Guest Editors
Prof. Kai Wang, Qingdao University, China
Dr. Xiufeng Liu, Technical University of Denmark, Denmark
Prof. Licheng Wang, Zhejiang University of Technology, China
Dr. Yang Zhang, Strategic Research Institute, State Power Investment Corporation, China
Summary
Energy demand worldwide grows every year. Thus, there is a great interest in reducing energy consumption (both domestic and industrial) and in optimizing energy supply systems. The amount of data available from industrial systems or domestic buildings can be used to prevent faults or to optimize production in energy systems. An additional important goal is to use these data to optimize maintenance and control strategies with the goal of reducing energy consumption in industrial applications or in domestic buildings.
The increasing penetration of stochastic and uncertain inverter-based distributed energy resources (DERs), such as wind and solar photovoltaic (PV), has a considerable influence on power system dynamics, causing reliability and resilience concerns. This requires innovations in power system modelling, operation, and control to deal with these emerging challenges. In addition, coordinated control among different devices typically relies on communication systems. Communication-control coupled systems bring both opportunities and challenges to the future development of DER-rich power systems.
Artificial intelligence systems can make use of the available data to address the challenges discussed above. Accordingly, this Special Issue will focus on the artificial intelligence in renewable energy and storage systems (e.g., wind, solar, supercapacitor and fuel cells). We invite papers on innovative technical developments, case studies, and theoretical papers from different disciplines, which are relevant to renewable energy and storage systems. Original research and review articles are both welcome.
Potential topics include but are not limited to the following:
● Energy storage technologies and systems
● Plug-in hybrid electric vehicle (PHEV) systems, Compressed natural gas (CNG) vehicles, clean Energy
● Power electronic converters and drives
● Demand monitoring and energy efficient systems
● Modelling of communication-control coupled systems
● Frequency regulation in low inertia systems with high wind penetration
● Grid modelling, simulation, and data management
● Energy efficiency, conservation, and savings
● Big data for industrial and energy systems
● Grid protection, reliability, energy / power quality, and maintenance
● Smart metering, measurement, instrumentation, and control
● Renewable energy, wind, solar, fuel cells, and distributed generation within microgrids
● Computational intelligence and optimization
● Life cycle assessment, pricing, policies, and energy planning
● Artificial Intelligence for industrial process optimization
● Optimization of industrial applications and energy systems
● Artificial intelligence for renewable energies
Keywords
distributed energy resources, renewable energy, electric vehicle, storage systems, data driven, energy management
Published Papers
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Open Access
ARTICLE
Modeling, Analysis and Simulation of a High-Efficiency Battery Control System
Mohammed Ayad Alkhafaji, Yunus Uzun
Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 709-732, 2023, DOI:10.32604/cmes.2023.024236
（This article belongs to this Special Issue:
Artificial Intelligence in Renewable Energy and Storage Systems)
Abstract This paper explains step-by-step modeling and simulation of the full circuits of a battery control system and connected together starting from the AC input source to the battery control and storage system. The three-phase half-controlled rectifier has been designed to control and convert the AC power into DC power. In addition, two types of direct current converters have been used in this paper which are a buck and bidirectional DC/DC converters. These systems adjust the output voltage to be lower or higher than the input voltage. In the buck converters, the main switch operates in conduction or cut-off mode and…
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Open Access
ARTICLE
Low-Frequency Oscillation Analysis of Grid-Connected VSG System Considering Multi-Parameter Coupling
Shengyang Lu, Tong Wang, Yuanqing Liang, Shanshan Cheng, Yupeng Cai, Haixin Wang, Junyou Yang, Yuqiu Sui, Luyu Yang
Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2373-2386, 2023, DOI:10.32604/cmes.2023.024461
（This article belongs to this Special Issue:
Artificial Intelligence in Renewable Energy and Storage Systems)
Abstract With the increasing integration of new energy generation into the power system and the massive withdrawal of traditional fossil fuel generation, the power system is faced with a large number of stability problems. The phenomenon of low-frequency oscillation caused by lack of damping and moment of inertia is worth studying. In recent years, virtual synchronous generator (VSG) technique has been developed rapidly because it can provide considerable damping and moment of inertia. While improving the stability of the system, it also inevitably causes the problem of active power oscillation, especially the low mutual damping between the VSG and the power…
