01 July 2020, Volume 41 Issue 7

    

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  User-Side Data Application Framework Based on Cloud-Edge-User Collaboration in Power Internet of Things

  YUAN Lüzerui, GU Jie,JIN Zhijian

  Electric Power Construction. 2020, 41(7): 1-8. https://doi.org/10.12204/j.issn.1000-7229.2020.07.001

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  Power Internet of Things, which is formed by the application of Internet of Things technology to power system, undertakes the massive data streams of power system. It can promote to realize power data business through power business data and power network informationization. Nowadays, massive and fine-grained user-side data cannot be effectively applied because of the centralized data storage and processing methods based on cloud computing in power grid. In order to break the interaction barrier between the user end and the power system due to the limited computing resources, this paper proposes a user-side data application framework based on cloud-edge-user collaboration. Taking three kinds of user-side essential data applications as examples, i.e., prediction and early warning, classification and clustering, and demand response, the framework is designed according to the complementarity between edge computing and cloud computing. It aims to achieve the collaborative cycle of the bottom-top and top-bottom two-way data flow and business flow, so as to mine the value of user-side data widely and deeply. Finally, this paper analyzes and summarizes the key technologies of the framework from three aspects which are physical layer, platform layer and business layer.
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  Robust Optimal Combined Wind-Storage Scheduling Based on Regulatory Cloud

  JIANG Dajun， WU Fubao， WANG Qiyun， ZHANG Yanjun， SUN Lixia， WU Yingjun

  Electric Power Construction. 2020, 41(7): 9-16. https://doi.org/10.12204/j.issn.1000-7229.2020.07.002

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  Regulatory cloud based on cloud computing has the characteristics of comprehensive information perception， high processing efficiency， convenient and flexible application， which is very consistent with the future power grid characterized by high intelligence. This paper presents a robust scheduling optimization method for combined wind-storage system. Firstly， cluster analysis is made on the annual actual output big data of wind farm by using regulatory cloud. Wind power correction curves are formed on the basis of the typical set of wind power scenarios. Then， a joint robust scheduling method for wind power， energy storage and conventional units is proposed according to the wind power correction curves. Finally， the simulation results of IEEE 39-bus system verify that this method can effectively reduce the scheduling cost and wind curtailment.
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  Identification of Abnormal Operation of Large Power Grids According to Key Operating Indicators and Seq2Seq

  PANG Chuanjun，MOU Jianan，YU Jianming，WU Li

  Electric Power Construction. 2020, 41(7): 17-24. https://doi.org/10.12204/j.issn.1000-7229.2020.07.003

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  Situation awareness based on power grid operation indicators is the trend of future dispatching mode. Identification of anomalies is an important content of situation awareness. A comprehensive indicator system that comprehensively reflects the power grid operation is constructed. An auto-encoder composed of LSTM is used to construct the index abnormality identification model. In the absence of abnormal data on power grid operation indicators， an unsupervised approach is adopted to learn the internal model of the indicators from the historical data of the indicators under normal operating conditions of the power grid. On the basis of model reconstruction error distribution， this paper proposes an abnormal score reflecting the deviation of the index from the normal state. The real-time data of the grid operation indicators are sent to the trained model for reconstruction， and a large abnormal score will be generated when there is an abnormality. The experimental results show that the model can effectively identify the abnormal scores when the grid operation indicators are abnormal. This helps grid dispatchers perceive grid operation risks in a timely manner and take timely control measures to ensure grid security.
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  Equivalent Capacitance Calculation Method Based on Virtual Capacitance Control of DC Microgrid

  MENG Jianhui， ZHANG Yun， FAN Ying， WANG Yi， ZHAO Penghui， SONG Meiqi

  Electric Power Construction. 2020, 41(7): 25-32. https://doi.org/10.12204/j.issn.1000-7229.2020.07.004

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  Compared with AC power grid， DC microgrid not only has simple structure and high efficiency， but also can better absorb distributed new energy such as photovoltaic and wind power generation， while it has almost no inertia. The port converter can simulate the charging and discharging characteristics of capacitors when the virtual capacitor control is applied， which can improve the quality of DC voltage and enhance the stability of DC microgrid. However， the mechanism of inertia enhancement under virtual capacitance control is not clear. The problem that how much capacitance can be produced by virtual capacitor control remains to be further explored. Accordingly， analogous to the variation of load sharing by generators in AC microgrid according to inertia， the power regulation at each side of DC microgrid in the initial stage is allocated according to the proportion of capacitance value. And on this basis， the equivalent capacitance calculation method based on virtual capacitance control is proposed to explore the corresponding relationship between virtual capacitor and equivalent capacitor. Finally， the hardware-in-loop test platform in controller level is established to verify the effectiveness of virtual capacitance control， the correctness of the basis for power regulation allocation in DC microgrid and the corresponding relationship between virtual capacitance and equivalent capacitance.
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  Probabilistic Power Flow Analysis Based on Generalized Cumulant Methods and Maximum Entropy Methods

