Search Results (3)

This paper focuses on the potential for integrating Geographic Information System (GIS) software into Fifth-Generation District Heating and Cooling (5GDHC) systems to promote efficient and sustainable energy management, particularly in Kazakhstan. By reviewing the key literature, we identify three main areas where GIS software enhances the planning of 5GDHC systems: decision-making in the context of energy market regulations, operational data utilization, and modeling/simulations for technical design. The technical design emphasizes the role of heat pumps, ultra-low temperature district heating (ULTDH) networks, and end-user buildings. Previous research has explored various methodologies for integrating network and demand-side strategies, developing sustainable district heating and cooling (DHC) systems, and mapping urban areas suitable for DHC deployment. However, none has presented an open-source model incorporating GIS-based decision-making in designing 5GDHC systems. This study, for the first time, addresses this gap through a case study conducted in the Northern Industrial Zone of Karaganda, Kazakhstan, demonstrating how GIS-enhanced modeling can be effectively applied in a developing, industry-driven economy. We outline the mathematical framework for comparing existing simulation tools and developing a custom model suited to the region’s needs. Additionally, we discuss validation and calibration methods, which remain underexplored in the current literature. The proposed model incorporates waste heat recovery from local sources, including nearby wastewater treatment plants, showcasing a sustainable energy solution for the industrial park. The results indicate that a well-structured 5GDHC system, supported by GIS tools, can markedly enhance energy efficiency and sustainability, presenting a scalable and adaptable approach for other regions in Kazakhstan and beyond. Full article

District heating and cooling (DHC) networks, and in particular, the fifth generation of DHC networks, offer great potential in increasing the overall system efficiency and reducing CO₂ emissions in the heating and cooling of urban districts. Due to the growing complexity of these energy systems, the use of new planning methods, such as the use of dynamic simulation models based on Modelica, becomes more important. However, especially with large, complex thermal networks, there is a high effort for manual model construction and parameterization. For this reason, we present a framework for automated model generation of DHC networks based on simulation models in Modelica written in Python. The core function of the Python framework is to transform a graph representation of a district heating network into a dynamic simulation model. The authors briefly describe the workflow and demonstrate its applicability with three different use cases. We investigate the impact of different design decisions, e.g., comparing the difference between central and decentral pumps as well as a combination of both in one network. In addition, we present the results of evaluating the impact of different network temperature levels or pipe insulation compared to the overall energy supplied to the network, leading to the conclusion that the presented framework is capable of reducing the manual effort for performing DHC network simulations with Modelica and allows to easily perform parameter studies in an early planning phases in the future. Full article

Fifth-generation district heating and cooling (5th DHC) systems offer promising approaches to decarbonizing space heating, cooling and domestic hot water supply. By using these systems, clustered buildings combined with industrial waste heat can achieve a net-zero energy balance on a variety of time scales. Thanks to the low exergy approach, these systems are highly efficient. As part of the Smart Anergy Quarter Baden (SANBA) project, the thermal energy grid simulation tool TEGSim has been further developed and used to design an ultra-low-temperature district heating (ULTDH) network with hydraulic and thermal components fitted to the specific regional characteristics of the investigated case. Borehole thermal energy storage (BTES) used as seasonal storage ensures long-term feasibility. The annual discrepancy of input of thermal energy provided by space cooling and output of energy demanded by space heating and domestic hot water is supplied by an external low-grade industrial waste heat source. This paper presents the functionality of the simulation and shows how to interpret the findings concerning the design of all components and their interplay, energy consumption and efficiencies. Full article