Multi-Criteria Optimal Sizing and Allocation of Renewable and Non-Renewable Distributed Generation Resources at 63 kV/20 kV Substations

The optimal allocation and sizing of distributed generation (DG) resources are important in installing these resources, to improve the technical parameters of the network, including the power losses, voltage profile, and short-circuit level, as well as to increase economic factors. In this paper, a...

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Main Authors: Seyed Siavash Karimi Madahi, Andrija T. Sarić
Format: Article
Language:English
Published: MDPI AG 2020-10-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/13/20/5364
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spelling doaj-2c277ff2b42d40f481b148e6e9dbdaad2020-11-25T02:26:25ZengMDPI AGEnergies1996-10732020-10-01135364536410.3390/en13205364Multi-Criteria Optimal Sizing and Allocation of Renewable and Non-Renewable Distributed Generation Resources at 63 kV/20 kV SubstationsSeyed Siavash Karimi Madahi0Andrija T. Sarić1Department of Power Engineering, Faculty of Technical Sciences, University of Novi Sad, 21000 Novi Sad, SerbiaDepartment of Power Engineering, Faculty of Technical Sciences, University of Novi Sad, 21000 Novi Sad, SerbiaThe optimal allocation and sizing of distributed generation (DG) resources are important in installing these resources, to improve the technical parameters of the network, including the power losses, voltage profile, and short-circuit level, as well as to increase economic factors. In this paper, a new multi-criteria algorithm and objective function are proposed for the optimal sizing and allocation of renewable and non-renewable DG resources simultaneously. The proposed algorithm is implemented on 63/20 kV substations at 20 kV levels. In the proposed objective function, all important technical and economic factors as well as important constraints, such as penetration level of DGs and budget constraint, are considered in a way that all factors are assigned to monetary values. Moreover, a new mathematical formulation is introduced for the allocation of renewable DG resources to reduce run-time optimization. The genetic algorithm (GA) is employed in the proposed algorithm to minimize the objective function. For renewable DG resources, photovoltaic panels and wind turbines, and for non-renewable DG resources, gas turbines are considered. The 115 buses network of Bakhtar Regional Electric Company (BREC) in Iran is used to evaluate the performance of the proposed algorithm. The results demonstrate that the proposed algorithm improves technical factors efficiently and maximizes the profitability of the investment.https://www.mdpi.com/1996-1073/13/20/5364allocationdistributed generationmulti-criteriaoptimizationsizing
collection DOAJ
language English
format Article
sources DOAJ
author Seyed Siavash Karimi Madahi
Andrija T. Sarić
spellingShingle Seyed Siavash Karimi Madahi
Andrija T. Sarić
Multi-Criteria Optimal Sizing and Allocation of Renewable and Non-Renewable Distributed Generation Resources at 63 kV/20 kV Substations
Energies
allocation
distributed generation
multi-criteria
optimization
sizing
author_facet Seyed Siavash Karimi Madahi
Andrija T. Sarić
author_sort Seyed Siavash Karimi Madahi
title Multi-Criteria Optimal Sizing and Allocation of Renewable and Non-Renewable Distributed Generation Resources at 63 kV/20 kV Substations
title_short Multi-Criteria Optimal Sizing and Allocation of Renewable and Non-Renewable Distributed Generation Resources at 63 kV/20 kV Substations
title_full Multi-Criteria Optimal Sizing and Allocation of Renewable and Non-Renewable Distributed Generation Resources at 63 kV/20 kV Substations
title_fullStr Multi-Criteria Optimal Sizing and Allocation of Renewable and Non-Renewable Distributed Generation Resources at 63 kV/20 kV Substations
title_full_unstemmed Multi-Criteria Optimal Sizing and Allocation of Renewable and Non-Renewable Distributed Generation Resources at 63 kV/20 kV Substations
title_sort multi-criteria optimal sizing and allocation of renewable and non-renewable distributed generation resources at 63 kv/20 kv substations
publisher MDPI AG
series Energies
issn 1996-1073
publishDate 2020-10-01
description The optimal allocation and sizing of distributed generation (DG) resources are important in installing these resources, to improve the technical parameters of the network, including the power losses, voltage profile, and short-circuit level, as well as to increase economic factors. In this paper, a new multi-criteria algorithm and objective function are proposed for the optimal sizing and allocation of renewable and non-renewable DG resources simultaneously. The proposed algorithm is implemented on 63/20 kV substations at 20 kV levels. In the proposed objective function, all important technical and economic factors as well as important constraints, such as penetration level of DGs and budget constraint, are considered in a way that all factors are assigned to monetary values. Moreover, a new mathematical formulation is introduced for the allocation of renewable DG resources to reduce run-time optimization. The genetic algorithm (GA) is employed in the proposed algorithm to minimize the objective function. For renewable DG resources, photovoltaic panels and wind turbines, and for non-renewable DG resources, gas turbines are considered. The 115 buses network of Bakhtar Regional Electric Company (BREC) in Iran is used to evaluate the performance of the proposed algorithm. The results demonstrate that the proposed algorithm improves technical factors efficiently and maximizes the profitability of the investment.
topic allocation
distributed generation
multi-criteria
optimization
sizing
url https://www.mdpi.com/1996-1073/13/20/5364
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