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Table of Content

    28 April 2023, Volume 57 Issue 4 Previous Issue    Next Issue
    New Type Power System and the Integrated Energy
    Overview of Protection Principle of Power Grid in Integrated Energy System
    CHU Xu, BAO Zehong
    2023, 57 (4):  379-392.  doi: 10.16183/j.cnki.jsjtu.2021.492
    Abstract ( 484 )   HTML ( 1132 )   PDF (2110KB) ( 335 )   Save

    Integrated energy system (IES) has become the research hotspot of the energy system due to the characteristics of multi-energy joint coordination and energy efficiency. Because of the complex structure, control, and fault characteristics of IES, it is difficult for traditional protection principles and schemes to adapt to system requirements. This paper first analyzes the structural characteristics and control characteristics of IES, and studies the fault characteristics of the core power part based on its characteristics. Then, based on the fault characteristics used in the existing protection principles, it classifies and analyzes domestic and foreign research, improvement status, and protection applicability. Finally, it discusses and prospects the research and development direction of IES line protection principles and schemes.

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    Interaction Mechanism for Multiple Active Power Filters in DC Distribution Networks
    WANG Hao, HUANG Wentao, TAI Nengling, YU Moduo, SUN Guoliang
    2023, 57 (4):  393-402.  doi: 10.16183/j.cnki.jsjtu.2021.423
    Abstract ( 362 )   HTML ( 1191 )   PDF (5261KB) ( 278 )   Save

    DC distribution network is the main development direction of the power distribution system. Due to the influence of electronic equipment and other factors, the system is very easy to produce second harmonics, which seriously affects the stability of the system and the safety of electrical equipment. Multi-filter collaborative filtering in DC distribution network has become one of the methods to control the second harmonic. However, due to the coupling interference between the filters, the filtering effect is affected by multiple factors. This paper establishes a Norton equivalent grid-connected model of multiple filters and proposes a method for analyzing the interaction mechanism of multiple filters based on the relative gain matrix theory. This method establishes the matrix relationship between the change in the output current of the filter and the change in the harmonic source current and analyzes the influence of the grid parameters and controller parameters in the multi-filter grid-connected system on the filtering effect of the filter, and proposes a reasonable parameter selection method. Finally, this paper establishes a DC distribution network model with multiple DC filters in PSCAD/EMTDC, and simulates the parameters affecting the filtering effect and verifies the rationality of the analysis in the scenario of multiple harmonic sources. In addition, it builds a semi-physical simulation model in RT-LAB to further verify the effectiveness of the method.

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    Online Estimation of Power Shortage in Power Systems Driven by Local Frequency Measurement Data
    TANG Zhen, HAO Lihua, FENG Jing
    2023, 57 (4):  403-411.  doi: 10.16183/j.cnki.jsjtu.2021.401
    Abstract ( 425 )   HTML ( 1108 )   PDF (2128KB) ( 193 )   Save

    With the growing penetration of renewable generation, the inertia and frequency support ability of the renewable-dominated power system are continuously reduced, which leads to frequency collapse when the system is disturbed. Therefore, it is of great significance to promptly and accurately evaluate the power shortage after a major disturbance to fill the power shortage quickly. This paper proposes an online estimation approach of power shortage in power system based on deep convolution and long-short term memory composite neural network driven by local frequency measurement data. First, since using the synchronous measurements to obtain the frequency of center of inertia (COI) cannot adapt to the rapidity of online estimation, this paper employs the local frequency measurements to estimate the COI frequency, avoiding the delay effect caused by the complex communication. Then, it designs a deep composite neural network to mine the correlation information between massive frequency data and power shortage. Finally, it tests the simulations on a 39-bus system to verify the effectiveness of the proposed approach. The results demonstrate that the proposed approach is effective and fast.

