Electric Power

Configuration Optimization of Integrated Energy System for Data Center Considering Multiple Energy Storage Facilities

SUN Qiang, SUN Zhihuang, PAN Hangping, CHEN Jiejun, ZHU Chanxia, CHEN Qian, ZHOU Jiawei

2022, 55(9): 1-7. DOI: 10.11930/j.issn.1004-9649.202206048

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Data center is the key infrastructure of China digital development. It is urgent to carry out research on reducing the comprehensive energy cost of data center through configuring multiple energy storage facilities. An economic analysis is made on the energy storage technical paths for data center from the overall perspective of optimal configuration of the data center integrated energy system and operation strategy of energy system. A case study is made by taking a data center in Beijing as an example, and results show that optimal configuration of emergency and peak-shaving energy storage as well as system operation strategy can substantially reduce the system operating cost and annual equipment investment cost.

A Capacity Optimization Configuration Method for Photovoltaic and Energy Storage System of 5 G Base Station Considering Time-of-Use Electricity Price

HAN Ziyan, WANG Shouxiang, ZHAO Qianyu, ZHENG Zhijie

2022, 55(9): 8-15. DOI: 10.11930/j.issn.1004-9649.202109063

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With the rapid development of the 5th generation mobile communication technology (5G communication), the number of 5G base stations is increasing, and the problem of large power consumption and high electricity cost of 5G communication is becoming more and more prominent. Therefore, an optimal configuration method is proposed for the photovoltaic and energy storage system of 5G base station with consideration of the integration of photovoltaic power generation and energy storage to improve the economics of 5G base station operation. Firstly, considering the load of 5G base station and the time-of-use electricity price of distribution network, an economic dispatching model is built for the photovoltaic and energy storage system of 5G base station. Then, the quantum-behaved particle swarm optimization algorithm is used to calculate the minimum comprehensive cost of the photovoltaic and energy storage system of 5G base station in a typical day to determine the optimal capacity of photovoltaic power generation and energy storage. Finally, the calculation results show that reasonable capacity configuration of photovoltaic power generation and energy storage can improve the economy of 5G base station system. The configuration capacity of photovoltaic and energy storage is greatly affected by the energy storage cost and the peak-valley price difference. The economic benefits brought by the photovoltaic and energy storage system increase with the increase of peak-valley price difference and the decrease of energy storage cost.

An Energy Management Optimization Strategy for Regional Power Grid Energy Storage System Based on Improved Artificial Bee Colony Algorithm

WANG Ziqi, ZHANG Huiyuan, XU Jun, CHENG Jiehui

2022, 55(9): 16-22,55. DOI: 10.11930/j.issn.1004-9649.202101055

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In order to improve the new energy consumption level and system operation efficiency, it is necessary to optimize the charging and discharging power of energy storage system, so as to stabilize power fluctuation, reduce network loss and improve economic benefits. In this paper, the charging and discharging of energy storage is selected for each period based on the source and load status, and an energy storage management optimization model is established for regional power grid with the objectives of reducing the daily network loss, maximizing the daily arbitrage of energy storage and the daily environmental benefits, which comprehensively considers the constraints of energy storage itself and grid power flow state. In the process of solving the model, an improved artificial bee colony (IABC) algorithm is proposed, and simulation is designed out according to the structure and operation characteristics of the Turpan regional grid. Simulation results show that the energy management optimization of energy storage can improve the overall economic benefits, and the improved artificial bee colony algorithm has good global search ability and convergence.

A Reliability Evaluation Method for Power System with Energy Storage Based on Operation Optimization

ZHANG Liming, LI Hao, WU Yaxiong, GAO Chong, ZHANG Junxiao, LIU Yong

2022, 55(9): 23-28. DOI: 10.11930/j.issn.1004-9649.202202047

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In view of the problem that the traditional reliability evaluation method often leads to outage loss of power system, a new reliability evaluation method is proposed for power system with energy storage based on operation optimization. Firstly, a probabilistic model is established according to distributed generation output, and a profit-driven energy storage probability model is established under the peak-valley price mechanism. Secondly, the fault isolation range is refined according to fault types, and the non-fault isolation area is islanded and power matched through network reconfiguration to minimize power outage losses. Finally, a sequential Monte Carlo based reliability evaluation method is proposed. The effectiveness of method is verified through simulation.

