Open AccessQuasi‐oppositional harmony search algorithm based optimal dynamic load frequency control of a hybrid tidal–diesel power generation system
Author(s) -
Kumar Akshay,
Shankar Gauri
Publication year - 2018
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2017.1115
Subject(s) - harmony search , electric power system , automatic frequency control , control theory (sociology) , frequency deviation , tidal power , computer science , wind power , inertia , control engineering , engineering , power (physics) , control (management) , telecommunications , artificial intelligence , physics , electrical engineering , classical mechanics , quantum mechanics , marine engineering
In recent years, high penetration of distributed generations based on wind energy, solar energy and so on in the existing power system network has been noticed. However, due to their stochastic behaviour, operations under autonomous mode as well as in grid‐connected mode are not an easy task. This has forced the power utilities to re‐define frequency regulation criteria to enhance the overall system stability and reliability. In line with the same, dynamic performance analysis of load frequency control (LFC) of an autonomous hybrid power system model (HPSM) consisting of tidal power plant (TPP) and diesel power plant is explored in this study. A concept of deloaded TPP is adopted in the studied HPSM to utilise the available reserve power for the frequency support. Apart from this, the studied model also incorporates frequency regulation through inertia and damping control and supplementary control strategies. These control strategies are realised through conventional controllers whose gain values are optimised using quasi‐oppositional harmony search algorithm (QOHSA) for the optimal dynamic performance of LFC. The efficacy of the proposed QOHSA is corroborated by comparing the results with those yielded by few other existing state‐of‐the‐art algorithms.