Table of Content

28 February 2023, Volume 56 Issue 2

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Special Contribution

Practice Exploration and Prospect Analysis of Virtual Power Plant in Shanghai

ZHAO Jianli, XIANG Jiani, TANG Zhuofan, QI Lei, AI Qian, WANG Di, YIN Shuangrui

2023, 56(2):  1-13.  DOI: 10.11930/j.issn.1004-9649.202208078

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Due to the restrictions of the source-side and load-side characteristics, Shanghai Power Grid faces such problems as high pressure for renewable energy accommodation and lack of flexible regulation tools. To this end, Shanghai Electric Power Company carried out demonstration projects for virtual power plants to explore the innovative applications of virtual power plants and accelerate the construction of new power systems. First of all, the necessity for development of virtual power plants was analyzed from two aspects of social development and new power system construction. And then, the preliminary exploration work and innovative applications of Shanghai virtual power plants were introduced according to the technical route of “resource exploitation-market transaction-operation scheduling-information communication”. Subsequently, the development prospects of Shanghai virtual power plants were explored from the expansion of distributed resources, diversified market transactions and cloud-edge collaborative control. Finally, the transaction situation of Shanghai virtual power plants was investigated, and relevant experience in operating processes and mechanism design was summarized, which can provided a reference for development of virtual power plant projects in other provinces and cities.

Energy Consumption Perception and Friendly Interaction of Multivariate Demands

Centralized Regulation and Optimization Strategy for MV Distribution Network with PV Integration

WANG Zezhou, ZHANG Mingming, QIAN Fengqiang, ZHOU Hongyi, YU Haomiao

2023, 56(2):  15-22.  DOI: 10.11930/j.issn.1004-9649.202204109

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With increasing PV connected to MV distribution network, the problem of node voltage fluctuation and network loss is becoming more and more serious. Taking the communication conditions and calculation capabilities of MV distribution networks into account, a centralized regulation optimization strategy for distributed PV connected to MV distribution network is proposed to realize the suppression of voltage fluctuation and excessive network loss. Firstly, the impacts of PV integration on node voltage and network loss are analyzed. Then, a multi-objective optimal control model is established, with the power flow balance equation, node voltage, branch current and system operation as constrains, and with the minimal network loss, minimal voltage fluctuation and maximum consumption of DGs as objective. In addition, the commercial CPLEX is used to solve the model. Finally, the effectiveness of the proposed model is verified through case simulation. The results show that the proposed model can effectively reduce the voltage fluctuation and network loss, reasonably allocate the output of DGs and ensure the utilization of PV in a reasonable range.

Portal Dynamics Learning Method for Renewable-integrated Regional Power Networks Based on Neural Differential-Algebraic Equations

CAO Bin, SU Ke, YUAN Shuai, XIAO Tannan, CHEN Ying

2023, 56(2):  23-31.  DOI: 10.11930/j.issn.1004-9649.202208009

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In the context of high penetration of renewables, it is very important for new power system dynamic analysis to establish a dynamic model that can accurately describe the portal dynamics of renewable-integrated regional power networks under the influence of complex environmental factors. Therefore a neural differential-algebraic equations-based portal dynamics learning method is proposed for renewable-integrated regional power networks. In this method, the differential-algebraic neural network is used to learn the portal dynamics model expressed in the form of neural network based on the time series measurements of the access point of the regional power networks and the environmental measurement data such as the radiation intensity and temperature. The learned model is composed of an initial state extracting block, a neural differential equation block and an algebraic equation block, and can be directly integrated into power system transient simulations to analyze the overall dynamics of power systems. The proposed method is tested through simulation in the IEEE-39 system, and the test results show that the obtained model can adapt to different environmental scenarios with acceptable accuracy, which verifies the effectiveness of the proposed method. The modelling method only needs portal time series measurements and has great application potential in the dynamic analysis of new power systems.

