In landscape transitions toward smart neighborhood microgrids (MGs), local transactive energy markets provide promising opportunities for energy management. However, besides the positive features, this would be a bit of a challenging task due to a prompt proliferation of distributed energy resources (DERs). To tackle these issues, this study aims to design an efficient local market for energy transactions between residential and commercial loads within neighborhood MGs, with a focus on enhancing economic and technical objectives. The integration of DERs such as energy storage systems (ESS), photovoltaic (PV) systems, and plug-in hybrid electric vehicles (PHEV) would facilitate energy management optimization processes. Subsequently, in the proposed model, data interactions are conducted between the MGs and the distribution system operator (DSO). In this way, not only the MGs’ energy consumption costs are minimized but also the distribution system load profile deviation (LPD) would be diminished, too. Meanwhile, the effect of varying electricity tariffs is also explored on the net profit of the DSO. The developed models are mathematically implemented in general algebraic modeling system (GAMS) and surveyed in different simulation studies. The results indicate that through the proposed model, a constant minimum cost of energy consumption of MGs could be maintained while simultaneously enhancing the LPD by approximately 25%.