Quasi-oppositional atom search optimization algorithm for automatic generation control of deregulated power systems

Chandan Kumar Shiva (), Vedik Basetti () and Sumit Verma
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Chandan Kumar Shiva: SR Engineering College
Vedik Basetti: SR Engineering College
Sumit Verma: Indian Institute of Technology

International Journal of System Assurance Engineering and Management, 2022, vol. 13, issue 4, No 24, 1845-1863

Abstract: Abstract The restructuring of the interconnected power systems, supervised by the independent system operator, is the new independent electricity market which ultimate goals is to provide power to the consumers according to their own bilateral power contract demand. The changing of the power system structurally enforces the industry utility to use improved control strategy in various ancillary services such as frequency control based on load following which is a part of automatic generation control (AGC). The study of the power market reveals that frequency control is one of the profitable services for AGC. This can be accomplished by solving LFC optimization problems subjected to various conditions and limitations for the system's optimum performance. In the present study, this paper studies the AGC performance in deregulated environment with the impacts of a quasi-oppositional atom search optimization (QOASO) algorithm. The QOASO algorithm is applied in single- and two-area test power systems with multi-source generating units in deregulated domain. The single-area test system is taken to study the basic deregulated operation in AGC prospect. After this, the two-area test system model is taken into study in deregulated AGC domain. Sensitivity analysis of the designed controller is also studied in case of contract violation case study subjected to two-area test system. The study showed that the proposed QOASO algorithm performed better in deregulated power system study.

Keywords: Automatic generation control; Bilateral contracts; DISCO participation matrix; Optimization; Atom search optimization (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s13198-021-01575-0

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