Access Type
Open Access Dissertation
Date of Award
January 2019
Degree Type
Dissertation
Degree Name
Ph.D.
Department
Electrical and Computer Engineering
First Advisor
Caisheng Wang
Abstract
ABSTRACT
Analysis and Mitigation of the Impacts of Delays in Control of Power Systems
with Renewable Energy Sources
by
Chang Fu
Apr. 2019
Advisor : Dr. Caisheng Wang
Major : Electrical and Computer Engineering
Degree : Doctor of Philosophy
With the integration of renewable resources, electric vehicles and other uncertain
resources into power grid, varieties of control topology and algorithms have been proposed to
increase the stability and reliability of the operation system. Load modeling is an critical part
in such analysis since it significantly impacts the accuracy of the simulation in power system,
as well as stability and reliability analysis. Traditional power system composite load model
parameter identification problems can be essentially ascribed to optimization problems, and the
identied parameters are point estimations subject to dierent constraints. These conventional
point estimation based composite load modeling approaches suer from disturbances and noises
and provide limited information of the system dynamics. In this thesis, a statistic (Bayesian
Estimation) based distribution estimation approach is proposed for composite load models,
including static (ZIP) and dynamic (Induction Motor) parts, by implementing Gibbs sampling.
The proposed method provides a distribution estimation of coecients for load models and is
robust to measurement errors.
The overvoltage issue is another urgent issues need to be addressed, especially in a
high PV penetration level system. Various approaches including the real power control through
photovoltaic (PV) inverters have been proposed to mitigate such impact, however, most of the
existing methods did not include communication delays in the control loop. Communication delays, short or long, are inevitable in the PV voltage regulation loop and can not only deteriorate
the system performance with undesired voltage quality but also cause system instability. In this
thesis, a method is presented to convert the overvoltage control problem via PV inverters for
multiple PVs into a problem of single-input-single-output (SISO) systems. The method can handle
multiple PVs and dierent communication delays. The impact of communication delays is
also systematically analyzed and the maximum tolerable delay is rigorously obtained. Dierent
from linear matrix inequality (LMI) techniques that have been extensively studied in handling
systems with communication delays, the proposed method gives the necessary and sucient
condition for obtaining a controller and the design procedure is explicitly and constructively
given in the paper. The effectiveness of the proposed method is veried by simulation studies
on a distribution feeder and the widely-used 33-bus distribution test system.
The similar design strategy can be utilized to mitigate delay impacts in Load frequency
control (LFC) as well. LFC has been considered as one of the most important frequency
regulation mechanisms in modern power system. One of the inevitable problems involved in
LFC over a wide area is communication delay. In this thesis, an alternative design method is
proposed to devise delay compensators for LFC in one or multiple control areas. For one-area
LFC, a sucient and necessary condition is given for designing a delay compensator. For multiarea
LFC with area control errors (ACEs), it is demonstrated that each control area can have
its delay controller designed as that in a one-area system if the index of coupling among the
areas is below the threshold value determined by the small gain theorem. Effectiveness of the
proposed method is veried by simulation studies on LFCs with communication delays in one
and multiple interconnected areas with and without time-varying delays, respectively.
Recommended Citation
Fu, Chang, "Analysis And Mitigation Of The Impacts Of Delays In Control Of Power Systems With Renewable Energy Sources" (2019). Wayne State University Dissertations. 2219.
https://digitalcommons.wayne.edu/oa_dissertations/2219