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Open Access
ARTICLE
Scheduling an Energy-Aware Parallel Machine System with Deteriorating and Learning Effects Considering Multiple Optimization Objectives and Stochastic Processing Time
Lei Wang, Yuxin Qi
Computer Modeling in Engineering & Sciences, Vol.135, No.1, pp. 325-339, 2023, DOI:10.32604/cmes.2022.019730
（This article belongs to this Special Issue:
Artificial Intelligence in Renewable Energy and Storage Systems)
Abstract Currently, energy conservation draws wide attention in industrial manufacturing systems. In recent years, many studies have aimed at saving energy consumption in the process of manufacturing and scheduling is regarded as an effective approach. This paper puts forwards a multi-objective stochastic parallel machine scheduling problem with the consideration of deteriorating and learning effects. In it, the real processing time of jobs is calculated by using their processing speed and normal processing time. To describe this problem in a mathematical way, a multi-objective stochastic programming model aiming at realizing makespan and energy consumption minimization is formulated. Furthermore, we develop a multi-objective…
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Open Access
ARTICLE
Optimization of Charging/Battery-Swap Station Location of Electric Vehicles with an Improved Genetic Algorithm-Based Model
Bida Zhang, Qiang Yan, Hairui Zhang, Lin Zhang
Computer Modeling in Engineering & Sciences, Vol.134, No.2, pp. 1177-1194, 2023, DOI:10.32604/cmes.2022.022089
（This article belongs to this Special Issue:
Artificial Intelligence in Renewable Energy and Storage Systems)
Abstract The joint location planning of charging/battery-swap facilities for electric vehicles is a complex problem. Considering the differences between these two modes of power replenishment, we constructed a joint location-planning model to minimize construction and operation costs, user costs, and user satisfaction-related penalty costs. We designed an improved genetic algorithm that changes the crossover rate using the fitness value, memorizes, and transfers excellent genes. In addition, the present model addresses the problem of “premature convergence” in conventional genetic algorithms. A simulated example revealed that our proposed model could provide a basis for optimized location planning of charging/battery-swapping facilities at different levels…
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Open Access
ARTICLE
Research on Evaluation of Multi-Timescale Flexibility and Energy Storage Deployment for the High-Penetration Renewable Energy of Power Systems
Hongliang Wang, Jiahua Hu, Danhuang Dong, Cenfeng Wang, Feixia Tang, Yizheng Wang, Changsen Feng
Computer Modeling in Engineering & Sciences, Vol.134, No.2, pp. 1137-1158, 2023, DOI:10.32604/cmes.2022.021965
（This article belongs to this Special Issue:
Artificial Intelligence in Renewable Energy and Storage Systems)
Abstract With the rapid and wide deployment of renewable energy, the operations of the power system are facing greater challenges when dispatching flexible resources to keep power balance. The output power of renewable energy is uncertain, and thus flexible regulation for the power balance is highly demanded. Considering the multi-timescale output characteristics of renewable energy, a flexibility evaluation method based on multi-scale morphological decomposition and a multi-timescale energy storage deployment model based on bi-level decision-making are proposed in this paper. Through the multi-timescale decomposition algorithm on the basis of mathematical morphology, the multi-timescale components are separated to determine the flexibility requirements…
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Open Access
ARTICLE
Analysis and Power Quality Improvement in Hybrid Distributed Generation System with Utilization of Unified Power Quality Conditioner
Noor Zanib, Munira Batool, Saleem Riaz, Farkhanda Afzal, Sufian Munawar, Ibtisam Daqqa, Najma Saleem
Computer Modeling in Engineering & Sciences, Vol.134, No.2, pp. 1105-1136, 2023, DOI:10.32604/cmes.2022.021676
（This article belongs to this Special Issue:
Artificial Intelligence in Renewable Energy and Storage Systems)
Abstract This paper presents a comprehensive study that includes the sizing and power flow by series and parallel inverters
in a distributed generation system (DGs) that integrates the system of hybrid wind photovoltaic with a unified
power quality conditioner (UPQC). In addition to supplying active power to the utility grid, the system of
hybrid wind photovoltaic functions as a UPQC, compensating reactive power and suppressing the harmonic load
currents. Additionally, the load is supplied with harmonic-free, balanced and regulated output voltages. Since PVWind-UPQC is established on a dual compensation scheme, the series inverter works like a sinusoidal current
source, while the…
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Open Access
ARTICLE
A Fractional Order Fast Repetitive Control Paradigm of Vienna Rectifier for Power Quality Improvement
Sue Wang, Xintao Luo, Saleem Riaz, Haider Zaman, Chaohong Zhou, Pengfei Hao
