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Model predictive control of building HVAC system employing zone thermal energy requests

机译：利用区域热能需求的建筑HVAC系统的模型预测控制

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Control in buildings has been a subject of research interest in the control community for some time. Various control methods have shown a potential for a significant savings in the building operation costs, whereas a large economic gain in the operation of a heating, ventilation and air conditioning (HVAC) system can be obtained by employing information about the building thermal model and the model of actuators, weather conditions, energy demand cost as well as the energy requests in the zones. This paper proposes a model predictive controller for a building chiller that exploits respective information to minimise the cost of cooling in the electricity market with volatile electrical energy prices, while ensuring comfort within the zones and respecting the power demand limitations. Obtained optimal control problem is nonlinear and the minimisation is performed by employing the successive linear programming algorithm within the feasibility region and the gradient algorithm for finding the initial feasible point. A case study HVAC system model is used to validate the performance of the proposed controller in the simulation scenario. Obtained controller minimises the cost of cooling while adhering to the imposed comfort constraints.
机译：建筑物的控制一直是控制界的研究兴趣的主题。各种控制方法已经显示出在建筑运营成本中显着节省的潜力，而通过采用有关建筑物热模型和建筑物热模型的信息，可以获得加热，通风和空调（HVAC）系统的巨大经济增益。执行器，天气条件，能源需求成本以及区域中的能源要求的模型。本文提出了一种模型预测控制器，用于建筑冷却器，用于利用各种信息，以最小化电力市场的冷却成本以易失性的电能价格，同时确保区域内的舒适度并尊重电力需求限制。获得的最佳控制问题是非线性的，并且通过在可行性区域内采用连续的线性编程算法和用于查找初始可行点的梯度算法来执行最小化。案例研究HVAC系统模型用于验证建议控制器在模拟方案中的性能。获得的控制器最小化冷却成本，同时粘附到施加的舒适约束。

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