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01 June 2017, Volume 38 Issue 6
    

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  • XIE Min, DU Yuxin, CHENG Peijun, HU Xintong, LIU Mingbo
    Electric Power Construction. 2017, 38(6): 1. https://doi.org/103969/j.issn1000-7229201706001
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     This paper proposes the membrane computing method to solve the dynamic economic dispatch problem of power system. For convenient calculation, the multi-constrained dynamic economic dispatch problem is transformed into an unconstrained optimization problem through the quadratic penalty function. As for the three basic elements of the membrane computing method, membrane objects, membrane structure and evolution rules, this method takes the unit generation power during 24 hours as the membrane object, and adopts the cell type nested membrane structure including the parallel basic membranes and the golgi membranes. A set of evolution rules including crossover, mutation, correction and reserve are established in the parallel basic membranes, besides, transition, abstraction and target indication rules are established in the golgi membranes after its activated. Thus the objects in the membranes are constantly evolved and picked over, and the dynamic economic dispatch problem can be optimized and solved. The simulation results on IEEE 39 and IEEE 118-bus test system show that the proposed membrane computing method can effectively solve the optimization problem of the dynamic economic dispatch of power system, which can obtain a better optimal solution and has a more stable results compared with the genetic algorithm and particle swarm algorithm. This proposed membrane computing method has a good application prospect.
     
  • LI Ran, ZHANG Fan, JIN Baoyuan
    Electric Power Construction. 2017, 38(6): 7. https://doi.org/103969/j.issn1000-7229201706002
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     Inspired by the exploratory behavior of navigators in Age Discovery in fifteenth and sixteenth centuries, this paper proposes a novel meta-heuristic intelligent algorithm, called navigator optimization algorithm (NOA) to solve the optimal power flow problem for power system. The concept of “search cycle” is put forward in the new algorithm to balance the degree of “search” and “exploitation” in iterative process and can achieve better optimization performance. The proposed algorithm is applied to the optimal power flow calculation of IEEE 30-bus and IEEE 118-bus system and the superiority of NOA is verified by comparing the simulation results with some other intelligent algorithms. The new algorithm will have a certain reference value for the planning and operation of real power system.
     
  • ZHENG Yu, DONG Zhaoyang, ZHAO Junhua, LI Zhengjia, PAN Zhenning
    Electric Power Construction. 2017, 38(6): 15. https://doi.org/DOI: 103969/j.issn1000-7229201706003
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    ABSTRACT:  According to the optimization problem of electric vehicle (EV) charge/discharge under the situation of a system with several charge station or electric vehicle (EV) distributed energy management system (EV-DEMS), this paper takes the charge station and EV-DEMS as charge/discharge agents and proposes a distributed real-time schedule strategy to coordinate the charge/discharge of each agent with considering several charge/discharge agents. Under the premise of satisfying the charging demand of the owner, the model aims at minimizing the fluctuation of the daily load curve to achieve peak shaving and valley filling at the grid side. The simulation case shows that the distributed optimization model and algorithm can well coordinate and optimize the charging and discharging plan of each agent compared with traditional centralized optimization method, and can greatly increase the computation speed when the optimization result is guaranteed.
     
  • ZHENG Yu, ZHAO Junhua, MENG Ke, LI Zhengjia, QU Kaiping
    Electric Power Construction. 2017, 38(6): 21. https://doi.org/103969/j.issn1000-7229201706004
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     ABSTRACT:  To solve the global warming and improve economic and environmental benefits of power grid, this paper introduces the carbon trading mechanism to establish a power system optimal dispatching model with multiple distributed energy, which puts the sum of energy consumption cost and carbon transaction cost as the objective function. According to the correlation and randomness of distributed energy resources access and load fluctuation, this paper uses the multi-point estimation method based on Nataf transform to change the uncertain model into deterministic model. The effectiveness of the proposed model and method is verified by the simulation analysis of IEEE 57 power system and the comparison with Monte Carlo method. Finally, on the basis of the analysis, this paper analyzes the influence of the number of points on the algorithm and the influence of the carbon trading price on the system operation.
     
