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A modified walrus optimization algorithm for multi-objective sizing and excess energy management of hybrid microgrid in coastal communities with excess-driven freshwater desalination

Research output: Contribution to journalArticlepeer-review

Abstract

Energy–water nexus optimization is crucial for off-grid coastal communities, where freshwater production is energy-intensive and renewable resources are intermittent. In stand-alone hybrid renewable energy systems (HRESs), temporal mismatches between variable generation and demand often cause surplus energy curtailment. Integrating reverse-osmosis desalination (ROD) with HRES offers a sustainable solution by utilizing the ROD plant as a flexible load for excess renewable output. This study proposes a stand-alone hybrid microgrid for a coastal community in Yanbu, Saudi Arabia, designed for joint energy–water optimization. The system integrates solar photovoltaic (PV), wind turbines (WTs), battery storage (BAT), and a diesel generator (DsG) to ensure a reliable power and freshwater supply. System sizing is performed using a modified Walrus Optimization (mWO) algorithm that mitigates premature convergence and local optima issues of the original WO. The mWO incorporates leader-based mutation–selection (LBM), orthogonal learning (OL), and an adaptive exploration–exploitation controller for enhanced search balance. The objective function minimizes the levelized cost of energy (LCOE), loss of power supply probability (LPSP), and unutilized excess energy under operational constraints. The mWO is rigorously validated on benchmark functions and compared with the original WO and seven recent metaheuristics, showing faster and more stable convergence. Applied to the Yanbu case study and benchmarked against 18 algorithms, it achieves statistically superior performance. The optimal PV/WT/DsG/BAT/ROD configuration achieves an LCOE of 0.1714 $/kWh, a cost of water of 0.7715 $/m3, a 71.9% renewable fraction, and 1,500 tons/year of emissions. The results confirm that mWO-driven co-optimization offers a robust, low-cost, and sustainable pathway for autonomous coastal desalination microgrids.

Original languageEnglish
Article number101658
JournalEnergy Conversion and Management: X
Volume30
DOIs
StatePublished - May 2026

Bibliographical note

Publisher Copyright:
© 2026 The Author(s)

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 6 - Clean Water and Sanitation
    SDG 6 Clean Water and Sanitation
  2. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy
  3. SDG 14 - Life Below Water
    SDG 14 Life Below Water
  4. SDG 15 - Life on Land
    SDG 15 Life on Land

Keywords

  • Cost of water
  • Energy-water nexus
  • Excess energy management
  • Levelized cost of energy
  • Modified walrus optimization (mWO)
  • Reverse osmosis desalination

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • Nuclear Energy and Engineering
  • Fuel Technology
  • Energy Engineering and Power Technology

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