Dynamic load modeling based on a nonparametric ANN

Not only static load model but dynamic load model is necessary for improving the accuracy of time-domain simulation results because only dynamic load model can express the dynamic response of the load. The measurement based auto-derivation method for estimating load model parameters from PQVF monitoring devices has been developed. The PQVF monitoring device which has already been installed into power system captures disturbance data triggered by voltage deviation and frequency deviation. The transfer-function based load model which consists of voltage characteristics index, frequency characteristics coefficient, transient gain, and time constant was used as the dynamic load model. The simple transfer function-based dynamic load model can express 80% of 182 load responses precisely. Therefore, the transfer function-based dynamic model can have applicability to represent the dynamic behavior of the load response concisely and accurately on condition that the quantity of voltage drop during the disturbance is less than 30%.

This study proposes a novel approach for load modelling fulfilled in Guangdong Power Grid, Southern China. Dynamic load modelling lies on real‐time data provided by load disturbances. These data can be acquired by power quality equipment fixed on each substation. This study introduces the approach to data processing and load modelling during asymmetric disturbance to solve the problems of insufficient inartificial disturbance data. In order to improve the global optimisation capability and identification efficiency in multi‐dimensional function, an improved clone selection algorithm is proposed, which includes adaptive‐adjust Gaussian mutation operators and the directional evolution mechanism, and also using the character of parameters independence between induction motor model and ZIP model referring to the third‐order induction‐motor paralleling ZIP model in BPA. The results of practical load modelling prove that the proposed algorithm has great effects on improving model precision and adaptability. Finally, the influences on power angle, frequency, voltage and power between dynamic load model and ZIP are discussed.

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.

The importance of having accurate load models in power system stability studies has been well established in the literature as being essential for precise power system transient event investigations. The power industry presently uses composite load models in typical stability programs (e.g. LOADSYN and PSS/E). However, the parameters of the composite load models need to be tuned for each type of disturbance based on an assumed load composition, and are often inadequate for matching the modeled dynamics of the power system disturbance event to actual measured results. A stochastic time series technique in the form of an ARMAX mathematical model is presented in this paper as a novel alternative for dynamic load modeling. The model parameters are estimated using on-line measurement data for a number of disturbance events, collected from five substations in the Victorian electricity network in Australia. The performance of the model is then evaluated for other transient events, and compared against the recorded response for these events. The results achieved show that this heuristic-based model is robust and effective in predicting the dynamic response of a power system load across a range of events spanning various seasons and locations.

Microgrids suitable operation depends on the system's proper design, based on accurate component models. A complete model considering entire system dynamics is a vital necessity for a successful design. Using dynamic load in microgrid small‐signal model results in a model that shows transient and steady‐state dynamics, since designing a low‐inertia system like microgrid need extra accuracy. In this paper, an inverter‐based microgrid's small‐signal model in islanded operation mode containing a dynamic load model has been achieved. The Exponential Recovery Load (ERL) model is presented here to study the dynamic behavior of load. Microgrid stability analysis has been carried out for both static and dynamic load models. To attain this goal, the entire component equations are obtained and linearized around an operating point, then the state‐space model is formed and eigenvalues are derived. System stability condition has been investigated by plotting eigenvalues and root locus method. In the final step, a simulation on Matlab/Simulink is performed to show the microgrids operation in the presence of a static and dynamic load.

In a large-scale transmission network, such as the European power system, the regional characteristics of electrical demand may have an impact on local voltage stability. The dynamic load behaviour depends on the sectoral composition of demand, which is subject to regional and seasonal variation. An aggregate load model is presented, which accounts for the sectoral characteristics of 210 European regions for all hours a year from the perspective of the high, medium, and low voltage levels. The proposed load model is used to better understand the influence of regional characteristics on voltage recovery during a short-circuit event, as well as the static point of voltage collapse. Several countries are considered in terms of their sectoral composition, to represent intermediate regions or such dominated by the industry and households. Moreover, the dynamic load model is benchmarked against two static load models, assuming a constant power (PQ) load or a constant impedance (Z) load. The conducted study demonstrates that regional differences in the composition of demand highly impact local voltage stability.

Online measurements can be used for aggregate load modeling, taking advantage of the advent of smart grids. In this paper initial load modeling results are presented using measurements recorded in a laboratory scale microgrid. The examined microgrid configuration includes a load bank and an adjustable speed drive. A methodology for the identification of the model parameters from measurements is presented and the performance of a static and a dynamic load model is investigated in grid-connected and islanded operation modes. Numerical studies indicate that the dynamic model behaves satisfactorily enough in both modes of operation, while the static model can only be used in the islanded case. Generic load models suitable to simulate the real and reactive power for a wide range of load disturbances are proposed and their accuracy is evaluated using the cross-validation technique.