Voltage Adjustment Strategy for High-Penetration Electric Vehicles Connected to Power Grid Based on Situation Awareness

LIU Zong, HE Jun, HUANG Wentao, ZHU Liwen, DENG Changhong

2023, 56(2):  32-44.  DOI: 10.11930/j.issn.1004-9649.202204108

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Along with the increase of EVs use, the regional distribution network will experience nodal voltage overlimit problem after high penetration EVs are connected to the distribution network. Based on situation awareness technology, this paper proposes a voltage adjustment strategy with the joint participation of reactive power compensation equipment and EVs in the regional distribution network to ensure the voltage status of the distribution network through constructing a secondary voltage regulation mode. In the situation perception stage, the information on the EV status, grid operation status and EV charging station status is collected; in the situation assessment stage, the information collected in the situation perception stage is used to establish an objective function with minimum comprehensive cost after high penetration EVs are connected to the grid; in the situation prediction stage, the voltage deviation of the distribution network is predicted according to the charging demand of EVs and the information of EV charging stations, and a global electrical distance matrix is established to correct the predicted voltage based on the power flow section and to confirm the voltage deviation of the grid; in the facilitation stage, the distribution network voltage deviation index is introduced to determine the degree of distribution network’s voltage deviation with consideration of the voltage regulation mode within the distribution network, and the secondary voltage regulation control strategy of the distribution network is determined for different degrees of voltage deviation. A simulation analysis is carried out with IEEE 30-node system, and the results have verified that the proposed method can effectively solve the grid voltage overlimit problem after high penetration of EVs are connected to the grid.

Power System

Safety Risk of Synchronous Condenser with Typical Asymmetric Magnetic Field Faults Under Extreme Operating Conditions

CAO Guizhou, CHEN Erqiang, FAN Xuanjie, WU Yucai, LI Zhenping, SHI Shuhuai

2023, 56(2):  45-52,76.  DOI: 10.11930/j.issn.1004-9649.202210010

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Under typical magnetic field asymmetry faults, the synchronous condenser has an increase in unbalance force formed by forced excitation and tripping risk. Firstly, an analysis is made of the influence mechanism of typical faults such as rotor dynamic eccentricity and rotor winding inter-turn short circuit on the magnetic field of the synchronous condenser. Then, the expression of unbalanced magnetic pull on the rotor is derived using air-gap permeance method, and the influence of forced excitation on the unbalanced electromagnetic force is further analyzed. Finally, the finite element electromagnetic transient simulation is carried out on a large synchronous machine to simulate the dynamic eccentricity and the rotor winding inter-turn short circuit fault. The unbalanced electromagnetic force on the rotor is extracted respectively under the conditions of normal excitation and forced excitation, and the possibility of tripping under forced excitation is evaluated. The results show that under the forced excitation, the unbalanced magnetic pull produced by the dynamic eccentricity fault of synchronous condensers will not cause severe vibration of the unit, while the rotor inter-turn short circuit fault produces a big unbalanced magnetic pull, which may result in the unit tripping.

Thermal Load Application Method for Temperature Cycle Test of Power Module PP-IGBT

LI Biaojun, LENG Mei, DAI Jiashui, WANG Ning

2023, 56(2):  53-58,67.  DOI: 10.11930/j.issn.1004-9649.202108069

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Temperature cycling test is an important test method to study the thermal fatigue aging characteristics of power module press pack insulated gate bipolar transistor (PP-IGBT) devices. Therefore, taking the PP-IGBT of flexible direct converter valve power module as the research object, and combined with theoretical calculation and finite element simulation analysis, a thermal load application method for temperature cycle test is proposed, and the corresponding electrical input target parameters are obtained. A temperature cycle test platform is built to monitor the device temperature in real time, and a comprehensive comparison analysis is made on the temperature data of the junction, shell and heatsink at the measuring point of the tested power module IGBT devices. The simulation results have verified the effectiveness of the proposed method, and can provide a research approach for the PP-IGBT test of the same type.

