Table of Content

28 May 2022, Volume 55 Issue 5

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Special Contribution

Realization Pathways and Key Problems of Carbon Neutrality in China's Energy and Power System

ZHOU Yuanbing, YANG Fang, YU Xiaoxiao, JIANG Han

2022, 55(5):  1-11.  DOI: 10.11930/j.issn.1004-9649.202203003

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Based on the actual national conditions of China’s economic and social, energy and power development, this paper analyzes China’s carbon neutralization mechanism framework and puts forward the mitigation solutions for carbon emissions with China energy interconnection. With the target of optimal cost for achieving carbon neutrality for the whole society, the MESSAGE integrated assessment model (IAM) is used to study the overall pathways for China's whole society carbon neutralization and the transition pathways for energy and power system based on the China energy interconnection. The results show that the carbon neutrality pathways before 2060 for China can be advanced in view of three stages of early peaking, rapid mitigation and overall neutrality. The carbon emissions will reach the peak around 2028; 90% of the energy demand will be met by clean energy in 2060, and the electricity will account for two-thirds in the whole society end-use energy consumption, achieving the total transition of energy use system. Besides, some key issues for achieving carbon neutralization are analyzed, including emission reduction speed and pace, power system balance and adjustment, and transition cost and allocation.

New Energy

Research on Effects of Renewable Energy Policy Based on Power Supply Chain Game

WU Qunli, XI Man

2022, 55(5):  12-20,38.  DOI: 10.11930/j.issn.1004-9649.202103148

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The renewable portfolio standards (RPS) are the target mechanism for the transition of China’s current renewable energy policy from the feed-in premium (FIP) to the combined action of government policies and market mechanisms. With the deepening of power system reform, renewable energy policy directly influences the game behavior of power supply chain subjects, resulting in different policy effects. Therefore, we assume the consumer side as the assessment subject of quota obligations and introduce a penalty function, and a two-level Nash equilibrium game model for the power supply chain is constructed, including the power generation side and the consumer side. The model sets three policy scenarios, i.e., FIP, RPS, and the parallel dual-track system of the two policies, and numerical simulations focus on analyzing the impact of quota and penalty parameter changes on the optimal power transaction volumes of each game subject and the price of the green certificate under RPS. Additionally, considering the welfare effect of policies, the differences in social welfare under three policy scenarios are compared. The results indicate that under RPS, the power transaction volume of renewable energy and the price of the green certificate increase initially and decrease afterward as the quota grows and increase as the penalty parameter rises. Under three policy scenarios, the social welfare function presents inverted U-shaped distribution with the increase in quotas. As the market share of renewable energy grows, the level of social welfare under the parallel dual-track system of the two policies is better than that under the implementation of the two policies separately.

Optimization and Response Analysis of Floating Truss Foundation for Offshore Wind Turbine

WANG Yuhang, WANG Wenling, ZHOU Xuhong, WANG Kang, LUO Yintao

2022, 55(5):  21-31.  DOI: 10.11930/j.issn.1004-9649.202107118

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In the context of increasingly severe environmental problems, optimizing the form of floating foundations becomes a major way for offshore wind engineering to reduce costs and increase efficiency. This study optimized the structure of a new floating truss foundation for a wind turbine with dual anti-sway mechanisms and conducted the parametric analysis of the different layout forms of the truss structure to find the most suitable tie rod layout form for the floating truss foundation. At the same time, the hydrodynamic response analysis of the optimized floating truss foundation was carried out to verify the feasibility of the optimized scheme. The results showed that in terms of the tie rod layout of the truss, the angle between the diagonal tie rod and the corner column should not be set to a large value, and reducing the cross-sectional area of horizontal tie rods and increasing that of diagonal tie rods could more effectively improve the lateral stiffness and load-bearing capacity of the structure. After optimization, the force performance of the floating foundation is better than that of the original floating truss foundation, and the economical efficiency of floating truss foundation is enhanced greatly. Meanwhile, its natural period on each degree of freedom is much larger than the typical wave period, which indicated a good seakeeping performance.

