The global challenge of food shortage, exacerbated by population growth, climate change, and economic disparities, demands innovative agricultural solutions. Vertical farming (VF) emerges as a promising alternative, offering higher yields, efficient land use, minimal water and nutrient usage, and the potential for urban integration. However, VFs face significant barriers, primarily due to their high energy demands for artificial lighting and climate control. This study investigates how vertical farming can contribute to local energy grid stabilization through optimized energy management strategies. Focusing on a case study in Zeeland, Netherlands, an area with significant grid congestion, this research develops a Mixed-Integer Linear Programming (MILP) model to dynamically adjust energy consumption based on real-time data from photovoltaic (PV) panels, battery storage, and grid prices. The primary objective is to minimize energy fed back to the grid, while a secondary objective is to reduce operational costs. Results indicate that optimized energy management can significantly reduce costs and impact on the grid. Flexible light schedules, aligned with periods of low energy costs and high solar PV generation, enhance grid stability and economic viability. This study highlights the potential of vertical farms to support the energy grid, contributing to the broader goal of a sustainable and resilient food system.