Emission/fuel energy restricted dynamic optimal power flow using fuzzy - ant lion optimizer

Abstract

Purpose

This study aims to minimize operating cost, adhere to pollution norms and maintain reserve and voltage levels subject to various operational concerns, including non linear characteristics of generators and fuel limitation issues, which are useful for the current power system applications.

Design/methodology/approach

Improved control settings are required while considering multiple conflicting operational objectives that necessitate using the modern bio-inspired algorithm ant lion optimizer (ALO) as the main optimization tool. Fuzzy decision-making mechanism is incorporated in ALO to extract the best compromise solution (BCS) among set of non-dominated solutions.

Findings

The BCS records of IEEE-30 bus and JEAS-118 bus systems are updated in this work. Numerical simulation results comparison and comprehensive performance analysis justify the applicability of the intended algorithm to solve multi-objective dynamic optimal power flow (DOPF) problem over the state-of-art methods.

Originality/value

Optimal control settings are obtained for IEEE-30 and JEAS-118 bus systems with the objectives of minimizing fuel cost and emission in dynamic environment considering take-or-pay fuel contract issue. The fuzzy supported ALO (FSALO) is applied first time to solve the DOPF problem.

Citation

Radha, J., Subramanian, S., Ganesan, S. and Abirami, M. (2017), "Emission/fuel energy restricted dynamic optimal power flow using fuzzy - ant lion optimizer", International Journal of Energy Sector Management, Vol. 11 No. 2, pp. 208-256. https://doi.org/10.1108/IJESM-04-2016-0003