Coordinated Scheduling of Distribution Networks and Microgrids Considering Heat Pump Load and Distributed Photovoltaic

LI Shihui, WANG Qi, JIA Xiaobo, WU Wenchuan, LIANG Huayang, ZHU Lin

2022, 55(9): 29-37. DOI: 10.11930/j.issn.1004-9649.202207028

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With the progress of the transformation of rural clean heating and the construction of urban distributed photovoltaics, a large number of rural microgrids have appeared in the distribution networks. However, the strong randomness and volatility of distributed photovoltaics also bring many challenges to the operation of the power systems and make the power grids face such problems as severe power flow fluctuations and voltage violations. Firstly, a decomposition and coordination model is constructed for distribution networks and microgrids considering heat pumps, photovoltaics and energy storage systems , in which the heat pumps are described by the equivalent state space model. Subsequently, an improved Benders decomposition algorithm is proposed to solve the active and reactive power coordination problem of distribution networks and microgrids. Finally, numerical tests are carried out on the D141-M4 system, which has verified the validity of the proposed method in reducing the peak load and alleviating voltage violations on the premise of ensuring the users' comfort.

Ensemble Learning-Based Day-Ahead Power Forecasting of Distributed Photovoltaic Generation

LIU Yijuan, CHEN Yunlong, LIU Jiyan, ZHANG Xuemei, WU Xiaoyu, KONG Weizheng

2022, 55(9): 38-45. DOI: 10.11930/j.issn.1004-9649.202204083

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Accurate day-ahead power prediction of photovoltaic generation is helpful to design future scheduling plan of power grid, reduce the impact of new energy generation on power grid and improve the accommodation rate. A day-ahead power forecasting method for photovoltaic generation is proposed based on the Boosting ensemble learning framework. Firstly, according to the characteristics of photovoltaic output which is mainly affected by weather, the meteorological factors with strong correlation are obtained through the Pearson coefficient, and the k-means ++ is used to cluster the total horizontal irradiance that is strongly correlated with photovoltaic generation power to obtain the similar daily datasets. And then, the extreme learning machine (ELM) is introduced into the Boosting framework to build the photovoltaic output day-ahead prediction model (B-ELMs). Finally, the validity of the model is verified using the operation data of real photovoltaic power stations. The proposed model shows good adaptability in the test process and has the highest decision coefficient (R²) of 0.9819. The experimental results show that due to the existence of ensemble learning framework, the B-ELMS can still provide accurate prediction results against the photovoltaic output curves with poor regularity and strong fluctuation under complex weather. At the same time, the B-ELMS has a faster convergence rate compared with deep-learning network, and can provide more accurate prediction results while maintaining faster training speed.

A Synergic Optimization Method for Service Scope and Load Management Technologies of Rural Power Distribution Network

HUANG Zishuo, LIU Yingfang, ZHANG Xinhe, HE Guixiong, XIONG Junjie

2022, 55(9): 46-55. DOI: 10.11930/j.issn.1004-9649.202204014

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Various types of electricity users in rural areas are scattered and have low load density. The average utilization rate of power grids in the distribution networks is much lower than that in urban areas. The fluctuation characteristics of the load curve of each user are different, and the average load is different when different users are combined together. Optimizing the energy supply scope of the distribution networks has the potential to improve the utilization rate of power equipment. At the same time, various demand-side load management measures can also be applied to adjust the load curves of various users and reduce the peak-to-valley difference in power supply. In order to realize the coordinated optimization of rural distribution network planning and the demand side load management schemes, a user aggregation and user demand load management synergic optimization model is built to comprehensively optimize the energy consumption management of each user and the energy service scope of distribution network lines. The case study shows that the coordinated optimization of the energy supply scope of the distribution networks and the demand side load management measures of users can significantly improve the average utilization rate of the rural power grid lines and auxiliary equipment and reduce the construction cost of the rural power grids.

