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

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. De...

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Vydáno v:International journal of energy sector management Ročník 11; číslo 2; s. 208 - 256
Hlavní autoři: Radha, Janagaraman, Subramanian, Srikrishna, Ganesan, Sivarajan, Abirami, Manoharan
Médium: Journal Article
Jazyk:angličtina
Vydáno: Bradford Emerald Publishing Limited 01.01.2017
Emerald Group Publishing Limited
Témata:
Algorithms
Bees
Buses
Buses (vehicles)
Computer simulation
Control methods
Control systems
Decision making
Design improvements
Dynamical systems
Electric potential
Electric power
Electric utilities
Electrical engineering
Emission
Emissions
Energy consumption
Fuels
Fuzzy sets
Generators
Heuristic
Linear programming
Mathematical models
Methods
Multiple objective analysis
Norms
Objectives
Operating costs
Optimal control
Optimization
Power flow
Reserve requirements
Upgrading
Vibration
Decision-making
Cost minimization
Simulation
Optimization
ISSN:1750-6220, 1750-6239
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Shrnutí: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.
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ISSN:1750-6220
1750-6239
DOI:10.1108/IJESM-04-2016-0003