Power Flow Variations Research Articles

A global plasma and surface model of hydrogen/methane inductively coupled discharge to analyze hydrocarbon plasma–surface interactions in extreme-ultraviolet lithography machines

Hydrocarbon contamination is associated with light transmission losses in modern lithography machines, which contain extreme-ultraviolet-induced plasma. A volume-averaged global and deposition/etch surface model of a reference hydrogen/methane inductive discharge is developed to investigate the plasma–surface interactions. The simulation results are validated against a wide variety of experiments and verified with respect to multiple sets of computational data. The deposition rate is calculated for a variation in methane impurity (10–10 000 ppm), power, pressure, and net mass flow. The simulations conclude that the hydrocarbon plasma deposition can be minimized by reducing methane impurity and excluding solid organic structures.

Secondary voltage regulation based on full-state feedback — performance assessment with Dyna[formula omitted]o

This paper discusses the performance assessment of new secondary voltage regulators currently under study in France to address challenges posed by the energy transition. With renewable integration and increasing cross-border interconnections, power flow variations surge across the network. Coupled with the historical SVRs’ relatively slow response, operational since the late 1970s, recent observations show higher voltage volatility. Prior research has already highlighted the potential of two novel regulators: the Average Q-SVR and the LQ-SVR, in mitigating these issues. Our focus here centres on the latter and begins by discussing the implications of control design hypotheses on closed-loop system performance. These include linearisation, neglecting communication delays, and assuming uniform dynamic behaviour across all resources. We then propose a two-step control design, leveraging Linear Quadratic Regulator (LQR) and eigenstructure placement methods and demonstrate that this approach surpasses the LQR method alone in terms of transient reactive power tracking.

Design and Performance Evaluation of Fuzzy Controller based Energy Storage Enabled Statcom for Electrical Distribution Network

In order to fulfill the demand for power, the production of locally accessible resources, such as solar and wind energy, has increased dramatically during the past ten years. Their integration into the distribution of electrical network (EDN) has affected the operation of the network. Variations in the real power flow and an increase in reactive power demand have impacted the EDN voltage/frequency profiles and distribution transformer strain. Hence to improve the voltage regulation and reduce the active power fluctuations, there is a need for a system network of electrical distribution (EDN). It has the ability to support both reactive and active power. Thus, the energy storage device with STATCOM is introduced i.e. an energy storage device linked to Statcom (EsSt) has been proposed in this paper. The Common Coupling Point (CCP) voltage can be adjusted by energy storage connected to Statcom (EsSt) to satisfy the amount of power required actively at EDN. The EsSt has an integrated battery storage system and may be controlled using a voltage source converter by employing the proper control strategy to deliver the necessary energy support and VAR compensation. The voltage at the dc-link has been integrated using DC-DC converter based half bridge. The use of conventional PI controllers provides poor transient response. To improve the transient performance, It is suggested that a fuzzy logic controller be used in place of the PI controller. Analysis of comparison using MATLAB. The rule-based fuzzy logic controller performs better than the PI controller, according to the Simulink environment.

A grid voltage perturbations based bidirectional impedance uniform control for grid‐connected DC/AC converter

AbstractFor bidirectional grid‐connected DC/AC converters, the power flow variation substantially alters the system stability, and especially severs under heavy load. Towards this problem, this paper proposes a novel impedance uniform control method to eliminate the stability degradation under power flow variations, which is achieved by reshaping the converter negative incremental impedance to resistive in the stability fragile mode. The d‐axis voltage perturbation is extracted to dynamically modify the active power current reference. Hence, the system bidirectional damping performance can be simultaneously improved by this dedicated design. Without switching control modes or sacrificing dynamic performance, the grid‐connected converter system can maintain satisfied stability under bidirectional power flow variations. Finally, the effectiveness of the proposed control method has been validated by both simulations and experiments.

