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.
- Digital system control
- Distributed resource optimization
- Distribution locational marginal prices
- Solid state controllers
- State estimation
ASJC Scopus subject areas
- Computer Science(all)