Algorithm for Dynamic Reactive Power Optimization of Regional Power Grid Based on Interior Point Method and Neighborhood Search Decoupling Dynamic Programming Method

ZHANG Jie, WANG Hengfeng, LIU Shengchun, WANG Huabiao, WANG Canghai, RAN Yao, WANG Xianmin, MA Yongfei, YAN Wei

2023, 56(2):  59-67.  DOI: 10.11930/j.issn.1004-9649.202107042

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The dynamic programming method can efficiently and accurately solve the dynamic reactive power optimization problem of the small-scale regional power grid. However, with the power grid scale increment, the optimization problem would have the combination explosion issue, which would lead to the rapid growth of solution time. Therefore, a two-stage hybrid dynamic reactive power optimization method based on the interior point method and the neighborhood search decoupling dynamic programming method is proposed. In the first stage, Sigmoid function is used to achieve the continuity of the original model, and then the interior point method is adopted to find the continuous optimal solution; while in the second stage, on the basis of the continuous solution, the heuristic neighborhood search strategy is employed to determine the search space of the decoupling dynamic programming method. The regional power grid dynamic reactive power optimization problem is solved through the decoupling between stations, the decoupled coordination of voltage regulation and reactive power compensation equipment, and the dynamic programming within the stations. The two-stage method could not only ensure the quality of the optimal solution, but also avoid solving the state combination explosion problem with discrete variables, which greatly improves the computational efficiency. The effectiveness of the proposed method is verified by the simulations on a 220 kV control zone.

Deep Deterministic Policy Gradient Algorithm Based Wind-Photovoltaic-Storage Hybrid System Joint Dispatch

ZHANG Shuxing, MA Chi, YANG Zhixue, WANG Yao, WU Hao, REN Zhouyang

2023, 56(2):  68-76.  DOI: 10.11930/j.issn.1004-9649.202107065

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A deep reinforcement learning based wind-photovoltaic-storage system joint dispatch model is proposed. First, a joint dispatch model that fully considers the constraints of various wind and solar storage stations is established, where tracking dispatch plans, wind and solar curtailment, and energy storage operation costs are considered in the objective function. Then, the state variables, action variables and reward function under the reinforcement learning framework are defined. Later, a deep deterministic policy gradient algorithm is introduced, using its environmental interaction and strategy exploration mechanism to learn the joint scheduling strategy, so as to achieve the dispatch strategy tracking, reduce wind and solar abandonment, and reduce energy storage charging and discharging. Finally, the historical data of wind power, photovoltaic, and dispatch plan in a certain area of northwestern China are employed to train and analyze the model. The results of the case studies show that the proposed method can adapt well to the changes in the wind power and photovoltaic power in different periods, and the joint scheduling strategy can be obtained under given data of wind and photovoltaic.

Analysis of Radio Interference Measurement Data for 750 kV AC Transmission Lines at High Altitude

ZHANG Yemao, LI Ni, ZHOU Cuijuan, LU Haonan

2023, 56(2):  77-85.  DOI: 10.11930/j.issn.1004-9649.202210028

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In order to build ultra-high voltage AC transmission lines at high altitude, it is necessary to master the corona characteristics of transmission lines at high altitude to guide the transmission lines design. The typical radio interference data of the 750 kV single circuit transmission lines measured at the Guan-ting long-term observation station were analyzed. The study results showed that the radio interference under fair weather was basically below 55 dB, which met the control limit requirements; the measurement results under fog and haze weathers generally had little difference from those under fair weather. The radio interference before and after line outage and line recharged was measured separately, and the radio interference could be used as the criterion to determine whether the transmission lines were powered or not. After the transmission lines were recharged, the radio interference was larger and increased gradually with the time, and decreased after removal of the dust on the conductor surface. The variation characteristics of the radio interference with rainfall and snowfall were obtained. The radio interference spectrum had a tendency of attenuation in the range between 0.15 MHz and 20.00 MHz. The standard spectrum in the lower frequency band between 0.15 MHz to 1.00 MHz was basically consistent with the actual measurement results. With the increase of the frequency, the standard spectrum level was larger than the measurement results, and a closer fitting curve was given.

Performance Analysis of a Domestic Crosslinked Polyethylene Insulating Material for 500 kV Power Cable

YAN Hongda, LI Wenpeng, ZHANG Chong, SUI Rui, LI Fei, HE Lin, ZHONG Lisheng

2023, 56(2):  86-92.  DOI: 10.11930/j.issn.1004-9649.202210100

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The applicability of a new domestic super clean XLPE insulating material for 500 kV AC cables is discussed. Firstly, the similarities and differences between domestic and imported base resins in molecular weight and chain structure are analyzed. Furthermore, the electrical, thermal and mechanical properties of the domestic XLPE is studied and compared with those of two imported XLPE. It is found that the three materials have similar properties and all meet the requirements for 500 kV cables. Finally, based on the molecular chain structure of the base resin, it is concluded that the introduction of more terminal double bonds in the base resin to improve crosslinking efficiency may be one of the directions for the subsequent improvement of domestic insulating materials.

