Development of measurement-based load models for the dynamic simulation of distribution grids

The advent of new types of loads, such as power electronics and the increased penetration of low-inertia motors in the existing distribution grids alter the dynamic behavior of conventional power systems. Therefore, more accurate dynamic, aggregate, load models are required for the rigorous assessment of the stability limits of modern distribution networks. In this paper, a measurement-based, input/output, aggregate load model is proposed, suitable for dynamic simulations of distribution grids. The new model can simulate complex load dynamics by employing variable-order transfer functions. The minimum required model order is automatically determined through an iterative procedure. The applicability and accuracy of the proposed model are thoroughly evaluated under distinct loading conditions and network topologies using measurements acquired from a laboratory-scale test setup. Furthermore, the performance of the proposed model is compared against other conventional load models, using the mean absolute percentage error

An Investigative Study on Impact of Frequency Dynamics in Load Modeling

Load modeling plays a significant impact in assessing power system stability margin, control, and protection. Frequency in the power system is desired to be kept constant, but in a real sense, it is not constant as loads continually change with time. In much literature, frequency dynamics are ignored in the formulation of load models for the basic assumption that it does not affect the models.  In this paper, the composite load model was formulated with Voltage-Frequency Dependency (V-FD) on real and reactive powers and applied to estimate the load model. 2- Area network 4- machines Kundur test network was used for testing the developed model.  The model was trained with measurements from a low voltage distribution network supplying the Electrical Engineering department at Ahmadu Bello University, Zaria. Both training and testing data were captured under normal system operation (dynamics). To evaluate the V-FD model performance, Voltage-Dependent (VD) model was examined on the same measured data. The work makes use of the Feed Forward Neural Network (FFNN) as a nonlinear estimator. Results obtained indicate that including frequency dynamics in modeling active power reduces the accuracy of the model. While in modeling reactive power the model performance improves. Hence, it can be said that including frequency dynamics in load modeling depends on the intended application of the model

Load modeling techniques in distribution networks: a review

Power system operation and control required models of generators, lines and loads to be accurately estimated, this is to enable operators make a reliable decision on the system.  Generators and lines models are so far considered accurate, while load models are considered perplexing due to invention of new types of loads, distribution system are transforming from passive to active. Future distribution systems are desired to be smart and for a network to be smart the system as to be fully and accurately represented. Penetration of renewable energy and application of power electronic devices as well as participation of active customers in distribution systems make traditional methods of load modeling absolute. Accurate load modeling is required to address the new challenges evolving in the task of power system operation, control and stability studies. It is also an interest of power system researchers globally to realize Smart Networks (SNs), in which accurate load models are required. This work described a review of techniques and approaches for load modeling from traditional methods to the state of art in the area. In addition, gaps in the literature as well as research directions are also pointed out

New data-based load modeling for active distribution networks

Electric systems are experiencing fast development, mainly motivated by the carbon reduction policies in the energy sector and the technological developments that introduce new elements and processes. The transition to active distribution networks (ADNs) represents a significant technological advancement in this ever-evolving context. Accurate models for each device present in ADNs are crucial for adequately representing their dynamics; however, load modeling poses challenges due to the vast diversity of load components, variations over time, and dependence on several factors. Despite these challenges, understanding load behavior is fundamental for efficient planning and operation of ADNs. Therefore, precise load models are indispensable for conducting preventive and forensic studies. This paper analyzes various scientific documents from the most relevant scientific databases, explicitly focusing on the challenge of measurement-based load modeling in ADNs. The main contribution of this document lies in enhancing the representation and understanding of loads in ADNs through the analysis of current approaches, challenges, and measurement-based modeling strategies. Additionally, it serves as a reference for future research in the field of load modeling

New data-based load modeling for active distribution networks

Electric systems are experiencing fast development, mainly motivated by the carbon reduction policies in the energy sector and the technological developments that introduce new elements and processes. The transition to active distribution networks (ADNs) represents a significant technological advancement in this ever-evolving context. Accurate models for each device present in ADNs are crucial for adequately representing their dynamics; however, load modeling poses challenges due to the vast diversity of load components, variations over time, and dependence on several factors. Despite these challenges, understanding load behavior is fundamental for efficient planning and operation of ADNs. Therefore, precise load models are indispensable for conducting preventive and forensic studies. This paper analyzes various scientific documents from the most relevant scientific databases, explicitly focusing on the challenge of measurement-based load modeling in ADNs. The main contribution of this document lies in enhancing the representation and understanding of loads in ADNs through the analysis of current approaches, challenges, and measurement-based modeling strategies. Additionally, it serves as a reference for future research in the field of load modeling