy produces immerging requirement for power system simulation technology. Electromechanical transient simulation, as the main power system simulation tool, can not simulate the precise dynamic characteristics of power electronics devices. Electromagnetics transient simulation (EMT) is difficult to be implemented in large-scale power system analysis due to its unbearable calculation cost. This paper proposes the new largescale EMT digital-Analog simulation technology based on ADPSS, which includes two kinds of parallel technologies and the advanced HVDC modelling technology. With these new proposed methods on ADPSS, it is achieved that the high accurate fault inversion study in East China Power grid, which demonstrates that the EMT simulation can be implemented in large-scale power system study with high accuracy and efficiency.

Data-Driven Optimization of Transmission Section Limits and Their Adaptability for New Power Systems With High Penetration of Renewable Energy

In traditional power systems, the transmission section limits are often set to predetermined values according to the typical peak-to-valley demand modes, which may be difficult to adapt to the complex and diverse operation modes of the new power systems with high penetration of renewable energy, and it cannot consider the coupling characteristics of AC and DC transmission sections also. In order to make better use of the efficiency of the transmission sections, a mathematical model for optimizing the adaptability of the transmission section limit is firstly proposed, in which a data-driven typical demand mode extraction method based on K-means clustering is proposed according to the load forecast, renewable energy forecast and market transaction data. Then, the adaptability assessment of the section limit and the transmission requirements are carried out. Finally, the power perturbation method is used to calculate the influence factor matrix of associated transmission section limit and stability margin of its dominant fault. And the influence factors are optimized according to section limit adaptability and stability margin influence, and the best adaptable limit of the associated transmission sections are obtained. The calculation and optimization results of the actual case of the interconnection corridor between Xinjiang and the northwest main power system of China verify the effectiveness and practicability of the proposed limit optimization model, which is able to improve the flexibility and adaptability of the actual power system operation.

SMA-based optimal energy management study in a connected PV/MT/ DG/V2G/BESS/WT on IEEE-33 bus considering network losses and voltage deviations

The unpredictable nature of renewable energy resources (RERs) makes obtaining optimum operation and grid integration in today’s smart power distribution networks challenging. Thus, to mitigate the fluctuations in RERs, the penetration of diesel generators, batteries, and electric vehicles (EV) must be considered for an effective energy management study (EMS) in the IEEE-33 bus system. This paper addresses the energy management of a microgrid linked to the main power system under deterministic and probabilistic circumstances. Apart from economic considerations, modern distribution networks must maintain an acceptable range of system reliability indexes. Failure of reliability in the distribution network may result in irreversible harm to the distribution network. For multi-objective functions such as cost reduction, voltage profile improvement, and voltage stability improvement are the main objectives of this article. An efficient method known as a novel slime mould algorithm (SMA) is used to solve these issues and validate the performance with the existing evolutionary algorithms. However, the SMA can optimally address the grid-connected various types of RERs installed, which can significantly compensate network losses, voltage deviations and improve the system performance. Finally, the algorithm’s effectiveness on the EMS approach is verified under different algorithms through 2021a MATLAB/Simulink and the proposed methods prove the best results with the convergence of other algorithms also.