Multi-Objective Optimization for DC Microgrid Using Combination of NSGA-II Algorithm and Linear Search Method
Author:
Affiliation:
1. School of Electrical Engineering, Southeast University, Nanjing, China
2. State Key Laboratory of HVDC, Electric Power Research Institute, China Southern Power Grid Company Ltd., Guangzhou, China
Funder
National Natural Science Foundation of China
Science and Technology Project of China Southern Power Grid
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/5503868/10251074/10146269.pdf?arnumber=10146269
Reference22 articles.
1. Real-time Energy Management of a Low-Carbon Micro-Grid Based on Deep Reinforcement Learning
2. Data-Driven Distributed Online Learning Control for Islanded Microgrids
3. Deep Reinforcement Learning-Based Model-Free On-Line Dynamic Multi-Microgrid Formation to Enhance Resilience
4. PBI Based Multi-Objective Optimization via Deep Reinforcement Elite Learning Strategy for Micro-Grid Dispatch With Frequency Dynamics
5. Weather data and probability analysis of hybrid photovoltaic–wind power generation systems in Hong Kong
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