GWO BASED AWDO TECHNIQUE FOR EMISSION CONSTRAINED OPTIMAL GENERATION OF ALLOCATION

The current work focuses on a meta-heuristic solution of a multi-objective CEED (Combined Economic Emission Dispatch) problem on the Distributed Energy Resources (DERs). The proposed algorithm is based on a hybrid optimization technique, Grey Wolf Optimization-based-Adaptive Wind Driven Optimization...

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Bibliographic Details
Published inScientific Bulletin. Series C, Electrical Engineering and Computer Science no. 4; p. 83
Main Authors Banerjee, Swaraj, Sarkar, Dipu
Format Journal Article
LanguageEnglish
Published Bucharest University Polytechnica of Bucharest 01.01.2019
Subjects
Algorithms
Computer simulation
Constraints
Distributed generation
Energy sources
Environmental effects
Heuristic methods
Multiple objective analysis
Optimization
Optimization techniques
Pollutants
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Summary:The current work focuses on a meta-heuristic solution of a multi-objective CEED (Combined Economic Emission Dispatch) problem on the Distributed Energy Resources (DERs). The proposed algorithm is based on a hybrid optimization technique, Grey Wolf Optimization-based-Adaptive Wind Driven Optimization (GWO -AWDO) where the search agents are initiated and randomized by GWO but position vectors are governed by AWDO. The CEED problem focuses on both the environmental effects from the gaseous pollutants from fossil-fueled power generating plants and generation cost meeting the needs of satisfying all operational constraints and load demand as well at the same time. Therefore, CEED problem has been formulated as a multi-objective, non-linear, non-smooth problem and that has later been converted into a single objective function using price penalty factor. The key objective is to solve the CEED problem with the proposed algorithm and analyze its effectiveness of with the help of the simulation results which later have been compared with other existing algorithms for two test systems (10 thermal units and 40 thermal units) where in both cases GWO-AWDO has proved to be the best and outperformed other existing methods.
ISSN:2286-3540