The expansion of power communication network scale and the deployment of smart grid have brought massive data and computational pressure to operation and maintenance center. Edge computing technology can alleviate the pressure of the power grid management platform to process massive data and reduce the computational cost, and help the operation and maintenance personnel to efficiently complete the defect diagnosis and maintenance. Focusing on the operation and maintenance process of power communication network under the new ecology of edge computing, a technical scheme of power communication network defect diagnosis based on edge computing architecture and knowledge map technology is proposed. In order to improve the traditional rule-based defect diagnosis technology and improve its reliability and efficiency,The system combines a variety of intelligent methods to realize the defect diagnosis under the edge computing architecture, and realizes the timely detection and dispatch maintenance of defects through the analysis of equipment alarm logs and the tracking of network topology.
A multi-objective optimization design model of distributed micro-grid for local wind and solar energy consumption is
proposed. Firstly, in view of the smooth grid connection of high permeability renewable micro sources, the wind output
power is decomposed by wavelet packet frequency in different decomposition frequency bands, and the corresponding
power primary command is obtained. Combining with power primary command and the configuration of hybrid energy
storage system (Hess), the smoothness index after suppression is calculated, using multilayer feed forward neural network,
the neural network model of micro-grid design parameters—smoothness index is trained to design parameters of micro
network. Then, the K/P/Q — neural network economic cost mathematical model was established by using genetic
algorithm to solve the problems of cycle life and charge and discharge power consumption investment cost of lead-carbon
battery, so as to realize the multi-objective optimization design of micro-grid and minimize the investment cost. Finally,
Matlab is used to verify the feasibility and effectiveness of the proposed model in the evaluation of the smoothness index
and the optimal allocation of capacity of the micro-grid.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.