Improved representation of power system load dynamics using heuristic models

The behavior of the load model in power system stability studies has been shown by various investigators to be a very important factor in determining the stability of power system elements. Load models which are presently available in typical stability programs make it difficult if not impossible to model the actual dynamics of power system load. Present load models allow easy static representations, but require detailed individual dynamic models such as induction or synchronous motor models. Thus a simple load model that can represent power system composite load dynamics will be a valuable tool in the stability study Presented herein is a second order state space load model which can represent power system composite load dynamics. In addition, the parameters of this state space load model can be identified from actual system load measurements by a weighted least squares parameter identification process. Several authors recognized the significance of load behavior to changes in voltage as long as 25 years ago. However, most of the attention in stability studies has been directed toward improved generator and control system models. Until recently, little modeling has been considered necessary for power system loads since the effects of load models in stability studies were considered only secondary. At present the load representation in typical stability programs is limited to a static load model where the load is represented as constant MVA, constant current, constant impedance, or some combination of the three.

Monitoring power quality events that occur in a power grid and determining their causes are important in terms of taking preventive actions. Power quality events are generally caused by structural changes in the network. Network loads are also affected by power quality events as a part of the network or they may cause power quality events themselves due to a sudden change in their structure. In this respect, when a power quality event occurs, the estimation of the behavior of the network loads contributes to the determination of the causes of the power quality events. In this study, a new method is developed to identify the parameters of a composite load model to estimate the response of network loads to certain power quality events. The method identifies model parameters using the voltage sag or swell data. By this model, it is possible to estimate the response of the loads and detect whether there is a change in the load. In this way, it becomes easier to understand whether the event is caused by the load or the network, which eventually helps us find the causes of power quality events. Simulation studies show that the load parameters identified by the method using a voltage sag are close to the actual load parameters, and the load behavior estimated by the load model in case of any power quality event is very close to the real load. Cite this article as: M. Karadeniz, M. T. Aydemir & S. Ayasun. Online parameter identification of a simplified composite load model by voltage sag events.Turk J Electr Power Energy Syst, 2022; 2(1): 21-30.

The time-varying parameter identification of load models has attracted broadly attention when large amounts of intermittent distributed generations (DGs) and stochastic loads are integrated in active distribution network (ADN). However, in traditional time-varying parameter identification approaches, the load model is usually developed with the composite load model (CLM) or synthesis load model (SLM), which are not suitable for representing the dynamics of DGs. Moreover, the plateau phenomenon and the continuous low-quality data further reduce the performance of traditional load models with time-varying parameter. Therefore, to address these issues, a novel time-varying parameter identification approach with extended Kalman filter (EKF) is designed for the load modeling. To represent the behavior of modern loads, an improved load model contains a parallel SLM and voltage source converter (VSC) is developed. Then, the target parameters, whose changes produce larger variations in model outputs, are selected with trajectory sensitivity to avoid plateau phenomenon. Also, the Chi-square test and the proposed weighted suppression strategy are utilized to suppress the continuous low-quality data. The simulation results on a system-level ADN model show that the proposed approach could accurately identify the parameters of time-varying load models.

This paper presents the results of composite load model validation based on the distribution-level micro- phasor measurement unit (PMU) measurements. The actual micro-PMU measurements from the distribution feeders are collected by Lawrence Berkley National Laboratory (LBNL). The composite load model parameters are initially generated using the load model data tool developed by Pacific Northwest National Laboratory (PNNL). The generated load models are calibrated to match the performances with the micro-PMU measurements using disturbance records “play-in” capabilities available in GE PSLF simulation package. A trial-and-error approach based on engineering judgement is proposed in this paper to benchmark the generated load model parameters and is implemented in the prototype of load model validation tool, which would be a supplement to the load model data tool.

A methodology for measurement-based load modeling based on integrating dynamic models is presented in this paper. A composite load model (CLM) and an exponential recovery load (ERL) model are combined and used as a model structure for load representation coupled with a heuristic criterion. An improved particle swarm optimization (IPSO) algorithm that considers a speed update modification to enhance its global search capabilities is used to identify the model's parameters. Several simulations are performed in two test systems, using load response measurements after small and severe disturbances, considering noise measurement to simulate monitoring devices. Results verify that the proposed load model has a better performance than the individual load models, and also IPSO algorithm is adequate for parameter identification.

while it has been widely accepted that the constant P-Q leads to conservative load margin calculation of voltage stability, lately the studies show that induction motor loads can lead to an even more conservative load margin calculation. This paper analyzes the impacts of the composite load model (the composite of ZIP and induction motor load models) on the load margin of voltage stability. In order to take into consideration the composite load model, a new set of parameterized power flow equations is derived. A procedure of integrating the composite load model is integrated into CPFLOW to model the load increase. Numerical studies on test system are conducted and numerical results indicate that the load margin with the composite load model can be significantly less than that with the constant P-Q load model. These numerical results are contradicted to the belief that the constant P-Q leads to conservative load margin calculation of voltage stability.

