Hydropower remains a cornerstone of renewable energy, yet small-scale plants in developing regions often underperform due to suboptimal design and outdated optimization approaches. This study addresses these limitations by developing a novel dual-objective optimization framework for the Challawa Gorge Dam in Kano State, Nigeria, leveraging Sequential Quadratic Programming (SQP) to simultaneously maximize power output and minimize water consumption. Using MATLAB-based simulations integrated with Monte Carlo flow analysis, we optimize penstock design, turbine selection, and operational parameters under real-world constraints (cavitation index σ > 0.12, surge pressure < 5% gross head). Our results demonstrate a 19.8% increase in power generation (5.73 MW achieved) alongside a 12.1% reduction in water usage (8.79 m3/s), outperforming conventional Particle Swarm Optimization (PSO) methods by 15.3% in efficiency. This work provides both a technical roadmap for sustainable hydropower expansion and actionable insights for policymakers targeting Nigeria’s 2030 renewable energy goals.
| Primary Language | English |
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| Subjects | Hydroelectric Energy Systems |
| Journal Section | Research Article |
| Authors | |
| Publication Date | June 26, 2025 |
| Submission Date | January 24, 2025 |
| Acceptance Date | May 30, 2025 |
| Published in Issue | Year 2025 Volume: 10 Issue: 2 |