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Distributed Generation and Storage Optimal Control With State Estimation
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AI
DOI：10.1109/TSG.2013.2266328.png)
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Abstract
En 中文
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.
Keywords:
Digital system control
distributed resource optimization
distribution locational marginal prices
solid state controllers
state estimation
Journal
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9.8
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5.7K
Citations:
4.3W
