Data Mining-based Multi-objective Economic Dispatching of Distribution Network with Distributed Generation and Electric Vehicle

With the increasing development of distributed generation (DG) and electric vehicles (EV), the characteristics of sources and loads in the distribution network are changing dynamically, and the requirements for high data quality in the dispatching process are growing constantly. Besides, with more u...

Full description

Saved in:
Bibliographic Details
Published in2021 IEEE Sustainable Power and Energy Conference (iSPEC) pp. 268 - 273
Main Authors Qianhao, Sun, Yunhao, Li, Zeyu, Du, Chenggang, Zhang, Pengtao, Wu, Yao, Zhang
Format Conference Proceeding
LanguageEnglish
Published IEEE 23.12.2021
Subjects
data mining
Data models
Dispatching
distributed generation (DG)
Distributed power generation
distribution network
Distribution networks
economic dispatching
Electric vehicles
electric vehicles (EV)
Renewable energy sources
Simulation
Online AccessGet full text

Cover

More Information
Summary:With the increasing development of distributed generation (DG) and electric vehicles (EV), the characteristics of sources and loads in the distribution network are changing dynamically, and the requirements for high data quality in the dispatching process are growing constantly. Besides, with more users participating in demand response program, it is necessary to redesign the optimization objective of economic dispatching in many aspects. Therefore, we propose an outlier detection and data clustering method for the dataset collected from sensors in the distribution network. And, a multi-objective economic dispatching model is proposed based on our proposed data mining procedure. The simulation results demonstrate that the proposed model can reach the minimum dispatching cost and improve the utilization of renewable energy simultaneously.
DOI:10.1109/iSPEC53008.2021.9735877