Multi-Objective Optimization Of PV Solar Integration In Smart Grids: Balancing Technical Reliability, Economic Viability, And Environmental Sustainability

Abstract

The rapid growth of solar photovoltaic (PV) deployment is reshaping modern power systems, creating opportunities for decarbonization but also challenges in ensuring grid reliability, cost efficiency, and environmental sustainability. This study presents a tri-objective optimization framework for PV integration in smart grids, simultaneously minimizing reliability indices (LOLP, SAIDI, SAIFI), economic costs (LCOE, NPC), and lifecycle CO₂ emissions, with explicit modeling of uncertainty in load demand, solar variability, and electricity market prices. A Monte Carlo simulation approach captures stochastic fluctuations, while the optimization is executed using NSGA-II and benchmarked against MOPSO and MOEA/D. The framework is validated on the IEEE 118-bus system using real South Zone demand, NIWE solar irradiance, and IEX market data. Results show that high PV penetration increases curtailment and duck-curve effects, but coordinated deployment of battery energy storage systems (BESS) significantly improves reliability, reduces NPC by up to 15%, and lowers CO₂ emissions by 26–32%. Multi-criteria decision analysis identifies 40% PV+BESS as the most balanced configuration. The proposed framework provides a scalable decision-support tool for policymakers and utilities pursuing resilient and sustainable smart grids.