## 6 Conclusions  
This paper presents an integrated framework of LEM-CDT that maximizes the flexibility potential of the participants and improves the market's operations efficiency. A detailed market design with different pricing mechanisms for handling LEM transactions is also introduced. The results of the proposed framework are summarized as follows:  
* Consumer preferences regarding thermal comfort and residential loads are proved to be valuable inputs for optimizing LEM operations.
* The attainment of optimal energy exchange with the external grid and the maximization of social welfare is accomplished.  
Figure 11: Consumer digital twin dashboard.  
* The enhancement of consumer-centricity and ease of implementation, as the participants are not required to actively submit energy selling or buying offers through a bidding process.
* The democratization of LEM through CDT-enabled automated participation broadens the potential participant base, positioning it as a more environmentally-friendly, attractive, and consumer-centric alternative to traditional energy markets.
* The generation and demand stochasticity is modeled by a chance-constrained scheduling optimization algorithm that ensures lower balancing needs with minimal requirements for market participation or remedial actions, despite the higher costs.  
The proposed solution encounters challenges with regard to regulatory compliance and ensuring the confidentiality of participants' data. Despite a current dearth of clear guidelines for LEMs design and operations, efforts are being undertaken to rectify this. In order to establish trust and attract new members, LEMs must prioritize creating a reliable environment. Additionally, the integration of a large number of IoT devices accentuates the necessity for robust cybersecurity measures to safeguard against potential breaches.  
The proposed model holds the potential for further enhancement in two directions. One area of improvement would be the integration of a more comprehensive collection of consumer preferences, with the aim of augmenting its consumer-centric orientation and further refining the consumer priorities for LEM operation. Another avenue for research would be to incorporate the distribution network constraints within LEM, in order to prevent voltage and line congestion incidents. Additionally, the proposed integration of LEM-CDT should be assessed in a larger-scale study utilizing a larger volume of data.  
Conceptualization, N.A., K.P., C.M. and J.G.; Methodology, N.A., K.P., C.M., J.G. and A.B.; Software, N.A. and C.M.; Validation, N.A., K.P., C.M. and J.G.; Writing--original draft preparation, N.A., K.P., C.M. and J.G.; Writing--review and editing, A.B., S.K. and A.P.; Visualization, N.A., K.P., C.M. and J.G.; Funding acquisition, J.G. and A.B. All authors have read and agreed to the published version of the manuscript.  
This work has been supported by TwinERGY project, No 957736, \"Intelligent Interconnection of Prosumers in Positive Energy Communities with Twins of Things for Digital Energy Markets-TwinERGY\", H2020-LC-SC3-2020-EC-ES-SCCRIA.  
Not applicable.  
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.  
The following abbreviations are used in this manuscript:  
AHP Analytic Hierarchy Process  
CDT Consumer Digital Twin  
DA Day-Ahead Market  
DES Distributed Energy Resources  
DR Demand Response  
DT Digital Twin  
EVs Electric Vehicles  
HVAC Controlling Heating, Ventilation and Air Conditioning  
LEM Local Energy Market  
P2P Peer-to-Peer  
RES Renewable Energy Resources  
TES Transactive Energy Systems