Computer Modeling in Engineering & Sciences, Vol.134, No.2, pp. 1159-1176, 2023, DOI:10.32604/cmes.2022.021850
（This article belongs to this Special Issue:
Artificial Intelligence in Renewable Energy and Storage Systems)
Abstract Due to attractive features, including high efficiency, low device stress, and ability to boost voltage, a Vienna rectifier
is commonly employed as a battery charger in an electric vehicle (EV). However, the 6k ± 1 harmonics in the acside current of the Vienna rectifier deteriorate the THD of the ac current, thus lowering the power factor. Therefore,
the current closed-loop for suppressing 6k ± 1 harmonics is essential to meet the desired total harmonic distortion
(THD). Fast repetitive control (FRC) is generally adopted; however, the deviation of power grid frequency causes
delay link in the six frequency fast repetitive control…
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Open Access
ARTICLE
Research on Volt/Var Control of Distribution Networks Based on PPO Algorithm
Chao Zhu, Lei Wang, Dai Pan, Zifei Wang, Tao Wang, Licheng Wang, Chengjin Ye
Computer Modeling in Engineering & Sciences, Vol.134, No.1, pp. 599-609, 2023, DOI:10.32604/cmes.2022.021052
（This article belongs to this Special Issue:
Artificial Intelligence in Renewable Energy and Storage Systems)
Abstract In this paper, a model free volt/var control (VVC) algorithm is developed by using deep reinforcement learning
(DRL). We transform the VVC problem of distribution networks into the network framework of PPO algorithm,
in order to avoid directly solving a large-scale nonlinear optimization problem. We select photovoltaic inverters as
agents to adjust system voltage in a distribution network, taking the reactive power output of inverters as action
variables. An appropriate reward function is designed to guide the interaction between photovoltaic inverters
and the distribution network environment. OPENDSS is used to output system node voltage and network loss.
This method realizes…
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Open Access
ARTICLE
A Fault Risk Warning Method of Integrated Energy Systems Based on RelieF-Softmax Algorithm
Qidai Lin, Ying Gong, Yizhi Shi, Changsen Feng, Youbing Zhang
Computer Modeling in Engineering & Sciences, Vol.132, No.3, pp. 929-944, 2022, DOI:10.32604/cmes.2022.020752
（This article belongs to this Special Issue:
Artificial Intelligence in Renewable Energy and Storage Systems)
Abstract The integrated energy systems, usually including electric energy, natural gas and thermal energy, play a pivotal role in the energy Internet project, which could improve the accommodation of renewable energy through multi-energy complementary ways. Focusing on the regional integrated energy system composed of electrical microgrid and natural gas network, a fault risk warning method based on the improved RelieF-softmax method is proposed in this paper. The raw data-set was first clustered by the K-maxmin method to improve the preference of the random sampling process in the RelieF algorithm, and thereby achieved a hierarchical and non-repeated sampling. Then, the improved RelieF…
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Open Access
ARTICLE
Research on Distributed Cooperative Control Strategy of Microgrid Hybrid Energy Storage Based on Adaptive Event Triggering
Wenqian Zhang, Jingwen Chen, Saleem Riaz, Naiwen Zheng, Li Li
Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 585-604, 2022, DOI:10.32604/cmes.2022.020523
（This article belongs to this Special Issue:
Artificial Intelligence in Renewable Energy and Storage Systems)
Abstract Distributed collaborative control strategies for microgrids often use periodic time to trigger communication,
which is likely to enhance the burden of communication and increase the frequency of controller updates, leading
to greater waste of communication resources. In response to this problem, a distributed cooperative control
strategy triggered by an adaptive event is proposed. By introducing an adaptive event triggering mechanism in
the distributed controller, the triggering parameters are dynamically adjusted so that the distributed controller can
communicate only at a certain time, the communication pressure is reduced, and the DC bus voltage deviation
is effectively reduced, at the same time,…
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Open Access
ARTICLE
Accelerated Iterative Learning Control for Linear Discrete Systems with Parametric Perturbation and Measurement Noise
Xiaoxin Yang, Saleem Riaz
Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 605-626, 2022, DOI:10.32604/cmes.2022.020412
（This article belongs to this Special Issue:
Artificial Intelligence in Renewable Energy and Storage Systems)
Abstract An iterative learning control algorithm based on error backward association and control parameter correction has
been proposed for a class of linear discrete time-invariant systems with repeated operation characteristics, parameter disturbance, and measurement noise taking PD type example. Firstly, the concrete form of the accelerated
learning law is presented, based on the detailed description of how the control factor is obtained in the algorithm.
