Template-Type: ReDIF-Article 1.0 Author-Name: Xiaojun Zhu Author-X-Name-First: Xiaojun Author-X-Name-Last: Zhu Author-Name: Yan Li Author-X-Name-First: Yan Author-X-Name-Last: Li Author-Name: Decheng Wang Author-X-Name-First: Decheng Author-X-Name-Last: Wang Author-Name: Qun Zhang Author-X-Name-First: Qun Author-X-Name-Last: Zhang Author-Name: Yinzhe Xie Author-X-Name-First: Yinzhe Author-X-Name-Last: Xie Author-Name: Na Li Author-X-Name-First: Na Author-X-Name-Last: Li Author-Name: Zhu Chen Author-X-Name-First: Zhu Author-X-Name-Last: Chen Title: Method for predicting comprehensive energy demand in industrial parks based on echo state networks Abstract: To achieve accurate prediction of energy demand, this study designed a new method for predicting comprehensive energy demand in industrial parks using echo state networks. Firstly, analyse the comprehensive energy structure of the park, then collect and supplement historical comprehensive energy load consumption data. Secondly, select the factors that affect the load demand forecast, and calculate the comprehensive similarity of similar days of historical energy demand according to the mutual information between the influencing factors. Finally, input the calculation results into the optimised echo state network of the crossbar algorithm, and output the predicted comprehensive energy demand of the park. Experiment shows that after applying this method, the predicted values fluctuate between 1.410%-2.384%, RMSE values fluctuate between 176.4 MW-205.3 MW, indicating that the error of the predicted results using this method is relatively small. Journal: Int. J. of Energy Technology and Policy Pages: 2-16 Issue: 1/2 Volume: 19 Year: 2024 Keywords: comprehensive energy system of the park; energy demand; cold/hot/electrical loads; crossover algorithm; echo state network; demand forecast. File-URL: http://www.inderscience.com/link.php?id=138535 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetpo:v:19:y:2024:i:1/2:p:2-16 Template-Type: ReDIF-Article 1.0 Author-Name: Guangquan Zhou Author-X-Name-First: Guangquan Author-X-Name-Last: Zhou Author-Name: Zhiyu Fu Author-X-Name-First: Zhiyu Author-X-Name-Last: Fu Author-Name: Yong Liu Author-X-Name-First: Yong Author-X-Name-Last: Liu Author-Name: Zhengya He Author-X-Name-First: Zhengya Author-X-Name-Last: He Author-Name: Mengya Cai Author-X-Name-First: Mengya Author-X-Name-Last: Cai Author-Name: Liang Luo Author-X-Name-First: Liang Author-X-Name-Last: Luo Title: The dynamic impact of regional construction industry economy, energy and carbon emissions based on HMM Abstract: Aiming at the uncertainty of the internal correlation between economic growth, energy consumption and carbon emissions in regional construction industry, a dynamic impact research method based on hidden Markov model (HMM) was proposed. Firstly, the dynamic correlation of three variables in the region was established based on HMM, the optimisation parameter estimation of time window was set, and the optimal prediction of carbon emission state was achieved with Viterbi algorithm. Then, the dynamic parameters of the model with the best prediction effect were obtained, and further describes the evolution of the interaction of the three variables in the region. Finally, the empirical analysis of the East China region shows that the average prediction accuracy of HMM under the optimal time window is more than 93%, and its dynamic parameters intuitively describe the change in regional carbon emission development state and the dynamic relationship between carbon emissions, economic growth, and energy consumption. Journal: Int. J. of Energy Technology and Policy Pages: 17-34 Issue: 1/2 Volume: 19 Year: 2024 Keywords: building carbon emissions; improved HMM; state prediction; dynamic impact. File-URL: http://www.inderscience.com/link.php?id=138536 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetpo:v:19:y:2024:i:1/2:p:17-34 Template-Type: ReDIF-Article 1.0 Author-Name: Wei He Author-X-Name-First: Wei Author-X-Name-Last: He Author-Name: Rujie Liu Author-X-Name-First: Rujie Author-X-Name-Last: Liu Author-Name: Jicheng Zhang Author-X-Name-First: Jicheng Author-X-Name-Last: Zhang Author-Name: Lixin Wu Author-X-Name-First: Lixin Author-X-Name-Last: Wu Title: Evaluation method for energy conservation and emission reduction potential of photovoltaic new energy based on entropy weighted matter element Abstract: In order to shorten the evaluation