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01 July 2017, Volume 38 Issue 7
    

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  • WANG Hongkun, GE Leijiao, LI Hongwei, CHI Fujian
    Electric Power Construction. 2017, 38(7): 1. https://doi.org/10.3969/j.issn.1000-7229.2017.07.001
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     ABSTRACT:   With the rapid development of photovoltaic (PV) industry in recent years, the application of the large-scale distributed PV has become a trend. A large number of distributed PV with strong intermittent access to the distribution network causes many problems to the distribution network, such as power quality, harmonic and so on, which affects the safe and stable operation of power grid. In order to solve those problems effectively, it is necessary to analyze the characteristics of distributed PV and predict the output of distribution PV power generation. Firstly, this paper analyzes the current situation of the development of distributed PV in China and abroad. Secondly, this paper discusses the latest progress in China and abroad on the output characteristics, prediction technology and prediction software of the distributed PV power generation. Finally, this paper discusses the key contents of the future research of the distributed PV,  in order to provide the suggestions for the popularization and application of large-scale distributed PV in China.
     
  • PENG Xiaosheng,FAN Wenhan,WANG Bo,ZHANG Tao,WEN Jinyu,DENG Diyuan,XIONG Lei,CHE Jianfeng
    Electric Power Construction. 2017, 38(7): 10. https://doi.org/10.3969/j.issn.1000-7229.2017.07.002
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     ABSTRACT: Wind power prediction of large scale wind farm clusters will contribute to the scientific and reasonable power generation schedule establishment and enhance the robustness of the power grid. Spatial resources matching algorithm (SRMA) based wind power prediction of regions is with higher prediction accuracy and less computing time than the method of up-scaling approach, which is widely adopted by industrial companies. However, there is only one matching parameter of the SRMA method, which restricts the further improvement of the prediction accuracy. This paper presents an improved SRMA method, which contains the parameter of the historical wind power output, based on the introduction of the SRMA method. Then, this paper predicts the wind power within 0~12 hours with the data derived from one wind farm cluster which contains 52 wind farms. The results show that, the prediction accuracy of the improved SRMA method within 4 hours is higher than that of the traditional SRMA method, and is applicable for industrial application. 
     
  • ZHAO Yu,XIAO Bai,GU Bing,WANG Xiaoyi,ZHANG Yu,WANG Chenglong
    Electric Power Construction. 2017, 38(7): 18. https://doi.org/10.3969/j.issn.1000-7229.2017.07.003
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     ABSTRACT:  The simulation of wind power time series is of great significance in the planning and evaluation of wind power grid-connected systems. In order to solve the problem that the original Markov chain can not keep its autocorrelation in wind power modeling, this paper constructs a wind power time series model based on improved Markov chain. This paper firstly analyzes the seasonal characteristics, daily characteristics and fluctuation characteristics of wind power; and then subdivides the wind power data according to different months and time periods to generate the corresponding state transition probability matrix. Finally, this paper fits the probability distribution of wind power fluctuation and increase the amount of fluctuation to establish the wind power time series model based on improved Markov chain. The case analysis shows that the wind power series generated by the proposed model is superior to the existing model in the aspects of general statistical parameters, probability density distribution and autocorrelation, while preserving the historical sequence autocorrelation.
     
  • SUN Yanping,LI Hong,YANG Wenhai,GAO Yajing
    Electric Power Construction. 2017, 38(7): 25. https://doi.org/10.3969/j.issn.1000-7229.2017.07.004
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     Fully tapping the demand response (DR) of the aggregate object and reasonably aggregating high-quality users with both good DR and low default rates, are effective ways for load aggregator (LA) to guarantee the profits, lower the risk and strengthen the market competitiveness. Firstly, this paper classifies the loads according to the residential users load characteristics and establishes corresponding response model. Secondly, the DR potential vector, which is composed of 24 periods of response potential value of residential users, is regarded as the input vector of the self-organizing map (SOM) neural network algorithm, in order to obtain the classification of response types and levels of residential users. Thirdly, considering the default probability during the response process, this paper establishes an optimized aggregation model for LA users with risk. Finally, an example is given to verify the validity and effectiveness of the model.
     
