Open AccessLoad frequency control of multi‐source electrical power system integrated with solar‐thermal and electric vehicle
Author(s) -
Farooq Zahid,
Rahman Asadur,
Lone Shameem Ahmad
Publication year - 2021
Publication title -
international transactions on electrical energy systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.428
H-Index - 42
ISSN - 2050-7038
DOI - 10.1002/2050-7038.12918
Subject(s) - control theory (sociology) , automatic generation control , automatic frequency control , electric power system , controller (irrigation) , computer science , robustness (evolution) , photovoltaic system , control engineering , engineering , power (physics) , control (management) , telecommunications , electrical engineering , quantum mechanics , biochemistry , chemistry , artificial intelligence , gene , agronomy , biology , physics
Summary Delivering reliable and adequate power to the consumer is essentially critical. Standard quality of power is measured by its frequency stability and power flow between different control areas. Therefore, power‐system‐control is generally attained with load‐frequency‐control (LFC). This paper presents the LFC of a hybrid power system comprising of conventional‐thermal, solar‐thermal and electric vehicle (EV). The inclusion of EVs into the utility grid, generation‐rate‐constraint of thermal plants and time‐delay in all three control areas makes the proposed power system more realistic and a practical one. This makes the system a bit complex and requires a robust controller to function optimally. An integral‐double‐derivative (IDD) controller is applied for this study and the system responses are compared with those of classical controllers. The controller gains are optimized using the powerful magnetotactic bacteria optimization (MBO) technique, which find its maiden application in power system studies. MBO optimized IDD controller performs better in contrast to other classical controllers. Further, a fuzzy logic control (FLC) is developed to optimize the gains of optimal IDD controller. System dynamic responses comparison of both fuzzy optimized IDD and MBO optimized IDD controller reveals an inclination towards the performance of fuzzy optimized IDD controller. This is validated with the help of demerit index. Robustness analysis is also done to highlight the strength of IDD controller optimized with both MBO and FLC for various system changes, such as load perturbation, system loading and solar irradiance. The critical review of all these analysis infers the effective performance of fuzzy optimized IDD controller.