  SUN Rong，L Zhenhua，LIAO Xingxing，CHEN Bing，WANG Rui，ZHU Chenchen，WEI Zhinong

  Electric Power Construction. 2020, 41(7): 33-41. https://doi.org/10.12204/j.issn.1000-7229.2020.07.005

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  Large-scale new energy access dilutes the inertia of the power grid， which brings greater challenges to the system frequency and voltage security and stability. In order to solve the above problems， this paper proposes a probabilistic power flow analysis method based on generalized cumulant method， which includes frequency. Firstly， a power flow model with frequency is constructed and the probability distribution of new energy output is fitted by Copula model. Secondly， aiming at the uncertainty of the output variables of the power flow model with frequency， a probabilistic power flow calculation method based on cumulant method is proposed， so as to obtain the probability density function of the state variables quantitatively. Due to the large-scale new energy access， the linearization error of the conventional cumulant method increases， and the generalized cumulant method is proposed to overcome this problem. Finally， the maximum entropy method is used to fit the probability distribution curve of state variables， and the accuracy and practicability of the proposed method are verified by an example of a real power grid in a certain area.
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  Microgrid Power Distribution Strategy Based on Improved Control Strategy of Virtual Synchronous Generator

  ZHAO Jinxin， MIAO Hong， ZENG Chengbi

  Electric Power Construction. 2020, 41(7): 42-48. https://doi.org/10.12204/j.issn.1000-7229.2020.07.006

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  In a low-voltage microgrid， the virtual synchronous generator （VSG） strategy is adopted to control the parallel operation of multiple inverters. Due to the difference in line impedance， the accurate allocation of output power according to capacity cannot be realized. In view of this problem， this paper proposes an improved VSG control strategy， in which feedback and integration of voltage of common coupling point are introduced into the reactive voltage control loop to eliminate the influence of line impedance on reactive power distribution. The reactive power feedback is introduced into the virtual impedance loop to adjust the resistance value of the virtual impedance in real time according to the operation of the system. The simulation which results in Matlab/Simulink show that， the improved control strategy can realize the accurate distribution of active and reactive power， also can reduce the amplitude drop of inverter output voltage， and has strong robustness.
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  Control Strategies of Air-Conditioning and Model of Virtual Power Plant for Power Grid Peak Clipping

  LI Hengqiang， WANG Jun， JIANG Xingran， KUANG Zhongqin， XU Shiming,YANG Yongbiao

  Electric Power Construction. 2020, 41(7): 49-57. https://doi.org/10.12204/j.issn.1000-7229.2020.07.007

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  With the economic structure regulation of China， the increasing air-conditioning load has become the main factor that leads to the growing of tertiary industry and residential power consumption， extension of seasonal peak-valley difference， and deterioration of load characteristics. Thus， air-conditioning load can be regarded as one of the demand-side resources for power grid ancillary services， which will improve the power grid load characteristics and promote safer and more economic operation. Firstly， on the basis of the basic air-conditioning load model， this paper constructs the control strategies of central air-conditioning considering its consumption characteristic. Secondly， air-conditioning load virtual power plant （ACVPP） is modeled on the basis of proposed control strategies from the aspects of dispatched index and power output control. Last， the effect of proposed control strategies and ACVPP power output is verified with a simulation.
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  Research on Multi-Objective Bi-Level Optimization of Network-Storage Considering Transient Stability

  FANG Chaoxiong， WU Xiaosheng， JIANG Yuewen

  Electric Power Construction. 2020, 41(7): 58-66. https://doi.org/10.12204/j.issn.1000-7229.2020.07.008

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  With the continuous development of wind power and load demands， new challenges are brought to power grid planning by the issues including transmission congestion， wind curtailment， and operation safety and so on. Due to the fast response， flexible configuration and wide application， energy storage systems play an important role in wind power accommodation， transmission congestion， and system safe operation. In order to improve the transmission capacity and anti-disturbance capability of a power grid， the power transmission capacity， wind curtailment level and transient stability are comprehensively considered at the planning and operation level by involving the transient operation characteristics after faults. A two-layer network-storage joint planning model is established in multi-objective form with the system construction-operation indicator and system stability indicator. The outer-layer model is a multi-objective model considering the locating and sizing of the energy storage systems. The inner-layer model is a transmission network expansion planning model considering the unit commitment problem. In order to improve the solution efficiency， the power flow constraint of the expanded line， the charge and discharge model of the energy storage system and the generation cost curve are linearized. By solving the proposed model using NSGA-Ⅱ algorithm combined with GUROBI and developing the case study in the improved Garver 6-bus system， the validity and rationality of this model are verified in different scenarios.
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  A Robust Expansion Planning Method for Distribution Networks Considering Extreme Scenarios

