Abstract

When the microgrid disconnects from the main grid in response to, say, upstream disturbance or voltage fluctuation and goes to islanding mode, both voltage and frequency at all locations in the microgrid have to be regulated to nominal values in a short amount of time before the operation of protective relays. Motivated by this, we studied the application of intelligent pinning of distributed cooperative secondary control of distributed generators in islanded microgrid operation in a power system. In the first part, the problem of single and multi-pinning of distributed cooperative secondary control of DGs in a microgrid is formulated. It is shown that the intelligent selection of a pinning set based on the number of its connections and distance of leader DG/DGs from the rest of the network, i.e., degree of connectivity, strengthens microgrid voltage and frequency regulation performance both in transient and steady state. The proposed control strategy and algorithm are validated by simulation in MATLAB/SIMULINK using different microgrid topologies. It is shown that it is much easier to stabilize the microgrid voltage and frequency in islanding mode operation by specifically placing the pinning node on the DGs with high degrees of connectivity than by randomly placing pinning nodes into the network. In all of these research study cases, DGs are only required to communicate with their neighboring units which facilitates the distributed control strategy. Historically, the models for primary control are developed for power grids with centralized power generation, in which the transmission lines are assumed to be primarily inductive. However, for distributed power generation, this assumption does not hold since the network has significant resistive impedance as well. Hence, it is of utmost importance to generalize the droop equations, i.e., primary control, to arrive at a proper model for microgrid systems. Motivated by this, we proposed the secondary adaptive voltage and frequency control of distributed generators for low and medium voltage microgrid in autonomous mode to overcome the drawback of existing classical droop based control techniques. Our proposed secondary control strategy is adaptive with line parameters and can be applied to all types of microgrids to address the simultaneous impacts of active and reactive power on the microgrids voltage and frequency. Also, since the parameters in the network model are unknown or uncertain, the second part of our research studies adaptive distributed estimation/compensation. It is shown that this is an effective method to robustly regulate the microgrid variables to their desired values. The security of power systems against malicious cyberphysical data attacks is the third topic of this dissertation. The adversary always attempts to manipulate the information structure of the power system and inject malicious data to deviate state variables while evading the existing detection techniques based on residual test. The solutions proposed in the literature are capable of immunizing the power system against false data injection but they might be too costly and physically not practical in the expansive distribution network. To this end, we define an algebraic condition for trustworthy power system to evade malicious data injection. The proposed protection scheme secures the power system by deterministically reconfiguring the information structure and corresponding residual test. More importantly, it does not require any physical effort in either microgrid or network level. The identification scheme of finding meters being attacked is proposed as well. Eventually, a well-known IEEE 30-bus system is adopted to demonstrate the effectiveness of the proposed schemes.

Notes

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Graduation Date

2016

Semester

Summer

Advisor

Behal, Aman

Degree

Doctor of Philosophy (Ph.D.)

College

College of Engineering and Computer Science

Department

Electrical Engineering and Computer Engineering

Degree Program

Electrical Engineering

Format

application/pdf

Identifier

CFE0006338

URL

http://purl.fcla.edu/fcla/etd/CFE0006338

Language

English

Release Date

August 2016

Length of Campus-only Access

None

Access Status

Doctoral Dissertation (Open Access)

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