time of energy-saving and emission reduction potential and reduce evaluation errors, a method based on entropy weighted matter element for evaluating the energy-saving and emission reduction potential of photovoltaic new energy is proposed. First, an evaluation index system is established for the potential of energy conservation and emission reduction in photovoltaic new energy. Then, by calculating the information gain rate of each indicator, measuring the importance of each indicator, and achieving quantitative processing of the indicator system, accurate evaluation results can be obtained. Finally, A matter element model is constructed for evaluating the potential for energy conservation and emission reduction of photovoltaic new energy, and the entropy weight of the evaluation indicators is calculated to complete the evaluation of energy conservation and emission reduction potential. The experimental results show that the proposed method can reduce evaluation errors and time overhead, with a maximum evaluation error of only 1.5%. Journal: Int. J. of Energy Technology and Policy Pages: 50-64 Issue: 1/2 Volume: 19 Year: 2024 Keywords: entropy weight matter element; photovoltaic new energy; energy conservation and emission reduction; potential assessment. File-URL: http://www.inderscience.com/link.php?id=138537 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetpo:v:19:y:2024:i:1/2:p:50-64 Template-Type: ReDIF-Article 1.0 Author-Name: Huige Chen Author-X-Name-First: Huige Author-X-Name-Last: Chen Title: Fuzzy PID-based temperature control method for power transformer coils Abstract: To improve the response speed and control stability of power transformer coil temperature control, a fuzzy PID-based power transformer coil temperature control method is studied. Based on the physical model of power transformers, a mathematical model for temperature control of power transformer coils is constructed. For the constructed mathematical model, the fuzzy PID control algorithm is used to control the temperature of the power transformer coil. The PID control part uses proportional, integral, and differential operations to control the coil temperature. The fuzzy control algorithm is used to set fuzzy rules for the PID control parameters, and the power transformer coil temperature control results are output through the fuzzy inference process. The results show that using this method, the coil temperature can be controlled at the target temperature within 0.1 seconds, with fast response speed and high control stability. Journal: Int. J. of Energy Technology and Policy Pages: 86-104 Issue: 1/2 Volume: 19 Year: 2024 Keywords: fuzzy PID; power transformer; coil temperature; control methods. File-URL: http://www.inderscience.com/link.php?id=138538 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetpo:v:19:y:2024:i:1/2:p:86-104 Template-Type: ReDIF-Article 1.0 Author-Name: Kai Sun Author-X-Name-First: Kai Author-X-Name-Last: Sun Author-Name: Xiaohui Zhai Author-X-Name-First: Xiaohui Author-X-Name-Last: Zhai Author-Name: Yanling Sun Author-X-Name-First: Yanling Author-X-Name-Last: Sun Author-Name: Yan Du Author-X-Name-First: Yan Author-X-Name-Last: Du Author-Name: Yuning Fa Author-X-Name-First: Yuning Author-X-Name-Last: Fa Title: Low voltage current transformer defect detection method based on Hausdorff distance algorithm under charged state Abstract: In order to accurately detect the defects of low-voltage current transformers, a defect detection method of low-voltage current transformers based on Hausdorff distance algorithm under charged state is proposed. In the charged state, the noise variance of the defect image of low-voltage current transformer is calculated, the grey variance in the bilateral filter function is adjusted, and the defect image of low-voltage current transformer after noise removal is obtained. The Canny edge results are calculated to obtain the distance transform map. The mask convolution processing is performed on the distance transform map to cluster the results, and then the defect characteristics of different types of low-voltage current transformers are obtained. At the same time, the Hausdorff distance algorithm and elastic graph matching are effectively combined to realise defect detection of low-voltage current transformers. The experimental results show that the proposed method can quickly and accurately detect the defects of low-voltage current transformers. Journal: