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Real-time combined heat and power operational strategy using a hierarchical optimization algorithm

机译:使用分层优化算法的实时热电联产运营策略

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Existing attempts to optimize the operation of combined heat and power (CHP) systems for building applications have two major limitations: the electrical and thermal loads are obtained from historical weather profiles; and the CHP system models ignore transient responses by using constant equipment efficiencies. This article considers the transient response of a building combined with a hierarchical CHP optimal control algorithm to obtain a real-time integrated system that uses the most recent weather and electric load information. This is accomplished by running concurrent simulations of two transient building models. The first transient building model uses current as well as forecast input information to obtain short-term predictions of the thermal and electric building loads. The predictions are then used by an optimization algorithm (i.e. a hierarchical controller that decides the amount of fuel and of electrical energy to be allocated at the current time step). In a simulation, the actual physical building is not available and, hence, to simulate a real-time environment, a second, building model with similar but not identical input loads are used to represent the actual building. A state-variable feedback loop is completed at the beginning of each time step by copying (i.e. measuring, the state variable from the actual building and restarting the predictive model using these 'measured' values as initial conditions). The simulation environment presented in this article features non-linear effects such as the dependence of the heat exchanger effectiveness on their operating conditions. The results indicate that the CHP engine operation dictated by the proposed hierarchical controller with uncertain weather conditions has the potential to yield significant savings when compared with conventional systems using current values of electricity and fuel prices.
机译:现有的为建筑应用优化热电联产(CHP)系统运行的尝试有两个主要局限性:电气和热负荷是从历史天气概况中获得的; CHP系统模型通过使用恒定的设备效率来忽略瞬态响应。本文考虑了建筑物的瞬态响应,并结合了分层的CHP最优控制算法来获得使用最新天气和电力负荷信息的实时集成系统。这是通过同时运行两个瞬态构建模型的仿真来完成的。第一个瞬态建筑模型使用当前以及预测输入信息来获得热和电建筑负荷的短期预测。然后,通过优化算法(即确定当前时间步长要分配的燃料和电能的量的分层控制器)使用预测。在模拟中,实际的物理建筑物不可用,因此,为了模拟实时环境,将使用具有相似但不相同的输入负载的第二个建筑物模型来代表实际建筑物。通过复制(即从实际建筑物中测量状态变量并使用这些“测量”值作为初始条件重新启动预测模型),在每个时间步的开始就完成了状态变量反馈环。本文介绍的模拟环境具有非线性效应,例如热交换器效率对其运行条件的依赖性。结果表明,与使用电流和燃料价格的当前值的常规系统相比,所提出的分层控制器在不确定的天气条件下所决定的CHP发动机运行具有节省大量能源的潜力。

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