Template-Type: ReDIF-Article 1.0 Author-Name: Zheng Xie Author-X-Name-First: Zheng Author-X-Name-Last: Xie Title: Comprehensive energy retail market transaction evaluation model based on carbon neutrality Abstract: In view of the low Pearson correlation coefficient and Kendall correlation coefficient in traditional methods, the paper proposes a comprehensive energy retail market transaction evaluation model based on carbon neutrality. Firstly, with the goal of carbon-neutral development, we put forward two constraints: carbon dioxide emissions constraint and energy balance constraint. Secondly, the comprehensive energy retail market and its transaction structure are analysed, and transaction evaluation model is designed. Finally, taking the supply side, retail side and demand side data as the input variables of the model, and the transaction evaluation results as the output variables of the model, and a comprehensive energy retail market transaction evaluation model with carbon neutrality as the development goal is built. The experiment shows that the Pearson correlation coefficient of this method is closer to 1, and the Kendall correlation coefficient increases from 0.93 to 0.97. Journal: Int. J. of Energy Technology and Policy Pages: 312-325 Issue: 3/4/5 Volume: 18 Year: 2023 Keywords: carbon neutrality; CO2 emissions constraints; energy balance constraints; comprehensive energy retail market; transaction structure; transaction evaluation. File-URL: http://www.inderscience.com/link.php?id=134158 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetpo:v:18:y:2023:i:3/4/5:p:312-325 Template-Type: ReDIF-Article 1.0 Author-Name: Zhenzhuo Wang Author-X-Name-First: Zhenzhuo Author-X-Name-Last: Wang Author-Name: Yijie Zhu Author-X-Name-First: Yijie Author-X-Name-Last: Zhu Title: Fault identification method of electrical automation distribution equipment in distribution networks based on neural network Abstract: Fault identification of power distribution equipment is of great significance in ensuring the reliability of power supply, saving operating costs, and improving work efficiency. Therefore, a fault identification method of electrical automation distribution equipment in distribution networks based on neural network is proposed. AT89C51 microcontroller is used to establish the architecture of equipment running status signal acquisition, and carry out noise reduction processing. The BP neural network is used to build a fault identification model for power distribution equipment, with the filtered signal used as the model input parameter, and the fault identification result used as the model output parameter, to obtain the fault identification result. The experimental results show that the signal-to-noise ratio of the equipment operation signal of this method has an average value of 54.61 dB, the recognition accuracy remains above 95%, and the average completion time of the identification task is 69.1 ms. Journal: Int. J. of Energy Technology and Policy Pages: 257-274 Issue: 3/4/5 Volume: 18 Year: 2023 Keywords: neural network; distribution networks; fault identification; architecture; electrical automation. File-URL: http://www.inderscience.com/link.php?id=134159 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetpo:v:18:y:2023:i:3/4/5:p:257-274 Template-Type: ReDIF-Article 1.0 Author-Name: Man-Li Zhao Author-X-Name-First: Man-Li Author-X-Name-Last: Zhao Author-Name: Zi-Qin You Author-X-Name-First: Zi-Qin Author-X-Name-Last: You Author-Name: Jing-Lu Li Author-X-Name-First: Jing-Lu Author-X-Name-Last: Li Title: Investment benefit evaluation of wind power energy storage based on improved minimum cross entropy method Abstract: In order to overcome the problems of low evaluation accuracy and poor correlation in the selection of evaluation parameters in existing benefit evaluation methods, a wind power generation energy storage investment benefit evaluation method based on the improved minimum cross entropy method is proposed. Firstly, in order to clarify the output characteristics of wind power generation, a wind power generation characteristic model is constructed. Then, based on the output characteristics of wind power generation, investment benefit evaluation indicators are determined from the perspectives of economic benefits, cost benefits, and environmental benefits. Finally, the continuous function improved minimum cross entropy method is introduced to calculate the weight of the evaluation index. An investment benefit evaluation model is then built. The test results show that the proposed method can improve the accuracy of investment benefit evaluation, with an evaluation accuracy of over 95%, and the parameter correlation in the evaluation is high. Journal: Int. J. of Energy Technology and Policy Pages: 179-194 Issue: 3/4/5 Volume: 18 Year: 2023 Keywords: improved minimum cross entropy method; wind power generation; energy storage investment; benefit evaluation; continuous function. File-URL: http://www.inderscience.com/link.php?id=134160 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetpo:v:18:y:2023:i:3/4/5:p:179-194 