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13 pages, 2503 KiB

Open AccessArticle

A Machine Learning-Based Energy Management Agent for Fine Dust Concentration Control in Railway Stations

by Kyung-Bin Kwon, Su-Min Hong, Jae-Haeng Heo, Hosung Jung and Jong-young Park

Sustainability 2022, 14(23), 15550; https://0-doi-org.brum.beds.ac.uk/10.3390/su142315550 - 22 Nov 2022

Cited by 3 | Viewed by 1055

This study developed a reinforcement learning-based energy management agent that controls the fine dust concentration by controlling facilities such as blowers and air conditioners to efficiently manage the fine dust concentration in the station. To this end, we formulated an optimization problem based [...] Read more.

This study developed a reinforcement learning-based energy management agent that controls the fine dust concentration by controlling facilities such as blowers and air conditioners to efficiently manage the fine dust concentration in the station. To this end, we formulated an optimization problem based on the Markov decision-making process and developed a model for predicting the concentration of fine dust in the station by training an artificial neural network (ANN) based on supervised learning to develop the transfer function. In addition to the prediction model, the optimal policy for controlling the blower and air conditioner according to the current state was obtained based on the ANN to which the Deep Q-Network (DQN) algorithm was applied. In the case study, it is confirmed that the ANN and DQN of the predictive model were trained based on the actual data of Nam-Gwangju Station to converge to the optimal policy. The comparison between the proposed method and conventional method shows that the proposed method can use less power consumption but achieved better performance on reducing fine dust concentration than the conventional method. In addition, by increasing the value of the ratio that represents the compensation due to the fine dust reduction, the learned agent achieved more reduction on the fine dust concentration by increasing the power consumption of the blower and air conditioner. Full article

(This article belongs to the Special Issue Advances in Sustainable Electrical Engineering)

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18 pages, 4281 KiB

Open AccessArticle

Developed Design of Battle Royale Optimizer for the Optimum Identification of Solid Oxide Fuel Cell

by Keyvan Karamnejadi Azar, Armin Kakouee, Morteza Mollajafari, Ali Majdi, Noradin Ghadimi and Mojtaba Ghadamyari

Sustainability 2022, 14(16), 9882; https://0-doi-org.brum.beds.ac.uk/10.3390/su14169882 - 10 Aug 2022

Cited by 36 | Viewed by 2180

Abstract

One of the most appropriate electricity production systems is solid oxide fuel cells (SOFCs), which are important because they are highly efficient, flexible to fuel, and have fewer environmental degradation effects. A new optimum technique has been provided for providing well-organized unknown parameters [...] Read more.

One of the most appropriate electricity production systems is solid oxide fuel cells (SOFCs), which are important because they are highly efficient, flexible to fuel, and have fewer environmental degradation effects. A new optimum technique has been provided for providing well-organized unknown parameters identification of the solid oxide fuel cell system. The main idea is to achieve the lowest amount of the sum of square error between the model’s output voltage and the empirical voltage datapoints. To get efficient results, the minimum error value has been achieved by designing a new metaheuristic algorithm, called the Developed version of Battle Royale algorithm. The reason for using this version of Battle Royale algorithm is to achieve results with higher accuracy and better convergence. The proposed technique was then applied to a 96-cell SOFC stack under different temperature and pressure values and its achievements were compared with several different latest methods to show the proposed method’s efficiency. Full article

(This article belongs to the Special Issue Advances in Sustainable Electrical Engineering)

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15 pages, 1730 KiB

Open AccessArticle

Intelligent Identification of the Line-Transformer Relationship in Distribution Networks Based on GAN Processing Unbalanced Data

by Yan Wang, Xinyu Zhang, Haofeng Liu, Boqiang Li, Jinyun Yu, Kaipei Liu and Liang Qin

Sustainability 2022, 14(14), 8611; https://0-doi-org.brum.beds.ac.uk/10.3390/su14148611 - 14 Jul 2022

Cited by 3 | Viewed by 1190

Abstract

The wrong line-transformer relationship is one of the main reasons that leads to the failure of the line loss assessment of the distribution network with voltage levels of 10 kV and below. The traditional manual method to verify the line-transformer relationship is time-consuming, [...] Read more.

