Nowadays, energy management in a standalone system consists of distributed renewable energy sources, and distributed energy storage has been a major challenge. Adaptable system architecture may help to address this issue. The thesis proposes a solar photovoltaic system (SPVS) connected to distributed energy storage (battery) using DC-DC converters. The proposed system would consist of a DC-DC boost converter (BC) and a bidirectional switched quasi-Z-source DC-DC converter (BSQZSDC). These converters coordinate the management of power sources, energy storage systems, and DC loads. The BC is connected to the SPVS to harvest maximum power from the PV panel using the maximum power point tracking (MPPT) algorithm. The MPPT perturbation period is largely affected by the actual insolation conditions at weather in the PV generation area. If the insolation changes rapidly in the real weather environment, the MPPT control period should be set short for fast transient response characteristics. Therefore, in order to determine the optimum MPPT perturbation period and the magnitude of the perturbation voltage, it is necessary to analyze the performance of the MPPT controller for actual insolation conditions in a real weather environment. So, an optimum adaptive MPPT  with a variable step size algorithm is used. The low voltage side of the BSQZSDC is connected to the distributed energy storage (battery), and the high voltage side is connected to the DC-link side. The BSQZSDC  operates as a boost converter when load demand exceeds the energy generated in the PV source and the same operation as a buck converter when the load is less than the generation. To regulate dc-link voltage, different controller techniques are used in this thesis.  Firstly, the performance of the proposed system with distributed energy storage is examined using a dual loop proportional Integral controller (DLPIC). Since the PI controller is a linear controller with certain restrictions, its performance is later compared to nonlinear controllers such as sliding mode (SM) and Lyapunov function-based controllers. The performances of these controllers have been compared in terms of dynamic and steady-state responses.  Finally, flexible architecture develops coordination in proper energy management among PV generation, energy storage systems, and DC load.