A Multi-impedance Optimization Control for AC Microgrid DC Interconnected Converter System

LIU Zhenguo, JIN Ming, YU Hai, CHEN Wentao, YANG Dingqian

2023, 56(2):  93-101,156.  DOI: 10.11930/j.issn.1004-9649.202203057

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The two AC microgrids are DC interconnected through back-to-back structured VSC converters. Usually one side converter adopts DC voltage control, and the other side converter adopts constant active power control. Under bidirectional power flow, when the power-controlled converter mode is used as a power load, its DC or AC port impedance will show negative impedance characteristics, reducing system damping and stability. To solve this problem, a multi-impedance optimization control is proposed, which not only optimizes the negative impedance to positive impedance, but also reduces the phase difference on DC side, enhancing the stability of the system completely. First, the structure of the AC micro-grid DC interconnected converter system, the topology and control of the converter are briefly introduced. Secondly, small-signal modeling was modelled of the multiple ports of the converters on both sides before the optimization, and the impedance characteristics were analyzed. Then, the working mechanism of multi-impedance optimization control is analyzed, and the optimized port impedance is re-modeled. The results show that the proposed multi-impedance optimization control can optimize the impedance of multiple ports in the system. It can not only optimize the negative impedance of the original AC and DC sides to positive impedance, but also reduce the phase difference between the impedances of the DC side，maintaining a larger stability margin and greatly improving system stability.

New Energy

Three-Layer Energy Optimization Strategy for CHP Microgrid Considering Path Loss

LING Kai, WANG Can, ZHANG Gaorui, WANG Aoqi, CHU Sihu, TIAN Fuyin, LI Xinran

2023, 56(2):  102-113.  DOI: 10.11930/j.issn.1004-9649.202206113

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In order to reduce the dependence of the microgrid on the external system and the operating cost of the microgrid itself, a three-layer energy optimization strategy is proposed for the combined heat and power microgrid cluster. This strategy not only constructs a lower layer optimal operation model aiming at minimizing the operation cost of each microgrid and an upper layer optimal operation model aiming at minimizing the interaction cost between agents but also constructs a new middle layer optimal operation model aiming at minimizing the loss of energy transmission path. The middle layer model improves the energy mutual aid ability between microgrids through barter and trading transactions and searches for the optimal transmission path for energy transactions between microgrids based on the Floyd-Warshall algorithm. The example results show that the three-layer optimization strategy proposed in this paper has good applicability. Compared with other optimization strategies, the proposed strategy has a lower energy transmission process loss, a stronger energy mutual aid ability between microgrids, and a smaller operation cost for each microgrid.

Optimization of Active Heat Storage in Heat-Supply Network Considering Curtailed Wind Power Consumption

WANG Nan, ZHANG Chen, HE Xudao, YANG Yuwei, CHEN Lian, LIU Hao, WANG Chenchen, JIANG Xudong, YE Cheng

2023, 56(2):  114-122.  DOI: 10.11930/j.issn.1004-9649.202206104

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To overcome the wind power curtailment caused by the thermoelectric coupling characteristics of combined heat and power units, this paper proposes an operation optimization strategy for integrated energy systems based on active heat storage of heat-supply networks by utilizing adjustable heat load. By analyzing the variations in unit output power, the heat storage effect of the heat-supply system, and the equivalent heat load in different scenarios, the paper explores the influences of passive heat storage of the heat-supply system and adjustable heat load on wind power consumption and system operation performance, respectively. The results show that both passive heat storage of the heat-supply system and flexible heat load can raise the level of wind power consumption, although the effect of the latter measure is better than that of the former one. In addition, adjustable heat load can be leveraged for positive heat storage in the heat-supply network to a certain extent.

