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Cited by 122Optimal Power Flow DistributionElectric Power System OptimizationMicrogrid Control and Optimization

Optimal placement and sizing of renewable distributed generation using hybrid metaheuristic algorithm

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Radosavljevic, Jordan, Arsic, Nebojsa, Milovanovic, Milos, Ktena, Aphrodite·2020·Journal of Modern Power Systems and Clean Energy
DOI 10.35833/mpce.2019.000259
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Abstract

The problem of optimal placement and sizing (OPS) of renewable distributed generation (RDG) is followed by numerous technical, economical, geographical, and ecological constraints. In this paper, it is investigated from two viewpoints, namely the simultaneous minimization of total energy loss of a distribution network and the maximization of profit for RDG owner. The stochastic nature of RDG such as the wind turbine and photovoltaic generation is accounted using suitable probabilistic models. To solve this problem, a hybrid metaheuristic algorithm is proposed, which is a combination of the phasor particle swarm optimization and the gravitational search algorithm. The proposed algorithm is tested on an IEEE 69-bus system for several cases in two scenarios. The results obtained by the hybrid algorithm shows that it provides high-quality solution for all cases considered and has better performances for solving the OPS problem compared to other metaheuristic population-based techniques.

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  • PV generators suffer from variability and stochasticity of their output power, which is their main drawback.

    “However, they suffer from variability and stochasticity of the output power which is their main drawback [2] and a challenge attracting the interest of research community.”

    From Dynamic Optimal Power Dispatch in Unbalanced Distribution Networks with Single-Phase Solar PV Units and BESS (2023) · cites this paper as [2]

    The PV Generation Modeling section (page unavailable) describes solar irradiance as stochastic and says PV power output depends on its possible states. The Simulation Results section shows PV generation varying by season and falling to zero at night. These passages support variable, stochastic output, but the paper does not identify it as PV generators’ main drawback. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

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Research works printed but not linked: 33

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Cited by

Sorted by citations

Authors
Radosavljevic, J., Arsic, N., Milovanovic, M., & Ktena, A.
Affiliations
  • University of Priština - Kosovska Mitrovica (XK)
  • National and Kapodistrian University of Athens (GR)
ORCID
Venue
Journal of Modern Power Systems and Clean Energy
Publisher
Journal of Modern Power Systems and Clean Energy
Published
2020
Volume
8
Issue
3
Pages
499-510
ISSN
  • 2196-5420 (ISSN-L)
  • 2196-5625
DOI
10.35833/mpce.2019.000259
OpenAlex
W3026758110
Cited by
122
References
0
Citations by year
2026: 9 · 2025: 17 · 2024: 28 · 2023: 30 · 2022: 18 · 2021: 19 · 2020: 1
FWCI
5.84
Type
journal article
Language
en
Open access
Locations
  • Journal of Modern Power Systems and Clean Energy (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
Ministarstvo Prosvete, Nauke i Tehnološkog Razvoja (TR33046, 33046)
Topics
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Optimal Power Flow Distribution
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Power System Optimization
  • Physical Sciences › Engineering › Control and Systems Engineering › Microgrid Control and Optimization
Keywords
optimal placement and sizing, distributed renewable energy, hybrid metaheuristic, gravitational search algorithm, wind power uncertainty, photovoltaic uncertainty, IEEE 69-bus system

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