Digital overcurrent relays coordination in renewable microgrids utilizing several operating characteristics using educational competition optimizer

Faculty Engineering Year: 2025
Type of Publication: ZU Hosted Pages:
Authors:
Journal: Energy Reports Elsevier Volume:
Keywords : Digital overcurrent relays coordination , renewable microgrids    
Abstract:
Renewable microgrids (MGs), characterized by bi-directional power flow, require enhanced attention in designing protection schemes, particularly in the coordination of overcurrent relays (OCRs). Accordingly, a fresh metaheuristic algorithm named educational competition optimizer (ECO) is proposed in this study to solve the OCRs coordination problem with various operation scenarios among digital relays. Additionally, two fitness functions are incorporated into the optimization mechanism considering several relay operating characteristics (CCs) along with continuous current pickup and time dial. In this context, the programmed simulation model is validated rigorously against two other metaheuristic optimizers: artificial bee colony (ABC) and dung beetle optimizer (DBO). Initially, the effectiveness of the ECO is assessed on the IEEE 15-bus benchmark network prior to validating the proposed methodology in the IEC benchmark MG. Considering all operational scenarios, ECO attempts the best shot in minimizing the total operating time (TOT) of OCRs in both investigated networks. For instance, the ECO attains TOT of 3.2704 s and 6.3968 s with various operating CCs for 15-bus and IEC MG respectively. Undoubtedly, ECO earns this rival for all scenarios compared to ABC and DBO besides additional 16 metaheuristic literature algorithms. It is worth highlighting that when optimizing the OCR’s curve among 17 CCs, TOT is enhanced by 64.9 % and 43 % compared to fixed standard curve for 15-bus and MG respectively. Eventually, ECO consistently proves its superiority over other published optimizers in addressing the complex problem of OCR’s coordination especially in renewable MGs.
   
     
 
       

Author Related Publications

  • Attia Abdelaziz Hussien Ali, "Artificial ecosystem-based optimiser to electrically characterise PV generating systems under various operating conditions reinforced by experimental validations", Wiley, 2021 More
  • Attia Abdelaziz Hussien Ali, "An Improved Artificial Jellyfish Search Optimizer for Parameter Identification of Photovoltaic Models", Multidisciplinary Digital Publishing Institute, 2021 More
  • Attia Abdelaziz Hussien Ali, "Parameters identification of PV triple-diode model using improved generalized normal distribution algorithm", Multidisciplinary Digital Publishing Institute, 2021 More
  • Attia Abdelaziz Hussien Ali, "Adaptive and efficient optimization model for optimal parameters of proton exchange membrane fuel cells: A comprehensive analysis", Elsevier, 2021 More
  • Attia Abdelaziz Hussien Ali, "Model parameters extraction of solid oxide fuel cells based on semi-empirical and memory-based chameleon swarm algorithm", Wiley, 2021 More

Department Related Publications

  • Raef Seam Sayed Ahmed, "Model predictive control algorithm for fault ride-through of stand-alone microgrid inverter", Elsevier Ltd., 2021 More
  • Enas Ahmed Mohamed Abdelhay, "Recent Maximum Power Point Tracking Methods for Wind Energy Conversion System", Elsevier, 2024 More
  • Raef Seam Sayed Ahmed, "Optimal design and analysis of DC–DC converter with maximum power controller for stand-alone PV system", Elsevier Ltd., 2021 More
  • Raef Seam Sayed Ahmed, "Parameters identification and optimization of photovoltaic panels under real conditions using Lambert W-function", Elsevier Ltd., 2021 More
  • Attia Abdelaziz Hussien Ali, "Artificial ecosystem-based optimiser to electrically characterise PV generating systems under various operating conditions reinforced by experimental validations", Wiley, 2021 More
Tweet