A Knowledge Learning Model for Intelligent Check of Wind Farm Dynamic Parameters Based on DDPG

ZHOU Qingfeng, WANG Sichun, LI Dexin, LIU Jiaqi, LI Tong

2022, 55(5):  32-38.  DOI: 10.11930/j.issn.1004-9649.202102071

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As the penetration rate of wind power increases and a large number of power electronic components are connected, the dynamic characteristics exhibited by wind farms become more and more complex. The traditional simulation verification methods based on a small number of cases and analysis are facing challenges. The successful application of a new generation of artificial intelligence represented by deep reinforcement learning in multiple fields provides a reference for the intelligent check of the dynamic parameters of wind farms. Based on the equivalent model of doubly-fed wind farms and the deep deterministic policy gradient ( DDPG) algorithm, a knowledge learning model for intelligent check of wind farm dynamic parameters is proposed. The proposed model gradually obtains the intelligent check knowledge of the wind farm dynamic parameters through a large number of simulations and learning, initially realizing the “knowledge”-based check of wind farm dynamic parameters. Finally, based on the measured disturbance data of wind turbines in a wind farm, the parameter check knowledge obtained through intelligent learning are used to correct the dominant parameters of wind farm dynamic characteristics, and the results are compared with traditional heuristic algorithms, which verifies the effectiveness of the proposed method.

Mechanism Analysis and Suppression Strategy of Torsional Vibrations of DFIG Shaft System Considering Torque Control of Wind Turbine

SUN Sujuan, HUO Qiantao, SUN Lixin, GUO Liang, WANG Rui, KONG Xiangmei

2022, 55(5):  39-46.  DOI: 10.11930/j.issn.1004-9649.202102032

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The shafting model of the doubly-fed induction generator (DFIG) can be equivalent to the wind turbine mass connected to the generator mass via the flexible shaft, and the shaft system has great flexibility and low damping and encounters torsional vibrations on site. Therefore, an electromechanical small-signal model of DFIG is proposed for analyzing the dynamic characteristics of the shaft system. In the model, the torque control of the wind turbine is embedded into the double-mass mathematical model of DFIG, and small signals are linearized. On this basis, this paper analyzes the torsional vibration mechanism and designs the suppression strategy. It is found that the essential reason for torsional vibrations of the shaft system is that the phase angle between the electromagnetic torque and the generator speed in the torsional vibration frequency band registers a lag of 90–270°, which is equivalent to reducing the damping of the generator mass or even make the damping negative. Thus, adjusting the torque control lag of the wind turbine or increasing the damping of the transmission chain can indirectly increase the generator mass damping for the suppression of torsional vibrations. In view of the actual mechanical shafting characteristics of DFIG, a model was built for the time-domain simulation analysis and suppression strategy validation of torsional vibrations, and the suppression effect was tested on a 2MW unit on site. The results reveal that the torsional vibration of the shaft system is effectively suppressed upon the adjustment of torque control.

Combined Wind Power Prediction Method Based on CNN-LSTM&GRU with Adaptive Weights

JIA Rui, YANG Guohua, ZHENG Haofeng, ZHANG Honghao, LIU Xuan, YU Hang

2022, 55(5):  47-56,110.  DOI: 10.11930/j.issn.1004-9649.202104023

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Accurate wind power prediction can improve the safety and reliability of grid operation. To further enhance the accuracy of short-term wind power prediction, this paper proposes a CNN-LSTM&GRU multi-model combined prediction method considering the difficulty in obtaining optimal prediction results with a single model. Firstly, a convolutional neural network (CNN) is used to extract local features of data and combined with a long short-term memory (LSTM) network to construct a CNN-LSTM network structure that incorporates local feature pre-extraction modules. Then, the CNN-LSTM network is paralleled with a gated recurrent unit (GRU) network. An adaptive weight learning module is employed to select the best weights for the outputs of the CNN-LSTM module and the GRU module. In this way, the paper constructs a combined short-term prediction model based on CNN-LSTM&GRU. Finally, the model is applied to the power prediction of a wind farm in northwestern China. The experimental results show that the proposed model has a smaller mean absolute error (MAE), a smaller root mean square error (RMSE), and higher prediction accuracy than single models and other combined models.