Int. J. of Energy Technology and Policy Pages: 65-85 Issue: 1/2 Volume: 19 Year: 2024 Keywords: charged state; Hausdorff distance algorithm; low voltage current transformer; defect detection. File-URL: http://www.inderscience.com/link.php?id=138539 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetpo:v:19:y:2024:i:1/2:p:65-85 Template-Type: ReDIF-Article 1.0 Author-Name: Shun Liu Author-X-Name-First: Shun Author-X-Name-Last: Liu Author-Name: Yajuan Zhou Author-X-Name-First: Yajuan Author-X-Name-Last: Zhou Author-Name: Yue Lu Author-X-Name-First: Yue Author-X-Name-Last: Lu Author-Name: Yang Liu Author-X-Name-First: Yang Author-X-Name-Last: Liu Author-Name: Qingtao Li Author-X-Name-First: Qingtao Author-X-Name-Last: Li Title: Load coordination control method of new energy vehicle charging pile based on Markov chain Abstract: In order to reduce the load peak valley difference of a charging station and improve the stability of load operation, a load coordination control method of new energy vehicle charging station based on Markov chain was proposed. The Markov chain theory is applied to determine the state transition form of the new energy vehicle charging load, and the required charging time is calculated. The least square method and inverse linear regression equation are used to predict the output load of new energy vehicle charging station. The load objective function and constraint conditions of the charging station are constructed, and the load coordination control objective is determined to achieve accurate control of the charging load. The experimental results show that after using this method, while meeting the charging demand, the peak to valley load difference can only reach 1.70 kW. This shows that the method can ensure the operation stability of a charging station. Journal: Int. J. of Energy Technology and Policy Pages: 105-119 Issue: 1/2 Volume: 19 Year: 2024 Keywords: Markov chain; new energy vehicles; energy crisis; load control; power grid operation; least square method. File-URL: http://www.inderscience.com/link.php?id=138540 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetpo:v:19:y:2024:i:1/2:p:105-119 Template-Type: ReDIF-Article 1.0 Author-Name: Jiawen Liu Author-X-Name-First: Jiawen Author-X-Name-Last: Liu Author-Name: Xiaodong Lan Author-X-Name-First: Xiaodong Author-X-Name-Last: Lan Author-Name: Chungeng He Author-X-Name-First: Chungeng Author-X-Name-Last: He Title: Evaluation method of enterprise carbon asset value based on analytic hierarchy process and grey correlation method in the context of carbon neutrality Abstract: In the context of carbon neutrality, there is a problem of low sensitivity coefficient of carbon asset value in the evaluation of corporate carbon asset value. To this end, a method for evaluating the value of carbon assets in enterprises using the analytic hierarchy process and grey correlation method in the context of carbon neutrality is proposed. Firstly, the construction of an indicator system based on the different forms of corporate carbon assets is completed. Then, through regression calculation of value evaluation indicators, the selection of value evaluation indicators is achieved. Finally, through the analytic hierarchy process - grey correlation method, a carbon asset value evaluation model for enterprises is constructed to achieve value evaluation research. The experimental results indicate that the sensitivity coefficient of using the proposed method to evaluate the value of carbon assets is high, and the evaluation effect is good. Journal: Int. J. of Energy Technology and Policy Pages: 154-170 Issue: 1/2 Volume: 19 Year: 2024 Keywords: carbon neutrality background; analytic hierarchy process; AHP; grey correlation method; regression calculation; information gain; indicator weight; factor set. File-URL: http://www.inderscience.com/link.php?id=138542 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetpo:v:19:y:2024:i:1/2:p:154-170 Template-Type: ReDIF-Article 1.0 Author-Name: Shengchun Liu Author-X-Name-First: Shengchun Author-X-Name-Last: Liu Author-Name: Jie Zhang Author-X-Name-First: Jie Author-X-Name-Last: Zhang Title: Partial discharge detection method for power equipment based on UHF method Abstract: In order to avoid the impact of noise on the performance of partial discharge detection and improve the accuracy of detection results, a partial discharge detection method for power equipment based on ultra-high frequency