Secondly, with the help of the vector method, the convergence of the algorithm for the strict mathematical proof,
combined with the theory of spectral radius, sucient conditions for the convergence of the algorithm is presented
for…
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Open Access
ARTICLE
State Estimation of Regional Power Systems with Source-Load Two-Terminal Uncertainties
Ziwei Jiang, Shuaibing Li, Xiping Ma, Xingmin Li, Yongqiang Kang, Hongwei Li, Haiying Dong
Computer Modeling in Engineering & Sciences, Vol.132, No.1, pp. 295-317, 2022, DOI:10.32604/cmes.2022.019996
（This article belongs to this Special Issue:
Artificial Intelligence in Renewable Energy and Storage Systems)
Abstract The development and utilization of large-scale distributed power generation and the increase of impact loads represented by electric locomotives and new energy electric vehicles have brought great challenges to the stable operation of the regional power grid. To improve the prediction accuracy of power systems with source-load two-terminal uncertainties, an adaptive cubature Kalman filter algorithm based on improved initial noise covariance matrix Q0 is proposed in this paper. In the algorithm, the Q0 is used to offset the modeling error, and solves the problem of large voltage amplitude and phase fluctuation of the source-load two-terminal uncertain systems. Verification of the… More >
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Open Access
ARTICLE
Low Carbon Economic Dispatch of Integrated Energy System Considering Power Supply Reliability and Integrated Demand Response
Jian Dong, Haixin Wang, Junyou Yang, Liu Gao, Kang Wang, Xiran Zhou
Computer Modeling in Engineering & Sciences, Vol.132, No.1, pp. 319-340, 2022, DOI:10.32604/cmes.2022.020394
（This article belongs to this Special Issue:
Artificial Intelligence in Renewable Energy and Storage Systems)
Abstract Integrated energy system optimization scheduling can improve energy efficiency and low carbon economy. This
paper studies an electric-gas-heat integrated energy system, including the carbon capture system, energy coupling
equipment, and renewable energy. An energy scheduling strategy based on deep reinforcement learning is proposed
to minimize operation cost, carbon emission and enhance the power supply reliability. Firstly, the low-carbon
mathematical model of combined thermal and power unit, carbon capture system and power to gas unit (CCP)
is established. Subsequently, we establish a low carbon multi-objective optimization model considering system
operation cost, carbon emissions cost, integrated demand response, wind and photovoltaic curtailment,…
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Open Access
ARTICLE
Optimal Scheduling for Flexible Regional Integrated Energy System with Soft Open Point
Wen Xu, Dongdong Ren, Biyi Yi, Haoqing Zhen, Youbing Zhang, Xuesong Zhang
Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 1101-1123, 2022, DOI:10.32604/cmes.2022.019564
（This article belongs to this Special Issue:
Artificial Intelligence in Renewable Energy and Storage Systems)
Abstract The Regional Integrated Energy System (RIES) has brought new modes of development, utilization, conversion,
storage of energy. The introduction of Soft Open Point (SOP) and the application of Power to Gas (P2G) technology
will greatly deepen the coupling of the electricity-gas integrated energy system, improve the flexibility and safety of
the operation of the power system, and bring a deal of benefits to the power system. On this background, an optimal
dispatch model of RIES combined cold, heat, gas and electricity with SOP is proposed. Firstly, RIES architecture
with SOP and P2G is designed and its mathematical model also is…
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Open Access
ARTICLE
Fractal Dimension Analysis Based Aging State Assessment of Insulating Paper with Surface Microscopic Images
Shuaibing Li, Jiaqi Cui, Yongqiang Kang
Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 1083-1099, 2022, DOI:10.32604/cmes.2022.019671
（This article belongs to this Special Issue:
Artificial Intelligence in Renewable Energy and Storage Systems)
Abstract The insulating paper of the transformer is affected by many factors during the operation, meanwhile, the surface
texture of the paper is easy to change. To explore the relationship between the aging state and surface texture change
of insulating paper, firstly, the thermal aging experiment of insulating paper is carried out, and the insulating paper
samples with different aging times are obtained. After then, the images of the aged insulating paper samples are
collected and pre-processed. The pre-processing effect is verified by constructing and calculating the gray surface
of the sample. Secondly, the texture features of the insulating paper image…
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