Smart distribution system automation is the key to realizing a highly reconfigurable, reliable, flexible and active distribution system. Automated network reconfiguration including restoration is the most studied area in distribution automation, and it contributes to power loss minimization, voltage improvement and also can enable the distribution network to respond to contingencies and changes happened in the grid. Distributed energy resources at the customer premises, energy storage systems and plug-in electric vehicles are indispensable parts of future smart distribution systems. Their participations have brought more dynamics and uncertainties into the grid, and hence new technologies at both planning and operation levels must be developed to manage the energy dispatched from distributed energy resources and energy storage units, the charging and discharging behaviors of electric vehicles so that the entire power distribution system could operate stably and efficiently. Meantime, due to the intermittent, imperfectly predicted renewable energy and more complicated, uncertain load patterns, two challenges have arisen on network reconfiguration study, including more frequent reconfiguration actions and more complicated optimization problems for determining the optimal network topology. Thus, new approaches for reconfiguring distribution networks must be developed to overcome these challenges.
In order to address the above challenges which distribution systems are facing to and develop new technologies for realizing smart distribution automation, a comprehensive study on network reconfiguration and energy management of distributed generation systems was studied. The contributions of this dissertation include: (1) proposed a novel problem formulation for network reconfiguration problem based on “switch states”; (2) developed three new methods to solve the optimization problem including heuristic algorithm, hybrid algorithm and revised genetic algorithm; (3) proposed a hierarchical, decentralized network reconfiguration approach that has been proved to have significant computational advantage compared with other existing methods; (4) proposed the concept of “dynamic network reconfiguration” in which the impact of time-varying load demands, renewable energy generation and other contingencies on the optimal distribution network topology were fully addressed and analyzed. (5) Since DG has become one of the most important parts in distribution systems. The mechanism of distributed generation itself and the impact of distributed generation on distribution system analysis must be studied. This dissertation has studied the modeling and reactive control of multiple DG systems, and also studied the unbalanced distribution feeder reconfiguration and proposed energy management strategy for controlling all grid-connected DGs in order to optimize distribution system operation.