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article · IEEE Access

Effective Automation of Distribution Systems With Joint Integration of DGs/ SVCs Considering Reconfiguration Capability by Jellyfish Search Algorithm

202182 citationsOpen accessKafr el-Sheikh University

In plain language

Modern automated distribution systems require optimal operational strategies to control line switches and manage controllable devices effectively. A proposed technique uses the Jellyfish Search Algorithm to achieve optimal voltage and reactive power coordination in automated distribution systems. This approach jointly considers network reconfiguration, distributed generation unit integration, and the operation of distribution static reactive power compensators. Applied to manage the dynamic operation of networks under regular daily loading conditions, the algorithm aims to minimise energy losses and cut emissions. The methodology was evaluated on standard 33-bus and 69-bus power distribution systems across multiple operational scenarios. In these evaluations, the algorithm successfully solved the complex control problem, consistently outperforming comparable approaches. The findings highlight its potential utility as an operational tool within modern distribution system control centres.

Key takeaways

  • A technique based on the Jellyfish Search Algorithm optimises voltage and reactive power coordination in automated distribution systems.
  • The approach jointly manages network reconfiguration, distributed generation integration, and static reactive power compensators.
  • Dynamic implementation under daily load profiles effectively reduces system losses and lowers emissions.
  • Validation on 33-bus and 69-bus test distribution networks showed superior performance compared to similar optimisation methods.

Why it matters

As power grids incorporate more local generation and automated controls, managing switch configurations and equipment becomes increasingly complex. Optimising these systems dynamically ensures electricity reaches consumers with fewer energy losses and lower operational emissions. Reliable automated control tools help utilities operate modern distribution networks more efficiently, supporting cleaner energy integration while maintaining grid stability under changing daily demand.

Commercialisation angle

The method could enable software tools for real-time network management, targeting power system operators and control centre engineers in utilities running automated distribution systems. Evaluated on standard simulated test feeders such as 33-bus and 69-bus networks, the work represents applied, simulation-tested research that would require integration and testing within commercial grid management systems before reaching operational use.

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Abstract

Power system operators and planners have progressively shown an interest in maximizing distribution automation technologies. The automated distribution systems (ADS) provide the capability of efficient and reliable control which require an optimal operation strategy to control the status of the line switches and also dispatch the controllable devices. Therefore, this paper introduces an efficient and robust technique based on Jellyfish Search Algorithm (JFSA) for optimal Volt/VAr coordination in ADSs based on joint distribution system reconfiguration (DSR), distributed generation units (DGs) integration and Distribution static VAr compensators (SVCs) operation. The suggested technique is used for the dynamic operation of ADS in order to minimize losses and reduce emissions when considering regular daily loading conditions. The 33-bus and 69-bus delivery DSs have been subjected to a variety of scenarios. These situations are mostly concerned with achieving optimum distribution system operation and control, as well as validating the proposed methodology. Despite the problem’s complexity, the proposed technique based on JFSA is shown to be the best solution in all of the cases considered. Furthermore, a comparison of the proposed JFSA with other similar approaches demonstrates its usefulness as a method to be used in modern ADS control centers.

Research topics

  • Optimal Power Flow Distribution
  • Microgrid Control and Optimization
  • Smart Grid Energy Management

Sustainable Development Goals

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DOI: 10.1109/access.2021.3092337

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