PV Power Short-Term Forecasting Method Based on VMD-GWO-ELMAN

ZHANG Na, REN Qiang, LIU Guangchen, GUO Liping, LI Jingyu

2022, 55(5):  57-65.  DOI: 10.11930/j.issn.1004-9649.202104033

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This paper aims to further improve the accuracy and reliability of short-term photovoltaic (PV) output power forecasting. Considering the blindness and randomness of weights and thresholds of traditional Elman neural networks and the fluctuation and nonstationarity of PV output power signal, the paper proposes a short-term prediction model of PV output power based on variational mode decomposition (VMD) and an Elman neural network optimized by grey wolf optimization (GWO) algorithm. Firstly, the K-means algorithm is used to cluster the original data according to weather types. Then, VMD is employed to decompose the PV output power data of each weather type, and the decomposition subsequences are input into the Elman neural network optimized by GWO for PV output power forecasting. Finally, the forecasting results are superimposed. An example shows that the model has improved forecasting accuracy.

Power System

Improved Fuzzy Evaluation Model and Assessment of Power Grid Development Diagnosis

AI Xin, HU Huanyu, REN Dapeng, PENG Dong, LIU Huichuan, XUE Yawei, ZHANG Tianqi

2022, 55(5):  66-75,165.  DOI: 10.11930/j.issn.1004-9649.202004115

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With the establishment and acceleration of power grid new infrastructure construction, the power grid is becoming increasingly complicated. It is very important to correctly understand the development state of power grid. Therefore, an improved dynamic fuzzy evaluation model is proposed for power grid development diagnosis, and corresponding rating assessment on power grid development is carried out. Firstly, a dynamic evaluation index system is established based on an analysis of the important indexes in all aspects of power grid development. Then, the trend characteristics of each state are analyzed by the methods of membership function and cluster analysis. Finally, the hidden Markov model is used for the comprehensive rating of power grid development. A case study is carried out with actual data of a provincial power grid, which shows that the rating results conform with the actual status, and are helpful to understand the dynamic features of power grid development.

A Setting Optimization Strategy for Distance Protection Ⅱ after Connection of Synchronous Condensers

LI Dongsheng, HAO Liangliang, GUO Zhilin, CAO Hong, WANG Xingguo

2022, 55(5):  76-83.  DOI: 10.11930/j.issn.1004-9649.202110027

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The large-scale access of synchronous condensers (SCs) to the power grid will reduce the protection range of the distance protection section Ⅱ, and reasonable optimization of the protection setting is a feasible way to solve this problem. For this reason, based on an investigation of the influence of the SCs connection on the distance protection section Ⅱ, a setting value optimization strategy is proposed to increase the protection range of the distance protection section Ⅱ. Firstly, the steady-state current and short-circuit current of SCs are analyzed, and the influence of the SCs access on the protection range under the traditional distance protection Ⅱ setting is investigated from the perspective of the protection range. And then, for the purpose of reasonable selection of the protection range setting value and accurate calculation of branch coefficients, a setting value optimization strategy of distance protection section Ⅱ is proposed, which effectively improves the protection range of the distance protection section Ⅱ after SCs access. Finally, a simulation analysis is conducted on the setting value optimization strategy proposed in this paper, and the results show that the protection range obtained by the proposed method is less affected by the number of SCs and the impedance ratio of adjacent lines, and can be close to the preset value.

