用户指定的开尔文小时预算在节能建筑模型预测控制中的应用：仿真与现场演示
User-specified Kelvin-hour budgets within model predictive control for energy-efficient buildings: Simulation and field demonstration
- EPFL（洛桑联邦理工学院）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本文提出一种开尔文小时预算模型预测控制方法，允许用户指定温度违规预算，在仿真和现场部署中显著降低能耗和违规，实现节能与舒适度的可调平衡。
AI中文摘要：
对于节能建筑控制，模型预测控制（MPC）已被广泛提出，以在维持规定的室内温度界限的同时减少能源使用。在实践中，由于模型失配、天气预报误差以及为保持可行性而引入的软约束，MPC实现仍可能产生温度界限违规。现有的软约束MPC通常通过松弛权重调整来处理这种权衡，因此用户无法在运行前规定违规严重性预算。本文开发了一种开尔文小时（Kh）预算MPC，允许用户指定温度界限违规严重性的运行平均预算。在运行期间，控制器利用已实现的Kh预算盈余或超支来更新温度界限，提供逐步的预算反馈。我们在两个高保真BOPTEST仿真案例和一个有人居住的住宅部署中评估了该方法。在第一个单区域案例中，规定的预算在各种预测器和扰动设置下产生了清晰的平均Kh违规响应。在规定的预算为0.005 Kh/步时，与内置默认控制器相比，控制器将能源使用减少了31.9%，Kh违规减少了36.2%。在第二个耦合双区域案例中，单独的区域预算产生了区域级响应，能源减少18.9%-20.5%，区域级Kh违规减少9.4%-64.3%。在有人居住的住宅部署中，在真实传感、执行、天气和占用条件下，运行平均Kh违规保持接近或低于其规定预算。
英文摘要：
For energy-efficient building control, model predictive control (MPC) has been widely proposed to reduce energy use while maintaining prescribed indoor temperature bounds. In practice, MPC implementations may still produce temperature-bound violations because of model mismatch, weather-forecast errors, and softened constraints introduced to preserve feasibility. Existing soft- constrained MPC usually handles this trade-off through slack-weight tuning, so users cannot prescribe a violation-severity budget before operation. This paper develops a Kelvin-hour (Kh)-budget MPC that allows users to specify a running-average budget for temperature-bound violation severity. During operation, the controller uses the realized Kh budget surplus or overspend to update the temperature bounds, providing step-by-step budget feedback. We evaluate the method in two high-fidelity BOPTEST simulation cases and in an occupied residential deployment. In the first one-zone case, prescribed budgets produce clear running-average Kh violation responses across predictors and disturbance settings. At a prescribed budget of 0.005 Kh/step, the controller reduces energy use by 31.9% and Kh violation by 36.2% relative to the built-in default controller. In the second coupled two-zone case, separate zone budgets produce zone-level responses, with 18.9%-20.5% energy reduction and 9.4%-64.3% zone-level Kh violation reduction. In the occupied residential deployment, the running-average Kh violations remain close to or below their prescribed budgets under real sensing, actuation, weather, and occupancy conditions.