State-of-Charge Estimation of Batteries for Hybrid Urban Air Mobility

This paper proposes a framework for accurately estimating the state-of-charge (SOC) and current sensor bias, with the aim of integrating it into urban air mobility (UAM) with hybrid propulsion. Considering the heightened safety concerns in an airborne environment, more reliable state estimation is required, particularly for the UAM that uses a battery as its primary power source. To ensure the suitability of the framework for the UAM, a two-pronged approach is taken. First, realistic test profiles, reflecting actual operational scenarios for the UAM, are used to model the battery and validate its state estimator. These profiles incorporate variations in battery power flow, namely, charge-depleting and charge-sustaining modes, during the different phases of the UAM’s flight, including take-off, cruise, and landing. Moreover, the current sensor bias is estimated and corrected concurrently with the SOC. An extended Kalman filter-based bias estimator is developed and experimentally validated using actual current measurements from a Hall sensor, which is prone to noise. With this correction, a SOC estimation error is consistently maintained at 2% or lower, even during transitions between operational modes.

Frequency Regulation of Interlinked Microgrid System Using Mayfly Algorithm-Based PID Controller

The primary goal of this article is to design and implement a secondary controller with which to control the system frequency in a networked microgrid system. The proposed power system comprises of Renewable energy sources (RESs), energy-storing units (ESUs), and synchronous generator. RESs include photovoltaic (PV) and wind turbine generator (WTG) units. The ESU is composed of a flywheel and a battery. Because renewable energy sources are not constant in nature, their values fluctuate from time to time, causing an effect on system frequency and power flow variation in the tie line. The nonlinear output from the RESs is balanced with the support of ESUs. In order to address this situation, a proportional integral derivative (PID) controller based on the Mayfly algorithm (MA) is proposed and built. Comparing the responses of controllers based on the genetic algorithm (GA), differential evolution (DE), and particle swarm optimization (PSO) technique-optimized to demonstrate the superiority of the MA-tuned controller.. The results of the validation comparisons reveal that the implemented MA-PID controller delivers and is capable of regulating system frequency under various load demand changes and renewable energy sources. A robustness analysis test was also performed in order to determine the effectiveness of the suggested optimization technique (1%, 2%, 5%, and 10%) step load perturbation (SLP) with ±25% and ±50% variation from the nominal governor and reheater time constant).

A chaotic equilibrium optimization for temperature-dependent optimal power flow

ABSTRACT Optimal power flow (OPF) is one of the common problems in power systems. In general, the branch resistance of the system is assumed to be constant with respect to temperature variation in conventional optimal power flow. However, the temperature correlation of the branch resistance should be taken into account to enhance the accurate calculation of the power flow and branch losses. This paper suggests a new and efficient method, which is chaotic equilibrium optimization (CEO) to deal with the temperature-dependent optimal power flow (TDOPF) problem. The CEO is validated on IEEE 30-bus and 118-bus networks with different objective functions, including generating fuel cost, total active power losses, voltage profile enhancement, voltage stability improvement, and emission reduction. Furthermore, the temperature effect on the TDOPF problem is also analyzed. In the case of fuel cost optimization in the 30-bus network, fuel cost increases from 799.85 $/h to 802.9474 $/h when the temperature increases from 0°C to 100°C, corresponding to a fuel cost increase of 0.04% for each 10°C. From the obtained outcomes, the efficacy of the CEO has been proven in finding accurate solutions for the TDOPF problem.

Power grid segmentation for local topological controllers

The massive integration of renewable energies into the power grid leads to more complex flow management that requires faster reactivity. Because they can react quickly and allow optimization parallelization, decentralized management with local closed-loop controllers is a promising solution for real-time constraints management due to rapid power flow variation. However, determining the area that a local closed-loop controller should control is decisive for their proper functioning. The controlled area must allow the appropriate remedial actions and not create constraints outside of it, especially for a topological agent. This paper proposes a method to identify these areas for a topological agent. Thus, we first describe the topological agent implemented to evaluate the method. Then we describe the three steps of the method pipeline: the construction of an influence graph adapted to topological actions, the clustering of this influence graph, the evaluation of the capacity to host topological local-closed-loop controller of the zones resulting from the segmentation. Finally, we conducted simulations of local action controllers acting on areas identified by the method to test the procedure’s robustness. We eventually assess them and compare them to a centralized optimization scheme.

