Title: Quantum-Theoretic Optimization Framework for Smart Renewable Energy Integration and Techno-Economic Stability in Hybrid Power Systems
Authors: Amadi Oko Amadi
Onuoha Raymond Udochukwu
Ifeanyi Moses Iwueze
Volume: 10
Issue: 6
Pages: 10-16
Publication Date: 2026/06/28
Abstract:
The rapid growth of renewable energy deployment within modern power systems has created significant opportunities for sustainable electricity generation while simultaneously introducing challenges related to intermittency, uncertainty, grid stability, and economic viability. Although conventional optimization techniques such as Particle Swarm Optimization (PSO) and Genetic Algorithms (GA) have been widely applied to renewable energy management, their effectiveness is often limited when addressing the complex multi-objective requirements of hybrid renewable energy systems (Deb et al., 2020; Wang et al., 2023). This study proposes a Quantum-Theoretic Optimization Framework (QTOF) for smart renewable energy integration aimed at enhancing techno-economic stability in hybrid power systems comprising solar photovoltaic (PV), wind energy, battery energy storage systems (BESS), and grid-connected backup generation. The framework integrates quantum probability theory, quantum-inspired optimization algorithms, and multi-objective decision-making strategies to optimize energy dispatch, storage scheduling, and load balancing under uncertain operating conditions (Biamonte et al., 2017; Ajagekar and You, 2020). Empirical evaluation was conducted using a simulated 10 MW hybrid renewable energy microgrid consisting of solar PV (40%), wind energy (30%), battery storage (20%), and utility grid support (10%). Results indicate that the proposed framework reduced operational costs by 28.6%, increased renewable energy utilization by 35.2%, improved grid stability by 24.7%, and reduced carbon emissions by 41.3% compared with conventional optimization approaches. Furthermore, the Levelized Cost of Electricity (LCOE) decreased from US$0.142/kWh to US$0.101/kWh, while system reliability increased from 92.8% to 98.1%. Statistical analysis confirmed significant improvements in operational efficiency, reliability, and economic performance (p < 0.05). The findings demonstrate that quantum-theoretic optimization offers a viable pathway for achieving intelligent, resilient, and economically sustainable smart grids, thereby supporting global renewable energy integration and net-zero carbon transition objectives (Lund et al., 2022; IEA, 2024).