method is proposed. Firstly, use a conical antenna sensor to collect ultra-high frequency signals during partial discharge of power equipment. Then, wavelet entropy is used to denoise the collected ultra-high frequency partial discharge signal, removing the noise components contained in the signal and retaining the effective information components of the signal. Extract features such as signal skewness, steepness, discharge level, phase, and cross correlation, and use chicken swarm algorithm to detect partial discharge of power equipment based on the extracted features. The experimental results show that the detection result of this method is the most accurate, and the number of false samples for partial discharge signal type is 0, indicating that its detection effect is good. Journal: Int. J. of Energy Technology and Policy Pages: 120-134 Issue: 1/2 Volume: 19 Year: 2024 Keywords: UHF; power equipment; partial discharge; antenna sensor; wavelet entropy; feature extraction. File-URL: http://www.inderscience.com/link.php?id=138543 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetpo:v:19:y:2024:i:1/2:p:120-134 Template-Type: ReDIF-Article 1.0 Author-Name: Wenwei Zhu Author-X-Name-First: Wenwei Author-X-Name-Last: Zhu Author-Name: Baichong Pan Author-X-Name-First: Baichong Author-X-Name-Last: Pan Author-Name: Weixian Che Author-X-Name-First: Weixian Author-X-Name-Last: Che Author-Name: Chenghao Xu Author-X-Name-First: Chenghao Author-X-Name-Last: Xu Title: Research on carbon emission accounting of SF6 electrical equipment based on improved random forest algorithm Abstract: Due to the large convergence error and high interference coefficient of carbon emissions accounting, research on carbon emission accounting of SF<SUB align="right"><SMALL>6</SMALL></SUB> electrical equipment based on improved random forest algorithm is proposed. Firstly, the arc extinguishing characteristics and insulation performance of SF<SUB align="right"><SMALL>6</SMALL></SUB> electrical equipment are determined. Then, the differences in the decomposition of substances in SF<SUB align="right"><SMALL>6</SMALL></SUB> electrical equipment under various conditions are analysed, and differential optical absorption spectroscopy is used to determine the carbon emission equivalent of the equipment. Finally, the OOB error estimation algorithm is introduced to build an improved random forest algorithm model, and the nonlinear activation function is used to determine the synapse strength, and the information function is used to adjust the convergence value of accounting error to complete the carbon emissions accounting. The results indicate that the proposed method can reduce the convergence value of accounting errors and the interference coefficient of accounting results. Journal: Int. J. of Energy Technology and Policy Pages: 135-153 Issue: 1/2 Volume: 19 Year: 2024 Keywords: SF6 electrical equipment; carbon emissions; accounting; arc extinguishing characteristics; OOB error estimation; non-linear activation function. File-URL: http://www.inderscience.com/link.php?id=138544 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetpo:v:19:y:2024:i:1/2:p:135-153 Template-Type: ReDIF-Article 1.0 Author-Name: Hongwei Dong Author-X-Name-First: Hongwei Author-X-Name-Last: Dong Author-Name: Zhuoyu Jiang Author-X-Name-First: Zhuoyu Author-X-Name-Last: Jiang Author-Name: Tao Han Author-X-Name-First: Tao Author-X-Name-Last: Han Author-Name: Jingyuan Yin Author-X-Name-First: Jingyuan Author-X-Name-Last: Yin Title: Multi-objective capacity optimisation method for renewable energy generation systems based on artificial bee colony algorithm Abstract: In order to reduce energy loss and improve charging and discharging efficiency, a multi-objective capacity optimisation method for renewable energy power generation systems based on artificial bee colony algorithm is proposed. Firstly, build models for wind power, optoelectronics, and batteries. Secondly, a multi-objective capacity optimisation objective function for renewable energy generation systems is constructed from three aspects: the daily cost borne by power users, the volatility of wind and solar energy, and the energy loss of storage batteries, and constraint conditions are set. Finally, artificial bee colony algorithm is used to continuously search for new honey sources, in order to obtain the optimal solution of the optimisation objective function and achieve multi-objective capacity