  • SHI Jiaqi,ZHANG Jianhua
    Electric Power Construction. 2017, 38(6): 28. https://doi.org/103969/j.issn1000-7229201706005
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     ABSTRACT:  Accurate ultra short-term power forecasting of photovoltaic (PV) generation is very important for dispatching of power grid and the optimal operation of PV system. The progress of machine learning and artificial intelligence technology provides an effective way for refined analysis of PV power prediction factors and the improvement of forecasting accuracy. This paper proposes an ultra short-term power forecasting method for PV based on the deep structure network model. Firstly, according to the mechanism characteristics of PV generation system, we analyzed the feasibility of deep learning algorithm to deal with the PV power forecasting problem. And then, we presented PV power forecasting mode based on deep learning algorithm which learns the structure internal characteristics by deep belief network based on restricted boltzmann machine to extract deep features as unsupervised learning process, and used the supervised BP neural network as conventional fitting layer to obtain the forecasting results. In addition, based on the actual demand we established a two-stage PV power generation forecasting system including off-line training and on-line prediction, to analyze the input properties of the weather information and historical information. At last, we verified the validity and accuracy of the algorithm through the actual operating data of PV system, and explained its importance in forecasting through comparing whether the depth structure contained unsupervised learning process.
     
  • YIN Hao, DONG Zhen, MA Liuyang
    Electric Power Construction. 2017, 38(6): 36. https://doi.org/103969/j.issn1000-7229201706006
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    ABSTRACT:   Aiming at the problem that wind speed time series are always nonlinear so that it is difficult to predict accurately, this paper proposes a combined model based on variational mode decomposition (VMD) and extreme learning machine (ELM) optimized by dynamic NW small world crisscross optimization (NWCSO) for short-term wind speed prediction. We used a novel VMD technique to decompose the original wind speed time series into a series of mode components with different bandwidth to reduce its non-linearity. Then, we  established the extreme learning machine for predicting all components, and adopted the NWCSO to optimize the input weights and the bias of hidden nodes of ELM in order to obtain the best prediction effect. The results have demonstrated that the proposed model based on VMD has higher prediction accuracy than other conventional decomposition methods.
     
  • LING Kaiyuan, GUAN Zhijian, WU Han, YUAN Yue, FAN Xuanran
    Electric Power Construction. 2017, 38(6): 44. https://doi.org/103969/j.issn1000-7229201706007
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     ABSTRACT:  This paper proposes a day-ahead dispatch strategy for active distribution network with movable storage considering voltage control, responding to the voltage violation caused by large amount of distributed generation connection to active distribution network, as well as the big investment of energy storage and the difficulty of electric vehicles dispatching. We establish a bi-level optimal model with taking distribution network and movable storage as different benefit subjects. The upper layer is distribution network layer with the goal of the minimum line loss, instructing the lower layer according to the predicted voltage violation degree. The lower layer is movable storage operation layer which optimizes the charge/discharge power of movable storage with the goal of the maximum revenue, responds to the instructions of upper layer and return the results to upper layer to determine the access node of movable storage. In lower layer, we consider the effect of state of charge of movable storage on its maximum power available; set the charging node and discharge node in distribution network nodes to decrease the effect of movable storage on the line loss of distribution network, and then present a strategy of access node choice and change for movable storage. The simulation results of IEEE 33-nodes system show that the proposed strategy can solve the voltage violation, reduce line loss and could make movable storage profitable.
     
  • YIN Zhongdong, WANG Pei
    Electric Power Construction. 2017, 38(6): 52. https://doi.org/103969/j.issn1000-7229201706008
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     ABSTRACT:   DC power supply mode is used for high power fast charging of electric vehicles, the voltage ripple generated by the former rectifier causes overvoltage and overcurrent in the battery, which can reduce the battery life and the operation stability of the rear level DC-DC chopper, and affect the quality of charging. Hence it is vitally important to restrict voltage ripple generated by rectifier below the level set. Taking nonlinear and strongly coupled three-phase bridge PWM rectifier as the research subject, this paper introduces the active disturbance rejection control technique into rectifier control. Under two-phase synchronous rotation d-q coordinate system, we establish the system model, and adopt voltage current double closed loop control. On the basis of the mathematical relation between DC-side output voltage and d-axis current, we use active disturbance rejection controller in voltage outer-loop control. The simulation results in PSCAD show that, compared with the traditional PI controllers, active disturbance rejection controller can track output instructions with high-speed and accuracy, reduce the voltage ripple, improve the dynamic characteristics of system and have good anti-load-disturbance performance.
     