The wrong line-transformer relationship is one of the main reasons that leads to the failure of the line loss assessment of the distribution network with voltage levels of 10 kV and below. The traditional manual method to verify the line-transformer relationship is time-consuming, labor-intensive and inefficient. At the same time, due to the small sample size of the data with abnormal line-transformer relationship, the unbalanced sample data reduces the accuracy of the artificial intelligence algorithm. To this end, this paper proposes an intelligent identification method for distribution network line-transformer relationship based on Generative Adversarial Networks (GAN) processing unbalanced data. Firstly, perform data preprocessing and feature extraction based on the input power of the distribution line and the power consumption of each distribution transformer; then, build a GAN-based model for expanding the data of only a small number of abnormal line-transformer relationship samples, so as to solve the problem of unbalanced sample data distribution; and finally, establish a support vector machine (SVM) to realize the classification of the line-transformer relationship. The results of the example simulation show that, compared with the traditional Synthetic Minority Oversampling Technique (SMOTE) for processing unbalanced data, the classification effect of the proposed GAN-based data augmentation method has been significantly improved. In addition, the recall rate of the three types of the line-transformer relationship (line hanging error, magnification error and normal) under the line-transformer relationship identification method proposed in this paper is more than 92%, which proves the effectiveness and feasibility of the method. Full article

(This article belongs to the Special Issue Advances in Sustainable Electrical Engineering)

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14 pages, 6653 KiB

Open AccessArticle

D-distance Risk Factor for Transmission Line Maintenance Management and Cost Analysis

by Waraporn Luejai, Thanapong Suwanasri and Cattareeya Suwanasri

Sustainability 2021, 13(15), 8208; https://0-doi-org.brum.beds.ac.uk/10.3390/su13158208 - 22 Jul 2021

Cited by 6 | Viewed by 5477

Abstract

In this paper, a D-distance risk factor was proposed to prioritize high-voltage transmission lines from high to low risk in transmission line maintenance and renovation management. Various conditions and importance assessment criteria together with the weighting and scoring method were proposed to calculate [...] Read more.

In this paper, a D-distance risk factor was proposed to prioritize high-voltage transmission lines from high to low risk in transmission line maintenance and renovation management. Various conditions and importance assessment criteria together with the weighting and scoring method were proposed to calculate both the renovation and importance indices of transmission lines. The scores of different test methods and visual inspection were differentiated from zero to five as end-of-life to very good condition to evaluate the condition of the line and its components. Additionally, the scores of different importance criteria were modified to assess the line importance from low to high importance. Moreover, the analytic hierarchy process was applied to determine the important weight of all test methods and importance criteria, which were evaluated by utility experts. The renovation and importance indices were combined in a risk matrix to finally determine the risk of the line by using the D-distance technique. Later, the risk of every transmission line was plotted in a risk matrix to prioritize and manage maintenance tasks. Finally, a maintenance cost was analyzed by applying the D-distance risk factor and compared with the replacement cost of a new transmission line for maintenance planning and cost minimization. Twenty out of 115, 230 and 500 kV transmission lines fleet in Thailand were practically analyzed with actual data. The results were realistic to feasibly implement in a transmission system for sustainable management. Full article

(This article belongs to the Special Issue Advances in Sustainable Electrical Engineering)

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17 pages, 4969 KiB

Open AccessArticle

Improved Adaptive Hamiltonian Control Law for Constant Power Load Stability Issue in DC Microgrid: Case Study for Multiphase Interleaved Fuel Cell Boost Converter

by Phatiphat Thounthong, Pongsiri Mungporn, Babak Nahid-Mobarakeh, Nicu Bizon, Serge Pierfederici and Damien Guilbert

Sustainability 2021, 13(14), 8093; https://0-doi-org.brum.beds.ac.uk/10.3390/su13148093 - 20 Jul 2021

Cited by 4 | Viewed by 1765

Abstract

The cascaded connection of power converters in a DC microgrid may cause instabilities. Indeed, power converters operating as external loads exhibit constant power load (CPL) behaviors. In this study, the design of the feedback controller of a multi–cell interleaved fuel cell (FC) step–up [...] Read more.

The cascaded connection of power converters in a DC microgrid may cause instabilities. Indeed, power converters operating as external loads exhibit constant power load (CPL) behaviors. In this study, the design of the feedback controller of a multi–cell interleaved fuel cell (FC) step–up power circuit is based on the adaptive Hamiltonian control law. It includes two integral terms to confirm that there is no steady-state error in the DC bus voltage, and to guarantee the current balancing of each input inductor current. The design confirms that the desired equilibrium point is (locally) asymptotically stable by using the Lyapunov stability proof. The control approach is validated via digital simulations and experimental tests performed with a 2500 W FC converter supplied by an FC/reformer size of 2500 W and 50 V. Full article

(This article belongs to the Special Issue Advances in Sustainable Electrical Engineering)

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16 pages, 3867 KiB

Open AccessArticle

Hybrid Forecasting Methodology for Wind Power-Photovoltaic-Concentrating Solar Power Generation Clustered Renewable Energy Systems

by Simian Pang, Zixuan Zheng, Fan Luo, Xianyong Xiao and Lanlan Xu

Sustainability 2021, 13(12), 6681; https://0-doi-org.brum.beds.ac.uk/10.3390/su13126681 - 11 Jun 2021

Cited by 10 | Viewed by 2938

Abstract

Forecasting of large-scale renewable energy clusters composed of wind power generation, photovoltaic and concentrating solar power (CSP) generation encounters complex uncertainties due to spatial scale dispersion and time scale random fluctuation. In response to this, a short-term forecasting method is proposed to improve [...] Read more.

