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Load modeling—A review
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 …
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
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 …
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
Due to the increasing penetration of distributed energy resources (DERs), the load
composition in distribution grids has significantly changed. This inverter-based device has …
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
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 …
integration that is impacting the bulk power system planning and operations. Grid regulators …
Dependency analysis and improved parameter estimation for dynamic composite load modeling
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 …
crucial for power system dynamic studies. The WECC composite load model (CMPLDW) has …
Mathematical representation of WECC composite load model
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 …
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
The uncertainty of power resources introduces significant challenges for classic load
modeling approaches. Moreover, load parameter identification techniques are affected by …
modeling approaches. Moreover, load parameter identification techniques are affected by …
Wide-area composite load parameter identification based on multi-residual deep neural network
Accurate and practical load modeling plays a critical role in the power system studies
including stability, control, and protection. Recently, wide-area measurement systems …
including stability, control, and protection. Recently, wide-area measurement systems …
Robust time-varying synthesis load modeling in distribution networks considering voltage disturbances
Uncertain power sources are increasingly integrated into distribution networks and causes
more challenges for the traditional load modeling. A variety of distributed load components …
more challenges for the traditional load modeling. A variety of distributed load components …
Amortized bayesian parameter estimation approach for wecc composite load model
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 …
challenge due to the presence of high-dimension parameters. This paper proposes an …