Discovering Communities for Microgrids with Spatial-Temporal Net Energy

Smart grid has integrated an increasing number of distributed energy resources to improve the efficiency and flexibility of power generation and consumption as well as the resilience of the power grid. The energy consumers on the power grid, e.g., households, equipped with distributed energy resources can be considered as “microgrids” that both generate and consume electricity. In this paper, we study the energy community discovery problems which identify energy communities for the microgrids to facilitate energy management, e.g., load balancing, energy sharing and trading on the grid. Specifically, we present efficient algorithms to discover such communities of microgrids considering both their geo-locations and net energy (NE) over any period. Finally, we experimentally validate the performance of the algorithms using both synthetic and real datasets

Cooperative Control For Self-Organizing Microgrids And Game Strategies For Optimal Dispatch Of Distributed Renewable Generations

The small size, extensively dispersed and decentralized, and high penetration level of renewable energy sources in the future smart grids make the application of conventional optimal power flow (OPF) neither practical nor economical. In this paper, a practical approach is proposed to realize high penetration of distributed generators (DGs) by organizing them in some groups within a microgrid and dispatching the generated power aggregately. Each group may have virtual leaders which define the power policy of the group, and all other DGs cooperatively follow that policy. A fair utilization ratio is defined and will be introduced to the group by the virtual leaders. The utilization ratio indicates what percentage of the available power each DG has to feed to the grid, and this ratio will also be propagated within the group using cooperative control. As such, a smartgrid may treat microgrids as individually dispatchable loads or generators. Meanwhile, the interaction between each microgrid and the main grid can be formulated as a Stackelberg game. The main grid as the leader, by offering proper energy price to the micro grid, minimizes its cost and secures the power supply that the microgrid, as the follower, is willing to dispatch. It is shown that this game theoretic approach not only guarantees profit optimization, but also provides a convenient technique to optimize power flow from microgrids to the main grid. Numerical and simulation results for a case of study are provided to demonstrate the effectiveness of the proposed techniques. © 2012 Springer-Verlag