Forward temperatures and production planning in district heating systems

21st International Scientific Conference on Advanced in Civil Engineering "Construction - The Formation of Living Environment"

土木建筑工程

Kultyaev, Svyatoslav^1

Yury Gagarin Saratov State Technical University, Politekhnicheskaya str. 77, Saratov, Russia^1

关键词: Controlling parameters;    Distribution planning;    District heating system;    Prediction and control;    Production Planning;    Short term planning;    Supply temperatures;    Traditional models;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/365/2/022053/pdf
DOI  :  10.1088/1757-899X/365/2/022053

学科分类：土木及结构工程学

来源: IOP

【 摘 要 】

Subject of study: short-term planning in district heating systems. The major goal is to minimize the operation cost, subject to the condition of fulfilling the heat demand. We propose a new concept for controlling the supply temperature in district heating systems using stochastic modeling, prediction and control. A district heating systems is a difficult system tocontrol (optimally) as the dynamic relationship between supply temperature(the control variable) and key parameters such as network temperature and flow rate are time-varying and difficult to establish,which in both cases can be attributed to the time-varying heat load in the system. Materials and methods: we have summarized results of many research papers on District heating systems and primary principles of heat exchange theory. Results: describes a concept for controlling the supply temperature in district heating systems using stochastic modeling, prediction and control.. Conclusions: This document discusses how to consider distribution planning, with a focus on how to handle the forward temperature. Focus is on how to handle the forward temperature. Two alternative approaches are suggested. The first applies transformation of data before an ordinary load prediction algorithm is applied. The second models the district heating system as a network As we all know the controlling parameter for modeling the heating system is temperature. However, the traditional model does not account for the change in load of the consumers in time. Temperature forward still needs to be predicted, or more correctly, to optimize In that sense the load forecasting problem and the planning problem are linked.