Analysis of Investment Economy of Electric Boilers with Thermal Storage in Source-Load Application Scenarios

XU Yanping, SHI Haobo, QIN Xiaohui, ZHAO Mingxin, BAI Jie, Ding Baodi

2023, 56(2):  123-132.  DOI: 10.11930/j.issn.1004-9649.202208125

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Electric boilers with thermal storage are a kind of electric-thermal conversion equipment, and they can be applied on both the source side and the load side of a power system to improve the flexibility of the system. This paper was designed to analyze the investment economy of electric boilers with thermal storage. Specifically, it built operation constraint models for electric boilers with thermal storage in different scenarios on the basis of the different operation modes of electric boilers with thermal storage in source-load scenarios and analyzed the composition of the economic benefits and comprehensive social benefits of the investment entities in different modes. Then, time-series production simulation was performed to construct an optimization model for the economic benefits of the investment entities for electric boilers with thermal storage with the objective of maximizing the annual economic benefits. Finally, the investment economy of the investment entities for electric heating with thermal storage was analyzed and evaluated by the net present value method. A provincial power grid in the Three North Region of China was further analyzed as an example, and investment economy was calculated according to the Northeast Electric Power Auxiliary Service Market Operation Rules. The results show that the application modes all have obvious comprehensive social benefits. The investment mode of thermal power plants has the highest profitability. In contrast, the investment modes of wind farms and load-side independent entities are not economically sustainable and thus require the adjustment of the corresponding market operation strategies.

Multi-agent Peak Shaving and Valley Filling Strategy Considering the Flexibility of Electric-Thermal System with Optical Storage

ZENG Shuang, LIANG Anqi, WANG Liyong, LI Xianglong, MA Lin, WANG Zhe, WANG Linyu, LIU Lan, ZHAO Wei

2023, 56(2):  133-142.  DOI: 10.11930/j.issn.1004-9649.202209016

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This paper proposes a multi-agent peak shaving and valley filling strategy to solve the problem of collaborative participation of an electric-thermal system (ETS) with optical storage in peak shaving and valley filling of power grids and reduce the impact of load prediction errors and volatility of new energy on the regulation effect. The strategy is implemented based on a multi-agent system consisting of a distribution network agent, regional agents, ETS/photovoltaic (PV) agents, and execution units, and it contains centralized energy optimization and distributed energy management links. In the centralized energy optimization process, the distribution network agent can provide an intra-day active power cap scheme for the regional agents and their internal photovoltaic systems by solving a model predictive control (MPC) optimization model with the optimization objective of minimizing its own operating costs. In the distributed energy management process, the regional agents and ETS/PV agents obtain correction values of the active power for the heating equipment based on a multi-agent consistency algorithm so that the deviation between the actual active power of the regional agents and its planned value can be reduced. The simulation results show that the proposed method allows the system to collaborate in peak shaving and valley filling with more accurate results.

Forecast of Photovoltaic Power Based on IWPA-LSSVM Considering Weather Types and Similar Days

XU Yilun, ZHANG Binqiao, HUANG Jing, XIE Xiao, WANG Ruoxin, SHEN Danqing, HE Lina, YANG Kaifan

2023, 56(2):  143-149.  DOI: 10.11930/j.issn.1004-9649.202108059

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In order to improve the prediction accuracy of photovoltaic power, the input of the photovoltaic power prediction model is determined according to the characteristics of photovoltaic output power under different weather types. Aiming at the defects of the wolf pack algorithm (WPA), an improved wolf pack algorithm (IWPA) was obtained by improving the walking position and running step of the wolf pack. The least squares support vector machine (lSSVM) was optimized by IWPA, and an IWPA-LSSVM based photovoltaic power prediction model was established considering weather types and similar days. The photovoltaic power generation data under different weather types were used for simulation, and the simulation results show that the proposed method has a higher prediction accuracy and the error fluctuation of regression fitting is smaller whether the weather is sunny, cloudy or rainy.

