This analysis reveals how AI-driven optimization and IoT can achieve net-zero carbon in the water sector, suggesting significant economic and environmental advantages.
This study presents an integrated smart water-energy nexus framework combining IoT-based water monitoring, hybrid renewables (hydropower/solar/wind), and AI-driven optimization. Real-time sensor data enables automated grid management, while AI analytics optimize operations and predict maintenance needs through a closed-loop system. The solution achieves bidirectional energy exchange, with the full hybrid system (G + H + PV + W) reducing costs by 41.5% (€831K) and LCOE by 57.2% (€0.0475/kWh). Financial analysis confirms viability with 26.4% IRR and 3.8-year payback, while achieving negative CO2 emissions (−160,476 kg/year). Progressive renewable integration enhances all key performance indicators (KPIs), cutting OPEX by 89.9% (€7,156/year) through optimized operations. Dual water-energy performance metrics (leakage, pressure, % renewable share) ensure balanced and sustainable grid management. Key innovations include IoT-energy synergy, AI-driven predictive maintenance, and circular resource efficiency. The framework demonstrates how smart water grids can achieve both economic and environmental benefits through renewable energy integration and advanced digital solutions.
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Ramos et al. (2025) studied this question.
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