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Integrated Energy Networks and Microgrids

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A1: Smart Grids and Microgrids".

Deadline for manuscript submissions: closed (31 August 2022) | Viewed by 7207

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Guest Editor
School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China
Interests: solid oxide fuel cells; performance evaluation; fault diagnosis; health control; solid oxide electrolyzer cell; proton-exchange membrane fuel cells; microgrids; nitrogen and oxygen sensors; hybrid power generation systems; clean energy
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Special Issue Information

Dear Colleagues,

In power systems with a high proportion of renewable energy, the problem of wind and light abandonment is becoming more and more prominent as the total installed capacity of wind power and photovoltaic continues to increase. Due to the limited accuracy of wind power and PV output prediction, the randomness of their output will cause a certain impact on the power grid. The integrated energy network and microgrid system can use the surplus power of new energy to produce hydrogen and store it or use it for downstream industries; when the load of the power system increases, the stored hydrogen energy can be fed back to the grid using fuel cells to generate electricity, and the process is clean, efficient, and flexible.

Integrated energy networks and micro-grid systems are the future direction of multi-energy utilization, covering various forms and characteristics of multienergy, such as photovoltaic, wind power, fuel cell, etc., and various forms of energy storage systems and devices, such as lithium battery, super capacitor, electrolytic tank, etc., in order to realize the integration of electricity, gas, heat and other complementary multienergy, but also to realize the source network, load, and storage of the whole link highly coordinated and flexible interaction, centralized and distributed combined with each other.

Further, the power system requires power generation and grid load demand to achieve transient balance, but with the landscape and other grid-connected new energy generation and demand-side resource ratio increases, its strong volatility and high uncertainty significantly increase the probability of power imbalance in the grid and seriously limit the grid to renewable energy consumption capacity, resulting in the phenomenon of “wind and light abandonment”, which is particularly frequent. At the same time, in the pursuit of its consumption capacity, without sufficient feasible technical support, a high proportion of renewable energy access to the grid may cause line overload, loss of load, static voltage instability, and other risks, making the power system face serious security problems. In essence, it is a requirement and challenge for the overall control architecture and renewable energy consumption mode of integrated energy networks and microgrids.

The purpose of this Special Issue is to collect research papers and reviews on “Integrated Energy Networks and Microgrids” to reflect the latest trends and challenges in this topic. The scope of this Special Issue includes high-precision modeling, dynamic and static analysis, and optimal control methods for integrated energy networks and microgrids, as well as research on microgrid performance evaluation and fault diagnosis algorithms.

Prof. Dr. Xi Li
Guest Editor

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Keywords

  • integrated energy networks
  • microgrids
  • high precision modeling
  • dynamic and static analysis
  • optimal control methods
  • performance evaluation
  • fault diagnosis

Published Papers (4 papers)