  • JIANG Shigong, WU Zhili, LI Hongjun, WANG Yunfei, ZHENG Hao
    Electric Power Construction. 2017, 38(6): 59. https://doi.org/103969/j.issn1000-7229201706009
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     ABSTRACT:  Compared with AC distribution system, the DC distribution technology has obvious advantages on reliability, power supply capacity, power supply distance and economy. Firstly, this paper analyzes the voltage grade of DC distribution network and its research status from aspects of all kinds of distributed power supply, typical DC load, DC microgrid system and related voltage standards at home and abroad, etc. Through analyzing the main influence factors on the voltage grade of DC distribution network, this paper proposes the constraint conditions and the DC voltage grade based on the marching principle of the transmission capacity of AC/DC distribution system. According to the proposed constraint conditions, the verification analysis on transmission capacity, transmission distance and the applicability of DC distribution equipment shows that the proposed voltage grade is effective. To simplify the planning and design, this paper calculates the DC load distance of each typical conductor section when the proposed voltage grade of DC distribution network meets the 10% voltage deviation on power line terminal.
     
  • ZHANG Aiping,LU Zhengang,SONG Jieying,LIU Haijun,LI Weiguo
    Electric Power Construction. 2017, 38(6): 66. https://doi.org/103969/j.issn1000-7229201706010
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     ABSTRACT:  This paper proposes a power electronic transformer (PET) topological structure which can be applied to AC/DC hybrid distribution network according to the demands of the network. Compared with traditional PET, the advantage of new PET is that it can provide interfaces for DC sources and DC loads and has the DC fault ride-through capability, so it can remarkably reduce the number of the converters in the network and improve the reliability of the power supply. Meanwhile, this paper analyzes the operation mode of new PET in typical AC/DC hybrid distribution network. On this basis, this paper designs the control and modulation strategy of PET. Finally, the rationality of the topology and control strategy is verified by simulation, which highlights the energy regulation function of PET in AC/DC hybrid distribution network. 
     
  • QU Yanxia,MA Qinfeng, SHI Bonian
    Electric Power Construction. 2017, 38(6): 73. https://doi.org/103969/j.issn1000-7229201706011
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     ABSTRACT:   The regional power grid is connected with other large power grid through the AC and VSC-HVDC transmission channels. When AC transmission channel fault leads to the regional power grid isolated, active power control mode of VSC-HVDC limits the ability of large power grid to support regional power grid. According to the fast and reliable characteristics of VSC-HVDC power flow control, this paper designs an isolated frequency fast control scheme of VSC-HVDC interconnected grid based on the combination of offline calculation and online judgment. First of all, through the offline strategy we preliminarily determine the power shortage, and then select coarse or fine tuning actual control measures according to the on-line frequency change rate. The off-line calculation results for coarse tuning make online judge have small computation, less sampling, fast action; the frequency limit controller (FLC) for fine tuning can achieve non differential regulation, supplement the coarse tuning results, improve the reliability and work closely with the regional power grid cut off generator (load). The simulation results show that the proposed frequency fast control scheme of fault island can effectively solve the problem of frequency stability.
     
  • LIU Qing, WANG Hao
    Electric Power Construction. 2017, 38(6): 80. https://doi.org/103969/j.issn1000-7229201706012
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     ABSTRACT:   Voltage stability can be ensured by fast var control of STATCOM, whereas uncoordinated control will contribute to negative interactions. Modal analysis and relative gain array (RGA) are combined to analyze the negative interactions, and exact linearization via feedback is employed to modify the inner current control. The state-space model of the system with multiple STATCOMs is constructed and modal analysis adopted to determine the control parameters which leads to negative damped oscillation mode. RGA is deduced by the matrices form state equations and the relationship between interactions and input signal as well as electrical distance is presented. The results show that new local oscillation mode could exist with uncoordinated proportional gain parameters of STATCOM controller, which may result in low frequency power oscillations. Besides, voltage references and electric coupling are also the significant factors of negative interactions. Acccording to traditional inner current control, nonlinear control theory is employed to modify the control system. With input-state linearization via feedback a modified controller is designed. The state feedback matrix is determined by the linear quadratic control theory to deduce the optimal control strategy, which can achieve the optimal approximation of a controlled state to a desired state. The simulation results show that the nonlinear controller can effectively improved power fluctuation caused by the step of reference signal and significantly increases system damping.
     
