Load forecasting and energy management in self-sufficient buildings have become increasingly important due to the growing demand for sustainable, reliable, and resilient energy systems. This paper presents a comprehensive framework for forecasting and optimal energy scheduling of a building equipped with distributed generation resources capable of supplying its energy demand independently from the utility grid while maintaining the capability of power exchange with the upstream network when required. To improve system reliability and operational flexibility, a combination of renewable and non-renewable energy resources, including photovoltaic systems, wind turbines, microturbines, combined heat and power (CHP) units, boilers, and electrical and thermal energy storage systems, is considered.To achieve more accurate energy planning, uncertainties associated with electrical load demand, wind speed, and solar irradiance are modeled using Monte Carlo simulation, Weibull probability distribution, and Beta probability distribution, respectively. The energy management problem is formulated as a multi-objective optimization model with the simultaneous objectives of minimizing operating costs and environmental emissions while satisfying technical and operational constraints.The main contribution of this study is the development of an integrated framework that simultaneously considers renewable generation uncertainties, grid-connected and islanded operating modes, and the implementation of a high step-up switching power converter based on an enhanced SEPIC topology. The proposed converter offers high voltage gain, reduced component count, lower current stress on switches and diodes, improved efficiency, and enhanced reliability, thereby supporting passive defense requirements and increasing the resilience of the building energy system.