  • LIANG Junjie, LAN Fei, NONG Zhigui, LI Jinghua
    Electric Power Construction. 2017, 38(7): 34. https://doi.org/10.3969/j.issn.1000-7229.2017.07.005
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     ABSTRACT:   Due to the nonlinear correlation of wind powers, it is of significance to consider the wind power nonlinear in the probability load flow of distribution network, especially in the aspects of security, reliability and economy of the system. In this paper, a method for calculating probability load flow of distribution network is proposed, based on the empirical copula function of wind power. Compared with the traditional methods, such as the methods based on Gauss distribution and t distribution, the samples of wind power generated by proposed method has better performances on approximating the wind power characteristics. The mathematic model of distribution network power flow with wind power is formulated. Also, the treatment methods for the PQ nodes, PV nodes and PQ (U) node are introduced. The forward and backward substitution method is applied in calculating the power flow of distribution network. Finally, the proposed method is applied to the probabilistic load flow calculation of the pure radial distribution network and the weakly meshed distribution network, comparing with the results of no correlation and liner correlation. The results indicate that the proposed method can obtain better results, which provides more accurate reference information for the operation of power system. 
     
  • LIU Dunnan, LI Qi, QIN Lijuan, ZHAO Jiawei
    Electric Power Construction. 2017, 38(7): 44. https://doi.org/10.3969/j.issn.1000-7229.2017.07.006
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     ABSTRACT:    The volatility and randomization of wind power and solar energy make power grid regard them as negative load in daily dispatch. The uncontrollable factors caused by renewable energy ratio in system lead to the results that the abilities for power grid to receive wind power and solar energy might be limited, including power grids peak-load regulation capacity, frequency regulation capacity, renewable energy output characteristics, load characteristics, external transmission channel of power network and so forth. Setting up renewable resources accepted index can reflect the “saturation level” of power grid, which can provide reference and evaluation basis for the operation and management of electric system. This paper presents the indicator system which can reflect multi-time scale power grids acceptance ability for renewable resources, based on the multiple factors influencing power grids acceptance ability. And then, this paper systematically evaluates the acceptance capacity of grid in short term, mid-term and long term three time dimensions respectively, with taking into account the operation security and economic factors of the system. Through index quantization value the power grids acceptance ability with the different proportion of renewable resources can be reflected. 
     
  • LI Xingyu, QIU Xiaoyan, ZHAO Jinshuai, WANG Yue, CHEN Kebin
    Electric Power Construction. 2017, 38(7): 51. https://doi.org/10.3969/j.issn.1000-7229.2017.07.007
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     ABSTRACT:  In the background of global Energy Internet, wind power as a clean energy has attracted much attention. But the volatility of wind power causes a strong impact on the security and stable operation of the power system, abandoned wind becomes more and more serious. Therefore, this paper proposes a new wind power consumptive strategy, which adopts the extreme-point symmetric mode decomposition (ESMD) to decompose the original wind power output into the smooth output curve and the fluctuating component, uses hybrid energy storage to absorb its fluctuating component, at the same time in the operation of the system accommodates more wind power through demand response. According to the shortcoming that the particle swarm optimization (PSO) algorithm is easy to fall into local optimum, we introduce the Levy flight PSO algorithm to enhance the ability of the particles to jump out of the “premature”. The numerical example proves the effectiveness of this wind power consumptive strategy, that the use of hybrid energy storage and demand response can improve the ability of accommodating wind power system, while maintaining a certain running cost. 
     
  • HE Ping, SHI Feng, YAO Yilin, QU Zhongjie, GENG Sihan
    Electric Power Construction. 2017, 38(7): 59. https://doi.org/10.3969/j.issn.1000-7229.2017.07.008
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     ABSTRACT:   With large-scale development and utilization of renewable power especially wind power, the structure of traditional power system has been changed, and wind power integration has brought new challenges to power system stable operation and control. Based on the characteristics of large-scale wind power, this paper concludes the recent progress and new trends on research of power system probabilistic small signal  stability with high wind power integration, and then discusses the control strategy of probabilistic  small signal stability wind farm integration when improving power system. Finally, this paper proposes some suggestions for further research in this area, which can provide reference and guidance for the research of the power system  probabilistic  small signal stability  with high wind power integration. 
     
  • ZHANG Rui, HUANG Guori, WEN Fushuan, ZHAO Junhua, DONG Zhaoyang
    Electric Power Construction. 2017, 38(7): 67. https://doi.org/10.3969/j.issn.1000-7229.2017.07.009
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     ABSTRACT: In recent years, with the ever-increasing penetration of natural gas generation in actual power systems, it is necessary to consider the impacts of the natural gas systems on the planning and operation of the concerned power systems. Meanwhile, the interconnection of multiple energy sources represents one of the development trends of future energy systems. Hence, unified planning and operation of a power system and a natural gas system concerned are important issues to be addressed. Given this background, based on the steady-state gas flow model of natural gas systems, this paper preliminarily studies the unified planning of integrated electricity and natural gas energy systems. Firstly, we study the unified planning problem of integrated electricity and natural gas energy systems considering the boundary conditions of the electric power system and natural gas system, so as to optimally determine the locations and capabilities of natural gas-fired plants, transmission lines, natural gas supply stations and natural gas pipelines, and construct a mixed integer nonconvex nonlinear programming model (MINNPM). Then, we adopt the Benders decomposition algorithm to simplify the presented MINNPM into a two-level optimization framework including master and sub problems, which can be iteratively solved respectively by the commercial CPLEX and IPOPT solvers. Finally, we establish an integrated electricity and natural gas energy system including a 54-node power system and 19-node natural gas network to demonstrate the feasibility of the developed unified planning model based on Benders decomposition. 
     
