Abstract

As the contribution of renewable energy to the current power grid is becoming an essential part of the global energy system, it is of critical importance to study the effects of this increased penetration of the renewable sources on the power system. Focusing on solar energy, its intermittent nature makes it difficult to predict the output when connecting to the power grid. Therefore, well-structured control methods should be used to assure a continuous and steady system performance with regard to the system frequency variation.

In this thesis, a PV system is modelled and connected to a grid served by a conventional thermal power system with 45% penetration level. Then, the system frequency errors due to load changes are studied in this PV connected power grid. Appropriate and effective controllers are designed to regulate these errors to keep the system response within the required specifications.

In addition, single-area as well as two-area interconnected power systems are considered in this research. The power exchange among the two areas will add another significant parameter that is essential in the efficient operation of the system and that affects the behavior of the system in terms of the frequency error response.

Two advanced control methods, namely Linear Quadratic Regulator (LQR) and Fuzzy Logic Control (FLC) are applied to control the single-area and the two-area systems. The appropriate controllers are designed, assessed and the responses are analyzed and compared. These designed controllers demonstrated a superior performance in the controlled system by achieving the required specifications of undershoot, settling time and steady state error for the system frequency. For the single-area PV connected power system, the LQR controller gave the best response in comparison to the two other types of controllers, while in the two-area system the fuzzy logic controller was the most suitable as it met the specifications to the best possible extent.

Library of Congress Subject Headings

Photovoltaic power systems--Automatic control; H2 control; Fuzzy logic--Industrial applications

Publication Date

3-2018

Document Type

Thesis

Student Type

Graduate

Degree Name

Electrical Engineering (MS)

Department, Program, or Center

Electrical Engineering (KGCOE)

Advisor

Abdulla Ismail

Advisor/Committee Member

Yousef Al Assaf

Advisor/Committee Member

Ghalib Kahwaji

Campus

RIT Dubai

Plan Codes

EEEE-MS

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