optimisation of the power generation system. The experimental results show that this method can effectively reduce the energy loss, the daily energy loss is about 0.1 kWh, and the charging and discharging efficiency is always above 91%. Journal: Int. J. of Energy Technology and Policy Pages: 35-49 Issue: 1/2 Volume: 19 Year: 2024 Keywords: artificial bee colony algorithm; renewable energy; power generation system; multiple objectives; capacity planning. File-URL: http://www.inderscience.com/link.php?id=138546 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetpo:v:19:y:2024:i:1/2:p:35-49 Template-Type: ReDIF-Article 1.0 Author-Name: Niharika Agrawal Author-X-Name-First: Niharika Author-X-Name-Last: Agrawal Author-Name: Faheem Ahmed Khan Author-X-Name-First: Faheem Ahmed Author-X-Name-Last: Khan Author-Name: Mamatha Gowda Author-X-Name-First: Mamatha Author-X-Name-Last: Gowda Title: Robust design of damping controller for power system using a combination of snake optimisation algorithm and optimal control theory Abstract: Low-frequency oscillations (LFO) are created in the power system due to various disturbances. The LFO if not controlled, grows and causes the system separation. There is a huge financial loss due to the interruption of the power supply caused by disturbances. With the increasing complexity of the modern power system, there is a need for the design of a more accurate and detailed modelling. An Advanced Heffron Phillips Model (AHPM) is developed with a higher order Synchronous Generator Model 1.1, based on ten K-Constants for stability improvement. This AHPM employs the combination of snake optimisation algorithm (SOA) and linear quadratic regulator (LQR) from optimal control theory. The highest damping ratio (99.98%) is obtained by AHPM in coordination with PSS, and TCSC based on SOA and LQR. For various parameters, the settling time ranges from 1.5 to 2.0 seconds. This AHPM is robust and capable of meeting the challenges of grid integration with renewables. Journal: Int. J. of Energy Technology and Policy Pages: 171-215 Issue: 1/2 Volume: 19 Year: 2024 Keywords: algorithm; damping; efficient; modelling; oscillations; power system; robust; stability; low-frequency oscillations; LFO; snake optimisation algorithm; SOA; linear quadratic regulator; LQR. File-URL: http://www.inderscience.com/link.php?id=138547 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetpo:v:19:y:2024:i:1/2:p:171-215 Template-Type: ReDIF-Article 1.0 Author-Name: Bingjie Li Author-X-Name-First: Bingjie Author-X-Name-Last: Li Author-Name: Zesen Li Author-X-Name-First: Zesen Author-X-Name-Last: Li Author-Name: Guojing Liu Author-X-Name-First: Guojing Author-X-Name-Last: Liu Title: Frequency modulation control of electric energy storage system based on abundance index Abstract: In order to overcome the problems of high time consumption and low accuracy of frequency regulation control in power energy storage systems, this paper proposes a frequency regulation control method for power energy storage systems based on adequacy indicators. Firstly, the control principle of energy storage charging and discharging are analysed, and a frequency characteristic model of the power energy storage system is constructed. Then, considering the adequacy index of power generation capacity, a bundle condition for capacity balance of the power energy storage system is constructed. Finally, the frequency modulation of the power energy storage system is controlled through the equivalent frequency modulation coefficient. The experimental results show that the frequency modulation control takes only 8.2 seconds, and the accuracy of frequency modulation control can reach 99.90%, indicating that the method proposed in this paper can effectively improve the effectiveness of power energy storage systems. Journal: Int. J. of Energy Technology and Policy Pages: 216-229 Issue: 1/2 Volume: 19 Year: 2024 Keywords: electric energy storage system; frequency modulation control; abundance index; equivalent frequency modulation coefficient; capacity balancing. File-URL: http://www.inderscience.com/link.php?id=138548 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetpo:v:19:y:2024:i:1/2:p:216-229 Template-Type: ReDIF-Article 1.0 Author-Name: Alvaro Ferney Algarra Rincon Author-X-Name-First: Alvaro Ferney Algarra Author-X-Name-Last: Rincon Author-Name: Samuel Alberto Ouana Author-X-Name-First: Samuel Alberto Author-X-Name-Last: Ouana