Demand Side Feasible Region Aggregation Considering Flexibility Revenue

ZHOU Hailang, LIU Yipan, CHEN Yuguo, WANG Zishi, QU Shengpeng, HE Kai, BAO Shiyuan

2022, 55(9): 56-63,155. DOI: 10.11930/j.issn.1004-9649.202110056

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The flexibility of demand-side resources needs to be aggregated through a feasible region aggregation technique to participate in the spot market. This paper presents a feasible region aggregation method of demand-side resources considering flexibility revenue. Firstly, a feasible region approximation method based on Zonotope is presented, which could approximate the feasible region of power, state, and climbing constraints effectively. Secondly, the revenue of flexibility in different periods is considered, and the feasible domain with variable weight is designed to approximate the optimization objective. Finally, the efficient aggregation of the feasible domain of demand-side resources is realized, which provides the system with high-value flexible resources. The validity of the proposed method is verified based on real electricity price data and the energy storage model.

A Control Algorithm Based on Two-Stage Aggregation for P2P Energy Trading in Community Microgrids

CHEN Peiyu, CHONG Zhiqiang, LI Shuqing, XI Xiaoguang, LI Zhenbin, WANG Huiyuan

2022, 55(9): 64-69. DOI: 10.11930/j.issn.1004-9649.202103029

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In order to better realize peer-to-peer (P2P) energy trading, a two-stage aggregated control strategy is proposed. where only one measurement point and one-way communication from the measurement point to individual prosumers are required. In the first stage, the constrained non-linear programming (CNLP) optimization is used to minimize the energy costs of the community. In the second stage, a rule-based real-time control strategy is adopted. The proposed control algorithm is validated for its effectiveness through case simulation, and comparison has been carried out between different control algorithms to identify the most effective approach in reducing energy losses and prosumers’ energy bills.

Research on Inrush Current Suppression of Transformer Based on Changeable Closing Angle

LI Haitao, LIU Beiyang, TENG Wentao, LI Kuan, LIU Dongchao, XU Lei

2022, 55(9): 70-78. DOI: 10.11930/j.issn.1004-9649.202201098

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The transformer no-load closing inrush current may cause safety problems in power grid, and the controlled switching technology with fixed target angle still has room for improvement in suppressing inrush current. A transformer inrush current suppression method and controlled-switching strategy are thus proposed based on changeable closing angle. The high voltage side PT or low voltage side PT of transformer is used to calculate the residual flux, and the target closing angle is adjusted according to residual flux. The key factors influencing the residual flux are determined, and the principles for choosing the target closing angle are proposed. A device prototype is developed and its effectiveness is verified through dynamic simulation and test station, which can provide reference for its engineering application.

A Coupling Analysis of Multiphysical Field for ZnO Surge Arrester Installed in Photovoltaic Substation

ZHANG Tianyi, LIANG Zhijian, ZHU Rui

2022, 55(9): 79-87. DOI: 10.11930/j.issn.1004-9649.202205080

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Conventional finite element analysis(FEA) employed in multiphysical field coupling analysis usually suffers from such drawbacks as large computational effort and heavy reliance on grid quality. Taking a 220 kV ZnO surge arrester installed in a photovoltaic substation as an example, a new multiphysical field coupling analysis is proposed based on combined FEA and meshless method to solve thermal transfer problem. Firstly, a three-dimensional fluid field FEA model is established for surge arrester to obtain the detailed fluid distributions. Secondly, the calculated convective heat transfer coefficients are taken as the boundary conditions of thermal field analysis. The FEA and meshless method are used to calculate the thermal rise of surge arrester under rated operation and aging condition. Finally, the simulation result of the proposed method are compared with that obtained by conventional FEA and experiments, which verifies the effectiveness of the proposed method with a computational speed much higher than that of the conventional FEA.

