International Journal of Energy Technology and Policy (13 papers in press)

Regular Issues

• Method for Predicting Comprehensive Energy Demand in Industrial Parks Based on Echo State Networks  
  by Xiaojun Zhu, Yan Li, Decheng Wang, Qun Zhang, Yinzhe Xie, Na Li, Zhu Chen 
  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, 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.
  Keywords: comprehensive energy system of the park; energy demand; cold/hot/electrical loads; crossover algorithm; echo state network; demand forecast.
  DOI: 10.1504/IJETP.2024.10061515
   
  
• The dynamic impact of regional construction industry economy, energy and carbon emissions based on HMM  
  by Guangquan Zhou, Zhiyu Fu, Yong Liu, Zhengya He, Mengya Cai, Liang Luo 
  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 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 of regional carbon emission development state and the dynamic relationship between carbon emission, economic growth and energy consumption.
  Keywords: building carbon emissions; improved HMM; state prediction; dynamic impact.
  DOI: 10.1504/IJETP.2024.10062210
   
  
• Evaluation Method for Energy Conservation and Emission Reduction Potential of Photovoltaic New Energy Based on Entropy Weighted Matter Element  
  by Wei He, Rujie Liu, Jicheng ZHANG, Lixin Wu 
  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. Establish an evaluation index system for the potential of energy conservation and emission reduction in photovoltaic new energy. 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. Construct a matter element model for evaluating the potential for energy conservation and emission reduction of photovoltaic new energy, and calculate the entropy weight of the evaluation indicators 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%.
  Keywords: entropy weight matter element; photovoltaic new energy; energy conservation and emission reduction; potential assessment.
  DOI: 10.1504/IJETP.2024.10061516
   
  
• Fuzzy PID based temperature control method for power transformer coils  
  by Huige Chen 
  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.
  Keywords: fuzzy PID; power transformer; coil temperature; control methods.
  DOI: 10.1504/IJETP.2024.10061517
   
  
• Low voltage current transformer defect detection method based on Hausdorff distance algorithm under Charged state  
  by Kai Sun, Xiaohui Zhai, Yanling Sun, Yan Du, Yuning Fa 
  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, calculate the noise variance of the defect image of low-voltage current transformer, adjust the grey variance in the bilateral filter function, and obtain the defect image of low-voltage current transformer after noise removal. 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.
  Keywords: charged state; Hausdorff distance algorithm; low voltage current transformer; defect detection.
  DOI: 10.1504/IJETP.2024.10061518
   
  
• Load coordination control method of new energy vehicle Charging pile based on Markov chain  
  by Shun Liu, Yajuan Zhou, Yue Lu, Yang Liu, Qingtao Li 
  Abstract: In order to reduce the load peak valley difference of 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 calculate the required charging time. 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 charging station.
  Keywords: Markov chain; new energy vehicles; energy crisis; load control; power grid operation; least square method.
  DOI: 10.1504/IJETP.2024.10061519
   
  
• Evaluation Method of Enterprise Carbon Asset Value Based on Analytic Hierarchy Process and Grey Correlation Method in the Context of Carbon Neutrality  
  by Jiawen Liu, Xiaodong Lan, Chungeng He 
  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, complete the construction of an indicator system based on the different forms of corporate carbon assets. 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.
  Keywords: carbon neutrality background; analytic hierarchy process; AHP; grey correlation method; regression calculation; information gain; indicator weight; factor set.
  DOI: 10.1504/IJETP.2024.10062112
   
  
• Partial Discharge Detection Method for Power Equipment Based on UHF Method  
  by Shengchun Liu, Jie Zhang 
  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.
  Keywords: UHF; Power equipment; Partial discharge; Antenna sensor; Wavelet entropy; Feature extraction.
  DOI: 10.1504/IJETP.2024.10062119
   
  
• Research on Carbon Emission Accounting of SF6 Electrical Equipment Based on Improved Random Forest Algorithm  
  by Wenwei ZHU, Baichong Pan, Weixian CHE, Chenghao XU 
  Abstract: Due to the large convergence error and high interference coefficient of carbon emissions accounting, research on carbon emission accounting of SF6 electrical equipment based on improved random forest algorithm is proposed. Firstly, determine the arc extinguishing characteristics and insulation performance of SF6 electrical equipment. Then, analyze the differences in the decomposition of substances in SF6 electrical equipment under various conditions, and use differential optical absorption spectroscopy 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.
  Keywords: SF6 electrical equipment; Carbon emissions; Accounting; Arc extinguishing characteristics; OOB error estimation; Nonlinear activation function.
  DOI: 10.1504/IJETP.2024.10062120
   
  
• Multi-objective capacity optimization method for renewable energy generation systems based on artificial bee colony algorithm  
  by Hongwei Dong, Zhuoyu Jiang, Tao Han, Jingyuan Yin 
  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%.
  Keywords: artificial bee colony algorithm; renewable energy; power generation system; multiple objectives; capacity planning.
  DOI: 10.1504/IJETP.2024.10062891
   
  
• Robust design of damping controller for power system using a combination of snake optimization algorithm and optimal control theory  
  by Niharika Agrawal, Faheem Ahmed Khan, Mamatha Gowda 
  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 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.
  Keywords: algorithm; damping; efficient; modelling; oscillations; power system; robust; stability; low-frequency oscillations; LFO; snake optimisation algorithm; SOA; linear quadratic regulator; LQR.
  DOI: 10.1504/IJETP.2024.10063018
   
  
• Frequency modulation control of electric energy storage system based on abundance index  
  by Bingjie Li, Zesen Li, Guojing Liu 
  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, analyse the control principle of energy storage charging and discharging, and construct a frequency characteristic model of the power energy storage system; 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.
  Keywords: electric energy storage system; frequency modulation control; abundance index; equivalent frequency modulation coefficient; capacity balancing.
  DOI: 10.1504/IJETP.2024.10063177
   
  
• Recent technological advances in the production of green hydrogen: a review  
  by Alvaro Ferney Algarra Rincon, Samuel Alberto Ouana, Tania Cristina De Souza, Daniel Azevedo Vieira, Jéssica De Oliveira Notório Ribeiro 
  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.
  Keywords: energy transition; green hydrogen; production technologies.
  DOI: 10.1504/IJETP.2024.10063697