A Cluster Partition Method for Distributed Generation Considering Flexibility Supply-Demand Balance and Response Speed

YE Chang, YI Huamao, ZHU Jiongda, ZHAO Jingjing, WU Lian

2023, 56(2):  150-156.  DOI: 10.11930/j.issn.1004-9649.202203115

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The large-scale connection of distributed generation (DG) to the power grid brings about significant difficulties to the conventional centralized regulation of the power system. In order to improve the regulation flexibility of distributed generation cluster (DGC), a cluster partition method is proposed considering the supply-demand balance and response speed of DGC. Firstly, the cluster climbing flexibility is analyzed and a power allocation strategy is proposed to meet the demand of FM flexibility. Then, the DGC supply and demand balance index and response speed index are proposed, and the cluster partition method is obtained. Finally, an IEEE 33 node example is given to verify the effectiveness of the proposed method.

Technology and Economics

LM-CNN-based Automatic Cost Calculation Model for Power Transmission and Transformation Projects

WU Xiaolin, LUAN Ling, PAN Lianwu, LI Hailong

2023, 56(2):  157-163.  DOI: 10.11930/j.issn.1004-9649.202103063

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The cost calculation of power transmission and transformation project is the core part of cost control technology. The quality of the cost calculation model directly affects the efficiency and reliability of the cost management of power transmission and transformation projects. However, the existing models cannot reconcile the computational speed, accuracy and stability. Considering above-mentioned problems, firstly, a convolutional neural network model is constructed with its input and output determined according to the practical cost requirements of the power transmission and transformation projects. Then, the historical cost data are input into the network model as samples to calculate the network output. Finally, in view of the big difference between the expected output and the actual output, the Levenberg-Marquart algorithm is utilized to optimize the weight parameters of the convolutional neural network to complete the model training. Compared with the BP neural network and GD-CNN, the proposed model with higher prediction accuracy and stability combines the advantages of Levenberg-Marquart algorithm and convolutional neural network model to improve the calculation effect of power transmission and transformation project cost.

Optimal Configuration and Economic Analysis of User-Side Energy Storage Participating in Auxiliary Services

SHANG Boyang, XU Yin, WANG Ying, ZHANG Jingping

2023, 56(2):  164-170,178.  DOI: 10.11930/j.issn.1004-9649.202103054

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In order to maximize the benefits of user-side energy storage, a user-side energy storage optimization allocation method is proposed to participate in the auxiliary service market. First, a life-cycle cost model of user-side energy storage and a benefit model considering ancillary services are established. Secondly, under the two-part electricity price system, based on the consideration of the operating characteristics of energy storage batteries and user load characteristics, a user-side energy storage optimization configuration model is established to participate in auxiliary services. The energy storage capacity and auxiliary service parameters are taken as optimization variables to optimize the net income of industrial users during the whole life cycle. Then, taking the energy storage auxiliary service market in Guangxi as an example, the optimization of configuration under the optimal user-side energy storage capacity is realized, and the variable values involved in the auxiliary service are determined. Finally, the economic benefits of different auxiliary services are compared and analyzed by changing the policy sensitivity, which provides guidance for future energy storage investment.

Energy Conservation and Environmental Protection

Analysis of Air Pollutant Emission Characteristics of Ultra-low Emission Coal-Fired Units Based on CEMS Data

QU Litao, QI Xiaohui, WANG Dexin, YU Honghai

2023, 56(2):  171-178.  DOI: 10.11930/j.issn.1004-9649.202203075

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Taking 54 ultra-low emission coal-fired units as the research object, the annual emission compliance rate, annual emission concentration, emission performance and other emission characteristics of major air pollutants (particulate matter, SO₂, NO_x) were compared and analyzed. The causes of excessive emissions and failures were analyzed on the basis of the survey of the commissioning and failures of environmental protection facilities. As shown by the results, the annual up-to-standard emission rates of particulate matter, SO₂, and NO_x in the coal-fired units participating in the survey were 99.981%, 99.962%, and 99.893%; The average emission performance of particulate matter, SO₂, and NO_x were 11.11, 68.16, and 140.26 mg/(kW·h), respectively, which meet and exceed the requirements of national standards; The proportions of the emission of particulate matter, SO₂, and NO_x exceeding the standard during the start-stop period were 54%, 64%, and 57%, respectively, indicating that the emission concentrations of particulate matter, SO₂, and NO_x during the start-stop process of the units were difficult to control. Therefore, eliminating the influencing factors that restrict the normal operation of environmental protection facilities during start-stop period is the research direction of subsequent technical public relations.