Distributed Generation and Storage Optimal Control With State Estimation

The increasing demand coupled with expanding installation of distributed resources call for the development of smart technologies to control and optimize distribution system operations. In this paper, a distributed generation and storage optimization algorithm is proposed using pricing signals as distribution locational marginal pricing (DLMP). This signal is used to optimize the day-ahead operation planning of distributed generation and energy storage. A distribution level state estimation algorithm is also designed. The main conclusion is that the proposed optimal control and state estimation will improve the energy efficiency and economic benefits in a digitally controlled distribution power system.