Template-Type: ReDIF-Article 1.0 Author-Name: Jing Zeng Author-X-Name-First: Jing Author-X-Name-Last: Zeng Title: Prediction method of carbon emission trading price based on claim rights Abstract: Predicting carbon emissions trading prices is of great significance for improving market transparency. Therefore, this paper proposes a carbon emissions trading price prediction method based on claim rights. Firstly, a factor analysis model to determine six factors that affect the price of carbon emission rights is constructed, including the ratio of industrial added value, coal price, maximum temperature, closing price, natural gas closing price, and policy. Then, a transfer rate matrix is constructed based on Markov functions, and a carbon emission rights option price prediction model is constructed using claim rights. Finally, the influence parameters are substituted into the prediction model, and the European call option method is used to determine the equivalent consideration expectations, achieving the transaction price solution. The results show that the prediction error of this method is only +0.0014 yuan/ton, with an accuracy of 96%, indicating that this method can improve the prediction effect of transaction prices. Journal: Int. J. of Energy Technology and Policy Pages: 246-256 Issue: 3/4/5 Volume: 18 Year: 2023 Keywords: right of claim; carbon emission rights; transaction price; European call options; transfer rate matrix; Markov. File-URL: http://www.inderscience.com/link.php?id=134161 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetpo:v:18:y:2023:i:3/4/5:p:246-256 Template-Type: ReDIF-Article 1.0 Author-Name: Shuangling Wang Author-X-Name-First: Shuangling Author-X-Name-Last: Wang Author-Name: Shudong He Author-X-Name-First: Shudong Author-X-Name-Last: He Title: Load parameter identification method of power system with time delay based on Kalman filter Abstract: Aiming at the problems of low accuracy and large identification error of existing load parameter identification methods, a load parameter identification method of power system with time delay based on Kalman filter is proposed. Firstly, according to the relationship between the time-delay link and the voltage variation in the system, the operation characteristics of the time-delay power system are analysed. Secondly, power function and motor equivalent circuit method are used to characterise different property parameters, and the property analysis of load parameters of power system with time delay is completed. Finally, the load parameter state prediction equation is constructed, and the Kalman gain value of the load parameter is calculated. The parameter identification model of Kalman filter is constructed to complete the power system load parameter identification. The experimental results show that the proposed method can reduce the error of load parameter identification, and the minimum error is only 0.11%. Journal: Int. J. of Energy Technology and Policy Pages: 208-219 Issue: 3/4/5 Volume: 18 Year: 2023 Keywords: Kalman filter; time delay power system; load parameter identification; power function; equivalent circuit; excitation control. File-URL: http://www.inderscience.com/link.php?id=134162 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetpo:v:18:y:2023:i:3/4/5:p:208-219 Template-Type: ReDIF-Article 1.0 Author-Name: Yuanliang Zhang Author-X-Name-First: Yuanliang Author-X-Name-Last: Zhang Author-Name: Bin Guo Author-X-Name-First: Bin Author-X-Name-Last: Guo Author-Name: Liyu Huang Author-X-Name-First: Liyu Author-X-Name-Last: Huang Author-Name: Yin Zheng Author-X-Name-First: Yin Author-X-Name-Last: Zheng Title: A coordinated and optimised scheduling method for integrated energy systems based on improved genetic algorithm Abstract: A coordinated and optimised scheduling method for integrated energy systems based on improved genetic algorithm is proposed in order to improve the energy output efficiency of integrated energy systems. The multi-objective and multi-time dynamic loading model for an integrated energy system is constructed, and the power flow equation for the multi-energy network of electricity, gas and heat is established. The objective function for the coordinated scheduling model of the integrated energy system is designed by introducing the improved genetic algorithm, and the configuration parameters of the objective function are optimised by improving the crossover, variation and the rules of its own cold and heat conversion, so as to realise the coordinated and optimised scheduling of the integrated energy system and get the final scheduling model. The test results show that the proposed method can improve the balance of energy output and the energy efficiency of the system and shorten the convergence time. Journal: Int. J. of Energy Technology and Policy Pages: 195-207 Issue: 3/4/5 Volume: 18 Year: 2023 Keywords: improved genetic algorithm; comprehensive energy; system coordination; optimise scheduling; power flow equation for multi energy network. File-URL: