Energy management in commercial buildings is a challenging task due to their specific set of requirements. One such building that has not been fully investigated in the literature to provide energy efficiency is a university building. There are many challenges associated while managing the energy of a university building, such as-scheduling of classes, availability of faculty, and capacity of classrooms. To address these challenges for providing better energy efficiency, an efficient heating, ventilation, and air-conditioning (HVAC) management scheme for a university building is presented in this paper. The HVAC loads are chosen as these are more flexible in the classrooms than other loads, such as-lighting and projectors. In this paper, the HVAC energy management problem is formulated as a mixed-integer linear programming (MILP) problem. To solve this problem, a heuristic-based algorithm is proposed, which optimally minimizes the use of HVAC without affecting user comfort. Moreover, it also minimizes the cost of rescheduling the classes on a given day. The results obtained on the dataset traces taken from a university building clearly indicate that the proposed scheme reduces the energy demand of HVAC systems by 19.75% for an entire week without affecting the user comfort. Moreover, this scheme shows superior performance when compared with existing commercial demand response management schemes with respect to load reduction and cost savings.

中文翻译：

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基于启发式的大学建筑智能暖通空调能源管理方案


由于其特定的要求，商业建筑的能源管理是一项具有挑战性的任务。文献中尚未充分研究提供能源效率的此类建筑之一是一所大学建筑。管理大学建筑的能源时存在许多挑战，例如课程安排、教师的可用性和教室的容量。为了应对这些挑战，提供更好的能源效率，本文提出了一种针对大学建筑的高效供暖、通风和空调 (HVAC) 管理方案。选择 HVAC 负载是因为这些负载在教室中比其他负载（例如照明和投影仪）更灵活。在本文中，HVAC 能源管理问题被表述为混合整数线性规划（MILP）问题。为了解决这个问题，提出了一种基于启发式的算法，该算法可以在不影响用户舒适度的情况下最大限度地减少 HVAC 的使用。此外，它还最大限度地减少了在特定日期重新安排课程的成本。从一所大学建筑中获取的数据集轨迹获得的结果清楚地表明，所提出的方案将 HVAC 系统的能源需求降低了 19.75%，整整一周，而不影响用户的舒适度。此外，与现有的商业需求响应管理方案相比，该方案在减少负载和节省成本方面表现出优越的性能。