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    Dynamic Discrete Equivalent Model of Photovoltaic Power Generation System
    LIU Kezhen, CHEN Xueou, CHEN Leidan, LIN Zheng, SHEN Fu
    2023, 57 (4):  412-421.  doi: 10.16183/j.cnki.jsjtu.2021.505
    Abstract ( 469 )   HTML ( 285 )   PDF (6678KB) ( 435 )   Save

    The proportion of renewable energy in the new power system is further increased, and the grid connected capacity of photovoltaic units has a trend of obvious improvement. The dynamic behavior of the photovoltaic (PV) power generation system at different permeabilities has a significant impact on the load characteristics of the power grid. However, the complex dynamic model of photovoltaic power generation grid connection and the large number of parameters to be identified increase the difficulty of practical application of the model. Therefore, a dynamic discrete equivalent model of the PV power generation model based on the physical model of the PV power generation model is established, and the parameters of the dynamic discrete equivalent model for the PV power generation model are obtained. The IEEE 14-bus system, which is subject to various PV permeabilities, is adopted to verify the superb dynamic characteristics of the proposed discrete equivalent model for the PV power generation in power system simulations. The pertinent simulation results show that the dynamic discrete equivalent model of the PV power generation system can accurately describe the dynamic characteristics of the PV power generation system with a high accuracy and an easy identification performance.

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    Multi-Objective Planning of Power-Gas Integrated Energy System Considering Economy and Carbon Emission
    ZHU Hainan, WANG Juanjuan, CHEN Bingbing, ZHANG Houwang, CHEN Jian, WU Qiuwei
    2023, 57 (4):  422-431.  doi: 10.16183/j.cnki.jsjtu.2021.513
    Abstract ( 506 )   HTML ( 38 )   PDF (1667KB) ( 289 )   Save

    In order to accelerate the rapid and economic low-carbon transformation of the power-gas system, a multi-objective stochastic optimization programming model for the whole equipment of the power-gas system was established, which comprehensively considered the economic cost and carbon emissions. First, the mathematical model of the electric-gas network and related equipment was established, and the uncertainty characteristics of the electric and gas loads and photovoltaic output were analyzed by using the scenario method. Next, a mixed-integer quadratically constrained programming (MIQCP) model considering the economic cost and carbon emissions of the system was established. An overall planning was made for power feeders, gas network pipelines, substations, gas distribution stations, gas units, power-to-gas devices, photovoltaic, and energy storage devices. Finally, a numerical example was built to verify the feasibility and effectiveness of the model. The results show that the model can fully consider the coupling relationship between power-gas network lines and a variety of comprehensive energy equipment under different weight choices of objective function, and obtain the overall optimal planning scheme.

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    Power System Planning Considering Demand Response Resources and Capacity Value of Energy Storage
    HUANG Yuanming, ZHANG Yuxin, XIA Zanyang, WANG Haohao, WU Mingxing, WANG Ning, CHEN Qing, ZHU Tao, CHEN Xinyu
    2023, 57 (4):  432-441.  doi: 10.16183/j.cnki.jsjtu.2021.477
    Abstract ( 492 )   HTML ( 37 )   PDF (2827KB) ( 391 )   Save

    The access of a high proportion of renewable energy has posed new challenges to the supply reliability of the power system. The system must have sufficient capacity credit to cope with the output fluctuation and randomness of renewable energy. Due to the nonlinear relationship between energy storage capacity credit and power planning results, it is difficult to establish accurate capacity adequacy constraints for traditional power planning methods. Therefore, a generation expansion model is established, in which thermal power, renewable energy, energy storage, and demand response resources are incorporated, with the full-year hourly production simulation to ensure adequate operation flexibility and improved capacity adequacy constraint to incorporate the capacity value of energy storage and demand response resources. An iterative algorithm is designed to solve the nonlinear problem of energy storage capacity credit, and the validity of the model is verified by some regional grid in China. The results show that in the high-proportion renewable energy system, the system capacity is surplus, and the main factor affecting the system cost is the flexibility constraint. The introduction of a small amount of demand response resources can greatly reduce the system cost, which provides new ideas for power system planning at a high proportion of renewable energy.