Author-Name: Tania Cristina de Souza Author-X-Name-First: Tania Cristina de Author-X-Name-Last: Souza Author-Name: Daniel Azevedo Vieira Author-X-Name-First: Daniel Azevedo Author-X-Name-Last: Vieira Author-Name: Jéssica de Oliveira Notório Ribeiro Author-X-Name-First: Jéssica de Oliveira Notório Author-X-Name-Last: Ribeiro Title: Recent technological advances in the production of green hydrogen: a review Abstract: Hydrogen is recognised as the fuel of the future and a key component for sustainable energy transition in all spaces that currently use fossil fuels, such as the electricity, transport, and industrial sector. The most widely used hydrogen production process is water electrolysis and often requires large amounts of energy. However, to obtain clean hydrogen, it is essential that it comes from renewable and sustainable sources. Therefore, this article reviews the most recent advances in green hydrogen production technologies published during the 2019-2023 period. A global overview of green hydrogen production is compiled in this article, and studies on the mechanisms of electrolysis, photocatalysis and thermochemical cycles for water decomposition are also presented, as are new strategies for integrating technologies and efforts designed to make production more sustainable and competitive with conventional methods. Thermochemical cycle technology, it was identified as one of the most promising to produce green hydrogen. Journal: Int. J. of Energy Technology and Policy Pages: 261-285 Issue: 3/4 Volume: 19 Year: 2024 Keywords: energy transition; green hydrogen; production technologies. File-URL: http://www.inderscience.com/link.php?id=141379 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetpo:v:19:y:2024:i:3/4:p:261-285 Template-Type: ReDIF-Article 1.0 Author-Name: Kiran Jameel Author-X-Name-First: Kiran Author-X-Name-Last: Jameel Author-Name: Saima Tabassum Author-X-Name-First: Saima Author-X-Name-Last: Tabassum Author-Name: Atteeq Razzak Author-X-Name-First: Atteeq Author-X-Name-Last: Razzak Author-Name: Laeeq Janjua Author-X-Name-First: Laeeq Author-X-Name-Last: Janjua Author-Name: Shaher Bano Author-X-Name-First: Shaher Author-X-Name-Last: Bano Title: Underlying the impact of information communication technology and renewable-non-renewable energy on environmental sustainability under the shadow of industrial waste management - a fresh insight from China Abstract: Due to rapid economic growth and a high population, China is the largest energy user and CO<SUB align="right"><SMALL>2</SMALL></SUB> emitter. This research examines China's renewable energy (RE) use and its relationship to CO<SUB align="right"><SMALL>2</SMALL></SUB> emissions, industrial waste (IW), NRE, and ICT consumption. ARDL estimation was used to determine the long-term co-integration of variables for the data from 2000 to 2022 of China. The study output shows that ICT and NRE have a significant negative relationship with REC, and a 1% increase in ICT and NRE will respond to a decrease of 1.18% and 1.005% in REC. Furthermore, CO<SUB align="right"><SMALL>2</SMALL></SUB> has a positive relation with REC, and a 1% increase in CO<SUB align="right"><SMALL>2</SMALL></SUB> will result in an upsurge of 2.98% in REC. According to robustness check through FMOLS and DOLS estimators, empirical evidence shows there is a significant effect at a 5% level of significance of the variables NRE, IW, ICT CO<SUB align="right"><SMALL>2</SMALL></SUB> on REC in China in the long-run. Journal: Int. J. of Energy Technology and Policy Pages: 321-343 Issue: 3/4 Volume: 19 Year: 2024 Keywords: renewable energy consumption; environment degradation; CO2 emission; industrial waste; information communication technology; non-renewable energy consumption; ARDL; China. File-URL: http://www.inderscience.com/link.php?id=141386 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetpo:v:19:y:2024:i:3/4:p:321-343 Template-Type: ReDIF-Article 1.0 Author-Name: Haicheng Zhou Author-X-Name-First: Haicheng Author-X-Name-Last: Zhou Author-Name: Hengchu Shi Author-X-Name-First: Hengchu Author-X-Name-Last: Shi Author-Name: Qiutao Chen Author-X-Name-First: Qiutao Author-X-Name-Last: Chen Author-Name: Penghui Yang Author-X-Name-First: Penghui Author-X-Name-Last: Yang Author-Name: Xi Zhang Author-X-Name-First: Xi Author-X-Name-Last: Zhang Title: A multi-objective optimisation of relay protection settings in distribution networks based on improved grey wolf