Analysis of the applicability and results of swarm intelligence tools for the positioning of Energy Storage Systems

The integration of renewable energy is transforming traditional energy systems, blurring the distinction between producers and consumers and shifting towards a distributed grid network. This change demands innovative approaches to optimize Energy Storage Systems (ESS) and manage grid incidents effic...

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Vydané v:International journal of electrical power & energy systems Ročník 163; s. 110343
Hlavní autori: Divasson-J, Asier, Santamaria, Itxaso Aranzabal, Landaribar, Miren T. Bedialauneta, Aguirre, Paula Castillo
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier Ltd 01.12.2024
Elsevier
Predmet:
Distribution systems
Electrical systems
Energy storage systems
Optimization
Stochastic algorithms
Stochastic algorithms
Distribution systems
Energy storage systems
Electrical systems
Optimization
ISSN:0142-0615
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Shrnutí:The integration of renewable energy is transforming traditional energy systems, blurring the distinction between producers and consumers and shifting towards a distributed grid network. This change demands innovative approaches to optimize Energy Storage Systems (ESS) and manage grid incidents efficiently, all without significant infrastructural changes. While optimization algorithms like Swarm Intelligence are gaining traction, critical aspects, such as worst-case scenario analysis in distribution networks, remain underexplored. This study addresses this gap by applying stochastic optimization techniques to determine the optimal placement and capacity of ESS in a medium voltage radial distribution system, using the IEEE 33-bus model. The findings highlight the importance of considering worst-case scenarios, offering a balanced evaluation of current methodologies. This research provides valuable insights for improving system flexibility and resilience, contributing to more effective and practical energy optimization strategies in real-world applications. •Critical Analysis: Swarm intelligence on energy storage systems.•Swarm Intelligence: Tools to enhance management of distributed energy systems.•Current Energy Context: Increasing renewable sources and a shift in the paradigm.•Areas for Evolving: Potential future research detected in this ever-evolving field.
ISSN:0142-0615
DOI:10.1016/j.ijepes.2024.110343