Home Energy Management System (HEMS) is acknowledged as a promised approach to explore household appliances dynamic energy usage. The availability of an appropriate dataset is indispensable to evaluate the performance of HEMS operations in the designing phase. In this paper, we develop a tool capable of generating long-term semi-synthetic data to avoid deficiency of available datasets particularly, the lack of the major appliances measurements and non-electric information. Accordingly, a simple household with primary appliances located in two-main zones is simulated. The paper utilizes a statistical analysis of real-world data to create probabilistic models of appliances and consequently, produce time-extended stochastic power profiles. Afterward, a simulation structure is developed to generate the power consumption profiles of major appliances consisting of Electrical Space Heaters (ESH) and Electrical Water Heaters (EWH). In order to achieve its ambition, this study executes a post-processing practice to create on/off power profiles of these appliances using their models. The results show that the proposed tool can be exploited for different HEMS scenarios.