algorithm Abstract: In order to overcome the problems of high data mining accuracy, poor effectiveness, and long relay protection action time in traditional methods, a multi-objective optimisation method of relay protection settings in distribution networks based on improved grey wolf algorithm is proposed. Random forest algorithm is used for mining relay protection data in distribution networks. Taking the relay protection settings as the parameters to be optimised, a multi-objective optimisation function for relay protection settings is constructed using parameters such as relay protection action time, transmission line weight coefficient, and weight factors of vulnerability and sensitivity constraints. The improved grey wolf algorithm is used to solve the objective function and obtain relevant results. According to the analysis of relevant test results, the maximum data mining accuracy of the proposed method is 98.75%, good optimisation effect, and a maximum relay protection action time of 0.87 s. Journal: Int. J. of Energy Technology and Policy Pages: 302-320 Issue: 3/4 Volume: 19 Year: 2024 Keywords: improved grey wolf algorithm; distribution network; relay protection settings; multi-objective optimisation; random forest algorithms; objective function. File-URL: http://www.inderscience.com/link.php?id=141387 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetpo:v:19:y:2024:i:3/4:p:302-320 Template-Type: ReDIF-Article 1.0 Author-Name: Wei Tong Author-X-Name-First: Wei Author-X-Name-Last: Tong Author-Name: Qi-ping Huang Author-X-Name-First: Qi-ping Author-X-Name-Last: Huang Title: A method for power equipment condition monitoring and fault location based on improved ant colony algorithm Abstract: Different malfunctions may arise during the operation of power equipment, impacting the quality and dependability of the power supply. Conventional monitoring techniques face challenges, prompting the introduction of a novel power equipment monitoring and fault localisation method based on an enhanced ant colony algorithm. This approach entails gathering operational signals from the power equipment and amalgamating singular value decomposition with particle filtering methods to oversee the equipment's condition. Through enhancements to the pheromone configuration and update approach of the ant colony algorithm, a fault localisation assessment function is formulated to achieve precise fault localisation. Empirical findings have illustrated that this method has the capability to promptly monitor equipment status and attain fault localisation accuracy surpassing 90%. Journal: Int. J. of Energy Technology and Policy Pages: 363-376 Issue: 3/4 Volume: 19 Year: 2024 Keywords: improving ant colony algorithm; electrical equipment; condition monitoring; fault location. File-URL: http://www.inderscience.com/link.php?id=141388 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetpo:v:19:y:2024:i:3/4:p:363-376 Template-Type: ReDIF-Article 1.0 Author-Name: Yang Yang Author-X-Name-First: Yang Author-X-Name-Last: Yang Author-Name: Shenbing Hua Author-X-Name-First: Shenbing Author-X-Name-Last: Hua Author-Name: Hongxia Wang Author-X-Name-First: Hongxia Author-X-Name-Last: Wang Author-Name: Meng Li Author-X-Name-First: Meng Author-X-Name-Last: Li Author-Name: Qifei He Author-X-Name-First: Qifei Author-X-Name-Last: He Author-Name: Minguan Zhao Author-X-Name-First: Minguan Author-X-Name-Last: Zhao Author-Name: Yuanhao Wan Author-X-Name-First: Yuanhao Author-X-Name-Last: Wan Author-Name: Shuyang Ma Author-X-Name-First: Shuyang Author-X-Name-Last: Ma Title: Detection method of icing thickness of overhead transmission lines based on canny algorithm Abstract: This study proposes a novel detection approach utilising the canny algorithm to address the low accuracy issues in traditional icing thickness detection on overhead transmission lines. Employing an unmanned aerial vehicle equipped with a camera for collecting icing images, noise interference is mitigated via compressive sensing theory. Converting the images into greyscale enables edge detection using the canny algorithm. Utilising random Hough transform for extracting edge lines, which are then fused with edge images for subsequent processing and ice thickness calculation. Experimental results validate the substantial enhancement in detection accuracy and efficiency for icing thickness detection on overhead transmission lines with the application of this method. Journal: Int. J. of Energy Technology and Policy Pages: 344-362 Issue: 3/4 Volume: 19 Year: 2024 Keywords: canny algorithm; overhead transmission lines; thickness of ice cover; test method. File-URL: http://www.inderscience.com/link.php?id=141389 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetpo:v:19:y:2024:i:3/4:p:344-362 Template-Type: ReDIF-Article 1.0 Author-Name: Peidong He Author-X-Name-First: Peidong Author-X-Name-Last: He Author-Name: Xiaojun Li Author-X-Name-First: Xiaojun Author-X-Name-Last: Li Author-Name: Shuyu Deng Author-X-Name-First: Shuyu Author-X-Name-Last: Deng Author-Name: Yaxin Tu Author-X-Name-First: Yaxin Author-X-Name-Last: Tu Author-Name: Wenqi Shen Author-X-Name-First: Wenqi Author-X-Name-Last: Shen Title: Carbon emissions prediction method of industrial parks based on NSGA-II multi objective genetic algorithm Abstract: In order to address the significant discrepancies between the predicted results of existing industrial carbon emission forecasting methods and the actual results, this study investigates the prediction method of carbon emissions in industrial parks based on the NSGA-II multi-objective genetic algorithm. Firstly, the carbon emission prediction indicators are determined. Then, the normalisation method is applied to preprocess the indicator sample data and calculate the carbon emission prediction indicators for nine industrial parks. Lastly, based on the NSGA-II multi-objective genetic algorithm, non-dominated sorting and crowding distance are calculated to solve the objective function and achieve the prediction of carbon emissions in industrial parks. Through experimental verification, it has been demonstrated that the average absolute error of the prediction results in this study does not exceed 0.15, and the root mean square error remains below 0.10. This indicates that using the proposed method in this study can effectively reduce errors in carbon emission prediction for the industrial parks, resulting in good prediction performance. Journal: Int. J. of Energy Technology and Policy Pages: 286-301 Issue: 3/4 Volume: 19 Year: 2024 Keywords: industrial park; prediction of carbon emissions; NSGA-II multi-objective genetic algorithm; fitness function. File-URL: http://www.inderscience.com/link.php?id=141390 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetpo:v:19:y:2024:i:3/4:p:286-301 Template-Type: ReDIF-Article 1.0 Author-Name: Ayman Abdul Karim Alhijazi Author-X-Name-First: Ayman Abdul Karim Author-X-Name-Last: Alhijazi Author-Name: Ahmad Firas Alloush Author-X-Name-First: Ahmad Firas Author-X-Name-Last: Alloush Title: A review of renewable hybrid power plant technologies: a concept for improving the performance of hybrid solar-biogas power plants Abstract: This paper inspects the latest approaches and provides an overall review of the main studies on modelling and simulating hybrid renewable power plants in several locations worldwide, and exposes the common simulation software that may be used for designing and assessing hybrid power plants. So, the study's limitations include hybrid renewable power plants which use numerous renewable energy sources. The study's key goals include: 1) introducing a new classification method for renewable hybrid power plants; 2) investigated the levelised cost of energy (LCOE) and factors affecting it; 3) renewable share ratios in various hybrid renewable power plants with different configurations; 4) suggesting a concept for improving renewable hybrid power plants' performance with practical experience. The author experimented to produce biogas through five digesters at five different temperatures under the same conditions, which might be used as a reference for condensing temperature in the Rankin cycle. The actual average recorded temperatures were 33.17°C, 37.5°C, 43.52°C, 45.87°C, and 49.6°C. The maximum biogas volume was produced at 43.52°C; however, the suitable heating temperature must be investigated according to the changing efficiency of the Rankine cycle and the production of biogas. Journal: Int. J. of Energy Technology and Policy Pages: 231-260 Issue: 3/4 Volume: 19 Year: 2024 Keywords: energy technologies; renewable power plants; hybrid power plants; modelling software; levelised cost of electricity; LCOE; performance improving; solar energy; biogas. File-URL: http://www.inderscience.com/link.php?id=141394 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetpo:v:19:y:2024:i:3/4:p:231-260