Merit Evaluation of Peer‐to‐Peer Electricity Trading Between Prosumers

The enforcement of a feed‐in tariff (FIT) program in Japan has increased the number of installations of photovoltaic generation systems in its residential sector. After the end of an FIT program, the surplus electricity of an individual prosumer is purchased by the utility company at a reduced price, which may have an economic impact on the prosumer. To avoid this adverse effect, peer‐to‐peer (P2P) electricity transactions among prosumers based on blockchain and smart contract technologies as well as introduction of residence‐use stationary storage batteries are generating significant interest. In this study, the potential economic merit of P2P transactions and residential storage battery introduction are evaluated using a total optimization approach. For realizing a more practical perspective, this study also investigates the economic merit based on a partial optimization approach, in which an individual prosumer pursues its own profit. Furthermore, in this study, the grid‐side merit of P2P electricity transactions among prosumers is examined. Comparison of the merits determined by the total and partial optimization approaches shows that the realization of P2P transactions could provide a notable economic merit to the participants and reduce both the required facility capacity and power flow variation. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

IEC 61850 modeling of an AGC dispatching scheme for mitigation of short-term power flow variations

High penetration of renewable energy-based generators increases variability in power systems. To prevent transmission lines from overloading due to such variations, advanced power flow management system should be developed. This paper proposes an Automatic Generation Control (AGC) design that mitigates power flow increase on heavy load lines. The developed method optimizes dispatching of control order from AGC so as not to increase power flow of these lines. This is achieved by considering how the output change of each control unit effects power flow in the system. The performance of the proposed method is examined by simulation study with 10-machine power system model. Furthermore, the communication infrastructure of the developed AGC system and its components are developed according to IEC 61850 communication standard. Operational instructions are mapped onto IEC 61850 messages. Simulations are performed with network emulators to validate the developed communication models and their operation. The benefit of the proposed communication system with IEC 61850 is achieving plug and play capability with universal models. The results of both simulations show that communication infrastructure is successfully developed and AGC prevents power flow increase in heavily loaded lines by making use of remained capacity of light loaded lines as proposed.

Tractor Transmission Design With KISSsys Model

A tractor transmission is usually very complex with a lot of gear pairs, shafts and bearings in it. Modern transmissions have also several functionalities like shifting without clutch, 4WD/2WD forward/reverse shuttle and PTOs. They must work smoothly and quietly like an automotive transmission, but usually working condi-tions are much more severe. They must also be reliable in different kind of working conditions and fields of applications. Due to the wide variety of gears and speeds that can be chosen, calculations for safety factors and lifetime of components are typically very complicated, time consuming and difficult to manage. It is laborious, unproductive and error-prone to administer the many calculations that occur in a tractor transmission due to its complexity. The use of a calculation model, that sim-ultaneously administrates all the calculations, brings many advantages for the man-ufacturing process, planning of tests and sales support. A very complex and modern transmission was modeled in this project in order to be able to simultaneously meas-ure the entire tractor transmission driveline. Tractor with 12x12 driveline shifting system and power flow variations can be calculated the whole system’s gears, shafts, bearings with a load spectrum.

Water Cycle Algorithm Optimized Type II Fuzzy Controller for Load Frequency Control of a Multi-Area, Multi-Fuel System with Communication Time Delays

This paper puts forward the implementation of an intelligent type II fuzzy PID (T2-FPID) controller tweaked with a water cycle algorithm (WCA), subjected to an error multiplied with time area over integral (ITAE) objective index for regularizing the variations in frequency and interline power flow of an interconnected power system during load disturbances. The WCA-based T2-FPID is tested on a multi-area (MA) system comprising thermal-hydro-nuclear (THN) (MATHN) plants in each area. The dynamical behavior of the system is analyzed upon penetrating area 1 with a step load perturbation (SLP) of 10%. However, power system practicality constraints, such as generation rate constraints (GRCs) and time delays in communication (CTDs), are examined. Afterward, a territorial control scheme of a superconducting magnetic energy storage system (SMES) and a unified power flow controller (UPFC) is installed to further enhance the system performance. The dominancy of the presented WCA-tuned T2-FPID is revealed by testing it on a widely used dual-area hydro-thermal (DAHT) power system model named test system 1 in this paper. Analysis reveals the efficacy of the presented controller with other approaches reported in the recent literature. Finally, secondary and territorial regulation schemes are subjected to sensitivity analysis to deliberate the robustness.

