scholarly journals Predictive Control of District Heating System Using Multi-Stage Nonlinear Approximation with Selective Memory

Energies ◽  
2020 ◽  
Vol 13 (24) ◽  
pp. 6714
Author(s):  
Marius Reich ◽  
Jonas Gottschald ◽  
Philipp Riegebauer ◽  
Mario Adam

Innovative heating networks with a hybrid generation park can make an important contribution to the energy turnaround. By integrating heat from several heat generators and a high proportion of different renewable energies, they also have a high degree of flexibility. Optimizing the operation of such systems is a complex task due to the diversity of producers, the use of storage systems with stratified charging and continuous changes in system properties. Besides, it is necessary to consider conflicting economic and ecological targets. Operational optimization of district heating systems using nonlinear models is underrepresented in practice and science. Considering ecological and economic targets, the current work focuses on developing a procedure for an operational optimization, which ensures a continuous optimal operation of the heat and power generators of a local heating network. The approach presented uses machine learning methods, including Gaussian process regressions for a repeatedly updated multi-stage approximation of the nonlinear system behavior. For the formation of the approximation models, a selection algorithm is utilized to choose only essential and current process data. By using a global optimization algorithm, a multi-objective optimal setting of the controllable variables of the system can be found in feasible time. Implemented in the control system of a dynamic simulation, significant improvements of the target variables (operating costs, CO2 emissions) can be seen in comparison with a standard control system. The investigation of different scenarios illustrates the high relevance of the presented methodology.

2010 ◽  
Vol 27 (1) ◽  
pp. 6-18 ◽  
Author(s):  
Ui Sik Kim ◽  
Tae Chang Park ◽  
Lae-Hyun Kim ◽  
Yeong Koo Yeo

2014 ◽  
Vol 709 ◽  
pp. 294-299
Author(s):  
Hang Bing Wang ◽  
Dong Dong Lou ◽  
Ya Song Wang ◽  
Hua Rong Sun

This paper systematically presents a thorough analysis on the construction of the heating monitoring system in Nanjing General Hospital, China. The monitoring method and strategy of were discussed in detail. Besides, the optimization design of the simple closed loop control system was conducted. Finally, an optimal operation analysis system consisting of the heating host machine, costumer thermal monitoring system, and outside environment monitoring system for the heating room was established. As a result, the heating quality, the heating efficiency, and the relationship with costumer were greatly improved.


2021 ◽  
Vol 230 ◽  
pp. 110538
Author(s):  
Menglong Lu ◽  
Chao Zhang ◽  
Dayu Zhang ◽  
Ruixin Wang ◽  
Zhigang Zhou ◽  
...  

Author(s):  
Sara Cosentino ◽  
Elisa Guelpa ◽  
Roberto Melli ◽  
Adriano Sciacovelli ◽  
Enrico Sciubba ◽  
...  

District heating networks (DHNs) are crucial infrastructures for the implementation of energy efficiency and CO2 reduction plans, especially in countries with continental climate. DHNs are often complex systems and their energy performance may be largely affected by the operating conditions. Optimal operation of DHNs involves the optimization of the pumping system. This is particularly important for large networks and for low temperature networks. A common practice to perform optimization consists in using a phyical model. Nevertheless, simulation and optimization of DHNs may involve large computational resources, because of thire possible large extension and the number of scenarios to be examined. A reduced model, obtained from the physical model, can be effectively applied to multiple simulations of a network, with significant reduction of the computational time and resources. In this paper, a large district heating system, which supplies heating to a total volume of buildings of about 50 million of cubic meters, is considered. The use of a reduced model based on proper orthogonal decomposition (POD) is investigated. Various operating conditions corresponding to partial load operation are analyzed using a fluid-dynamic model of the network. Results show that optimal settings are not particularly regular with respect to load variation. This means that any variation in the thermal load generally involves changes in the set points of all groups. For this reason, a sensitivity analysis is performed using the POD model in order to check the opportunities to limit the number of variations in the pumping settings without significant penalization of the total pumping power. The proposed approach is shown to be very effective for the optimal management of complex district heating systems.


1995 ◽  
Vol 36 (5) ◽  
pp. 297-314 ◽  
Author(s):  
Atli Benonysson ◽  
Benny Bøhm ◽  
Hans F. Ravn

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