Medium-High Frequency Impedance Modeling of MMC and System Stability Analysis Considering Voltage Measurement Characteristics

LI Qinan, XIA Yongjun, ZHANG Xiaolin, SUN Baokui, SUN Huadong, ZHANG Fan, LI Lanfang, YANG Yuefeng, HAN Qingtao

2022, 55(5):  84-93.  DOI: 10.11930/j.issn.1004-9649.202107017

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In MMC impedance modelling, the existing research does not take into account the influence of the capacitive voltage transformer (CVT) measurement characteristics on the mid and high frequency bands of the MMC impedance, which may reduce the accuracy of the stability analysis of the flexible HVDC transmission system. By taking the south channel unit of the Yu’E flexible HVDC project as the research object, and based on an analysis of the influence of stray capacitance on the measurement characteristics of a 500kV fast saturated CVT, a MMC impedance modelling method is proposed using the multi-harmonic linearization method. The impedance analysis method is used to analyze the influence of the CVT broadband measurement characteristics on the stability of the HVDC system when the MMC station is connected to different AC systems and operates at different steady-state operating points. The results show that the CVT broadband measurement characteristics will cause the oscillation frequency of the system to change under certain working conditions. Through PSCAD/EMTTDC simulation, it is verified that the proposed MMC impedance model, which takes into account the CVT broadband measurement characteristics, can improve the accuracy of the stability analysis of the flexible HVDC system.

Temperature and Efficiency Analysis of Line Laser in Removing Tree Barriers for Overhead Lines

XU Xin, FANG Chunhua, ZHI Li, DING Can, DONG Xiaohu, CHENG Sheng, SUN Wei, TAO Yuning

2022, 55(5):  94-101.  DOI: 10.11930/j.issn.1004-9649.202004059

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Overhead line tree barriers may cause line tripping faults and are a major hidden danger to line operation. It is a safe and effective way to remove the tree barriers under the transmission lines by high energy laser. By taking six types of typical trees as the research objects, finite element models are established to analyze the temperature distribution characteristics and burning efficiency of these trees under point and line laser cauterization, and point and line cauterization experiments are conducted respectively. The results show that the temperature of the tree surface decreases sharply from the the laser spot center to the spot edge, and the thermal effect is only obvious in the center of the burning area, and the temperature rising rate at the spot center slows down with the heating time. Within the same time period, compared to other five tree types, Paulownia has the highest temperature, reaching 1259.20 °C at maximum in 15 s. When the output power of laser is the same, the point laser and line laser have an average burning speed of 0.37 mm/s and 5.45 mm/s, respectively. The experimental results show that the line laser is 6.53-8.45 times faster than the point laser in average burning speed, which indicates that the line laser has a significantly higher burning speed than that of point laser. The research results can provide an important basis for application of line laser in clearing tree barriers.

Multi-source Partial Discharge Pulse Classification Technology Based on t-SNE and CFSFDP Algorithms

SHI Qiang, LIU Kun, LI Jinsong, LI Fuchao

2022, 55(5):  102-110.  DOI: 10.11930/j.issn.1004-9649.202109115

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When multi-source partial discharge pulses are classified, the pulses cannot be effectively separated due to the distribution overlapping of their equivalent time-frequency features. In order to solve this problem a partial discharge pulse classification technology is proposed based on t-SNE and CFSFDP Algorithms. Firstly, a phase synchronization device is used to collect the discharge pulse signals and their corresponding phase information, and based on the time-frequency spectra of a single discharge pulse, the t-SNE algorithm is used to reduce the dimensionality of the spectrum data. And then the CFSFDP algorithm is used to cluster the dimensionality reduction results. Finally, based on the phase information collected with the phase synchronization device, the PRPD spectra of different discharge pulses are reconstructed for further analysis. The experimental results show that the t-SNE and CFSFDP based method can effectively classify different discharge pulses, and the PRPD spectrum reconstructed with the phase synchronization device meets the characteristics of discharge.