http://www.inderscience.com/link.php?id=134163 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetpo:v:18:y:2023:i:3/4/5:p:195-207 Template-Type: ReDIF-Article 1.0 Author-Name: Liyu Huang Author-X-Name-First: Liyu Author-X-Name-Last: Huang Author-Name: Miaozhuang Cai Author-X-Name-First: Miaozhuang Author-X-Name-Last: Cai Author-Name: Yin Zheng Author-X-Name-First: Yin Author-X-Name-Last: Zheng Author-Name: Yuanliang Zhang Author-X-Name-First: Yuanliang Author-X-Name-Last: Zhang Title: Evaluation method for energy saving and emission reduction effects of high energy-consuming enterprises based on K-means clustering Abstract: In order to quantitatively analyse the effect of energy conservation and emission reduction control of high energy consuming enterprises, an evaluation model of energy conservation and emission reduction effect of high energy consuming enterprises based on K-means clustering was proposed. In this study, the target object of energy saving and emission reduction effect evaluation is selected first, and the optimisation state model of energy saving and emission reduction effect evaluation is constructed. Then, dynamic feature extraction is carried out on model parameters, and the K-means data clustering algorithm is adopted to conduct block fusion clustering processing on characteristic values. Finally, expert knowledge base and empirical model library are constructed to realise energy saving and emission reduction control of high-energy-consuming enterprises. The test results show that this method can reduce the energy cost, develop a scientific management plan and ensure the realisation of energy conservation and emission reduction targets. Journal: Int. J. of Energy Technology and Policy Pages: 298-311 Issue: 3/4/5 Volume: 18 Year: 2023 Keywords: K-means clustering; high energy-consuming enterprises; energy saving; emission reduction; effect evaluation; profitability indicators. File-URL: http://www.inderscience.com/link.php?id=134164 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetpo:v:18:y:2023:i:3/4/5:p:298-311 Template-Type: ReDIF-Article 1.0 Author-Name: Mengdi Zeng Author-X-Name-First: Mengdi Author-X-Name-Last: Zeng Author-Name: Yu Cai Author-X-Name-First: Yu Author-X-Name-Last: Cai Author-Name: Kaihui Shen Author-X-Name-First: Kaihui Author-X-Name-Last: Shen Title: Optimal configuration of new energy grid connected energy storage capacity from the perspective of dual carbon Abstract: To reduce the load shortage rate of new energy grid connection and suppress grid connection fluctuations, an optimised configuration method for energy storage capacity is proposed. After constructing a new energy grid connected energy storage model, establish an objective function based on the dual carbon perspective. Following the principle of electricity balance, ensure that the electricity demand of the grid connected load is equivalent to the output of the power generation module, and calculate the energy storage capacity. Finally, based on power fluctuations, advanced control methods are used to reasonably regulate energy storage capacity. The experiment shows that after applying this method, the power fluctuation of new energy grid connection is between 30-40 kW, the state of charge of energy storage is between 80-90%, the load shortage rate is between 0.012-0.014%, and the service life of the battery can reach eight years, indicating the feasibility of this method. Journal: Int. J. of Energy Technology and Policy Pages: 326-342 Issue: 3/4/5 Volume: 18 Year: 2023 Keywords: new energy power generation; dual carbon theory; power grid connection; advance control; energy storage capacity configuration. File-URL: http://www.inderscience.com/link.php?id=134165 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetpo:v:18:y:2023:i:3/4/5:p:326-342 Template-Type: ReDIF-Article 1.0 Author-Name: Baoyu Ye Author-X-Name-First: Baoyu Author-X-Name-Last: Ye Author-Name: Xibin Yang Author-X-Name-First: Xibin Author-X-Name-Last: Yang Author-Name: Xiaoyu Yang Author-X-Name-First: Xiaoyu Author-X-Name-Last: Yang Title: Transient security state identification of smart grid based on multi feature fusion Abstract: In order to improve the power supply stability of the smart grid and accurately identify the transient safety status of the power grid, a smart grid transient safety status identification method based on multi feature fusion is proposed. Firstly, extract the transient zero sequence active energy features of the smart grid, and use the S transform to extract the transient energy features and comprehensive phase angle features. Secondly, based on the extracted multiple features, a deep belief network (DBN) is used to fuse multiple features. Finally, based on the results of multi feature fusion, the SVM algorithm is used to classify and identify the transient safety status of the power grid. The experimental results show that the transient safety state identification accuracy of this method is high, stable at 98%; and the misjudgement rate of this method has been reduced, with a maximum of no more than 