Dynamic Load Model Research Articles

IMPROVING DYNAMIC STABILITY OF POWER SYSTEMS BY USING AVR, POWER SYSTEM STABILIZER

This paper introduced a sum method for controlling electrical power systems for multi-machines under dynamic loads by using artificial intelligence. This paper includes complete descriptions of the sum methods used to controlling dynamic power system stability through the method of recognizing pattern and proposition of suitable control systems for re-adjusting the machines in power system for unstable cases. PSAT program had been used in analyzing the stability in the power systems. In this paper, the studied power system included dynamic load model, the program gave excellent results in standard time, and the used network consists of 9 bus bars – 4 generators.

Optimal Control Methods for Photovoltaic Enabled Grid With Abnormal Power Loads

This paper proposes two different control approaches to minimize the power loss subject to voltage constraints when photovoltaic (PV) cells are connected to the grid subject to abnormal (unexpected and extremely high) power loads. A dynamic load model is integrated with the DistFlow equations to describe the transient behavior of the real/reactive power, voltage, and loads. Based on this model, the proposed controllers utilize PV inverters to optimize performances of the grid by absorbing/injecting the reactive power. These controllers are particularly efficient to handle unexpected abnormal power loads. For demonstrations, a bidirectional, single branch distribution circuit with extremely high power load is used to test and compare our controllers with existing approaches, including the volt-ampere reactive control scheme specified by the IEEE Standard 1547 and adaptive method. The results show that our controllers indeed reduce the power loss compared with other methods and keep the voltage within the desired range.

A Computationally Efficient Method for Bounding Impacts of Multiple Uncertain Parameters in Dynamic Load Models

This paper develops a computationally efficient method to bound the impact of multiple uncertain parameters in a dynamic load model. Load model trajectory sensitivity is first conducted on regional dynamics only (e.g., a large industrial load bus and its model for adequately representing the bus voltage dynamics) to identify critical and correlated load parameters. Systemwide trajectory sensitivity on the entire power system model is then evaluated for this reduced set of parameters, and finally, the impact of multiple uncertain parameters on the representation of power system dynamics is bounded. To reinforce this reasoning, we elaborate on the conceptual meaning of the load model trajectory sensitivity, its implication, and its applicability to the entire power grid analysis. This research also develops a fluctuation index of trajectory sensitivity to effectively rank and select the model parameters based on the impact of their perturbations on the system's dynamic performance. Case studies for the Korean power system demonstrate the validity and efficacy of the developed methods for adequately bounding the uncertainty impacts with reference to the comprehensive time-domain dynamic simulation approach.

Steady-state link travel time methods: Formulation, derivation, classification, and unification

Travel times are one of the most important outputs of transport planning models, especially in a strategic context. It is therefore paramount that the methods that underpin the construction of travel times are well understood. A plethora of methods exists to extract and/or construct travel times given some underlying network loading procedure, also known as the traffic flow propagation model. However, the relation between these different travel time methods and the consistency between such methods has received relatively little attention in the literature. This might in part be due to the many different traffic flow propagation models in existence, ranging from vehicle based (microscopic), to flow based (macroscopic), and models that explicitly account for the time varying nature of traffic flows (dynamic) to models that do not (static). In this work, we limit ourselves to flow based, i.e. macroscopic, traffic flow models. Within this modelling paradigm we consider dynamic, semi-dynamic, and static traffic flow propagation formulations used to construct link travel times. The semi-dynamic and static approaches are considered as more aggregate versions of the dynamic formulation. Within this context we formulate a unified (link) travel time formulation that is consistent across these three modelling paradigms under the assumption of steady-state flow conditions. The dynamic link travel time formulation is based on a recent state-of-the-art continuous time macroscopic dynamic network loading model. In the dynamic model we assume steady-state conditions to remain consistent with steady-state semi-dynamic and static approaches. This allows us to derive semi-dynamic link travel time formulations from our dynamic model, while the static formulation is derived from its semi-dynamic counterpart. Throughout this work we explore link travel times from three different perspectives; an experienced perspective, which actively tracks the tail of a physical queue, and two functional perspectives, both of which do not require explicit queue tracking. Based on the existing literature and proposed formulations, a classification framework is proposed allowing one to compare existing (and future) methods in the literature in an objective fashion. We provide a number of explicit derivations of existing model formulations that can be considered special cases of our unified approach. A numerical example across the different perspectives is included and a significant number of representative existing methods in the literature has been classified based on our proposed framework for the reader's convenience.