Fault Diagnosis Method for Circuit Breaker Opening and Closing Coil Based on IEMD and GA-WNN

LI Tianhui, PANG Xianhai, FAN Hui, ZHEN Li, GU Chaomin, DONG Chi

2022, 55(5):  111-121.  DOI: 10.11930/j.issn.1004-9649.202201039

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The running state of the secondary circuit or operating mechanism of vacuum circuit breakers can be reflected by the characteristics of current curves. Firstly, three kinds of common faults, including core blockage, abnormal voltage (too high or too low) and breakdown, are simulated in laboratory, and a fault current curve characteristic library is established. Secondly, based on the property that the product of energy density in the inherent mode function of the fault current signals after ensemble mode decomposition and its corresponding average period is a constant, an improved empirical mode decomposition method（IEMD) is proposed to extract the current eigenvalues of the opening and closing coils, which are used as the input sample set of the neural network. On this basis, a circuit breaker fault diagnosis method is proposed by combining the improved genetic algorithm(GA) and wavelet neural network(WNN). This method uses the improved genetic algorithm to optimize the parameters of the neural network in order to solve the problem of parameter sensitivity of the wavelet neural network, thus improving the convergence speed of the diagnosis algorithm and the accuracy of fault diagnosis. Simulation results show that compared with the traditional neural network diagnosis method, the proposed fault diagnosis method has a diagnostic accuracy of 91%, increasing by 10 percentage point.

Prediction of 1 000 kV UHV Line Loss Based on Improved RBFNN

YANG Jianhua, XIAO Daqiang, ZHANG Wei, YU Mingqiong, YI Benshun

2022, 55(5):  122-127,142.  DOI: 10.11930/j.issn.1004-9649.202103090

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In view of the complex relationship between UHV transmission line loss and its characteristic parameters, this paper proposes a radial basis function neural network (RBFNN) model improved by use of the Canopy-K-means clustering algorithm and the adaptive second mutation differential evolution (ASMDE) algorithm to predict the UHV transmission line loss. The characteristic parameters of UHV transmission line loss determined by theoretical analysis are clustered through Canopy-K-means clustering algorithm to determine the hidden layer nodes of radial basis function (RBF) neural network, subsequently ensuring the RBF neural network to have a better hidden layer center. The RBF neural network optimized by ASMDE algorithm is trained with the sample data of characteristic parameters and line loss, so as to fit the complex nonlinear relationship between line loss and characteristic parameters. Finally, the historical data of a UHV transmission line in Central China is taken for simulation, and the results have verified the practicability and effectiveness of the proposed method.

Identification of Voltage Sag Source in Distribution Network Based on BAS-SVM

LIU Haitao, YE Xiaoyi, Lü Ganyun, YUAN Huajun, GENG Zongpu

2022, 55(5):  128-133.  DOI: 10.11930/j.issn.1004-9649.202003138

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Voltage sag is a kind of power quality problem. In order to improve the identification accuracy of different voltage sag disturbance sources, a voltage sag source identification method based on beetle antennae search (BAS) and support vector machine (SVM) is proposed. In this paper, the improved S-transform is applied to the time-frequency reversible analysis of voltage sag signal, and the related amplitude curve and 16 characteristic indexes are extracted. The penalty factor and kernel function parameters of SVM are optimized by BAS, and a BAS-SVM classifier is constructed. The extracted characteristic index data is normalized and divided into training sample set and test sample set by 5-fold cross validation, which are input into the new classifier to realize the recognition of different types of voltage sag sources in distribution network. Finally, the simulation results show that the classifier has better classification effect.