Load Current Feedforward Control Strategy for Power Electronic Transformer

LI Shuaihu, WANG Tingting, LIU Zhi, PENG Hanmei, TANG Kun

2022, 55(9): 88-97. DOI: 10.11930/j.issn.1004-9649.202103009

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Power Electronic Transformer (PET) consists of cascaded H-bridge (CHB) converters and dual active bridge (DAB) converters. However, the fluctuation of load causes large voltage fluctuation of high voltage DC (HVDC) and low voltage DC (LVDC) buses of PET. To address this problem, a load current feedforward control strategy for cascaded systems is proposed, which consists of two parts: the load current feedforward of DAB stage and CHB stage. The former obtains the compensated phase shift ratio of the DAB stage through calculation of the load current at the low voltage side, while the latter feeds forward the load current to the CHB stage with consideration of the power conservation of the cascade system. Moreover, considering the delay of the inner current loop of the CHB stage, the first order differential is introduced to the feedforward strategy in CHB stage, which further suppresses the voltage fluctuation on HVDC buses. The proposed control strategy only needs to sample the load current of LVDC bus, which saves the system cost greatly. In addition, the proposed strategy is easy to operate and implement. Simulation and Starsim experimental results verify the correctness and effectiveness of the proposed control method.

Numerical Simulation Analysis on a Composite Edge Terminal Reverse Blocking IGBT

CUI Lei, YANG Tong, ZHANG Ruliang, MA Li, LI Yichen

2022, 55(9): 98-104. DOI: 10.11930/j.issn.1004-9649.202011058

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Insulated gate bipolar transistor (IGBT) is usually used in combination with power diode in power electric circuit because it has no reverse blocking ability. In order to reduce cost and parasitic inductance, the freewheeling diode and IGBT are integrated by process method, and a reverse blocking insulated gate bipolar transistor (RB-IGBT) is thus proposed. For reducing the terminal area of conventional reverse blocking IGBT, an improved composite terminal structure is proposed. The double doped field limiting ring is used to introduce a n-type low doping region near the p-type field limiting ring, which can reduce the lateral expansion rate of depletion region, increase device reliability, improve terminal efficiency and save terminal size.

An Event Extraction Method for Power Dispatching Text Based on Hybrid Neural Network

LIU He, PI Junbo, SONG Pengcheng, ZHAO Hanlin, ZHANG Yue, LIU Xianzhuang

2022, 55(9): 105-110,120. DOI: 10.11930/j.issn.1004-9649.202111096

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In order to improve the application effect of power dispatching text in business scenarios, a method for extracting power dispatching text events is proposed based on hybrid neural network. Taking the power dispatching text fault handling plan as the research object, an event extraction model is established centering on the trigger words of the plan. It is proved through case simulation that the proposed method can better extract the entity elements in the plan event. Compared with other methods, the accuracy of the entity recognition and entity relation recognition is improved.

Hierarchical Layout Method for Automatic Transformation of Large-Scale Electromechanical-Electromagnetic Transient Simulation Model

HE Hailin, SHI Huabo, WANG Shunliang, MA Junpeng, LIU Tianqi

2022, 55(9): 111-120. DOI: 10.11930/j.issn.1004-9649.202206071

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The automatic layout of station nodes and network topology is a vitally important link to realize the automatic transformation of electromechanical-electromagnetic transient simulation model, which is of great significance to improve the modeling efficiency and accuracy of large-scale power system. Most of the existing layout algorithms are confined to the research of cross points and layout uniformity, while they don’t consider the actual relative position between nodes, resulting in extremely unstable layout results at every turn. Therefore, a spring-electronic model based hierarchical layout method is proposed for automatic transformation of large-scale electromechanical-electromagnetic transient simulation model. The approach considers the actual relative position between nodes, realizes the hierarchical layout of networks with different voltage levels, and avoids the problem of large difference in layout results of traditional methods. It can not only be used to draw electromechanical transient geographical wiring diagram, but also provide nodes coordinate information for the generation of large-scale electromagnetic transient simulation model. The effectiveness of the proposed approach is verified through case testing and analysis of the Western System Coordinating Council (WSCC) 3-generator 9-bus system, the New England 10-generator 39-bus system, and a regional power system.