3%. Journal: Int. J. of Energy Technology and Policy Pages: 220-232 Issue: 3/4/5 Volume: 18 Year: 2023 Keywords: multi-feature fusion; smart grid; transient security state; state identification. File-URL: http://www.inderscience.com/link.php?id=134166 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetpo:v:18:y:2023:i:3/4/5:p:220-232 Template-Type: ReDIF-Article 1.0 Author-Name: Yalei Shang Author-X-Name-First: Yalei Author-X-Name-Last: Shang Title: A control method for uninterruptible power supply in weak current systems based on virtual impedance Abstract: If there is a significant voltage control error in the uninterruptible power supply (UPS) of weak current systems, it will seriously reduce the stability of the power supply. Therefore, a virtual impedance based UPS control method for weak current systems is proposed. Firstly, analyse the basic structure of weak current systems and uninterruptible power supplies. Secondly, an inverter output inductor current feedback is added outside the voltage and current dual loop control of the UPS to form a virtual impedance loop. Finally, virtual impedance is used to suppress the inverter circulating current of the UPS in the weak current system, thereby completing the control of the UPS. The experimental results show that the maximum voltage control error of the proposed method does not exceed ±0.331 V. Therefore, it indicates that the UPS control performance of this method is good. Journal: Int. J. of Energy Technology and Policy Pages: 275-285 Issue: 3/4/5 Volume: 18 Year: 2023 Keywords: virtual impedance; weak current system; uninterruptible power supply control; UPS; circulation suppression. File-URL: http://www.inderscience.com/link.php?id=134167 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetpo:v:18:y:2023:i:3/4/5:p:275-285 Template-Type: ReDIF-Article 1.0 Author-Name: Zeyuan Zhou Author-X-Name-First: Zeyuan Author-X-Name-Last: Zhou Author-Name: Junrong Liu Author-X-Name-First: Junrong Author-X-Name-Last: Liu Author-Name: Linyan Zhou Author-X-Name-First: Linyan Author-X-Name-Last: Zhou Title: Power system state monitoring big data query based on multilevel index Abstract: The continuous operation of the power system generates a large amount of state data. By querying this data, the operation status of the power system can be judged, which is beneficial for improving the stability of the power system operation. Therefore, a multilevel index based big data query method for power system state monitoring is proposed. Firstly, density clustering algorithm is used to cluster the big data of power system status monitoring. Secondly, based on the clustering results, a distance sensitive hash algorithm is used to represent the mapping relationship of data points, and a multilevel index structure is constructed to complete the query of big data for power system status monitoring. The experimental results show that the proposed method reduces the response time of big data queries for power system status monitoring, improves query throughput and accuracy, and achieves a maximum query accuracy of 94.24%. Journal: Int. J. of Energy Technology and Policy Pages: 286-297 Issue: 3/4/5 Volume: 18 Year: 2023 Keywords: multilevel index; power system; status monitoring; big data query. File-URL: http://www.inderscience.com/link.php?id=134168 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetpo:v:18:y:2023:i:3/4/5:p:286-297 Template-Type: ReDIF-Article 1.0 Author-Name: Minlei Zhang Author-X-Name-First: Minlei Author-X-Name-Last: Zhang Author-Name: Yun Fu Author-X-Name-First: Yun Author-X-Name-Last: Fu Title: A safe operation control method for intelligent distribution network based on mode conversion Abstract: Once safety issues arise in the intelligent distribution network, it will have a significant impact on the stability of power supply. Therefore, a mode conversion based control method for the safe operation of the intelligent distribution network is proposed. Firstly, based on the structure of the intelligent distribution network, the safe operation reserve constraints are calculated and conversion strategies for multiple operating modes are generated. Secondly, considering the requirements of negative voltage offset and line load rate in the operation of the distribution network, and under the constraints of power flow, power output, compensation equipment capacity, and topology structure, a multi-stage control decision-making process is adopted to complete the safe operation control of the intelligent distribution network. The experimental results show that the control method studied can reduce the load fluctuation and overall fault rate of the distribution network, with a maximum fault rate of only 0.31%. Journal: Int. J. of Energy Technology and Policy Pages: 233-245 Issue: 3/4/5 Volume: 18 Year: 2023 Keywords: mode conversion; intelligent distribution network; safe operation control; current constraints. File-URL: http://www.inderscience.com/link.php?id=134169 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijetpo:v:18:y:2023:i:3/4/5:p:233-245