Dynamic ice contact load model for azimuthing thrusters

ABSTRACTFor ships operating in winter conditions, ice loads are important load scenarios for designing azimuthing main propulsion units. One such contact scenario is ice impacting into an azimuthing thruster. In this paper, the formulation of this type of load scenario is presented and existing calculation methods are investigated. A calculation method for dynamic contact load is proposed for ice impact against the main propulsion unit. The basic principle of the proposed load calculation method is an impact of moving bodies combined with dynamic reaction of the structure. The contact load determination is based on the contact pressure–area relationship between an ice block and a steel structure. The dynamic contact problem is solved with a forward difference method. The method is validated with a controlled laboratory-scale test and the test principle is introduced. The dynamic load model is applied to study the effect of dynamics on the response load level.

Bayesian Estimation on Load Model Coefficients of ZIP and Induction Motor Model

Parameter identification in load models is a critical factor for power system computation, simulation, and prediction, as well as stability and reliability analysis. Conventional point estimation based composite load modeling approaches suffer from disturbances and noises, and provide limited information of the system dynamics. In this work, a statistics (Bayesian Estimation) based distribution estimation approach is proposed for both static and dynamic load models. When dealing with multiple parameters, Gibbs sampling method is employed. The proposed method samples all parameters in each iteration and updates one parameter while others remain fixed. The proposed method provides a distribution estimation for load model coefficients and is robust for measuring errors. The proposed parameter identification approach is generic and can be applied to both transmission and distribution networks. Simulations using a 33-feeder system illustrated the efficiency and robustness of the proposal.

Queue Spillback and Demand Uncertainty in Dynamic Network Loading

In the field, queue spillback contributes substantially to urban congestion. Therefore, most dynamic network loading models either explicitly include spillback, or frame a failure to model spillback as an unfortunate consequence of mathematical or computational tractability that should be relaxed in future work. Although models with spillback are undeniably more realistic, they are also less robust to errors in input demand. We show that when there is high uncertainty in input demand, excluding spillback can actually reduce error by reducing sensitivity to demand errors. Our demonstrations include a small network that can be solved analytically, and dynamic user equilibrium on two real-world networks representing Austin, TX, and San Antonio, TX. We conclude that model realism must be carefully balanced against the accuracy of the input parameters, and the sensitivity of the model to any such errors in these inputs.

Decentralized model predictive hierarchical control strategy for islanded AC microgrids

This paper presents decentralized Model Predictive Control (MPC) based hierarchical control scheme with both primary and secondary level for an islanded AC microgrid to address power quality and unequal power sharing problems. The control scheme consists of an inner control loop, primary control and secondary control. Finite Control Set-Model Predictive Control (FCS-MPC) is incorporated in the inner loop to track the reference voltage and fix the capacitor voltage in each Distributed Generator (DG) unit. Primary control comprises of virtual impedance loop and droop control to control power flow and power sharing among DG systems. Moreover, state space predictor based secondary control is proposed for regulating frequency of the microgrid and node voltage to their nominal values in islanded operation. Furthermore, the performance of the proposed control method is analyzed with the static model of dynamic loads and validated with conventional control scheme under mismatched feeder impedance.

Reservoir-based surrogate modeling of dynamic user equilibrium

Abstract This paper proposes a new dynamic user equilibrium (DUE) traffic assignment model using reservoir-based network reduction techniques and surrogate dynamic network loading models. A traffic network is decomposed into a reservoir structure, and the DUE problem is formulated as a variational inequality, with an embedded surrogate model for the path delay operator to describe traffic dynamics at the reservoir level. The surrogate model is further enhanced by the reproducing kernel Hilbert space and adaptive sampling to reduce approximation error and improve computational efficiency. To solve the proposed surrogate-based DUE problem on reduced networks, we develop a customized algorithm that integrates the kernel trick with the generalized projection framework. A pre-computation scheme is proposed, which calculates and stores the of kernel matrices and vectors, could further reduce the computational burden. Numerical experiments of the proposed methods show significant reduction of the computational times, by up to 90 % , while maintaining low approximation errors (MAPE below 6 % ), when compared to the exact models and solution methods.

A general formulation for multi-modal dynamic traffic assignment considering multi-class vehicles, public transit and parking

Travel behavior and travel cost in modern urban transportation systems are impacted by many aspects including heterogeneous traffic (private cars, freight trucks, buses, etc.) on roads, parking availability near destinations, and travel modes available in the network, such as solo-driving, carpooling, ride-hailing, public transit and park-and-ride. Managing such a complex multi-modal system requires a holistic modeling framework of transportation network flow in terms of both passenger flow and vehicular flow. In this paper, we formulate and solve for spatio-temporal passenger and vehicular flows in a general multi-modal network explicitly considering multi-class vehicles, parking facilities and various travel modes. Vehicular flows, namely cars, trucks and buses, are integrated in a holistic dynamic network loading (DNL) models. Travel behavior of passenger demand on modes and routes choices is encapsulated by a multi-layer nested logit model. We formulate the multi-modal dynamic user equilibrium (MMDUE) that can be cast into a Variational Inequality (VI) problem. A closed-form flow solution based on the gradient projection is proposed and proven to efficiently solve for the VI problem on large-scale networks. Numerical experiments are conducted on a multi-modal network in the Pittsburgh region along with sensitivity analysis with respect to demand and management strategies. We show that many factors including total passenger demand, parking prices, transit fare, ride-sharing impedance can effectively impact the system performance and individual user costs. Experiments on a large-scale multi-modal network in Fresno, California also show our model and solution algorithms have satisfactory convergence performance and computational efficiency.

Runners on footbridges – a newVGRFmodel for heel strike running technique

In the paper the models of dynamic forces generated by people running referred to two running techniques i.e. forefoot strike running and heel strike (rearfoot strike) running are presented. The model of forces generated during forefoot strike running was refined taking into account proposals of various authors and the results of author’s own laboratory tests of running people. The model of the forces generated during heel strike running is a new author’s proposal elaborated on the basis of the results of laboratory tests. Presented results of analyses and the proposal of a new dynamic load model correct and complement the shortcomings of the existing models and complement the shortage of recommendations in the area of dynamic forces generated during heel strike running technique.

Using Recurrent Procedures in Adaptive Control System for Identify the Model Parameters of the Moving Vessel on the Cross Slipway

The article analyses the problems connected with ensuring the coordinated operation of slipway drives that arise during the launch of a ship. The dynamic model of load of the electric drive of the ship’s cart is obtained taking into account the peculiarities of the construction of the ship-lifting complex, which allows us to analyse the influence of external factors and random influences during the entire process of launching the ship. A linearized mathematical model of the dynamics of a complex vessel movement in the process of descent in the space of states is developed, which allows us to identify the mode of operation of the multi-drive system, taking into account its structure. The analysis of application efficiency of recurrent methods for identification (stochastic approximation and least squares) of the linearized model parameters in the space of states is carried out. A decision support system has been developed in the automated system of operational control by the module for estimating the situation and the control synthesis to ensure a coherent motion of a complex ship-carts object in a two-phase environment.