Phase Sequence Adjustment Method for Three-Phase Load Imbalance in Station Area Based on Improved Pigeon-inspired Optimization

HU Mingyue, ZHANG Huifen, MIAO Shuping, YANG Fan, QU Zhenming

2022, 55(9): 121-128. DOI: 10.11930/j.issn.1004-9649.202010074

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Aiming at the three-phase load imbalance phenomenon in the low-voltage distribution station area, a method for adjusting the load phase sequence based on commutation switch is studied. The unbalanced load commutation control strategy is used to establish an optimal commutation mathematical model with the goal of minimizing the three-phase current imbalance on the low-voltage side of the distribution transformers; the adaptive parameters and Cauchy disturbance are introduced to improve the original pigeon-inspired optimization (PIO) algorithm. The improved PIO algorithm is used to solve the optimal commutation scheme. Matlab simulation verifies the superiority of the improved PIO algorithm and its effectiveness in solving the optimal commutation scheme, and the the improved PIO algorithm can significantly reduce the imbalance of the three-phase load in the station area.

Hybrid-Timescale Robust Optimization in Active Distribution Network with Energy Storage System-Soft Open Point

RU Qiushi, MI Xuefeng, SONG Zhigang, LIU Jintao, LEI Xia

2022, 55(9): 129-139. DOI: 10.11930/j.issn.1004-9649.202203085

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Sudden fluctuation of feeder power and voltage over-limit caused by unbalanced source-load distribution in the distribution network often occur as the penetration rate of photovoltaic (PV) power generation increases. Therefore, this paper proposes a hybrid-timescale robust optimization model of active distribution network with energy storage system and soft open point (SOP), PV inverters, and voltage/var control (VVC) equipment, which improves the economy and stability of distribution network operations. Firstly, flexible interconnection devices combining SOP (E-SOP) are introduced between the ends of distribution network lines. Thus, a day ahead and intraday robust optimization model of distribution network considering various VVC equipment is built. Secondly, the inverter droop control model based on voltage sensitivity under robust situations is set up to deal with the risks of strongly stochastic PV generation. The model ensures the system voltage stability and balances the distribution of power source and load in the distribution network. Finally, the modified IEEE 33 bus system is utilized to verify the effectiveness of the proposed method.

Pattern Analysis of Regional Energy Consumption Based on Integrated Energy Measurement Data

WANG Xingang, ZHAO Fang, ZHU Wenjun

2022, 55(9): 140-145. DOI: 10.11930/j.issn.1004-9649.202105059

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The spatio-temporal pattern of users’ energy consumption can offer an important guideline for power system planning, and it is also one of the most important basis for power grid construction. Through widely deployed new-type advanced metering infrastructures, power grid operators are able to analyze the users’ energy consumption patterns, which can promote the efficient operation of power grids. Towards regional user profile for energy consumption, a regional energy consumption pattern analysis approach is proposed based on integrated energy measurement data. Using multi-meter integration energy-consumption acquisition system, the gas consumption data is introduced for analysis. The hierarchical clustering and self-organized maps (SOM) methods are used to describe the energy consumption patterns. Simulation and experimental results show that the proposed method is of practical use in energy consumption analysis and conducive to discovering high energy-consumption regions, which is helpful for power grid operators to formulate power system planning schemes.

An Optimization Strategy for Generator Start-up Sequence After Blackouts Considering the Cyber System Fault

