District energy system is an underground network used to cool and heat buildings efficiently, which has the characteristics of large scale, multiple equipment, large lag, nonlinear and time-varying dynamics. The traditional feedback control strategies not only cause mismatch and hysteresis of energy supply and load demand in time series but also lead to high energy consumption. Therefore, a forecasted load-and time delay-based model predictive control district energy system model is proposed in this paper. Taking a district energy system in Tianjin University as a test case, the superiority of the proposed control model is ascertained. A TRNSYS and MATLAB co-simulation platform is developed as the test platform. The results show that the proposed control model can not only improve matching the extent of energy supply and load demand in time series, but can also reduce the energy peak and total energy consumption of the district energy system. Specifically, energy consumption is reduced by 9.56% and 5.30% in summer and 7.75% and 2.61% in winter compared with the control models based on the traditional feedback control and load feedforward fuzzy control strategies, respectively.

中文翻译：

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基于预测负荷和时滞的模型预测控制（MPC）区域能源系统模型研究


区域能源系统是用于建筑物高效供冷、供热的地下管网，具有规模大、设备多、滞后大、非线性和时变动态等特点。传统的反馈控制策略不仅造成能源供应与负荷需求在时间序列上的不匹配和滞后，而且导致能源消耗较高。因此，本文提出了一种基于预测负荷和时滞的模型预测控制区域能源系统模型。以天津大学区域能源系统为例，验证了所提控制模型的优越性。开发了TRNSYS和MATLAB联合仿真平台作为测试平台。结果表明，所提出的控制模型不仅可以提高能源供应与负荷需求在时间序列上的匹配程度，而且可以降低区域能源系统的能源峰值和能源消耗总量。具体而言，与基于传统反馈控制和负荷前馈模糊控制策略的控制模型相比，夏季能耗分别降低了9.56%和5.30%，冬季能耗降低了7.75%和2.61%。