  • HE Jifeng, DU Zhi, HUANG Jiaqi, FANG Rengcun, ZHOU Yujie, LIU Yuan, YANG Jun
    Electric Power Construction. 2017, 38(6): 92. https://doi.org/103969/j.issn1000-7229201706013
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     HE Jifeng1, DU Zhi1, HUANG Jiaqi1, FANG Rengcun1, ZHOU Yujie1, LIU Yuan2, YANG Jun2
     
  • YAN Yu, ZHOU Qinyong, HE Hailei, LIANG Caihao
    Electric Power Construction. 2017, 38(6): 100. https://doi.org/103969/j.issn1000-7229201706014
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     ABSTRACT:   In order to solve the defect of tradition edge betweenness which takes the shortest path as the only path of power flow, this paper proposes the weighted maximum edge betweenness. This index considers both the influences of network topology and current operation mode on subarea division, which makes the subarea division is more suitable for real power network. Then, this paper proposes the ending criterion of subarea division to effectively utilize the key branches, which reduces the computation amount and prevents the isolated nodes from being a single zone. Finally, this paper obtains the transmission sections by searching the cut sets of network based on the subarea division. A case study of practical system verifies the feasibility of this method in key section search. Compared with the existing section search methods, the proposed method can get more fragile sections and neither depends on the selection of overload branches, nor requires the calculation of all cut sets, which can be better applied to the actual power grid.
     
  • WEI Mengyang, LIU Liming, LI Yaohua, WANG Yong, WANG Fei
    Electric Power Construction. 2017, 38(6): 108. https://doi.org/103969/j.issn1000-7229201706015
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     ABSTRACT:  The prediction accuracy of wind farm output is closely related to its output pattern (OP). However, it is unfair to evaluate wind farms with different OPs using unified evaluation criteria. This paper aims to investigate the relationship between different OPs and corresponding prediction errors, and provide a method to realize the reasonable evaluation. Firstly, three indexes, daily sample entropy (SE), proportion of days above SE threshold and monthly SE are extracted. On these basis, a density-based clustering algorithm is used to cluster different wind farms. Then, in order to illustrate the difference between various OPs on predictability, three methods are used to conduct prediction for these typical patterns including persistence method, single exponent smooth algorithm and  radical basis function (RBF) neural network method. A simulation is conducted to validate the effectiveness of the proposed method using actual wind power data of Yunnan wind farms. The result shows that the three features can effectively characterize the predictability of different OPs in different time scales. Finally, specific application of this study on wind power prediction evaluation is given.
     
  • WANG Yue,LYU Lin, LI Xingyu, NING Shichao, LIAO Qiuping
    Electric Power Construction. 2017, 38(6): 116. https://doi.org/103969/j.issn1000-7229201706016
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     ABSTRACT: In order to configure the appropriate micro grid energy storage capacity to stabilize the fluctuation of active power in network, this paper proposes a hybrid energy storage system capacity allocation model based on extreme-point symmetric mode decomposition (ESMD). Based on the net load power of the micro grid, the ESMD method is used to decompose the adaptive global moving average as the exchanging power between micro grid and power grid, and the low frequency and high frequency components are absorbed by the battery and the super capacitor. So as to make the optimal decomposition of each component, we analyze the influence of the residual pole number on the global moving average, and study the selection principle of the critical mode to obtain the appropriate low frequency and high frequency components. On this basis, with considering the operational life of storage equipment, we establish a cost model of micro grid hybrid energy storage system including annual investment cost and annual operating cost. The feasibility and economy of the model are verified by a simulation example.
     