Distributed PV Auxiliary Voltage Control Strategy in Low Voltage Distribution Network Based on Small AC Signals

YAN Xiangwu, WANG Chenguang, JIA Jiaoxin, MA Hongbin

2022, 55(5):  134-142.  DOI: 10.11930/j.issn.1004-9649.202006264

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With the progress of China's photovoltaic industry, the capacity of distributed photovoltaic sources connected with the low-voltage distribution network is increasing. When the solar irradiance is high, the distribution network may suffer serious out-of-limit voltage. This paper analyzes the causes of out-of-limit voltage phenomenon in the distribution network, and an auxiliary voltage control strategy of distributed photovoltaic source is proposed for this problem. The purpose of the strategy is to ensure the economic benefits of each photovoltaic source while giving the best play to the voltage control ability of each photovoltaic source. The proposed control strategy reduces part of active power to control voltage based on reactive power control strategy. It uses the maximum power estimation method to realize the reduction control of active power of photovoltaic source, and realizes the communication and coordination between photovoltaic sources by injecting small AC voltage signal into the power grid. Finally, the validity of the proposed strategy is verified by case study results.

Three-Phase Unbalanced Linear Power Flow Calculation Based on Voltage Magnitude Logarithmic Transformation

LI Hongwei, PAN Li, HAN Lu, GE Mingrui

2022, 55(5):  143-148.  DOI: 10.11930/j.issn.1004-9649.202101019

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The linear power flow calculation method can provide better robustness and higher efficiency for active distribution network analysis and operation regulation. In this paper, a new three-phase unbalanced linear power flow calculation method is proposed. The voltage magnitude of the three-phase power flow equation is transformed into logarithmic form under polar coordinates. And then a reasonable linear approximation is formed according to the actual characteristics of the three-phase distribution network. The proposed method avoids iterating and can directly calculate the three-phase unbalanced power flow of the radial and weak-loop distribution networks as well as the distribution networks containing PV nodes.The proposed method is tested and compared through an IEEE33 three-phase unbalanced example, and its effectiveness has been verified.

Information and Communication

A Trusted Batch Authentication Mechanism Based on Tree for Power Internet of Things

ZHAO Baohua, WANG Zhihao, CHEN Liandong, REN Chunhui, YU Fajiang, XU Qing

2022, 55(5):  149-157.  DOI: 10.11930/j.issn.1004-9649.202101024

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Devices in power Internet of things need to be trusted measurement. However, the existing data processing architecture has problems such as excessive pressure in cloud platform, and the existing trusted measurement architecture also has problems such as low efficiency and excessive consumption. This paper proposed a trusted batch authentication mechanism based on unbalanced hash tree, which is suitable for power Internet of things based on cloud-edge collaborative. The edge computing architecture of cloud-edge collaboration is adopted to lighten the load of cloud platform. The device adopts a lightweight trusted architecture for trusted measurement to obtain measurement information. The structure of unbalanced hash tree generates less verification information during device verification and protects privacy. The sparse Merkel tree multiproofs method is used to generate the verification information to implement the batch authentication of devices. In this paper, the security threat analysis, prototype implementation and performance analysis are carried out. The experimental results show that this mechanism is better than Merkel hash tree in building the tree, and better than IMA linear structure in trusted authentication of devices. And in batch verification, it can greatly reduce the size of verification information.

Information Entropy Based Multi-Source Power IoT Terminal Equipment Trust Degree Evaluation Method

ZHAI Feng, FENG Yun, CHENG Kai, CAI Shaotang, YU Liying, YANG Ting

2022, 55(5):  158-165.  DOI: 10.11930/j.issn.1004-9649.202006211

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Power Internet of things terminal (IoT) equipment is vulnerable to identity camouflage, information theft, data tampering and other security threats. Traditional security methods can not resist the network internal attacks from damaged terminals. Trust evaluation system is an effective mechanism to protect power IoT terminals from internal attacks. A trust evaluation method is proposed based on information entropy for power wireless private network communication terminals. Firstly, the direct trust value is estimated by the credibility model based on exponential distribution, and then the sliding window and forgetting factor are used to update the direct trust value. According to the entropy theory, the uncertainty of direct trust value is measured, and the indirect trust value is introduced to make up for the inaccuracy of direct trust judgment, and the judgment accuracy is improved through comprehensive evaluation of both. Simulation results show that the proposed method can effectively resist switch attacks and collusion attacks, and compared to the binomial trust management method and beta distribution based trust evaluation method, it can better evaluate malicious terminals and normal terminals.