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    Economic Dispatch Method of Distribution Network Considering Carbon Emission Index
    CHEN Yuting, ZHAO Yi, WU Junda, SUN Wenyao, XIA Shiwei
    2023, 57 (4):  442-451.  doi: 10.16183/j.cnki.jsjtu.2021.482
    Abstract ( 491 )   HTML ( 41 )   PDF (1253KB) ( 261 )   Save

    Under the vision of carbon neutrality, carbon dioxide emission allowance targets are gradually decreasing, and clean power sources will penetrate in an ultra-high proportion. The traditional distribution grid dispatching model needs to solve the problems of carbon emission compliance and strong intermittent leveling of clean power sources. Based on the analysis of the coupling relationship between carbon emission index and the economic cost of electric power, this paper proposes a novel dispatching model for the future state distribution grid with carbon and electric power couping, proposes an optimal dispatching strategy for distribution grid based on the second-order cone planning model for several scenarios of increasing carbon emission cost of system operaion, and verifies the effectiveness of the proposed method in the improved IEEE 33-node system. The example results show that the output and power generation cost of each distribution network change after considering the carbon emission index.

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    Price-Based Demand Response Mechanism of Prosumer Groups Considering Real-Time Carbon Emission Reduction
    ZHU Yueyao, QI Tong, WU Xingchen, LIU Di, HUA Haochen
    2023, 57 (4):  452-463.  doi: 10.16183/j.cnki.jsjtu.2022.062
    Abstract ( 303 )   HTML ( 270 )   PDF (2251KB) ( 157 )   Save

    With the continuous development of electricity market, electricity price mechanism has been continuously improved, but carbon emission factor has not been considered in the formulation of electricity price mechanism, and research on the demand side coupling of electricity price and carbon emission cost is still limited. Aiming at promoting carbon emission reduction, this paper fully considers the characteristics of prosumer differentiation in the process of load regulation and optimization of producers and consumers, and proposes a price demand response mechanism considering carbon emission and the edge cloud collaborative optimization strategy. By utilizing the proposed carbon electricity discount factor on the premise of fairness, prosumers who actively participate in the regulation of carbon emission reduction can obtain more electricity price discounts. The simulation results show that based on the proposed demand response mechanism with carbon electricity discount factor, the efficiency of electricity retailers can be increased by 2.4 and 0.9 times respectively when photovoltaic power generation is more or less than demand.

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    Analysis of Market Coupling Mechanism Between Distributed Photovoltaic Penetration and Electricity Market Under Background of Carbon Neutrality
    ZHANG Han, HAN Dong, LIU Tan, HUANG Yan
    2023, 57 (4):  464-472.  doi: 10.16183/j.cnki.jsjtu.2021.514
    Abstract ( 396 )   HTML ( 45 )   PDF (1872KB) ( 450 )   Save

    In order to evaluate the possibility of the ‘death spiral’ operation dilemma faced by the retailers with the high level penetration of distributed photovoltaic (PV) under the background of carbon neutrality, and to analyze the key factors that may lead to the ‘death spiral’, the system dynamics approach is applied for modeling. First, the model of customer-side distributed PV penetration guided by market conditions such as sales tariff is established. Then, a model of surplus of retailers is established based on the negative feedback relationship between distributed PV penetration level and the surplus of retailers. The case study evaluates the sensitivity effects of factors such as the generation of distributed PV and wholesale electricity prices on the surplus of retailers. The results show that the surplus of retailers tends to decrease slowly in the mid-long term. An extreme scenario may cause the ‘death spiral’ of retailers in which multiple factors such as transmission and distribution volumes, wholesale tariffs, and maintenance costs change significantly at the same time.

