z-logo
open-access-imgOpen Access
Power Grid Low Carbon Collaborative Planning Method Using Improved Cat Swarm Optimization Algorithm in Edge Cloud Computing Environment
Author(s) -
Xiang Li,
Chong Guo,
Chengjun Li,
Tianyuan Xu,
Songyu Wu
Publication year - 2022
Publication title -
wireless communications and mobile computing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.42
H-Index - 64
eISSN - 1530-8677
pISSN - 1530-8669
DOI - 10.1155/2022/5213270
Subject(s) - computer science , reliability (semiconductor) , grid , algorithm , cloud computing , enhanced data rates for gsm evolution , swarm behaviour , particle swarm optimization , power (physics) , electric power system , telecommunications , artificial intelligence , mathematics , physics , geometry , quantum mechanics , operating system
The current power grid planning mostly realizes the calculation and analysis based on the factors of operation reliability or operation economy, but low-carbon green operation has become the main melody of power system development. Aiming to support the green and reliable operation of the power grid, this paper proposes a power grid low-carbon collaborative planning method based on improved cat swarm optimization algorithm. First, the carbon emission characteristics of the whole cycle of power grid construction are analyzed on the edge side, and a power grid planning model including environmental, economic, and reliability is constructed; on the cloud side, the cat swarm optimization algorithm is improved based on quantum mechanics and chaotic algorithm to achieve efficient solution to the power grid low-carbon planning model, which can support the stable and sustainable operation. Finally, the simulation experiment is realized based on IEEE 39 bus system. In this experiment, the construction cost and carbon emission of the proposed collaborative planning method are 23 million yuan and 2.28 t/MWh, respectively, which can reduce carbon emission while optimizing the construction cost and maintaining the low-carbon and stable operation.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom