Stochastic model predictive control (SMPC) considering randomness constraints for weather characteristics has been widely adopted to achieve energy diminution and human comfort regulation for building energy management (BEM). However, the substantial computational loads involved in solving the complex optimization problem pose a significant challenge to the real-time implementation of SMPC in actual building systems. The event-triggered mechanism (ETM) has exhibited a huge potential that runs optimization only when the pre-specified events occur, contrasting with the time-triggered mechanism (TTM) that triggers at each step causing useless wastage of computational resources. To address this challenge, this paper develops a stochastic event-triggered mechanism (SETM), which determines the triggering instant of the SMPC controller via considering simultaneously current-future states and the inherent randomness of weather. This approach significantly reduces the controller update frequency without degrading the thermal comfort. Besides, the convergence properties of the proposed SET-SMPC strategy are rigorously analyzed, providing theoretical guarantees for closed-loop stability. Finally, the control performance of the suggested SET-SMPC strategy is validated through a real thermal environment variable air volume air conditioning (VAV-AC) system, and the results indicate the superior performance of SET-SMPC. Specifically compared to the MPC, the SET-SMPC and SMPC can reduce 30.08 %–33.3 % and 25 %–33.3 % energy consumption, respectively, and compared to MPC and SMPC strategies employing TTM, the SET-SMPC can reduce 48.1 %–67.6 % computational load while maintaining the comfortable.

中文翻译：

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用于建筑能源管理的事件触发随机模型室内热环境预测控制

考虑天气特性随机性约束的随机模型预测控制 （SMPC） 已被广泛采用，以实现建筑能源管理 （BEM） 的能量减少和人体舒适度调节。然而，解决复杂的优化问题所涉及的大量计算负载对 SMPC 在实际建筑系统中的实时实现构成了重大挑战。事件触发机制 （ETM） 表现出了巨大的潜力，它仅在预先指定的事件发生时运行优化，相比之下，时间触发机制 （TTM） 在每个步骤都会触发，从而导致无用的计算资源浪费。为了应对这一挑战，本文开发了一种随机事件触发机制 （SETM），它通过同时考虑当前-未来状态和天气的固有随机性来确定 SMPC 控制器的触发时刻。这种方法显著降低了控制器更新频率，而不会降低热舒适性。此外，对所提出的 SET-SMPC 策略的收敛特性进行了严格分析，为闭环稳定性提供了理论保证。最后，通过真实的热环境变风量空调 （VAV-AC） 系统验证了所提出的 SET-SMPC 策略的控制性能，结果表明 SET-SMPC 的优越性能。具体而言，与 MPC 相比，SET-SMPC 和 SMPC 可分别降低 30.08 %–33.3 % 和 25 %–33.3 % 的能耗，与采用 TTM 的 MPC 和 SMPC 策略相比，SET-SMPC 可降低 48.1 %–67.6 % 的计算负载，同时保持舒适性。