  HUANG Jiaqi， ZHANG Yuwei， HE Jifeng1， YAN Jiong， ZHU Xu， YANG Jun

  Electric Power Construction. 2020, 41(7): 67-74. https://doi.org/10.12204/j.issn.1000-7229.2020.07.009

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  In recent years， distributed energies represented by photovoltaic and wind power have developed rapidly. However， the uncertainty of their output will bring challenges to the distribution network planning and reliable and stable operation. Under the above background， this paper aims at adapting to the uncertainty of distributed energies and loads， taking the access location， installation quantity and new power lines of distributed power as investment decision content， and proposes a two-stage robust planning method for distribution networks. Firstly， a bi-level programming model of the distribution network is established， and the nonlinear model is transformed into a mixed integer linear model by the big M-approach and the second-order cone relaxation. Secondly， the extreme scenario method is used to deal with random variables， and a two-stage robust planning method for the distribution network is proposed. Then， the column and constraint generation based on the extreme scenario method is used to solve the problem. Finally， a 23-node distribution network example is used to verify the rationality and effectiveness of the proposed model.
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  Research on AC Protection Scheme Under the Background of Power Electronics

  SHEN Hongming， XIAO Zhihong， LIU Ying， GAO Xu， WANG Ziqi， LI Tiechen， DU Na

  Electric Power Construction. 2020, 41(7): 75-81. https://doi.org/10.12204/j.issn.1000-7229.2020.07.010

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  The application of a lot of power electronic equipment has caused a large change in the fault characteristics of the AC system， and the existing protection schemes faces greater challenge. This paper firstly analyzes the waveform characteristics of AC line fault current in different fault scenarios， such as pure AC systems， DC transmission systems and new energy grid-connection， and then a new protection scheme based on identification of transient current spectrum is proposed. At last， the effect of current transformer， sampling frequency and data window length is analyzed. The new protection scheme has many application scenarios， fast operation， and simple implementation. The conclusions are verified by the simulation results of EMTDC / PSCAD and prototype test.
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  Distributed Optimal Dispatch Based on Chance Constrained Goal Programming for Multi-Area Integrated Electricity-Natural Gas Energy Systems

  ZHANG Haoyu， QIU Xiaoyan， ZHOU Shengrui， ZHAO Youlin， LI Linghao，ZHANG Kai

  Electric Power Construction. 2020, 41(7): 82-91. https://doi.org/10.12204/j.issn.1000-7229.2020.07.011

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  The interaction of multiple integrated energy systems through electrical energy can effectively improve the level of wind power consumption in the system. It will become a necessary research work to seek the optimal strategy of multi-regional energy management under the uncertainty of wind power. In view of the random output characteristics of wind power and the safety and reliability of electrical energy transmission between regions， random optimization and hierarchical coordination techniques are combined to establish a distributed optimization model of multiple electricity-gas interconnected integrated energy systems on the basis of chance-constrained goal programming. The model firstly refines the modeling of a single electricity-gas interconnected integrated energy system. From the perspective of system economics， it introduces the opportunity constraint on the flexibility of interregional tie lines. The second-order cone relaxation and deterministic equivalent methods are further used to transform the model into a mixed integer second-order cone programming model. Using the general Benders decomposition （GBD） method， the model is decomposed into main and sub-problems and iteratively solved. Finally， the calculation example shows that the solution method has better convergence characteristics and computational efficiency， effectively guarantees the privacy of user information in different regions and has strong adaptability； and the establishment of the chance constrained goal programming model has a better economy and flexibility than the traditional chance constrained method.
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  Multi-Objective Optimal Dispatch for Integrated Energy System Considering Integrated Demand Response

  WEI Zhenbo， REN Xiaolin， HUANG Yuhan

  Electric Power Construction. 2020, 41(7): 92-99. https://doi.org/10.12204/j.issn.1000-7229.2020.07.012

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  In order to reconcile several dispatch objectives such as the cost of energy consumptions， pollutant emissions and wind power accommodation in the integrated energy system， the multi-objective optimal dispatch model of the integrated energy system considering integrated demand response is established in this paper. Firstly， the modeling of the regional integrated energy system including some devices such as power to gas， energy storage， and combined heat and power units is elaborated， and the modeling of the integrated demand response which consists of load shedding， load shifting， and load substituting is also considered in the system to decrease peak-valley difference. Secondly， the objectives that are respectively to minimize the comprehensive cost， wind power curtailment， and cost of pollutant treatment are established. The proposed multi-objective optimization method， which firstly utilizes multi-objective weighted fuzzy programming to obtain the Pareto front， and then pursue the minimum Euclidean distance between all the Pareto non-inferior solution and the ideal solution， is adopted to solve the optimal dispatch strategy. Finally， on the basis of the typical numerical simulations， the results demonstrate that the proposed multi-objective optimization algorithm can effectively balance the multiple dispatch objectives. The integrated energy system would have more advantages in the gross energy consumptions， environment， and the wind power accommodation after considering the integrated demand response.
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  Pareto-Based Multi-objective Reactive Power Optimization for Power Grid with High-Penetration Wind and Solar Renewable Energies