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    Design and Preparation Method of Capacitive Lithium-Titanate Battery
    WU Yuhang, LI Canbing, LI Xinxi, GU Huijun, GU Shanhua, ZHENG Xiaogeng
    2023, 57 (4):  473-481.  doi: 10.16183/j.cnki.jsjtu.2021.509
    Abstract ( 597 )   HTML ( 44 )   PDF (4934KB) ( 307 )   Save

    In order to solve the problem of battery bulging and capacity fading, this paper proposes an innovative battery capacitor structure and the related preparation process. This method integrates the physical energy storage method of the capacitor and the chemical energy storage method of the energy storage battery. In the preparation process, a novel technology of columnar lithium-ion battery soaking is adopted, which improves the soaking efficiency and reduces the internal moisture of the battery. The related performance tests show that the capacity retention rate of the new lithium-titanate battery can reach 92.5% after 9 548 cycles, and the battery capacity can be maintained above 75% at a low temperature. The proposed method provides an effective means for improving the performance of the lithium-titanate battery.

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    Extreme Learning Machine and Its Application in Parameter Identification of Proton Exchange Membrane Fuel Cell
    YANG Bo, ZENG Chunyuan, CHEN Yijun, SHU Hongchun, CAO Pulin
    2023, 57 (4):  482-494.  doi: 10.16183/j.cnki.jsjtu.2021.453
    Abstract ( 339 )   HTML ( 27 )   PDF (4860KB) ( 525 )   Save

    In order to develop an accurate model of proton exchange membrane fuel cell (PEMFC), it is essential to exactly identify unknown parameters in PEMFC. However, parameter identification of PEMFC is a multi-variable, multi-peak, and strongly coupled nonlinear optimization problem, of which traditional parameter identification methods often fail to achieve satisfactory results. In addition, noises generated under different operation conditions will hinder meta-heuristic algorithms (MhAs) to obtain accurate parameters. To handle these thorny obstacles, extreme learning machine based MhAs (ELM-MhAs) are proposed for PEMFC parameter identification, which can achieve denoising through ELM. ELM is used to train data to reduce or eliminate noises and provide more accurate and reliable fitness functions for MhAs, thus ensuring the accurate identification of PEMFC parameters by MhAs. To verify the feasibility and effectiveness of this strategy, 25 groups of voltage-current data are processed without denoising, with Bayesian regularization neural network (BRNN) denoising or with ELM denoising under two conditions—low temperature and low relative humidity; high temperature and high relative humidity, respectively. Subsequently, parameter identification results of six MhAs and a Levenberg-Marquardt backpropagation of different data are thoroughly compared. The simulation results indicate that ELM can significantly reduce the impact of noise on the data, while effectively improving the parameter identification accuracy of MhAs, compared with no denoising and BRNN denoising.

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    Energy-Saving Control of Central Air-Conditioning System Based on an Improved-SSA
    XIONG Lei, MIAO Yurun, FAN Xinzhou, YAO Ye
    2023, 57 (4):  495-504.  doi: 10.16183/j.cnki.jsjtu.2022.018
    Abstract ( 490 )   HTML ( 41 )   PDF (1517KB) ( 400 )   Save

    There are many terminals in the central air-conditioning system of which load demands vary frequently. Although conventional proportional integral derivative control or fixed parameter control can meet the load demand, there is a problem of energy waste caused by excess cooling. This paper proposes a central air-conditioning system energy-saving control method based on an improved sparrow search algorithm (ISSA) for the air-water system in the central air-conditioning system. The ISSA applies t-distribution to strengthening the search ability and enables the individual to learn from the best group based on the roulette wheel selection, which enhances the ability of the algorithm to jump out of the local optimum and improves the accuracy and stability of control parameters effectively. For the 12 test functions, most of the optimization accuracy and stability have been improved by more than 2 orders of magnitude. Compared with the original control strategy, the ISSA has shown a good energy-saving potential for energy optimization of air conditioning subsystems, reducing energy consumption by 25.13%. The feasibility of the ISSA in actual engineering problems has also been verified.

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