Forecasting of large-scale renewable energy clusters composed of wind power generation, photovoltaic and concentrating solar power (CSP) generation encounters complex uncertainties due to spatial scale dispersion and time scale random fluctuation. In response to this, a short-term forecasting method is proposed to improve the hybrid forecasting accuracy of multiple generation types in the same region. It is formed through training the long short-term memory (LSTM) network using spatial panel data. Historical power data and meteorological data for CSP plant, wind farm and photovoltaic (PV) plant are included in the dataset. Based on the data set, the correlation between these three types of power generation is proved by Pearson coefficient, and the feasibility of improving the forecasting ability through the hybrid renewable energy clusters is analyzed. Moreover, cases study indicates that the uncertainty of renewable energy cluster power tends to weaken due to partial controllability of CSP generation. Compared with the traditional prediction method, the hybrid prediction method has better prediction accuracy in the real case of renewable energy cluster in Northwest China. Full article

(This article belongs to the Special Issue Advances in Sustainable Electrical Engineering)

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19 pages, 5585 KiB

Open AccessArticle

Analyzing the Effect of Parasitic Capacitance in a Full-Bridge Class-D Current Source Rectifier on a High Step-Up Push–Pull Multiresonant Converter

by Anusak Bilsalam, Chainarin Ekkaravarodome, Viboon Chunkag and Phatiphat Thounthong

Sustainability 2021, 13(10), 5477; https://0-doi-org.brum.beds.ac.uk/10.3390/su13105477 - 13 May 2021

Cited by 3 | Viewed by 2315

Abstract

This paper presents an analysis on the effect of a parasitic capacitance full-bridge class-D current source rectifier (FB-CDCSR) on a high step-up push–pull multiresonant converter (HSPPMRC). The proposed converter can provide high voltage for a 12 V_DC battery using an isolated transformer [...] Read more.

This paper presents an analysis on the effect of a parasitic capacitance full-bridge class-D current source rectifier (FB-CDCSR) on a high step-up push–pull multiresonant converter (HSPPMRC). The proposed converter can provide high voltage for a 12 V_DC battery using an isolated transformer and an FB-CDCSR. The main switches of the push–pull and diode full-bridge rectifier can be operated under a zero-current switching condition (ZCS). The advantages of this technique are that it uses a leakage inductance to achieve the ZCS for the power switch, and the leakage inductance and parasitic junction capacitance are used to design the secondary side of the resonant circuit. A prototype HSPPMRC was built and operated at 200 kHz fixed switching frequency, 340 V_DC output voltage, and 250 W output power. In addition, the efficiency is equal to 96% at maximum load. Analysis of the effect of the parasitic junction capacitance on the full-bridge rectifier indicates that it has a significant impact on the operating point of the resonant tank and voltage. The proposed circuit design was verified via experimental results, which were found to be in agreement with the theoretical analysis. Full article

(This article belongs to the Special Issue Advances in Sustainable Electrical Engineering)

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Review

Jump to: Research

21 pages, 3964 KiB

Open AccessReview

Smart Grid Cyber Security Enhancement: Challenges and Solutions—A Review

by Turki Alsuwian, Aiman Shahid Butt and Arslan Ahmed Amin

Sustainability 2022, 14(21), 14226; https://0-doi-org.brum.beds.ac.uk/10.3390/su142114226 - 31 Oct 2022

Cited by 14 | Viewed by 4462

Abstract

The incorporation of communication technology with Smart Grid (SG) is proposed as an optimal solution to fulfill the requirements of the modern power system. A smart grid integrates multiple energy sources or microgrids and is supported by an extensive control and communication network [...] Read more.

The incorporation of communication technology with Smart Grid (SG) is proposed as an optimal solution to fulfill the requirements of the modern power system. A smart grid integrates multiple energy sources or microgrids and is supported by an extensive control and communication network using the Internet of Things (IoT) for a carbon-free, more reliable, and intelligent energy system. Along with many benefits, the system faces novel security challenges, data management, integration, and interoperability challenges. The advanced control and communication network in the smart grid is susceptible to cyber and cyber-physical threats. A lot of research has been done to improve the cyber security of the smart grid. This review aims to provide an overview of the types of cyber security threats present for smart grids with an insight into strategies to overcome the challenges. As the selection of techniques and technologies may vary according to the threats faced, therefore the adoption of researched methods is compared and discussed. As cyber-security is the greatest challenge in smart grid implementation, this review is beneficial during the planning and operation of smart grids for enhanced security. Full article

(This article belongs to the Special Issue Advances in Sustainable Electrical Engineering)

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