Complexity

Learning and Adaptation for Optimization and Control of Complex Renewable Energy Systems


Publishing date
01 Jan 2021
Status
Closed
Submission deadline
21 Aug 2020

Lead Editor

1Kunming University of Science and Technology, Kunming, China

2Universitat Politècnica de Catalunya (UPC), Barcelona, Spain

3Qingdao University, Qingdao, China

4Zhejiang University of Technology, Hangzhou, China

5University of Warwick, Coventry, Ireland

This issue is now closed for submissions.
More articles will be published in the near future.

Learning and Adaptation for Optimization and Control of Complex Renewable Energy Systems

This issue is now closed for submissions.
More articles will be published in the near future.

Description

To achieve sustainable development, renewable energies including solar, wind, nuclear, and fuel cells have become emerging choices in many applications. However, the guarantee of stable energy generation rate and safe system operation is not easy, because of their intermittent characteristics and the spatial complexity of renewable energy generation and transmission plants.

In general, accurate mathematical models for renewable energy systems are difficult to derive due to the existence of unavoidable parameter uncertainties, nonsmooth dynamics, and external disturbances. In this respect, developing efficient yet applicable learning and adaptation methods for modeling, optimization, and control of complex renewable energy systems could provide a new way to improve the system efficacy and efficiency. This has attracted significant attention worldwide.

The aim of this Special Issue is to collect the latest research results on the relevant topics of learning and adaptation for modelling, optimization, and control to promote the awareness of the related research methodologies of complex renewable energy systems. Authors are invited to present new modelling, optimization and control algorithms, hardware configuration, software architectures, experiments, and applications, which can bring new information about relevant theories and techniques of complex energy systems. All papers related to the theoretical methods and their application for optimization and control of complex energy systems are welcome. In particular, we encourage authors to submit their original research and review articles with either theoretical and methodological development or practical focus, such as simulation models, algorithms, experiments, and applications about advanced control and optimization techniques for complex energy systems.

Potential topics include but are not limited to the following:

  • Modelling, simulation and validation for complex renewable energy systems
  • Design and dynamic analysis for renewable energy systems with multiple energy storage components, generators, and motors
  • Modelling and compensation of nonsmooth dynamics in renewable energy generation systems
  • Bio-inspired optimization and optimal control for renewable energy systems with generators, storage, and motors
  • Artificial intelligence methods for learning, adaptation, and optimization
  • Data-driven modeling and control for renewable energy systems
  • Deep learning and integrative learning-based optimization and control designs
  • Adaptive parameter estimation for modeling of renewable energy systems
  • Learning and adaptation approaches for renewable energy generation, storage, and distribution
  • Adaptive dynamic programming for renewable energy generation and transmission
  • Intelligent control technique (e.g., neural network and fuzzy logic control) for renewable systems
  • Adaptive observer design and estimation for complex energy systems
  • Iterative learning for optimization and control with applications to renewable energy systems

Articles

  • Special Issue
  • - Volume 2020
  • - Article ID 9163675
  • - Research Article

Active Disturbance Rejection Control of Valve-Controlled Cylinder Servo Systems Based on MATLAB-AMESim Cosimulation

Wenxiao Guo | Yanbin Zhao | ... | Jianwei Zhang
  • Special Issue
  • - Volume 2020
  • - Article ID 9560135
  • - Research Article

Routing Optimization for Shared Electric Vehicles with Ride-Sharing

Chuanxiang Ren | Jinbo Wang | ... | Yu Zhang
  • Special Issue
  • - Volume 2020
  • - Article ID 9861642
  • - Research Article

Adaptive Chebyshev Neural Network Control for Ventilator Model under the Complex Mine Environment

Ranhui Liu | Xinyan Hu | ... | Chuanxi Liu
  • Special Issue
  • - Volume 2020
  • - Article ID 2625301
  • - Research Article

Centralized Airflow Control to Reduce Output Power Variation in a Complex OWC Ocean Energy Network

Sunil Kumar Mishra | Bhargav Appasani | ... | Aitor J. Garrido
  • Special Issue
  • - Volume 2020
  • - Article ID 4727412
  • - Research Article

Model-Free Adaptive Control of pH Value of Wet Desulfurization Slurry under Switching of Multiple Working Conditions

Jian Liu | Xiaoli Li | ... | Guimei Cui
  • Special Issue
  • - Volume 2020
  • - Article ID 6496030
  • - Research Article

Hesitant Bipolar-Valued Fuzzy Soft Sets and Their Application in Decision Making

Jin-Ying Wang | Yan-Ping Wang | Lei Liu
  • Special Issue
  • - Volume 2020
  • - Article ID 1094386
  • - Research Article

First-Order and High-Order Repetitive Control for Single-Phase Grid-Connected Inverter

Cheng Guo | Linzhen Zhong | ... | Yingbo Huang
  • Special Issue
  • - Volume 2020
  • - Article ID 8649428
  • - Research Article

Multivariable Controller Design for the Cooling System of a PEM Fuel Cell by considering Nearly Optimal Solutions in a Multiobjective Optimization Approach

Alberto Pajares | Xavier Blasco | ... | Raúl Simarro
  • Special Issue
  • - Volume 2020
  • - Article ID 8627492
  • - Research Article

Refined Upper Solution Bound of the Continuous Coupled Algebraic Riccati Equation

Li Wang
  • Special Issue
  • - Volume 2020
  • - Article ID 5306473
  • - Research Article

Fault Diagnosis of PMSG Wind Power Generation System Based on LMD and MSE

Hao Duan | Ming Lu | ... | Zuguo Chen
Complexity
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 Journal metrics
Acceptance rate43%
Submission to final decision64 days
Acceptance to publication35 days
CiteScore3.200
Impact Factor2.462
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