Multiobjective Optimization Model for Wind Power Allocation

There is an increasing need for the injection to the grid of renewable energy; therefore, to evaluate the optimal location of new renewable generation is an important task. The primary purpose of this work is to develop a multiobjective optimization model that permits finding multiple trade-off solu...

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Bibliographic Details
Published in:Mathematical problems in engineering 2017-01, Vol.2017 (2017), p.1-10
Main Authors: Arendarski, Bartlomiej, Lombardi, Pio, Magnago, Fernando, Alemany, Juan, Komarnicki, Przemyslaw
Format: Article
Language:English
Subjects:
Algorithms
Alternative energy sources
Capital costs
Decision making
Electric utilities
Electricity distribution
Energy resources
Enrichment
Environmental impact
Linear programming
Mathematical models
Mathematical problems
Maximization
Methodology
Methods
Multiple objective analysis
Networks
Objectives
Optimization
Optimization models
Wind power
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Summary:There is an increasing need for the injection to the grid of renewable energy; therefore, to evaluate the optimal location of new renewable generation is an important task. The primary purpose of this work is to develop a multiobjective optimization model that permits finding multiple trade-off solutions for the location of new wind power resources. It is based on the augmented ε-constrained methodology. Two competitive objectives are considered: maximization of preexisting energy injection and maximization of new wind energy injection, both embedded, in the maximization of load supply. The results show that the location of new renewable generation units affects considerably the transmission network flows, the load supply, and the preexisting energy injection. Moreover, there are diverse opportunities to benefit the preexisting generation, contrarily to the expected effect where renewable generation displaces conventional power. The proposed methodology produces a diverse range of equivalent solutions, expanding and enriching the horizon of options and giving flexibility to the decision-making process.
ISSN:1024-123X
1563-5147
DOI:10.1155/2017/1876934