  • FU Yang,MA Yuan,LIU Lujie,TANG Zhengqi,TU Niehua
    Electric Power Construction. 2017, 38(6): 124. https://doi.org/103969/j.issn1000-7229201706017
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     ABSTRACT:  Aiming at the problem of high maintenance cost caused by poor marine environment, combined with bathtub curve, this paper proposes a phasic preventive maintenance strategy for offshore wind turbines. Firstly, we introduce the capacity factorto revise the downtime loss per unit time of offshore wind turbines. Secondly, the wind turbine is regarded as a multi-component system, and the reliability of components and unit is updated according to the maintenance activity. Under the influence of preventive maintenance cost and reliability improvement, we construct the return on investment (ROI), and adopt the standard deviation method to determine the maintenance method of each component. Then, we take the maintenance cost per unit time as the goal, the component reliability as the constraint, and adopt opposition based learning-particle swarm optimization (OBL-PSO) algorithm to obtain the optimal maintenance interval and the number of preventive maintenance times in the whole life cycle. Finally,the simulation results of an offshore wind turbine caseshow that the proposed phasic preventive maintenancestrategy reduces the number of maintenance times and saves maintenance costs compared with the traditional preventive maintenance strategy, which can provide reference for the development of offshore wind turbine maintenance strategy.
     
  • LI Hui,WANG Dan,LI Gengyin,LIU Chongru,ZHANG Ning
    Electric Power Construction. 2017, 38(6): 133. https://doi.org/103969/j.issn1000-7229201706018
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     ABSTRACT: According to the nonlinear and strong coupling characters of the grid-side converter model of direct-driven permanent magnet synchronous generator (PMSG) based wind power generation system, this paper proposes a compound control strategy which combines the non-smooth control and back-stepping control. Based on the nonlinear mathematical model of the grid-side converter in dq synchronous rotating coordinate system, the grid-side outer-loop of DC voltage control strategy is designed by using non-smooth control principle and the inner-loop of current control scheme is designed by using back-stepping control method. In the aspect of outer-loop control, the DC voltage controller is designed by combining the finite-time feedback control method of non-smooth principle and the system disturbance estimation effect of extended state observer (ESO). The back-stepping control approach with additional disturbance compensation is applied in the inner-loop current control. By adopting ESO to estimate the uncertainties of system inner-loop caused by external disturbances, the back-stepping iterative control law is designed with the introduction of the estimated uncertainties for compensation. The appropriate Lyapunov function is established to obtain the principle of the inner-loop back-stepping current control, which makes the inner-loop system meet the Lyapunov asymptotic stability condition. The simulation results show that, compared with the conventional PI linear control strategy, the presented compound control strategy can effectively improve the grid-integration dynamic response performance of PMSG-based wind power generation system under the grid disturbance conditions.
     
  • DU Qingting, LIU Jichun, WANG Dong, YANG Chang
    Electric Power Construction. 2017, 38(6): 142. https://doi.org/103969/j.issn1000-7229201706019
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     ABSTRACT:  In  the  environment of power sale market  opening, in order to obtain the most social benefit and combine the market bidding behavior of power sale company with the management of kinds of inner flexible loads organically, this paper proposes a two-stage optimization model, the first stage of which is that power sale company participates in market bidding, the second stage of which is that power sale company manages kinds of inner flexible loads based on the first stage. In order to obtain the most social benefit, and get the minimum flexible load compensation fees, power sale company optimally managed the objective function, which included the interrupt cost, transfer cost and incentive cost of the internal electricity customers flexible loads. The practical example, which was verified by using genetic algorithm (GA) on standard IEEE 14 bus networks, shows that the model has improved the overall benefit of society effectively. 
     
  • LIN Yicheng,MENG Anbo
    Electric Power Construction. 2017, 38(6): 149. https://doi.org/103969/j.issn1000-7229201706020
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     ABSTRACT:   In order to solve the economic and environmental emission dispatch problem of complex combined heat and power, this paper proposes an improved multi-objective gray wolf optimization algorithm. The standard grey wolf algorithm is only suitable for dealing with single objective optimization problems. However, the improved grey wolf algorithm is also suitable for the multi-objective optimization, which improves the global search ability of the algorithm by modifying the direction of the wolves. Secondly, with the combination of fast and elitist non-dominated sorting, crowded distance calculation, etc., in the update wolves position, the algorithm uses ‘elite retention strategy’ to eliminate vulnerable wolves individual, further improves the convergence rate of the algorithm, and obtains the optimal solution by fuzzy decision theory. Finally, the simulation of a typical 7-unit combined heat and power system shows that the proposed method not only can effectively consider the optimal compromise between the economic and environmental protection of the cogeneration plan, but also overcome the defects of the standard gray wolf algorithm, and has obvious advantages in solving the quality and convergence compared with other swarm intelligence algorithms.