  • XU Yan, YANG Wentao, QI Feng, WEN Fushuan, ZHAO Junhua, DONG Zhaoyang
    Electric Power Construction. 2017, 38(7): 77. https://doi.org/10.3969/j.issn.1000-7229.2017.07.010
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     ABSTRACT:  With ever-growing interconnections of various kinds of energy sources, the coupling between a power system (PS) and a heating pipe network (HPN) has been progressively intensified. Thus, it is becoming more and more important to consider the interactions between a PS and a HPN in both planning and operation aspects. Given this background, the collaborative planning of an integrated electrical and heating system is addressed. The existing mathematical models of HPNs and related analytical methods are not elegant enough, and cannot meet the requirements of the collaborative planning. Thus, a distributed parameter model of HPNs is first developed, and the existing parallel solving method of the temperature field and pressure field is simplified and unified. The presented model is next linearized, and calculating methods of heat and pressure losses developed based on some pipeline and environmental parameters. Then, the thermal flow equations are built and solved uniformly with the power flow equations. On this basis, the collaborative planning problem of a PS and a HPN is formulated as a mixed integer nonlinear planning (MINLP) model, with the objective of minimizing the sum of the power generation cost as well as the electrical and thermal losses, and the operating constraints in PSs and HPNs respected. The commercial YALMIP toolbox is employed to solve the developed MINLP model. Finally, an integrated electrical and heating system is built with a modified version of the IEEE 30-bus system and an actual HPN included and served for demonstrating the feasibility and efficiency of the developed distributed parameter model of HPNs and the presented collaborative planning method. 
     
  • ZHENG Yu,LI Yang,JIAO Fengshun,WEN Fushuan,ZHAO Junhua,DONG Zhaoyang
    Electric Power Construction. 2017, 38(7): 88. https://doi.org/10.3969/j.issn.1000-7229.2017.07.011
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     ABSTRACT:  With the continuous development and commercialization of power-to-gas (P2G) technology, the coordinated operation between wind power generation units (WPGUs) and P2G facilities has attracted more and more attentions. The operational flexibility of P2G facilities can be employed to mitigate power output fluctuations of WPGUs, while both P2G facilities and WPGUs can form a virtual power plant (VPP) to participate in electricity market operation. Given this background, this paper studies the optimal bidding strategies for the VPP including WPGUs and P2G facilities. First, we present a modeling framework for a VPP with WPGUs and P2G facilities to participate in the operation of an electricity market. Then we construct the bidding strategy model for a VPP in a day-ahead electricity market with the objective of maximizing the overall profit, and determine the self-scheduling strategy of VPP. Considering uncertain forecasting error of the fluctuant outputs from wind power units, we develop both robust and opportunity bidding strategy models based on the information gap decision theory (IGDT), so as to reflect the risk preferences of various VPPs. And then, we adopt the well-developed commercial solver AMPL/IPOPT to solve the proposed nonlinear optimization model, and determine the robust and opportunity bidding strategy models for expected cost. Finally, case studies based on data from the Nord pool electricity market are carried out to demonstrate the characteristics of the developed optimization models and the employed solving method. 
     
  • JIANG Haorong, XU Maoxin, WANG Keying
    Electric Power Construction. 2017, 38(7): 96. https://doi.org/10.3969/j.issn.1000-7229.2017.07.012
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     ABSTRACT:  This paper establishes a carbon-energy combined-flow optimization model with carbon responsibility sharing, and proposes a grid knowledge transfer learning algorithm to realize the low-carbon, economical and safe optimal operation of power grid. The algorithm uses the binary coding method to realize the continuous-discrete space conversion, in order to solve the continuous state-action space learning and dimension disaster problem. This paper constructs the basic framework of knowledge migration from the relationship between the state information of the optimization task and the optimal Q value. In order to avoid the interference of the state feature information in the weak connection environment to the learning network, which affects the accuracy of the migration learning, this paper proposes a kind of grid information extraction method for decentralized extraction and migration of each local feature. Finally, the effectiveness of this algorithm is verified by the carbon-energy combined-flow optimization model of IEEE 118-bus system. 
     