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.

In this paper, a generic load model is presented, suitable for dynamic simulations over a wide range of loading conditions. The proposed model is based on the well-established exponential recovery load model. Contrary to the conventional first-order form of this model, the proposed formulation employs variable-order transfer functions, enabling the accurate simulation of high-order load dynamics. A complete methodology is proposed for the identification of the required load model parameters from real field measurements. For this purpose, the Vector Fitting technique is introduced for the first time as a method for measurement-based load modeling. Several simulation scenarios are performed using the NEPLAN software to validate the accuracy of the proposed model. Numerical studies indicate that the developed load model captures accurately the load dynamic behavior over a wide range of loading conditions.

As an extension of previous studies on modeling and identification of nonlinear dynamic load models, this letter describes the influence of the normalization in dynamic reactive load models. Using measured data from normal operation, it is shown that the reactive power level, which has previously used as normalization factor is inappropriate. If instead apparent power level is used, the variability in the parameters that describe the reactive load response is drastically reduced.

This paper presents a new method to construct dynamic models for large industrial and commercial facilities commonly connected to power transmission systems. These facilities typically draw large amounts of power and have complex dynamic responses to power system disturbances. Traditional load modeling approaches such as those based on load composition or site measurement are not adequate to produce dynamic models for such facilities. In this paper, a facility template based load modeling technique along with template scaling/equivalence algorithms is proposed to solve the facility modeling problem. Oil refinery facilities are used as an example to illustrate the proposed modeling technique. The technique requires minimal user input and can be implemented in a database program.

This paper presents an adaptive wide-area control strategy based on energy function. The proposed method enhances the post-fault oscillation damping capability of Static Var Compensators (SVC) by incorporating load dynamics in the wide-area controller design that adapts to load variations. The load dynamics are obtained using Phasor Measurement Units (PMU) through load power and voltage data measurements, which are used to estimate a Moving Average (MA) dynamic load model. The obtained load model is then integrated into the wide-area controller to obtain the required SVC supplementary control action which modulates the load power in response to a disturbance based on inter-area dynamics obtained by employing a nonlinear Kalman filter and PMU measurements. The performance of the proposed strategy is evaluated on the simplified 14 generator model of the southeast Australian power system by using composite load models comprised of induction motor loads of various sizes and combinations. The obtained results show significant improvements in the system stability when the proposed control strategy is applied.

With the addition of new distributed energy sources, a new and more accurate load model need to be established. Based on MATLAB/Simulink, this paper researches on the modeling and simulating of photovoltaic power generation system and battery energy storage and their equivalent model. First, a detailed model of the photovoltaic system is built. Boost circuit and MPPT control are selected on the DC side of photovoltaic power generation system. The double closed loop control method of current internal loop and external voltage loop is used for grid inverter control. The model is improved considering the capability of LVRT (low voltage ride through). Based on the above precise models, the model is equaled. The equivalent transfer function is calculated by the grid connected control loop, so the model is simplified. The battery energy storage module establishes a general mathematical model based on the charging and discharging principle. Charge and discharge are controlled through the DC/DC converter. And it is connected to the power grid after inverting and filtering. The common PQ control are selected in the inverter control mode. According to the same principle, the energy storage model is equaled. Finally, based on the traditional load model, the above load model is added to set up a new generalized integrated load model. And the actual model is replaced to build up an equivalent model. The equivalent model is compared with the actual model to verify the equivalent description ability.

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.

The PSS (Power System Stabilizer) is a low cost method to stabilize the inter-tie and local oscillations of power network. The PSS's parameters are usually adjusted for the one-machine infinite-bus system model. On the contrary, the real power systems consist of multi machine systems. Then, the PSS parameters coordinated setting considering the real characteristics of the power system network is expected to improve the stability. For this purpose, the MPM (Modal Performance Measure) method is applied for adjusting PSS parameters. The power network mathematical model that is required for this calculation is given by the system identification method. Utilizing the MPM method characteristics, the restrictions such as damping coefficient and maximum gain that are practical design specifications used for conventional controllers, are naturally introduced. Furthermore, RBF (Radial Based Function) frequency weighing is introduced for adjusting frequency responses. The favorable results as expected are obtained by the large scale power system simulations.