Modeling and Simulation of Fast Communication Network for Park Integrated Energy System Based on IoT

LV Hao, HE Yiming, TIAN Hao, WANG Tieqiang, QIU Xiaohong, MA Rui

2022, 55(5):  166-173.  DOI: 10.11930/j.issn.1004-9649.202011064

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With the increasing demands of park integrated energy system (IES) for system state perception and regulation level, the efficient transmission of key information in the communication network has become the key to the rapid perception and regulation of the IES state. Firstly, this paper proposes an information collection, transmission, and control system for the park IES based on the Internet of Things (IoT). Combined with the physical three-layer architecture of the IES, an IoT-based park IES three-layer star communication network model is established, in which the low-latency and high-throughput performance of the IES communication network is achieved through port-based virtual local area network (VLAN) division. On the basis of VLAN division, the link utilization rate and service response time threshold are set and the critical operating states of the communication network are explored under the set conditions, which can provide a quantitative analysis basis for the setting of the IES fast communication network scale. Simulation results have verified the feasibility of the proposed scheme.

Communication Technology Planning for Power Terminal Communication Access Networks in the “14th Five-Year Plan” Based on Analytic Hierarchy Process

WU Qing, WANG Yundi, ZENG Lingkang, SUN Yunxiao, CHEN Minlin

2022, 55(5):  174-181.  DOI: 10.11930/j.issn.1004-9649.202006161

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In the “13rd Five-Year Plan”, the construction, operation and management of power terminal communication access networks were mainly led by each business department, which resulted in some problems such as lacking of overall planning and scientific guidance for the selection of communication technologies, as well as repeat construction of communication networks. The energy internet in the “14th Five-Year Plan” will have the characteristics of terminal integration, business integration and network integration. A communication technology planning model for access networks is established based on analytic hierarchy process for the typical scenarios of multi-business integration. The principles for selecting telecommunication technology are proposed for power terminal communication access networks for different power supply areas, which can provide a reference for the planning and construction of power terminal communication access networks in the “14th Five-Year Plan”.

Generation Technology

Performance Analysis of Solar-Coal Cogeneration System for Wind Power Consumption

HUANG Chang, YAN Yixian, BAI Yao, ZHANG Qi, WANG Weiliang, LI Wenna

2022, 55(5):  182-188.  DOI: 10.11930/j.issn.1004-9649.202103062

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During the heating season, the limited peak shaving capacity of CCHP units is blamed as the major cause for the massive abandonment of wind and light in the "Three Norths" area. A mathematical model of key equipments for the solar aided CCHP system is established in this paper. Then a desk-top case of a 600MW direct air-cooled CCHP unit with a 100 MW wind farm, 510,000 m² solar field, and 3-hours storage system is investigated under actual weather conditions and load demands. The simulation results show that, in the heating mode, the lower limit of unit peak shaving can be reduced by 150 MW for wind power consumption so as to promote the integration of large scale wind power into the grid. The annual wind curtailment has dropped from 20 million kW·h by 62.2% to 7 million kW·h, and the wind curtailment rate has dropped from 7.91% to 2.7%. Meanwhile, the annual solar power generation has reached 150 million kW·h, equivalent to a total of 49000 tons of coal saved and 132000 tons of carbon dioxide emissions reduced, which has demonstrated significant environment and economy benefits.

