@Article{ee.2023.027537,
AUTHOR = {Tianfeng Xu, Tao Wang, Chengming Ye, Jing Zhang, Peng Xi, Yunhui Chen, Gengwu Zhang},
TITLE = {Research of Electric Cable Path Planning Based on Heuristic Optimization Algorithm in Mixed-Land Scenario},
JOURNAL = {Energy Engineering},
VOLUME = {120},
YEAR = {2023},
NUMBER = {11},
PAGES = {2629--2650},
URL = {http://www.techscience.com/energy/v120n11/54422},
ISSN = {1546-0118},
ABSTRACT = {In order to improve the reliability of power supply, the sophisticated design of the structure of electric cable
network has become an important issue for modern urban distribution networks. In this paper, an electric cable
path planning model based on heuristic optimization algorithm considering mixed-land scenario is proposed.
Firstly, based on different land samples, the kernel density estimation (KDE) and the analytic hierarchy process
(AHP) are used to estimate the construction cost of each unit grid, in order to construct the objective function of
comprehensive investment for electric cable loop network. Then, the ant colony optimization (ACO) was improved
in pheromone concentration, factor increment and search direction to accelerate the solving speed, and the cable
path planning result with minimum construction cost is obtained. Finally, the feeder’s tie line of the cable loop
network is planned by the genetic algorithm (GA) to achieve the minimum operating cost. In the case analysis,
compared with the traditional method, not only the subjective factors in the process of investment estimation can
be avoided, but also the speed of model solving and the quality of the optimal solution are improved.},
DOI = {10.32604/ee.2023.027537}
}