Artificial neural network–aided technique for low voltage ride-through wind turbines for controlling the dynamic behavior under different load conditions

At the level of the electrical distribution networks with wind generation, the disturbances may influence the voltage stability, particularly during low voltage ride-through wind turbine. This research is concerned with studying the effect of implementing different controllers and load types on the low voltage ride-through dynamic recovery performance during disturbances. A conventional proportional–integral–derivative controller is compared with the artificial neural network–based one. The controller construction and its gain are proposed for each type of controller and the impact of each controller on the dynamic behavior of the low voltage ride-through is investigated thoroughly under various operating conditions. Also, the dynamic performance of wind generators is examined with low voltage ride through and different dynamic load models. Both, dynamic induction motor load and composed static and exponential recovery load models are considered. In case of dynamic induction motor load, the effect of the inertia constant has been studied under two types of controllers. The overall system model is simulated using PSAT/MATLAB software in such a way that it can be suited for modeling of voltage controller and loads configurations. The low voltage ride-through performance has been changed with different controllers and load types.

Finite Element Analysis of R.C Beams Using Steel Scraps Under Cyclic Loading Using ETABS

In the modern trend peoples are looking for alternate material which is cost effective and high stability in while subject to dynamic loading. Considering this as one of the factor in our proposed we choose steel scrap as reinforced material which has high durability and strength. To find out the withstanding capacity of the dynamic loading model the structure using finite element software and analysis to predict the safety of the structure. From the analysis result we conclude for preventive measure of the structural failure and utilization of extra dampers has find out. To validating the result, analytical work is carried out and implemented by using ETAB software.

A macroscopic dynamic network loading model for multiple-reservoir system

In this paper, we present a dynamic network loading (DNL) model that captures the traffic dynamics for multiple-reservoir networks dependent on the relationship among macroscopic traffic characteristics, and develop a numerical method based on the Godunov scheme. The proposed DNL model consists of link model and node model. The traffic dynamics of the internal paths in a reservoir are specified by a system of Lighthill–Whitham–Richards-like partial differential equations, which build on the conservation law, while the flows at the boundaries between reservoirs are determined by the supply–demand balances between upstream and downstream reservoirs. A novel numerical method is developed based on the Godunov scheme to track the movement of vehicles in the network while maintaining the relevant priority rules. In comparison with previous approaches, the proposed numerical scheme is computationally efficient, considers the non-uniform cell sizes inherent in different internal paths within a reservoir, and conserves the flow through holding and balancing rules. Numerical experiments indicate that the proposed methodology can describe the dynamics of vehicles in large-scale traffic network efficiently.

Managing congestion and emissions in transportation networks with dynamic carbon credit charge scheme

Traffic congestion contributes to the air pollution problem due to the increased idling, braking and acceleration behaviors. This research puts forward an optimal dynamic credit charge scheme that can redistribute the traffic flows to attain mobility and emission goals. First, cell transmission model is used as dynamic network loading model to capture the flow propagation and dynamic user equilibrium (DUE) is formulated to investigate the flow redistribution in terms of simultaneous path and departure time choices under carbon credit charge scheme. Based on that, a bi-level formulation is proposed to describe the Stackelberg game between road manager and road users. For the higher level, road manager seeks to minimize system travel time and emissions by implementing credit charge schemes. For the lower level, heterogeneous users find dynamic user equilibrium by simultaneous path and departure time choices under given credit charge schemes. Given the non-convex property of the bi-level model, this paper proposes the pattern search algorithm embedded with projection method. Computational results on X-shape, Ziliaskopolous’ and Nyguen-Dupuis network are given to show the applicability of the proposed algorithm on reasonable-size networks. Results show that minimum travel time design does not always generate effective path and departure time switches across all user groups, especially for users with high value of travel time, while minimum emissions credit design yields desirable behavioral adjustments. Besides, minimum travel time credit design does not always generate minimum carbon emissions in the network, especially in networks with complex O–D pairs and paths. This research casts light on how to schedule a time-varying credit charge scheme to attain mobility and emission goals. Policy implications of credit charge scheme are provided.

