The incorporation of Phase Change Materials (PCM) into the building envelopes helps to increase indoor thermal comfort while lowering energy usage. The selection of PCM is directly related to its performance and might be viewed as an optimization challenge. The manuscript highlights the optimization of temperature distribution in building envelopes (walls and roofs) of Ahmedabad by choosing the suitable PCM and Nano-particle. Three different PCMs (RT31

RT 35

and RT42) and Nano-particles (Al

2

O

3

CuO

and ZnO) with different concentrations (12 %

16 %

and 20 %) are considered for the optimization. The PCMs are encapsulated into the building layer thickness to examine their characteristics like effective thermal conductivity

concentration

melting point

etc. These parameters are evaluated in a room that measures 5 m x 4 m x 3.5 m (L x W x H). The design-builder software (Version 7.0.2.006) is used to carry out the steady-state numerical simulations for this building envelope. The results suggest that the integration of PCM reduces the building's overall energy consumption by 7.92 kWh/m

2

per year. The optimal design is proposed by establishing a temperature difference (ΔT) in building envelopes and utilizing a hybrid optimization technique (a combination of Artificial neural network (ANN) and Genetic algorithm (GA)). This temperature difference o

f the building envelope is confirmed to be dependent on their PCM melting point

effective thermal conductivity

concentration (in%)

and PCM layer thickness. Hybrid optimization is found to be the most stable strategy for predicting temperature dilation and energy storage in building envelopes. Thus this paper gives a systematic understanding of the selection of PCM and Nano-particles and identifies the suitable PCM layer thickness for encapsulation.