Optimizing Distributed Generation Sizing and Siting using Particle Swarm Optimization: A Comparative Study

Ahmed, Eihab E.E.; Poyrazoglu, Gokturk

doi:10.1109/eeeic/icpseurope57605.2023.10194717

Cited by 3 publications

(1 citation statement)

References 17 publications

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“…The optimization of asset sizing for a reliable and sustainable NG assumes paramount importance in achieving optimal selfsufficiency, offering grid relief, and ensuring cost-effectiveness. Consequently, potential challenges arising from integrating renewables can be mitigated (Ahmed, 2023;Bandyopadhyay et al, 2020). In the design procedure of a PV-based microgrid or an NG, the optimal sizing of their components ensures the optimal utilization of the available solar energy and associated storage devices (Mathew et al, 2022).…”

Section: Research Articlementioning

confidence: 99%

An integrated framework for techno-enviro-economic assessment in nanogrids

El Sayed,

Poyrazoglu,

E. E. Ahmed

2024

Int. J. Renew. Energy Dev.

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This paper presents an integrated framework designed for capacity planning of grid-connected nanogrid, a small solar and energy storage system that can provide kilowatt-level services to individual buildings. This framework comprehensively evaluates nanogrid cost-effectiveness, sustainability, and reliability, employing a multi-faceted techno-enviro-economic assessment approach. Traditional nanogrid capacity planning often prioritizes peak load requirements, which may lack optimality owing to occasional peak load occurrences. Conversely, optimizing solely for base load requirements might also fall short of effectiveness, compromising reliability and sustainability objectives. The proposed framework employs a three-step, integrated process for nanogrid (NG) capacity planning. Firstly, the Planner module identifies optimal asset sizing considering a two-day look-ahead logic. Then, the Operator module serves as a digital twin for the system, conducting hourly calculations over a short-term horizon. Lastly, the Evaluator module evaluates technical, environmental, and economic metrics for each solution, assessing the effectiveness of asset-sizing decisions. A simulated case study has demonstrated the effectiveness of the proposed framework. The technical assessment revealed that a PV size of 24 kW and a storage capacity of 91 kWh led to the most reliable solution, with a probability of local sufficiency of 95 percent. Furthermore, the environmental assessment showcased a renewable fraction of 94% with a PV size of 26 kW and a storage of 85 kWh. Economically, the analysis identified that a PV size of 12 kW and a storage size of 24 kWh led to the minimum total cost. In contrast, a PV size of 26 kW and a storage size of 85 kWh yielded a total operating savings of $4,801.

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Section: Research Articlementioning

confidence: 99%

An integrated framework for techno-enviro-economic assessment in nanogrids

El Sayed,

Poyrazoglu,

E. E. Ahmed

2024

Int. J. Renew. Energy Dev.

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Optimal Planning and Allocation of DER in Radial Distribution Networks Using IPSO

El Sayed,

Ahmed,

Poyrazoglu

2024

2024 IEEE 8th Energy Conference (ENERGYCON)

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Analysis of Grid Performance with Diversified Distributed Resources and Storage Integration: A Bilevel Approach with Network-Oriented PSO

El Sayed,

Poyrazoglu

2024

Energies

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The growing deployment of distributed resources significantly affects the distribution grid performance in most countries. The optimal sizing and placement of these resources have become increasingly crucial to mitigating grid issues and reducing costs. Particle Swarm Optimization (PSO) is widely used to address such problems but faces computational inefficiency due to its numerical convergence behavior. This limits its effectiveness, especially for power system problems, because the numerical distance between two nodes in power systems might be different from the actual electrical distance. In this paper, a scalable bilevel optimization problem with two novel algorithms enhances PSO’s computational efficiency. While the resistivity-driven algorithm strategically targets low-resistivity regions and guides PSO toward areas with lower losses, the connectivity-driven algorithm aligns solution spaces with the grid’s physical topology. It prioritizes actual physical neighbors during the search to prevent local optima traps. The tests of the algorithms on the IEEE 33-bus and the 69-bus and Norwegian networks show significant reductions in power losses (up to 74% for PV, wind, and storage) and improved voltage stability (a 21% reduction in mean voltage deviation index) with respect to the results of classical PSO. The proposed network-oriented PSO outperforms classical PSO by achieving a 2.84% reduction in the average fitness value for the IEEE 69-bus case with PV, wind, and storage deployment. The Norwegian case study affirms the effectiveness of the proposed approach in real-world applications through significant improvements in loss reduction and voltage stability.

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Optimizing Distributed Generation Sizing and Siting using Particle Swarm Optimization: A Comparative Study

Cited by 3 publications

References 17 publications

An integrated framework for techno-enviro-economic assessment in nanogrids

An integrated framework for techno-enviro-economic assessment in nanogrids

Optimal Planning and Allocation of DER in Radial Distribution Networks Using IPSO

Analysis of Grid Performance with Diversified Distributed Resources and Storage Integration: A Bilevel Approach with Network-Oriented PSO

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