LI Mingming, SUN Lei, MA Yinghao

2022, 55(9): 146-155. DOI: 10.11930/j.issn.1004-9649.202205013

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A reasonable start-up sequence scheme of generator units after blackouts is conducive to increasing the generation capacity of power systems and speeding up power system restoration. Since the dispatching control of power systems highly depends on cyber systems, the cyber system fault will affect the start-up sequence of generator units in the process of power system restoration. Given this background, an optimal start-up sequence model of generator units is proposed with consideration of the cyber system faults. Firstly, the cyber system fault based on the denial of service (DoS) attack is introduced, and the effect of the cyber system fault on the restoration characteristics of generator units in the process of generators' restoration is analyzed. And then, the time uncertainty of cyber system fault is addressed by employing the scenario analysis method. An optimal start-up sequence model of generators is proposed with the expectation of maximum power systems’ total generation as objective function, and taking into account the constraints including the start-up time constraint of generator units, the auxiliary variables constraint related to the cyber system fault, and the start-up power constraint of generator units. The proposed model is linearized and reformulated into a mixed-integer linear programming model, and it can be efficiently solved by commercial solvers. Finally, the IEEE 39-bus power system is employed to verify the effectiveness of the proposed model.

Self-tuning Control Method of Active Frequency Support of Clustering Photovoltaic Power Plants

LIU Gang, CHEN Haidong, SUN Ruizhe, PENG Peipei

2022, 55(9): 156-162. DOI: 10.11930/j.issn.1004-9649.202112014

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As existing photovoltaic power plants implement droop control to adjust output and thereby suppress random and irregular output fluctuations on the supply side after detecting frequency changes, a time lag occurs in the frequency modulation process. On the basis of self-tuning control, this paper proposes a control strategy of active frequency support that can smooth second-level output fluctuations of photovoltaic power for photovoltaic power plants. According to the light fluctuation at the disturbed photovoltaic power plant, the reference active power is automatically corrected through feedforward compensation, and the active power setpoint of each photovoltaic power plant is redistributed adaptively. The output fluctuation at the disturbed power plant is thereby actively compensated before the frequency changes significantly. A simulation example is built with Matlab/Simulink. The simulation results show that compared with droop control, the proposed self-tuning control effectively improves the frequency performance of the system by elevating the lowest frequency point by about 0.04 Hz under disturbances and reducing the average frequency change rate by about 26.06%.

Influence of Static Var Generator on High Frequency Oscillation of Doubly-Fed Wind Farm

WU Linlin, CHENG Hao, LIU Jingbo, DU Dongye, GONG Chao, GUO Chunyi

2022, 55(9): 163-173,182. DOI: 10.11930/j.issn.1004-9649.202203109

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The connection of static var generator (SVG) in doubly-fed wind farms can easily cause high frequency oscillation in the system, which seriously threatens the safe and stable operation of wind farms. Therefore, this paper firstly builds a high frequency impedance model including doubly-fed wind turbines, collector lines, and SVG. In addition, in PSCAD/EMTDC, a doubly-fed simulation model considering four wind turbine links, collector lines, and SVG is built. The accuracy of the built high-frequency impedance model of the doubly-fed wind farm is verified by comparing the impedance scan with the theoretical impedance. Furthermore, the high-frequency oscillation of the doubly-fed wind farm is analyzed and the influence of SVG system parameters on the oscillation of the wind farm is explored. The research results show that the SVG delay, inner loop control parameters, and filter inductance are key factors affecting the high-frequency oscillation of SVG. Finally, the correctness of the above theoretical analysis is verified by simulation.

Harmonic Model of Static Var Generator and Analysis of Its Resonance Influence

LIU Ke, WANG Xuan, WANG Yang, WANG Xin, YANG Fangnan, LI Jianwu, LIU Dongping, GUO Cai, ZHANG Qisheng, CHEN Haimeng

2022, 55(9): 174-182. DOI: 10.11930/j.issn.1004-9649.202203061

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Static var generators (SVGs) are widely used in photovoltaic (PV) stations because of their fast response speed and wide regulation range, which can meet such needs of the system as dynamic reactive power compensation. However, the existing research lacks the analysis of the harmonic interaction between SVGs and PV stations and power grids, and it often ignores the impact of SVGs on the harmonic resonance of PV stations. To solve this problem, this paper builds a new SVG model in the form of harmonic coupling impedance on the basis of multi-frequency harmonic response. The model can fully reveal the frequency coupling effect in the system and can be used to quantitatively analyze the influence of SVGs on the harmonic resonance of PV stations. Finally, the time-domain simulations of an actual PV station verify the correctness of the proposed harmonic impedance model and the importance of frequency coupling in harmonic resonance analysis.

