The energy management problem of microgrid structures have developed and ramified into a diverse range of strategies, models, algorithms, and objectives. However, specific combinations of all these components suit different goals, and in this paper, the authors investigate the suitable energy management methods and objectives that can achieve the goal of minimizing energy consumption whilst ensuring livestock comfort in a farm microgrid. Two optimizing algorithms, gradient descent and particle swarm optimization, are used to seek out the balance between livestock’s thermal comfort and energy usage. This balance is mathematically represented by a priority-weighted two-component objective function that includes temperature and electricity consumption terms. After testing each algorithm on two cases, it was found that both of the algorithms provide more benefit with a schedule than without any optimization. Although each algorithm approaches the problem differently, they all show that the Heating, Ventilation, and Air Conditioning (HVAC) system can be scheduled for satisfying quality life of livestock and saving energy.