Open AccessIntroducing LQR-fuzzy for a dynamic multi area LFC-DR model
Author(s) -
P Srividya Devi,
R. Vijaya Santhi
Publication year - 2019
Publication title -
international journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.277
H-Index - 22
ISSN - 2088-8708
DOI - 10.11591/ijece.v9i2.pp861-874
Subject(s) - control theory (sociology) , computer science , automatic frequency control , electric power system , pid controller , fuzzy logic , controller (irrigation) , dynamic demand , smart grid , realization (probability) , demand response , load regulation , automatic generation control , control system , control engineering , power (physics) , control (management) , temperature control , engineering , telecommunications , mathematics , electricity , agronomy , statistics , physics , electrical engineering , quantum mechanics , artificial intelligence , biology
It is well known that Load Frequency Control (LFC) model plays a vital role in electric power system design and operation. In the literature, much research works has stated on the advantages and realization of DR (Demand Response), which has proved to be an important part of the future smart grid. In an interconnected power system, if a load demand changes randomly, both frequency and tie line power varies. LFC-DR model is tuned by standard controllers like PI, PD, PID controllers, as they have constant gains. Hence, they are incapable of acquiring desirable dynamic performance for an extensive variety of operating conditions and various load changes. This paper presents the idea of introducing a DR control loop in the traditional Multi area LFC model (called LFC -DR) using LQR- Fuzzy Logic Control. The effect of DR-CDL i.e. (Demand Response Communication Delay Latency) in the design is also considered and is linearized using Padé approximation. Simulation results shows that the addition of DR control loop with proposed controller guarantees stability of the overall closed-loop LFC-DR system which effectively improves the system dynamic performance and is superior over a classical controller at different operating scenarios.