Cost-Effective Maintenance Planning for Reliable Hybrid Solar and Wind Energy Systems

This paper presents a novel maintenance planning model for hybrid solar and wind energy systems, integrating optimized energy production with maintenance scheduling to achieve cost-effective and reliable operations. The study addresses two interconnected challenges: first, optimizing the energy production system by determining the required number of solar photovoltaic (PV) panels and wind turbines to meet fluctuating random load demands, and second, developing a maintenance strategy that minimizes costs while ensuring system reliability. The model utilizes theoretical production data to estimate failure rates for PV and wind turbine systems based on their energy outputs. These failure rates are used to compute the average number of failures across varying maintenance schedules for the hybrid system. The optimization results reveal that the optimal number of preventive maintenance actions is two (N = 2) over a 12-period planning horizon, corresponding to an optimal maintenance cost of 2,139,003 NGN, while maintaining system reliability above 90%. Sensitivity analysis demonstrates the model’s robustness, showing that an increase in corrective maintenance costs leads to a proportional increase in maintenance frequency, with the model consistently prioritizing subsystems with higher failure rates. These findings highlight the model’s potential as a valuable decision-support tool for energy managers, enabling the development of effective maintenance strategies that minimize disruptions to energy production and align with real-world operational patterns.