Load modeling—A review

A Arif, Z Wang, J Wang, B Mather… - … on Smart Grid, 2017 - ieeexplore.ieee.org
Load modeling has significant impact on power system studies. This paper presents a
review on load modeling and identification techniques. Load models can be classified into …

Two-stage WECC composite load modeling: A double deep Q-learning networks approach

X Wang, Y Wang, D Shi, J Wang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
With the increasing complexity of modern power system, conventional dynamic load
modeling with ZIP and induction motors (ZIP+ IM) is no longer adequate to address the …

WECC composite load model parameter identification using evolutionary deep reinforcement learning

F Bu, Z Ma, Y Yuan, Z Wang - IEEE Transactions on Smart Grid, 2020 - ieeexplore.ieee.org
Due to the increasing penetration of distributed energy resources (DERs), the load
composition in distribution grids has significantly changed. This inverter-based device has …

SMTD co-simulation framework with HELICS for future-grid analysis and synthetic measurement-data generation

AK Bharati, V Ajjarapu - IEEE Transactions on Industry …, 2021 - ieeexplore.ieee.org
The power grid is transforming with large amounts of distributed energy resource (DER)
integration that is impacting the bulk power system planning and operations. Grid regulators …

Dependency analysis and improved parameter estimation for dynamic composite load modeling

K Zhang, H Zhu, S Guo - IEEE Transactions on Power Systems, 2016 - ieeexplore.ieee.org
Dynamic load modeling by fitting the input-output measurements during fault events is
crucial for power system dynamic studies. The WECC composite load model (CMPLDW) has …

Mathematical representation of WECC composite load model

Z Ma, Z Wang, Y Wang, R Diao… - Journal of Modern Power …, 2020 - ieeexplore.ieee.org
Composite load model of Western Electricity Coordinating Council (WECC) is a newly
developed load model that has drawn great interest from the industry. To analyze its …

Probabilistic time-varying parameter identification for load modeling: A deep generative approach

M Khodayar, J Wang - IEEE Transactions on Industrial …, 2020 - ieeexplore.ieee.org
The uncertainty of power resources introduces significant challenges for classic load
modeling approaches. Moreover, load parameter identification techniques are affected by …

Wide-area composite load parameter identification based on multi-residual deep neural network

S Afrasiabi, M Afrasiabi, MA Jarrahi… - … on Neural Networks …, 2021 - ieeexplore.ieee.org
Accurate and practical load modeling plays a critical role in the power system studies
including stability, control, and protection. Recently, wide-area measurement systems …

Robust time-varying synthesis load modeling in distribution networks considering voltage disturbances

M Cui, J Wang, Y Wang, R Diao… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Uncertain power sources are increasingly integrated into distribution networks and causes
more challenges for the traditional load modeling. A variety of distributed load components …

Amortized bayesian parameter estimation approach for wecc composite load model

B Tan, J Zhao, N Duan - IEEE Transactions on Power Systems, 2023 - ieeexplore.ieee.org
Calibrating the composite load model with distributed generation (CMPLDWG) is of a great
challenge due to the presence of high-dimension parameters. This paper proposes an …