Integrating heat pumps into district heating systems: A multi-criteria decision analysis framework incorporating heat density and renewable energy mapping

The implementation of district heating (DH) projects necessitates a thorough and accurate evaluation and planning process. The availability of energy resources is often the key determinant in identifying the suitability of a specific location for district heating applications. Also, it is crucial to consider the other factors during the planning stage: the environment, economics, and technical parameters. This research aims to plan and implement a DH site selection model based on a geographic information system (GIS). This model employs Boolean and fuzzy toolboxes to analyze various layers, followed by the analytic hierarchy process (AHP) to identify the most appropriate locations for district heating in Gaziantep, Turkey. A mixed integer linear programming (MILP) approach is utilized to model proposed energy systems to achieve optimal operation and planning. The study's primary objective is to minimize the levelized cost of energy (LCOE), which encompasses initial costs, operations, maintenance, replacement expenses, and energy demand while also meeting the energy demand. A hybrid energy system that includes solar thermal/photovoltaic (ST, PV) energy, wind turbine (WT), and heat pump (HP) is considered, and its LCOE of optimal size is compared to other scenarios using HOMER simulation software. The results indicate that 270 km2 of the study area is suitable for DH implementation, with 83 km2 being highly suitable. Among the various scenarios, the hybrid energy system with a renewable energy penetration rate of approximately 78% achieves the best LCOE of 0.0442. The study concludes by providing a map of the potential for district heating and a discussion of the strengths and drawbacks of each scenario.

Automated summary

This study utilizes a geographic information system (GIS) to analyze different layers and identify the most suitable locations for district heating in Gaziantep, Turkey. The study employs a mixed integer linear programming (MILP) approach to model proposed energy systems and achieve optimal operation and planning. Results show that a hybrid energy system with a renewable energy penetration rate of 78% achieves the best levelized cost of energy (LCOE) of 0.0442.