IH 2 OA based on intelligent power flow management of HRES in smart grid

This manuscript proposes a hybrid strategy for power flow management under a smart grid system connected to a hybrid renewable energy system (HRES). The HRES is the combination of photovoltaic, wind turbine, fuel cell and energy storage system or battery. The proposed technique is the execution of the Integrated Harris Hawk Optimization algorithm (IH2OA). Here, Harris Hawk Optimization is the consolidation of crossover and mutation function, hence it is called IH2OA. Moreover, IH2OA is enhancing the voltage source inverter of control signals under the variation of power replace among source and load side. The numerous characteristics are made up of necessary grid active with reactive power variations created under the view of available power source. The IH2OA method ensures the location of control signals using parallel implementation as opposed to active with reactive power variation. In the IH2OA method, the control scheme-based optimizes the power controller under the power flow variation. The proposed system performed on MATLAB/Simulink platform and the efficiency are compared with diverse existing techniques.

Comprehensive power swing detection by current signal modeling and prediction using the GMDH method

Power swing is an undesirable variation in power flow. This can be caused by large disturbances in demand load, switching, disconnection or reclosing lines. This phenomenon may enter the zones of distance relays and cause relay malfunction leading to the disconnection of healthy lines and undermining network reliability. Accordingly, this paper presents a new power swing detection method based on the prediction of current signal with a GMDH (Group Method of Data Handling) artificial neural network. The main advantage of the proposed method over its counterparts is the immunity to noise effect in signals. In addition, the proposed method can detect stable, unstable, and multi-mode power swings and is capable of distinguishing them from the variety of permanent faults occurring simultaneously. The method is tested for different types of power swings and simultaneous faults using DIgSILENT and MATLAB, and compared with some latest power swing detection methods. The results demonstrate the superiority of the proposed method in terms of response time, the ability to detect power swings of different varieties, and the ability to detect different faults that may occur simultaneously with power swings.

Power grid optimization planning based on DG acceptance capability evaluation of hybrid AC/DC transmission system

Under the current background of the ubiquitous power Internet of things and strong smart grid, high-permeability DG is an important feature of the future power energy internet, which may cause problems such as voltage over limit flicker, increased network loss, bidirectional variation of power flow, and increased grid coupling[1-2]. In this paper, the operation state interval set of power system is proposed. Considering the influence of power supply capacity on the system security boundary and stability boundary after the DG is connected to the grid, the influence of the access location of the DG on the power system power quality is qualitatively analyzed. At the same time, on the premise of satisfying the consistency of interaction information between multi-source transmission and distribution system and load[3], the problem is decomposed into the acceptance capacity of power side and the optimization planning of power side. The interval mathematics method is adopted to analyze and calculate the DG acceptance capacity of the power grid, and explores the maximum capacity of DG under the condition of safe operation of the system. It also puts forward the optimization planning method of distribution network based on the improved PSO algorithm Considering the output power interval and load level interval of distributed power supply under any possible scenario, and exploring the hybrid transmission and distribution system optimization planning method from the transmission, transmission and distribution systems. It improves the reliability and flexibility of power grid operation, and provides a theoretical basis for a large number of new energy access, and has an important guiding significance for promoting the large-scale development of new energy.

Protection philosophy for distribution grids with high penetration of distributed generation✰

Distributed Generation (DG) can cause several problems in electrical systems that are not prepared to deal with these new sources: situations such as bidirectional power flow and large variations in short-circuit current values. This article presents changes in the actual distribution systems protection philosophy that intend to make the protection system always work properly and reliably eliminate any short-circuit. Furthermore, it shows that the actual philosophy is inefficient in systems with high DG penetration level and, through modifications in the actual philosophy, using available functions in the protection devices, it is possible to increase the reliability and assertiveness of the protection system for any fault.