Study on Operating Optimization of 660 MW Multi-stage Heating Unit Combined with Electric Boiler

CHEN Jialun, JIANG Huanchun, BIAN Shaoshuai, KANG Yingzhe, WU Zhe, HUANG Xin

2022, 55(5):  189-195.  DOI: 10.11930/j.issn.1004-9649.202105118

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Based on the analysis of multi-stage heating 660MW unit combined with electric boiler, the method of calculating the most economical high back pressure for unit real-time operation was put forward. The experiment proved that operating under the most economical high back pressure could effectively increase the output power of the unit in controlling the main steam flow of the unit and the external heat load conditions and improve the thermal economy of unit. After the technical transformation, the heating capacity could be enhanced 440 GJ. When the external heating load was constant, multi-stage heating could decrease generator power by 86 MW and improved the peak load regulation capacity of the unit. The economy of the unit under the second gear peak shaving condition had been calculated. If the electric boiler replaced part of multi-stage heating under the same heat load, the unit conversion standard coal consumption increased by 0.32 t/h when the electric boiler load increased by 1 MW .

Energy Conservation and Environmental Protection

Study on Emission Reduction and Energy Efficiency Characteristics of Wet Electrostatic Precipitator for Coal Fired Power Plants

LIU Hanxiao, WU Liming, ZHAO Lin, YU Liyuan, LI Jianguo, CUI Ying

2022, 55(5):  196-203.  DOI: 10.11930/j.issn.1004-9649.202105135

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The emission reduction characteristics and energy consumption of multiple pollutants were tested and analyzed on 122 sets of supporting Wet Electrostatic Precipitator (35 sets of metal plate type and 87 sets of conductive FRP type) of coal-fired power plants, under stable working conditions and load. The results show that the WESP has high removal efficiency for all kinds of pollutants, the particulate matter, PM_2.5, droplets and SO₃ at the exit of most WESP can be controlled below 5, 2.5, 25 and 10 mg/m³ respectively, and the ratio of PM_2.5/PM at the exit was increased significantly. Generally, the power supply parameters of conductive FRP type WESP could be raised to a higher level because of discontinuous spraying, so the SO₃ removal rate was higher than that of the metal plate WESP. Droplet concentration at the exit was lower. The specific power consumption of metal plate type and conductive FRP WESP were 0.68×10^-4~3.34×10^-4 and 0.74×10^-4~3.38×10^-4 kW·h/m³, respectively, and the average values were 1.55×10^-4 and 1.75×10^-4 kW·h/m³, respectively. The energy consumption for particle removal were 4.7~24.7 and 2.9~37.5 kW·h/kg, respectively, and the average values were 10.8 and 13.3 kW·h/kg, respectively. The higher the concentration of inlet particles, the lower the energy consumption for particle removal.This study can provide reference for the following energy saving and carbon reduction operation of ultra-low emission units.

Study of Flue Gas Pollutant Control in a 600 MW Coal-Fired Unit

ZHANG Zhiyong, MO Hua, WANG Meng, SHUAI Wei

2022, 55(5):  204-210.  DOI: 10.11930/j.issn.1004-9649.202105150

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Taking a 600MW supercritical coal-fired unit as an example, the ultra-low emissions effect of W-flame boiler burning high sulfur, medium and high ash and low volatile coal was studied.The unit adopts the ultra-low emissions technology route of " selective non-catalytic reduction (SNCR)＋selective catalytic reduction (SCR) denitrification, double-chamber five-electric field electrostatic precipitator with high-frequency power supply+rotating electrode, and double-tower double-cycle wet-FGD system (3+5 layer spray)".According to Distributed Control System (DCS) and Continuous Emission Monitoring System (CEMS) data of the unit, NO_x, particulate matter and SO₂ concentrations at chimney outlet can reach ultra-low emission level stably.The SNCR device is in good operating condition. The ammonia escape of SCR device is large, and the maximum ammonia escape reaches 27.51mg/m³. The probability of exceeding the designed value of 2.28mg/m³ on side A and side B is 51.86% and 45.96%, respectively. The reason is that the concentration field of denitration system is unevenly distributed. The slurry density of desulfurization system is well controlled. The pH value of the slurry in the first tower is well controlled, but the pH value in the second tower is relatively low. The emission intensity of SO₂, NO_x and particulate matter is 48.7%, 7.7% and 28.9% lower than the national average emission intensity in 2019.