Retirement-Driven Dynamic VAR Planning for Voltage Stability Enhancement of Power Systems With High-Level Wind Power

Conventional VAR compensation devices such as capacitor banks and synchronous condensers, after long periods of service, have become aged and less effective to satisfy stringent requirement of short-term voltage stability in high-level wind power penetrated power systems. STATCOMs with a rapid and dynamic reactive power support capability can be an ideal alternative, when combined with a proper equipment retirement and upgrades scheme. This paper proposes a systematic approach for optimal dynamic VAR resource planning and upgrading for a power system with increased wind power penetration and equipment retirement. The problem is constituted by two parts that are aged equipment retirement and new equipment placement. A multiobjective optimization model is proposed to minimize three objectives: the cost of retirement and upgrades, the index of proximity to steady-state voltage collapse, and the index of transient voltage unaccepted performance. To simulate real-world operating situation, multiple contingencies and uncertain dynamic load models are taken into account. Furthermore, low- and high-voltage ride through abilities for wind farms are modeled. The proposed model is tested on the New England 39-bus test system.

A path marginal cost approximation algorithm for system optimal quasi-dynamic traffic assignment

This study introduces an efficient path-based System-Optimal Quasi-Dynamic Traffic Assignment (SOQDTA) framework that benefits from the computational efficiency of static traffic assignment models, yet captures the realism of traffic flow, with less complexity and a lower computational burden, compared to dynamic traffic assignment models.To solve the proposed SOQDTA problem, we have developed a novel Path Marginal Cost (PMC) approximation algorithm, based on a Quasi-Dynamic Network Loading (QDNL) procedure (Bliemer et al., 2014), that incorporates a first order node model, and thus produces realistic path travel times consistent with queuing theory, and similar to those of dynamic network loading models, but at a lower computational cost. The model considers capacity constrained static flows, residual vertical/point queues and no spillback.The proposed SOQDTA model is applied to the test network of Sioux Falls and is demonstrated to result in system optimal traffic flow patterns that improve total system travel times compared to the user equilibrium solution. In the case study experiment, the convergence of the algorithm is demonstrated using a relative gap function. A sensitivity analysis is performed to realize the impact of perturbation size on the solution quality, and a discussion is presented on the selection of perturbation size for general network applications.

Modeling and Simulation of Railgun System Driven by Multiple HTSPPT Modules

In the rail-type electromagnetic launching system, the equivalent load of pulsed-power supplies (PSs) varies with the launching process, while it has a certain influence on the discharge of pulsed PS. However, in the analysis and design of pulsed PS, researchers usually use the fixed resistance and inductance to simulate the load, which is impossible to accurately study the characteristics of the pulsed PS. The electromagnetic launching needs high-amplitude current pulse. Therefore, in this paper, a mathematical model of electromagnetic launching system driven by multiple superconducting inductive pulsed PS modules is established. In this model, the fixed resistance and inductance load are replaced by the dynamic load model of the railgun; the effects of dynamic load and fixed load on the discharge characteristics are analyzed; the parallel discharge characteristics of multiple high-temperature superconducting pulsed-power transformer (HTSPPT) modules are studied; and the characteristics of the simple rail-type electromagnetic launching driven by multiple HTSPPT modules are analyzed. The simulation results show that a high amplitude of current pulse can be produced using synchronous parallel discharge of multiple HTSPPT modules. The simulation results show that when the resistance and inductance of load are fixed at 2 $\text{m}\Omega$ and 0.5 $\mu \text{H}$ , respectively, the current amplification factor is 15.666, and the maximum voltage of the auxiliary capacitor is 1079 V. In the dynamic load model, the current amplification factor is 17.174, and the error is 9.6%. The maximum voltage of the auxiliary capacitor is 983 V, and the error is 8.9%. Therefore, the discharge characteristics of pulsed PS can be more accurately studied using dynamic models.

A comparative analysis of selected models of pedestrian-generated dynamic loads on footbridges – vertical loads

In the paper the characteristics of selected dynamic load models of vertical forces generated during pedestrian movement (Vertical Ground Reaction Forces - VGRFs) and the results of dynamic numerical analyses and dynamic field tests of an exemplary footbridge were presented. Numerical analyses of the footbridge were performed taking into account recommendations of different authors and standards relating to VGRFs models as well as VGRFs measured by authors during laboratory tests using force platform. For comparative purposes, the dynamic field tests of the footbridge were carried out. The results and conclusions from comparative analyses of the dynamic responses of the footbridge obtained for various load models and field tests were presented.