  YANG Lei，WU Chen，HUANG Wei，GUO Cheng，XIANG Chuan，HE Xin，XING Chao，XI Xinze，ZHOU Xin，YANG Bo，ZHANG Xiaoshun

  Electric Power Construction. 2020, 41(7): 100-109. https://doi.org/10.12204/j.issn.1000-7229.2020.07.013

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  To adapt the trend of high-penetration renewable energies paralleled in power grid， this paper constructs a multi-objective reactive power optimization for power grid with the controlled participation of high-penetration wind and solar renewable energies. Particularly， the reactive power regulation capacities of renewable energies are evaluated according to the wind speed， solar irradiation， and temperature in different time. To obtain the optimal dispatch scheme of transformer taps， shunt capacitor states， voltage outputs of generators， and reactive power outputs of renewable energies， a multi-objective salp swarm algorithm （MSSA） is employed for the multi-objective reactive power optimization. Then an improved ideal-point based decision method is designed to select a compromise solution among multiple non-dominated points， thus three objectives of power loss， voltage deviation， and static voltage stability margin can be properly balanced. Finally， an extended IEEE 9-bus system and an extended IEEE 39-bus system are used to evaluate the performance of the proposed algorithm compared with conventional multi-objective intelligent optimization algorithms. Simulation results demonstrate that the proposed algorithm can obtain a widely spread and well-distributed Pareto front compared with conventional multi-objective optimization algorithms. Moreover， the improved ideal-point based decision method not only can effectively reduce the power loss and voltage deviation， but also can improve the static voltage stability margin.
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  Energy Storage Configuration Scheme Considering the Effect of Static Voltage Stability in Wind Power Systems

  ZHANG Kai， QIU Xiaoyan， LI Linghao， ZHANG Haoyu， ZHAO Youlin， LIU Mengyi

  Electric Power Construction. 2020, 41(7): 110-116. https://doi.org/10.12204/j.issn.1000-7229.2020.07.014

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  As the penetration rate of wind power in the power system gradually increases， large-scale grid-connection may cause poor power quality， instability of the power system， and even voltage collapse. The article proposes an energy storage configuration scheme that takes into account the effects of static voltage stability in a wind power system. It singularly decomposes the Jacobian matrix of the power flow， and calculates the condition number index according to the maximum and minimum singular values under all-day operating conditions. On the basis of the data at the time when the condition number is the maximum， the key nodes and key fans of the system are determined by using the weak node index and the generator participation factor to select the location of the energy storage configuration. This paper establishes an objective function that takes into account the constraints of the condition number to minimize the total active network loss， compares and analyzes the allocation capacity of energy storage in four different scenarios， uses particle swarm algorithm with convergence factor， and verifies with IEEE standard 39-node system. The results show that the energy storage capacity required at the key nodes is the least， and it is the most effective for static voltage stability control.
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  Model and Algorithm of Probabilistic Interval Constrained Power Flow Considering the Correlation Among Wind， Solar and Load

  HUAN Jiajia， HONG Haifeng， SUI Yu， YU Mengze，PAN Xianxian，WANG Chaoqun

  Electric Power Construction. 2020, 41(7): 117-128. https://doi.org/10.12204/j.issn.1000-7229.2020.07.015

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  A probabilistic interval power flow （PIPF） model considering the randomness and correlation of wind-solar-load is proposed， and it is solved by Monte Carlo （MC） method based on affine space transformation. Firstly， on the basis of two cases of whether the historical statistical data of uncertain variables are abundant， probabilistic variables and interval variables are used to describe their random change characteristics. Then， Box-Cox normal transformation and interval transformation are applied to normalize random variables subject to different distributions. Moreover， the sample correlation coefficient is extended to the uncertainty analysis that includes probability and interval random variables， and a correlation coefficient matrix of multivariate random variables is established. On the basis of the matrix， an affine space coordinate system is established by Cholesky decomposition， and the probabilistic and interval variables with correlation are mapped to independent random variables in the affine space. Finally， the interval and probability distribution of the variables to be calculated in PIPF are obtained by MC method. The calculation results of the IEEE 57-node and 118-node systems show that PIPF can quantitatively analyze the influence of uncertainty and correlation on power system， effectively realize the unity of probabilistic power flow and interval power flow， and have certain reference significance for guiding system planning and operation.