An Efficient Hybrid Technique for Power Flow Management in Smart Grid with Renewable Energy Resources

ABSTRACT In this paper, an optimal power flow management of a hybrid renewable energy source (HRES) with a hybrid approach is proposed. Here, the proposed method is the consolidation of Improved Bear Smell Search (IBSS) and Sparrow Search Algorithm (SSA); hence, it is named as IB4SA technique. Here, the IBSS generates the voltage source inverter control signals based on the power exchange variety between the source side and load side. In the proposed work, the Bear Smell Search (BSS) is incorporated by crossover and mutation function, therefore it is named as IBSS. The multi-objective function is designed by the grid needed active with reactive power varieties generated based on the available source power. SSA process guarantees the detection of online control signals using a parallel implementation against active with reactive power varieties. The control method based on the proposed approach improves the control parameters of the power controller under power flow variations. The power flow management of the smart-grid system is controlled using the proposed technique based on variations in the parameters of the source and load side. The proposed technique is responsible for controlling energy sources using both renewable energy sources and energy storage devices, in order to generate the power requirement by the grid. The proposed approach is executed in MATLAB/Simulink work site and the performance is analyzed with the existing approaches. The statistical analysis for Case 1, 2, and 3 using proposed as well as existing approaches are analyzed. In Case 1, using the proposed technique the parameter of Δ I d with mean represents 0.528, median represents 0.512 and standard deviation represents 0.033. In Case 2, using the proposed technique the parameter of Δ I q with mean implies 0.671, median implies 0.656, and standard deviation implies 0.026.

Power Flow Analysis on the Dual Input Transmission Mechanism of Small Wind Turbine Systems

A parallel planetary gear train design is proposed to construct the wind turbine system that has double inputs and one output. The proposed system is flexible for the application, which may use a combination of two rotors, as used for horizontal axis or vertical axis wind turbines. The proposed transmission mechanism merges the dual time varied input wind powers to a synchronous generator. The effect of the gear train parameters on the dynamic power flow variation is modeled and simulated for the proposed wind turbine system. Results indicate the proposed planetary gear train system is a feasible and efficient design for its application to wind turbine systems. The dynamic torque equilibrium equations between meshed gear pairs are employed to analyze the dynamic power flow. The nonlinear behavior of a synchronous generator is also included in the modeling. The dynamic responses of the dual input transmission mechanism are simulated using the 4th order Runge–Kutta method. The study also investigates the effect of system parameters used in this wind turbine system (i.e., the wind speed, the magnetic flux synchronous generator, and the inertia of flywheels) on variations in electrical power output.

Vibration Power Flow of an Infinite Cylindrical Shell Submerged in Viscous Fluids

In the previous investigations of the vibroacoustic characteristics of a submerged cylindrical shell in a flow field, the fluid viscosity was usually ignored. In this paper, the effect of fluid viscosity on the characteristics of vibration power flow in an infinite circular cylindrical shell immersed in a viscous acoustic medium is studied. Flügge’s thin shell theory for an isotropic, elastic, and thin cylindrical shell is employed to obtain the motion equations of the structure under circumferential-distributed line force. Together with the wave equations for the viscous flow field as well as continuity conditions at the interface, the vibroacoustic equation of motion in the coupled system is derived. Numerical analysis based on the additional-damping numerical integral method and ten-point Gaussian integral method is conducted to solve the vibroacoustic coupling equation with varying levels of viscosity. Then, the variation of the input power flow against the nondimensional axial wave number in the coupled system with different circumferential mode numbers is discussed in detail. It is found that the influence of fluid viscosity on the vibroacoustic coupled system is mainly concentrated in the low-frequency band, which is shown as the increase of the crest number and amplitude of the input power flow curves.

A comparison study of two DC microgrid controls for a fast and stable DC bus voltage

DC microgrids are the new trend for renewable energy distributed systems due to their high efficiency and more suitability to new load appliances. However, some problems are still open to discussion as it is an emerging concept. In a DC microgrid, a very important issue consists on an enhanced control of the DC bus voltage. This control should be reliable especially towards power flow variations which can be caused by distributed generation sources or by abrupt load demand. These oscillations are also caused by special load type called Constant Power Loads (CPL) when connected to the DC bus voltage due to the negative impedance they induce between source converter and load side. To overcome the above mentioned problems, this paper investigates two internal types of control in the primary level control to ensure a constant DC bus voltage with good performances firstly when a CPL is connected and secondly when a power flow change occurs from the source side or even the load one. The first control is based on cascaded PI regulators and the second one is a nonlinear control. Both control performances are compared for different load points using PSIM software. Simulation and experimental results are presented and discussed.