Research on Data-Driven Operation Control of Secondary Loop of District Heating System

2021 ◽  
Author(s):  
Wei Zhong ◽  
Encheng Feng ◽  
Xiaojie Lin ◽  
Jinfang Xie
Keyword(s):  
District Heating ◽  
Heating System ◽  
Data Driven ◽  
District Heating System ◽  
Secondary Loop ◽  
Operation Control

scholarly journals Data-Driven Machine-Learning Model in District Heating System for Heat Load Prediction: A Comparison Study

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Fisnik Dalipi ◽  
Sule Yildirim Yayilgan ◽  
Alemayehu Gebremedhin
Keyword(s):  
Machine Learning ◽  
Heat Load ◽  
District Heating ◽  
Heating System ◽  
Partial Least Square ◽  
Supervised Machine Learning ◽  
Data Driven ◽  
Support Vector ◽  
Load Prediction ◽  
District Heating System

We present our data-driven supervised machine-learning (ML) model to predict heat load for buildings in a district heating system (DHS). Even though ML has been used as an approach to heat load prediction in literature, it is hard to select an approach that will qualify as a solution for our case as existing solutions are quite problem specific. For that reason, we compared and evaluated three ML algorithms within a framework on operational data from a DH system in order to generate the required prediction model. The algorithms examined are Support Vector Regression (SVR), Partial Least Square (PLS), and random forest (RF). We use the data collected from buildings at several locations for a period of 29 weeks. Concerning the accuracy of predicting the heat load, we evaluate the performance of the proposed algorithms using mean absolute error (MAE), mean absolute percentage error (MAPE), and correlation coefficient. In order to determine which algorithm had the best accuracy, we conducted performance comparison among these ML algorithms. The comparison of the algorithms indicates that, for DH heat load prediction, SVR method presented in this paper is the most efficient one out of the three also compared to other methods found in the literature.

scholarly journals A Data-Driven Method for Fault Detection and Isolation of the Integrated Energy-Based District Heating System

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 23787-23801 ◽  
Author(s):  
Mengshi Li ◽  
Weimin Deng ◽  
Kaishun Xiahou ◽  
Tianyao Ji ◽  
Qinghua Wu
Keyword(s):  
Fault Detection ◽  
District Heating ◽  
Heating System ◽  
Fault Detection And Isolation ◽  
Data Driven ◽  
District Heating System

scholarly journals Technology Pathways and Economic Analysis for Transforming High Temperature to Low Temperature District Heating Systems

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3218
Author(s):  
Pedro Durán ◽  
Herena Torio ◽  
Patrik Schönfeldt ◽  
Peter Klement ◽  
Benedikt Hanke ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Renewable Energy ◽  
High Temperature ◽  
Low Temperature ◽  
Economic Analysis ◽  
District Heating ◽  
Heating System ◽  
District Heating System ◽  
Heating Systems ◽  
District Heating Systems

There are 1454 district heating systems in Germany. Most of them are fossil based and with high temperature levels, which is neither efficient nor sustainable and needs to be changed for reaching the 2050 climate goals. In this paper, we present a case study for transforming a high to low temperature district heating system which is more suitable for renewable energy supply. With the Carnot Toolbox, a dynamic model of a potential district heating system is simulated and then transformed to a low temperature supply. A sensitivity analysis is carried out to see the system performance in case space constrains restrict the transformation. Finally, an economic comparison is performed. Results show that it is technically possible to perform the transformation until a very low temperature system. The use of decentralized renewable sources, decentralized heat storage tanks and the placement of a heat pump on each building are the key points to achieve the transformation. Regarding the sensitivity analysis, the transformation is worth doing until the seasonal storage and solar collector field sizes are reduced to 60% and 80% of their values in the reference case, respectively. The economic analysis shows, however, that it is hard for highly efficient low temperature renewable based heat networks to compete with district heating systems based on a centralized fossile CHP solution. Thus, though the presented transformation is technically possible, there is a strong need to change existing economic schemes and policies for fostering a stronger promotion of renewable energy policies in the heat sector.

Predicting Hourly Heating Load in a District Heating System Based on a Hybrid CNN-LSTM Model

2021 ◽  
pp. 110998
Author(s):  
Jiancai Song ◽  
Liyi Zhang ◽  
Guixiang Xue ◽  
YunPeng Ma ◽  
Shan Gao ◽  
...  
Keyword(s):  
District Heating ◽  
Heating System ◽  
District Heating System ◽  
Heating Load

scholarly journals Upgrading a District Heating System by Means of the Integration of Modular Heat Pumps, Geothermal Waters, and PVs for Resilient and Sustainable Urban Energy

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2347
Author(s):  
Elżbieta Hałaj ◽  
Jarosław Kotyza ◽  
Marek Hajto ◽  
Grzegorz Pełka ◽  
Wojciech Luboń ◽  
...  
Keyword(s):  
District Heating ◽  
Heating System ◽  
Upper Jurassic ◽  
Heat Pumps ◽  
Water Levels ◽  
Energy Potential ◽  
Geothermal Waters ◽  
District Heating System ◽  
Heating And Cooling ◽  
The City

Krakow has an extensive district heating network, which is approximately 900 km long. It is the second largest city in terms of the number of inhabitants in Poland, resulting in a high demand for energy—for both heating and cooling. The district heating of the city is based on coal. The paper presents the conception of using the available renewable sources to integrate them into the city’s heating system, increasing the flexibility of the system and its decentralization. An innovative solution of the use of hybrid, modular heat pumps with power dependent on the needs of customers in a given location and combining them with geothermal waters and photovoltaics is presented. The potential of deep geothermal waters is based on two reservoirs built of carbonate rocks, namely Devonian and Upper Jurassic, which mainly consist of dolomite and limestone. The theoretical potential of water intake equal to the nominal heating capacity of a geothermal installation is estimated at 3.3 and 2.0 MW, respectively. Shallow geothermal energy potential varies within the city, reflecting the complex geological structure of the city. Apart from typical borehole heat exchangers (BHEs), the shallower water levels may represent a significant potential source for both heating and cooling by means of water heat pumps. For the heating network, it has been proposed to use modular heat pumps with hybrid sources, which will allow for the flexible development of the network in places previously unavailable or unprofitable. In the case of balancing production and demand, a photovoltaic installation can be an effective and sufficient source of electricity that will cover the annual electricity demand generated by the heat pump installation, when it is used for both heating and cooling. The alternating demand of facilities for heating and cooling energy, caused by changes in the seasons, suggests potential for using seasonal cold and heat storage.

Sign in / Sign up

Export Citation Format

Share Document