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Research

18 pages, 517 KiB  
Article
Optimization of Load Sharing in Compressor Station Based on Improved Salp Swarm Algorithm
by Jiawei Zhang, Lin Li, Qizhi Zhang and Yanbin Wu
Energies 2022, 15(15), 5720; https://doi.org/10.3390/en15155720 - 06 Aug 2022
Viewed by 1292
Abstract
In long-distance gas transmission pipelines, there are many booster compressor stations consisting of parallel compressors that provide pressure for the delivery of natural gas. So, it is economically important to optimize the operation of the booster compressor station. The booster compressor station optimization [...] Read more.
In long-distance gas transmission pipelines, there are many booster compressor stations consisting of parallel compressors that provide pressure for the delivery of natural gas. So, it is economically important to optimize the operation of the booster compressor station. The booster compressor station optimization problem is a typical mixed integer nonlinear programming (MINLP) problem, and solving it accurately and stably is a challenge. In this paper, we propose an improved salp swarm algorithm based on good point set, adaptive population division and adaptive inertia weight (GASSA) to solve this problem. In GASSA, three improvement strategies are utilized to enhance the global search capability of the algorithm and help the algorithm jump out of the local optimum. We also propose a constraint handling approach. By using semi-continuous variables, we directly describe the on or off state of the compressor instead of using auxiliary binary variables to reduce the number of variables and the difficulty of solving. The effectiveness of GASSA is firstly verified using eight standard benchmark functions, and the results show that GASSA has better performance than other selected algorithms. Then, GASSA is applied to optimize the booster compressor station load distribution model and compared with some well-known meta-heuristic algorithms. The results show that GASSA outperforms other algorithms in terms of accuracy and reliability. Full article
(This article belongs to the Special Issue Integrated Energy Networks and Microgrids)
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13 pages, 4005 KiB  
Article
Research on VFTO Identification of GIS Based on Wavelet Transform and Singular Value Decomposition
by Gang Xiao, Quansen Rong, Miaoran Yang, Peng Xiao, Qihong Chen, Junzhe Fan, Haoran Guo and Haonan Wang
Energies 2022, 15(9), 3367; https://doi.org/10.3390/en15093367 - 05 May 2022
Cited by 2 | Viewed by 1398
Abstract
The accurate identification of Very Fast Transient Overvoltage (VFTO) is the key of overvoltage control in modern smart grids. In order to accurately identify VFTO generated by the operation of a disconnector in Gas Insulated Substation (GIS), a VFTO identification method based on [...] Read more.
The accurate identification of Very Fast Transient Overvoltage (VFTO) is the key of overvoltage control in modern smart grids. In order to accurately identify VFTO generated by the operation of a disconnector in Gas Insulated Substation (GIS), a VFTO identification method based on Wavelet Transform (WT) and Singular Value Decomposition (SVD) is proposed. The simulation model of VFTO is established in ATP-EMTP software first, and then wavelet decomposition is used in MATLAB software for VFTO simulation of the waveform from the ATP-EMTP software. Then, the feature matrix is composed of the coefficients of each frequency layer of the wavelet. The SVD is used to decompose the feature matrix, and finally the characteristic parameters of the VFTO are obtained. The simulation results in Matlab software indicate that the characteristic parameters of VFTO have an obvious difference compared with those of power frequency AC voltage, especially in the load-side, which verifies the effectiveness of the VFTO identification method based on WT and SVD proposed in this paper. Full article
(This article belongs to the Special Issue Integrated Energy Networks and Microgrids)
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13 pages, 1424 KiB  
Article
Multiobjective Optimization for a Li-Ion Battery and Supercapacitor Hybrid Energy Storage Electric Vehicle
by Gang Xiao, Qihong Chen, Peng Xiao, Liyan Zhang and Quansen Rong
Energies 2022, 15(8), 2821; https://doi.org/10.3390/en15082821 - 12 Apr 2022
Cited by 10 | Viewed by 1679
Abstract
The acceptance of hybrid energy storage system (HESS) Electric vehicles (EVs) is increasing rapidly because they produce zero emissions and have a higher energy efficiency. Due to the nonlinear and strong coupling relationships between the sizing parameters of the HESS components and the [...] Read more.
The acceptance of hybrid energy storage system (HESS) Electric vehicles (EVs) is increasing rapidly because they produce zero emissions and have a higher energy efficiency. Due to the nonlinear and strong coupling relationships between the sizing parameters of the HESS components and the control strategy parameters and EV’s performances, energy consumption rate, running range and HESS cost, how to design the HESS EVs for different preferences is a key problem. How to get the real time performances from the HESS EV is a difficulty. The multiobjective optimization for the HESS EV considering the real time performances and the HESS cost is a solution. A Li-ion battery (BT) semi-active HESS and optimal energy control strategy were proposed for an EV. The multiobjectives include energy consumption over 100 km, acceleration time from 0–100 km per hour, maximum speed, running range and HESS cost of the EV. According to the degrees of impact on the multiobjectives, the scaled factors of BT capacity, the series number of Li-ion BTs, the series number of super-capacitors (SCs), the parallel number of SCs, and charge power of the SCs were chosen as the optimization variables. Two sets of different weights were used to simulate the multiobjective optimization problem in the ADVISOR software linked with MATLAB software. The simulation results show that some of the multiobjectives are sensitive to their weights. HESS EVs meeting different preferences can be designed through the weights of different objectives. Compared with the direct optimization algorithm, the genetic algorithm (GA) has a stronger optimization ability, and the single objective is more sensitive to its corresponding weight. The proposed optimization method is practical for a Li-ion BT and SC HESS EV design. Full article
(This article belongs to the Special Issue Integrated Energy Networks and Microgrids)
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19 pages, 32014 KiB  
Article
Modeling Analysis of SOFC System Oriented to Working Condition Identification
by Xiao-Long Wu, Hong Zhang, Hongli Liu, Yuan-Wu Xu, Jingxuan Peng, Zhiping Xia and Yongan Wang
Energies 2022, 15(5), 1804; https://doi.org/10.3390/en15051804 - 28 Feb 2022
Cited by 5 | Viewed by 2112
Abstract
Solid oxide fuel cell (SOFC) generation system is an important equipment to realize “carbon neutralization”. In SOFC system, a fault will cause changes in working conditions, which is difficult to detect early and find the reason due to the high temperature and seal [...] Read more.
Solid oxide fuel cell (SOFC) generation system is an important equipment to realize “carbon neutralization”. In SOFC system, a fault will cause changes in working conditions, which is difficult to detect early and find the reason due to the high temperature and seal environment. Therefore, the mechanistic model is a feasible way to find the reasons for the change of system working conditions. In this paper, based on the first law of thermodynamics, the system model of SOFC is built under multiple working conditions, and the influence of stack, afterburner, heat exchanger, and reformer fault is studied on the thermoelectric characteristics and efficiency of the system. The results show that with the introduction of these fault mechanistic models, the dynamic response characteristics of SOFC system under multiple working conditions can be obtained by tracking the key performance parameters qualitatively. The work of this paper is helpful for the guidance of the fault diagnosis of SOFC system in the future. Full article
(This article belongs to the Special Issue Integrated Energy Networks and Microgrids)
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