The increasing share of renewable energy sources makes energy supply more weather-dependent, challenging supply quality and system stability. To address these challenges without extensive infrastructure expansion, this paper presents a method for estimating and optimizing the energy flexibility potential of factory designs by correlating factory energy demand with the residual load—the portion of demand not met by renewables and a key indicator of local grid constraints. Using the relocation coefficient as a metric, we identify factory layouts that maximize flexibility and demonstrate the approach in an aluminum foundry, achieving reduced system stability costs without compromising production performance. Building on this, we introduce an operational optimization framework that integrates market and grid congestion signals into production planning via a digital twin, enabling real-time, multi-criteria optimization. Together, these methods support manufacturing enterprises in adapting to volatile energy systems and leveraging flexibility markets.