Aggregate load modeling in microgrids using online measurements

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.

This article proposes a unified controller for Cuk converter assisted variable speed wind turbine driven self-excited induction generator (SEIG) in dc nanogrid configuration for rural electrification. Cuk converter assisted SEIG based wind energy conversion system (WECS) is considered as a master source in the proposed nanogrid, which operates in both grid-connected and islanded mode of operation. In grid connected mode, the system operates in maximum power point tracking (MPPT) under varying wind velocity. A single sensor, modified perturb and observe (P&O) MPPT algorithm, which is independent of the generator parameter is developed and implemented through Cuk converter. During a fault, the WECS necessitates to operate in islanded mode with voltage regulation to supply the local loads continuously. The unified control strategy is developed for selecting the mode of operation, which are MPPT and voltage regulation in grid-connected and islanded mode, respectively. Harmonic spectrum analysis is carried to justify the selection of diode bridge rectifier over semicontrolled/controlled rectifier. The effectiveness and feasibility of the proposed system is verified by means of MATLAB/Simulink. To demonstrate the operational capability, a laboratory scaled prototype is fabricated and tested under various dynamic scenarios.

RETRACTED: Robust-based risk assessment of buildings in resiliency and self-scheduling operations for coordinated vehicle-to-home and renewable resources

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%.

The load model and its parameters have great effect on the accuracy of power system simulation. This paper proposed a method of real-timely collecting load data based on intelligent measuring equipment, charring out the bottom-up accurate modeling of power load under cyber physical system (CPS) environment. Using intelligent measuring equipment as online measurement and identification device, identified load model on different voltage levels based on online load data, and established the aggregated load model using the weighting-mean method based on the capacity. Finally, considering the distribution system parameter, established the integrated load model of 220/110kV bus by gradually converting. Proposed method can realize real-time dynamical update of power load model, and improve the accuracy of power system simulation. Simulation indicated that the load model obtained by proposed method can better reflect the load dynamic characteristics compared to the traditional overall identification method.

The existing distributed operation schemes for microgrids lack the ability to determine the power selling to the grid during normal operation mode and are unable to provide service reliability to critical loads, during islanded operation mode. In order to overcome these issues, in this study, we have proposed a distributed operation method for both grid-connected and islanded modes of microgrids. Unlike the existing studies, where the utility grid is considered as a dispatchable generator, the bi-directional flow of power with the grid is considered in this study. Similarly, different load agents are considered for different priority loads to assure the service reliability to the critical loads during islanding. A two-step operation method is proposed for both grid-connected and islanded mode operations. During the first step, each agent in the network shares information with its neighboring agents to determine the total load and available renewable power in the network. Whereas, in the second step, each agent in the network determines the optimal operation points based on the local information received from the neighboring agents. Moreover, a modified cost function for the battery is also proposed in this study, which utilizes the information of market price and load to enhance the battery operation. A comparison is made between the centralized method, conventional distributed method, and the proposed distributed operation method. Simulation results have proved the effectiveness of the proposed method for realizing distributed operation for microgrids in both grid-connected and islanded modes.

A novel hybrid control strategy for energy storage (ES) is applied in accordance to the recommendations by the IEEE Std. 1676. The strategy mainly consists of the model predictive controller (MPC), two-degree of freedom algorithm and modified droop control. In inverter control layer, MPC and two-degree of freedom algorithm are adopted to construct a generalized controller to enable ES operate in microgrid grid-connected and islanded operation modes with a single control structure, motivating the smooth transition between microgrid operating modes. And MPC and two-degree of freedom algorithm are used in the control layer’s current inner loop and voltage outer loop, respectively. Comparing with the traditional double loop control from the perspective of structure, with the novel strategy the control layer’s current inner loop is without pulse width modulation (PWM) and only a single proportional-integral (PI) controller is applied in its voltage outer loop, so that ES’s robust performance can be enhanced. And because of the high frequency inverter’s equivalent transfer function with the smaller time constant, MPC’s transfer function approximated as being unitary. Therefore, when the two-degree of freedom algorithm construct the inverse model for the controlled object in control layer’s voltage outer loop, from the application layer perspective, the control layer can be recognized as unity gain. Thus, the control layer’s harmful disturbances associated with the operation mode transitions can be removed. In the application layer, through adding decoupling inductance and introducing microgrid’s voltage and angular frequency feedforward compensations to carry out PQ and modified droop controls, the grid-connected and island control targets of ES application layer can be realized. In particular, when microgrid operation mode is switched to island, with the help of modified droop control, microgrid’s voltage and frequency can be quickly restored to standard values. Through the theoretical derivation and simulation results, it can be proved that under microgrid’s plan or non-plan operation mode switching, the proposed method can not only can not only implement the microgrid smooth switching, but also strengthen its transient performance.

Coordinated Control Strategy for Microgrid in Grid-Connected and Islanded Operation

This study aims to analyze the optimal settings of directional overcurrent relays (DOCRs) for the protection of an alternating current (AC) microgrid in both islanded and grid-connected operation modes. In this context, two different types of objective functions are used for comparing the total operating time of all primary DOCRs. The optimal settings obtained in either mode of the microgrid are different due to the variable magnitude of fault currents. The proposed protection coordination scheme is formulated as a mixed-integer non-linear programming problem, and the settings are obtained using various optimization techniques such as firefly algorithm, simulated annealing algorithm, and genetic algorithm. The results show that the settings obtained in common operation modes are robust as no miscoordination of relays occurs in any of the operation modes.

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.

Battery energy storage system (BESS) is the key element to integrate a distributed generation (DG) unit into a microgrid. This paper presents a microgrid consisting of singlephase photovoltaic (PV) arrays which function as the primary DG units and a BESS to supplement the intermittent PV power generation and demand variations in the microgrid. An energy management system is proposed to coordinate the operations of the microgrid during grid-connected and islanded modes of operation. The BESS is incorporated into the microgrid to deal with power imbalance and peak load demand during grid-connected operation and to compensate for any power shortage during islanded operation. The controller design for the voltage source inverter employs a model predictive control (MPC) algorithm which enables faster dynamic response. MATLAB/Simulink is used to simulate the proposed microgrid under different test scenarios. The simulation results show that the operations of the BESS in the microgrid can be coordinated effectively using the proposed control system to ensure stable operation of the overall microgrid.

<p>Load modeling is an important task in power system stability analysis and control. Taking this into account, the development of dynamic load models using a measurement-based load modeling strategy and an improved particle swarm optimization algorithm is presented in this paper. To accomplish this objective, a measurement-based parameter estimation method is used for identification of an exponential recovery load model. Measurements are obtained performing dynamic simulation of an IEEE 30-bus test system under several disturbances, and additionally, cross validation technique is applied for an analysis of load model generalization capability. An adequate load modeling improves the comprehension of load behavior and the capability of reproduce transient events on power systems.</p>

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.