Large-scale industries often deploy on-site fossil-fuel-based power sources alongside the central power grid to meet continuous high-power demand and reduce vulnerability, which increases their carbon footprint and operating costs. Appropriately sized renewable energy sources (RESs) and energy storage systems (ESSs) can meet demand during outages, reducing emissions and costs. However, accounting for techno-economic, operational, and weather-related variability of RESs remains a significant challenge. Several commercial and open-source optimisation tools have been developed and are widely used in industry to optimally size, plan, and manage RESs and ESSs, accounting for system integration, technical operations, weather conditions, expenditures, energy markets, and asset degradation. This article proposes a framework to optimally size, plan, and manage multi-energy systems for large-scale industrial plants by integrating power generation, storage, and the main grid, and compares it with existing optimisation tools. Power generation and storage capacities were compared based on different optimisation goals. The analysis uses identical power demand profiles, system configurations, and solver settings across all platforms, to the extent possible, to ensure a fair comparison. Some optimisation tools use preferred factors they consider necessary and lack transparency, which may lead to technically infeasible or economically suboptimal investment decisions in industrial energy infrastructure.