Research on Voltage Stability of Grid-Connected Photovoltaic System Based on Double-Side Voltage Feedback Control

XUE Fei, LI Xutao, LI Hongqiang, TIAN Bei

2022, 55(9): 183-191,203. DOI: 10.11930/j.issn.1004-9649.202202014

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In terms of the problem that the grid-connected photovoltaic DC system is unstable during low voltage ride through (LVRT), an improved double-side voltage control strategy is proposed. The voltage feedback control is introduced in the front converter circuits to form a hybrid control including voltage feedback and maximum power point tracking (MPPT). In addition, this paper combines the voltage feedback loop of the grid-connected inverter and comprehensively controls the grid-connected photovoltaic DC system during LVRT. Meanwhile, in order to realize the automatic balance between the voltage control and power control of the front converter, this paper designs adaptive weight coefficients of the voltage feedback loop and MPPT loop based on the actual bus voltage. To verify that the improved control strategy can stabilize the DC system during LVRT, the paper carries out a hardware-in-loop (HIL) test based on the RT-LAB platform. The test result shows that without a Chopper resistor, the double-side voltage feedback control strategy can reduce the variation of DC voltage from 136V to 60.5V during LVRT compared with the traditional control strategy, and the grid-connected impulse power can be decreased from 3 955W to 2 264W, which not only reduces the current stress of converter circuits but also improves the stability of the photovoltaic system during LVRT.

Steady-State Voltage Stability Evaluation of Power System Containing Wind Farm Based on Improved PEM and L Index

WU Yaning, LUO Yi, LEI Cheng, HUANG Yu, LIANG Yu, ZHOU Shengcun, NIE Jinfeng

2022, 55(9): 192-203. DOI: 10.11930/j.issn.1004-9649.202203001

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How to quickly and accurately evaluate the system voltage stability after large-scale wind power integration is of great significance to the safe operation of the power system. This paper proposes a method for evaluating the steady-state voltage stability of power system with wind farms based on the improved point estimate method (PEM) and local voltage stability index (L index). Firstly, an improved PEM is put forward to calculate the order moments and semi-invariants of the L index and obtain its probability distribution by combining the Cornish-Fisher series expansion. Compared with the traditional 2n+1 method, this method can improve the fitting accuracy of the L index distribution without complex calculations such as higher-order moments. Then the risk preference utility function is employed to define and calculate the voltage instability risk of each node for assessing the static voltage stability of the power system with wind farms and identifying the weak nodes of system voltage stability. Finally, on the basis of the risk degree, the wind power grid-connected voltage stability factor is introduced to analyze the influence of wind power grid integration on the steady-state voltage stability of the system. The example results of the IEEE-14 node and IEEE-39 node verify the feasibility and effectiveness of the proposed method.

Research on Coupling Heating under Varying Duty Based on the In-Depth Cascade Utilization of Heat Energy

QIAO Jiafei, LIANG Zhanwei, ZHANG Lei, WANG Shunsen

2022, 55(9): 204-212. DOI: 10.11930/j.issn.1004-9649.202206003

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In order to achieve the goal of energy-saving and carbon reduction for coal-fired units, a coupled heating system based on deep cascade utilization of thermal energy is proposed in this paper. The model is first established for the assessment of power supply and heating energy consumption of cogeneration unit by applying thermal analysis method. Then on the basis of the calculation of energy consumption of the coupled heating system using thermal power integration scheme Software (TPIS), the operating energy consumption of the coupled heating system under varying duty is studied. The results show that the temperature of water supply can be adjusted ranging from 44℃ to 90℃ by virtue of different coupled heating methods under variable parameter operation conditions. The thermal index varies in a different way as the unit load goes up or down. Regardless of different coupled heating methods implemented, the thermal efficiencies all decrease with the load increase at unit one, while they all increase with the load increase at unit three, and the unit thermal efficiencies vary from 63% to 80%. The study results are technically supportive of the variable operation optimization of cogeneration units, energy saving and carbon reduction.

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