# Improved Structural Local Thermal Energy Planning Based on Prosumer Profile: Part A
## 4 Conclusions  
This study presents a novel approach of prosumer classification depending on the thermal energy profile and occupational characteristics. The proposed mathematical model constitutes the first of a three-layer approach in which the complete techno-economic design of a LEC will be exploited. The presented layer aims to identify the level of energy intensity of the prosumers comprising the community (low, medium, or high) and their segmentation to distinct clusters. In the view of the authors, this is a significant step towards designing an energy production and delivery system that is able to respond to consumers' demands. The model exploits two well-established approaches for LEC formation, one quantitative--KIM--and one qualitative--RenewIslands methodology. A case study was presented in Kimmeria, Greece, where one of the country's largest LECs operates [45]. The hybrid approach uses empirical and quantifiable metrics to approach the classification issue and eliminates the results of the individual methodologies. The application of the HDLM approach indicated that the proposed model is highly applicable in TLEC cases and easy to use. However, the results suggested that the classification of the KIM and RenewIslands methods individually were not decisive. The HDLM definitively reached a classification solution for the prosumers of Kimmeria's LEC, which was \"Medium energy intensity users\". The novelty of the method is that: (i) KIM is used along with k-means clustering methodology and is further extrapolated via the FTS/SDF approach. By approaching KIM in that manner, the result is well-defined mathematically and can be used to classify the community's thermal energy needs deterministically and universally. (ii) The results of the RenewIsland methodology are used as a first approach to the community's thermal energy needs classification, but as they lack technical depth, they are reassessed further from the KIM approach. The combination of the two methodologies contributes to the following findings: (i) The RenewIslands methodology is qualitative and requires a low level of expertise  
Figure 6: The HDLM complete layer approach taking into account the thermal loads of the prosumers (first layer), the most case-appropriate technologies to be implemented (second layer) and the economic assessment (third layer) of the proposed scenario (to be optimized). and know- how of the system (valid for a first approach to the system), while KIM is mathematically defined and considers essential factors such as the occupation status, the m\({}^{2}\) of the building, and the specific energy consumption. (ii) The result of RenewIslands, considering only the thermal energy consumption and classifying the community as \"High energy intensity\", might lead to overdimensioning the equipment which will be selected to satisfy the demand. However, KIM combined with the SDF and the FTS redefines the classification methodology by applying quantitative measures. The study results highlight the importance of a unified mathematical tool which transcends the limitation of the existing methodologies in the energy profiling of prosumers. The accurate classification and quantified metric of energy consumption leads to technically sound energy production and delivery system design. By following that step, design flaws such as over- or underdimensioning are significantly reduced. The capital costs for these systems will be reduced, and the payback periods as well as the overall performance of the system will substantially improve. The combined approach unifies the qualitative and quantitative measures into one holistic approach which best describes the LEC's thermal energy profile. The output of the first layer (\"Medium energy intensity users\") will be projected on the second, whose primary purpose is the development of the superstructure (combination of types of equipment that will address the thermal energy demands calculated in the first layer).