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Alizadeh Pahlavani, M., Khosravi, M. (2019). Examining the Network Losses and Costs of Construction of Distributed Generation Plants Based on Multi-Objective Genetic Algorithm and Exchange Market Algorithm. Electronic and Cyber Defense, 10(3), 251-265.
mohammad reza Alizadeh Pahlavani; Majid Khosravi. "Examining the Network Losses and Costs of Construction of Distributed Generation Plants Based on Multi-Objective Genetic Algorithm and Exchange Market Algorithm". Electronic and Cyber Defense, 10, 3, 2019, 251-265.
Alizadeh Pahlavani, M., Khosravi, M. (2019). 'Examining the Network Losses and Costs of Construction of Distributed Generation Plants Based on Multi-Objective Genetic Algorithm and Exchange Market Algorithm', Electronic and Cyber Defense, 10(3), pp. 251-265.
Alizadeh Pahlavani, M., Khosravi, M. Examining the Network Losses and Costs of Construction of Distributed Generation Plants Based on Multi-Objective Genetic Algorithm and Exchange Market Algorithm. Electronic and Cyber Defense, 2019; 10(3): 251-265.

Examining the Network Losses and Costs of Construction of Distributed Generation Plants Based on Multi-Objective Genetic Algorithm and Exchange Market Algorithm

علوم و فناوریهای پدافند نوین
Article 5, Volume 10, Issue 3 - Serial Number 37, July 2019, Pages 251-265    PDF (1.72 M)
Document Type: -
Authors
mohammad reza Alizadeh Pahlavani* ; Majid Khosravi
Malek Ashtar University of Technology
Receive Date: 09 April 2018,  Revise Date: 21 September 2018,  Accept Date: 12 January 2019 
Abstract
IRAN and the world are moving away from central energy resource to distributed generation (DG) in order to lower carbon emissions. Renewable energy resources comprise a big percentage of DGs and their optimal integration to the grid is the main attempt of planning/developing projects with in electricity network. Feasibility and thorough conceptual design studies are required in the planning/development process as the most of the electricity networks are designed in the passed decades, not considering the challenges imposed by DGs. As an example, the issue of optimal placement and the capacity of DG’s become problematic when large amount of dispersed generation is connected to a distribution network. Therefore, optimized algorithms have been developed over the last decade in order to do the planning purpose optimally such as to alleviate the unwanted effects of DGs. In this article, after explaining the two proposed methods, the modified non-sorting genetic algorithm (NSGA)’s and Exchange Market Algorithm (EMA)’s results, based on MATPOWER’s systems have been compared, in order to find a fast and reliable solution to optimum planning.

 
Keywords
Distributed Generation; Non-Dominated Genetic Algorithm; Exchange Market Algorithm; Optimization
References

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