Load model has significant impact on power system simulation. Current load modeling approaches are inadequate on revealing the accuracy and time-variation of load compositions. The application of wireless sensors dispersed in power distribution networks provides further opportunities for load modeling. In this article, a data-driven online aggregated load modeling approach is proposed systematically. First, all the electricity consumers are clustered according to big data of power consumption behaviors. In each cluster, typical users are designated to stand for the characteristics of the cluster, and intrusive measurement is adapted to capture these typical users’ time-varying information by employing wireless intelligent terminals, which can identify the composition of static load and induction motor load online. Second, the load models of other users in each cluster are assumed identical to typical users, including static impedance–current–power models and induction motor models. Finally, the composite load model is achieved by hierarchical aggregation and bottom-to-up stepwise equivalence. Simulations demonstrate that the load model built by proposed approach reflects higher accuracy and adaptability in power system.

In this paper, a new generic composite load model structure for industrial facilities is proposed, which consists of four main loads, an induction motor, a synchronous motor, a motor drive system, and a static load. This structure can be applied to existing or future industry facilities. Major factors to be considered when developing this new composite load model are demonstrated. To achieve the final composite load model for an industrial facility of interest, a two-step procedure is recommended in this paper. Step 1 is to create a power system full model for existing or future industrial facilities. In this step, the full model for existing facilities can be created with the known system configurations and electrical single-line diagrams; while the full model for future industrial facilities with unknown system configurations can be created using the template-based load modeling technique. Step 2 is to perform effective load aggregation in order to obtain a simplified equivalent load model in the format of the proposed composite load model structure for industrial facilities.

This paper is a test case study based paper. In this paper, line indices-based approach is utilized for testing the effect of various load models on estimation of maximum acceptable load at weak bus of a particular power system. It has lot of importance for the voltage stability analysis. Based on result analysis, most preferable load at a bus or substation is also identified. Different exponential-type load models and composite load models are considered in this work. The change of weak bus voltage and maximum load for various load models are analyzed. Each line loss and total loss in the system for different load models are also analyzed. Methodology of this work is implemented on standard IEEE 14 bus test case system. All the simulations of this work are implemented in MATLAB 2019a.

Efficient identification of critical load model parameters affecting transient stability

This paper presents an update on the load model development undertaken by the utilities and grid operators in the Western Electricity Coordinating Council (WECC). The paper describes the driving forces for accurate load modeling in WECC. The structure of the proposed composite load model is presented. The paper also discusses the need for special modeling of compressor motors in single-phase air-conditioners and refrigerators. The paper describes the data requirements for the new composite load model and outlines the structure of the load model data tool. The issues related to load model validation are discussed. Finally, the paper provides expectations of the impact that the load model will have on the system performance studies

The WECC Composite Load Model (CLM) is one of the most comprehensive load models used in transmission system dynamic studies. It is expressed by numerous parameters representing an aggregated load. The default parameter values of the CLM cannot always properly represent the distribution system. In this paper, a systematic method for determining the values for the parameters affected by the load composition and configuration of a distribution system is described with the aid of the Combined Transmission-Distribution System (CoTDS) modeling method. Since the CoTDS model considers the detailed behavior of the loads in the distribution system, it serves as a guiding tool to tune the CLM parameters. Simulation of several test cases are performed using a WECC 9-bus transmission system with a 160-node distribution system feeder. The results demonstrate the effectiveness of the proposed method to properly represent the distribution system in the CLM.

Distributed resources (such as wind turbines) can provide power to local loads in the electrical distribution system as well as benefits such as improved reliability. As more wind energy is connected to utility systems, it becomes important to understand and manage the impact of wind generation on system operations. This paper studies the impact of wind generation on load modeling of distribution network based on MATLAB simulation tools and theory of measurement-based method. It is pointed out that the synthetic load of distribution network including wind generation can be described by the generalized composite load model of asynchronous machine in parallel with static load. In order to exactly reflect the influence of wind generation on composite load model, the value of proportion of dynamic load must be extended to any real number. The validity of this composite load model with any proportion of dynamic load is testified by modeling of three typical operation styles under different capacity proportions of wind generation and load level in this paper.

This paper proposes a new method for measurements-based modeling of nonlinear loads in power systems. This method includes a combination of a binary tree algorithm with Nonlinear Auto-Regressive with Exogenous Input (NARX) identification. The paper demonstrates that the new method performs well without any prior knowledge of the system structure. In contrast to other load modeling methods, which are typically aimed for particular studies or load types, the proposed method can be used with any load type and for any study. Accurate load modeling is particularly important for studies of industrial networks and grids. In this study, a field data set was collected in a mine site from a large electrical rope shovel. This data set has been used to develop a model of the rope shovel based on the proposed binary tree — NARX algorithm. When compared to other known methods, such as Wavelet and Sigmoid networks, the proposed method has shown the fastest training time and the highest accuracy. Finally, the modeling results have been verified against another set of field measurements from an existing network, and have shown a very good agreement.

Modelling of voltage dependent load is always a current topic due to existence of an adequate load model is a prerequisite for calculation of steady states and the analysis of transient regimes of power systems. Given that it is important to know the load model parameters, we have performed the measurements in electric power system of Bosnia and Herzegovina (EPS BIH). The main idea is to identify the values of voltage parameters of dynamic load model. Therefore, this paper describes the dynamic load models and the methodology for exponential dynamic load model parameter identification. It also presents the voltage parameters of dynamic load model for a node in EPS BIH and compares them to similar published studies, concluding that the difference in given parameter values is the consequence of local load characteristics.