Multi-objective optimisation of intermittent LSSPV placement for grid stability using FIPSMA

Aligned with Malaysia’s Twelfth Plan to accelerate renewable energy adoption, this thesis addresses the challenges of integrating high-penetration Large-Scale Solar Photovoltaic (LSSPV) systems into distribution networks which includes intermittency, voltage variability, reverse power flow and increased losses. A two-phase approach is developed to mitigate voltage instability, power loss, and intermittency issues. In Phase 1, the IEEE 39-bus system is embedded with a Western Electricity Coordinating Council (WECC) generic solar model and shunt capacitor compensation to examine system stability under fault conditions. The model demonstrates improved voltage performance and measurable loss reduction. Phase 2 introduces a hybrid optimisation technique, the Fast Iterative Process Slime Mould Algorithm (FIPSMA), formulated using a multi-objective function that incorporates power loss, voltage deviation and voltage stability indices. FIPSMA is tested on three LSSPV capacities (50 MW, 20 MW, and 10 MW) under varying intermittency scenarios based on high-resolution temporal load profiles. The novelty of this study lies in developing a new Typical LSSPV (TYP) profile representing ideal non-fluctuating output and introducing FIPSMA designed to improve convergence stability and overcome limitations found in PSO and GA. Across all scenarios, FIPSMA achieves significant improvement in voltage deviation, consistent reduction in total active and reactive power losses and up to 95% faster convergence compared to PSO and GA. The TYP profile demonstrates a strong correlation (R² = 0.835) with real operational data. Collectively, the proposed methods establish a robust and scalable framework for optimal LSSPV allocation and grid stability enhancement under uncertain demand and intermittent solar conditions.