A Multi-Objective Optimization Approach for Integrated Allocation of Distributed Generation and Protection Devices in Distribution Systems
This paper presents a methodology for the optimal and simultaneous allocation of Distributed Generation (DG), Control and Protection Devices (CPDs) in unbalanced electric power distribution systems. In the proposed approach, the allocation of DGs reduces system losses during operation and enables is...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11002463/ |
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| Summary: | This paper presents a methodology for the optimal and simultaneous allocation of Distributed Generation (DG), Control and Protection Devices (CPDs) in unbalanced electric power distribution systems. In the proposed approach, the allocation of DGs reduces system losses during operation and enables islanded operation under fault conditions. The network protection system is updated by installing new CPDs and relocating the existing ones. The problem formulation considers overcurrent relays, reclosers, fuses, automatic sectionalizing switches, and the islanding interconnection device. The mathematical model presents three objective functions: investment costs for the acquisition, installation, and maintenance of CPDs and DGs, costs of energy not supplied, and active power losses, considering permanent and temporary faults, as well as load growth over the planning horizon. The model is reformulated as a single-objective optimization problem using weighted sums and solved through genetic algorithm to present a set of solutions from which the grid planner can choose the one that best fits the company’s realities. The proposed methodology was validated using a real 135-bus system, and the results show that for a network in the planning phase, the integrated allocation reduced interruption costs by 55% and total costs by 8%, compared to projects that allocate DGs first and CPDs subsequently. Additionally, it is statistically demonstrated using the Pearson correlation coefficient that the three objective functions considered in this work are statistically related, and therefore, minimizing all three together has strong statistical relevance. |
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| ISSN: | 2169-3536 |