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 8071242
  • - Research Article

Emergy Comparison of Typical Coastal Urban Ecosystems in China

Fuqiang Qin | Lifang Wang | Shifen Shao
  • Special Issue
  • - Volume 2020
  • - Article ID 1492615
  • - Research Article

Adaptive Fuzzy Sliding Mode and Robust Tracking Control for Manipulators with Uncertain Dynamics

Sanxiu Wang
  • Special Issue
  • - Volume 2020
  • - Article ID 9371327
  • - Research Article

Structured Control of an Electric Power Steering System

Hongbo Zhou | Aiping Pang | ... | Zhen He
  • Special Issue
  • - Volume 2020
  • - Article ID 2073901
  • - Research Article

Vehicle Speed Optimized Fuzzy Energy Management for Hybrid Energy Storage System in Electric Vehicles

Xizheng Zhang | Zhangyu Lu | Ming Lu
  • Special Issue
  • - Volume 2020
  • - Article ID 3640210
  • - Research Article

Algorithms for U-Model-Based Dynamic Inversion (UM-Dynamic Inversion) for Continuous Time Control Systems

Ruobing Li | Quanmin Zhu | ... | Weicun Zhang
  • Special Issue
  • - Volume 2020
  • - Article ID 5910430
  • - Research Article

Modeling and Simulation of an Intelligent Photovoltaic Controller Based on Variable Step Algorithm of Versoria

Bo Sun | Yongquan You | ... | Chao Li
  • Special Issue
  • - Volume 2020
  • - Article ID 6128697
  • - Research Article

Multi-Innovation Stochastic Gradient Parameter and State Estimation Algorithm for Dual-Rate State-Space Systems with -Step Time Delay

Ya Gu | Quanmin Zhu | ... | Yongxin Chou
  • Special Issue
  • - Volume 2020
  • - Article ID 6835367
  • - Research Article

Image Defogging Algorithm Based on Sparse Representation

Di Fan | Xinyun Guo | ... | Bo Sun
  • Special Issue
  • - Volume 2020
  • - Article ID 5423487
  • - Research Article

An Energy-Saving Output Feedback Control of Single-Rod Electrohydraulic Servo System with Disturbance Observer

Yunfei Wang | Jiyun Zhao | ... | Jiaxiang Man
  • Special Issue
  • - Volume 2020
  • - Article ID 3507679
  • - Research Article

Analysis and Optimization of Interpolation Points for Quadruped Robots Joint Trajectory

Mingfang Chen | Kaixiang Zhang | ... | Yongxia Zhang
Complexity
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Acceptance rate43%
Submission to final decision64 days
Acceptance to publication35 days
CiteScore3.200
Impact Factor2.462
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