  • WEN Yun, ZHOU Bin, DU Zhenchuan, ZHANG Xiaoshun, YU Tao
    Electric Power Construction. 2017, 38(7): 106. https://doi.org/10.3969/j.issn.1000-7229.2017.07.013
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     ABSTRACT:   To improve the control standard performance of automatic generation control (AGC) in an area power grid, the massive plug-in electric vehicles are employed for participating in AGC. The evaluation model of real-time up/down regulation capacity of electric vehicle is constructed by satisfying the charging demand of the owners. Based on this, a multi-layer framework of generation command dispatch of AGC is presented for a coordinated regulation between a cluster of electric vehicles and conventional hydro, thermal units. In order to meet the rapid economic allocation of different types of upper units, this paper proposes a novel optimization algorithm of deep interactive teaching-learning (DITL), in which a single class of the standard teaching-learning-based optimization is extended to multiple classes, while the small world networks is adopted for constructing the interactive networks among different teachers/students, thus the global search ability and local search ability can be enhanced. In the cluster of electric vehicles, the second-layer generation command dispatch of AGC is executed based on the regulation cost coefficients of different local control center, then the bottom-layer generation command dispatch of AGC is achieved according to the charging time margin of each electric vehicle. The simulations of Hainan power grid indicate that the coordinated regulation between a cluster of electric vehicles and conventional hydro and thermal units can be effectively achieved by the proposed upper generation command dispatch, and DITL algorithm can efficiently improve the dynamic control performance of AGC and reduce the regulation cost of the system. 
     
  • TAN Yan,SUN Lei,QI Feng,XIANG Liling,LONG Fei,LIN Zhenzhi,WEN Fushuan
    Electric Power Construction. 2017, 38(7): 114. https://doi.org/10.3969/j.issn.1000-7229.2017.07.014
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     ABSTRACT:   A smart substation, which represents the development trend of advanced substation technology, is an important part of a smart grid. The configuration of smart substation could have significant impacts on the secure and economic operation of the distribution system concerned, and is an important problem to be addressed. Given this background, this paper studies the intelligent upgrading strategy of substations in power distribution system with reliability indices considered. First, we construct the intelligent upgrading optimization model of substations in power distribution system to minimize the upgrade costs of existing conventional substations and the interruption costs of customers, with considering the constraint conditions that two reliability indices including the system average interruption duration index (SAIDI) and average energy not supplied (AENS) dont exceed a given threshold. Secondly, we present a fault clearing model for power distribution system and propose an accurate assessment method for the users outage time. Then, we linearize the users outage time and outage cost function to obtain a mixed integer linear programming model for the intelligent upgrading strategy of substations, which is solved by efficient commercial solvers. Finally, the IEEE RBTS-Bus 4 distribution power system and an actual medium voltage distribution network in Denmark are served for demonstrating the basic characteristics of the presented method. 
     
  • LU Shaoqi,WANG Shijia,HOU Yuqiang,LIU Fusuo,XU Zheng
    Electric Power Construction. 2017, 38(7): 123. https://doi.org/10.3969/j.issn.1000-7229.2017.07.015
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     摘要:目前国内直流输电工程采用的控制策略主要有基于ABB技术路线的控制策略和基于SIEMENS技术路线的控制策略。该文对两类控制策略针对换相失败的应对方式进行了分析对比,指出基于SIEMENS路线的策略虽然有利于提高稳态运行时关断角的控制精度,但相对于基于ABB路线的控制策略换相失败持续时间更长,主要原因为逆变侧交流故障下前者仍采用比例积分控制器(proportional and integral ,PI)对触发角进行调节,响应速度较慢。基于上述分析,对基于SIEMENS路线的控制策略提出了附加复合移相控制策略,具体包括基于直流电流上升率检测的移相控制策略和基于交流电压不平衡度与幅值检测的移相控制策略,并给出控制器的详细设计参数。仿真结果显示,相对于原始控制策略,投入复合移相控制策略有助于预防换相失败或缩短换相失败时间,加速功率恢复,提升直流系统故障下响应特性。 
     
  • WANG Shoupeng, ZHAO Dongmei
    Electric Power Construction. 2017, 38(7): 131. https://doi.org/10.3969/j.issn.1000-7229.2017.07.016
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     ABSTRACT:   According to the uncertainty of fault information in the power grid fault diagnosis, this paper draws lessons from the humoral immune response mechanism addressing the problem. Firstly, we establish the relationship between the process of the humoral immune response and the basic amount of the power grid fault diagnosis. Secondly, we construct a fault diagnosis model based on humoral immune response mechanism via simulating the mechanism and structure of humoral immunity resisting the invasion of antigens. The proposed model has a higher fault-tolerant ability, which can not only detect known faults according to the prior knowledge, but also judge unknown faults through the continuous learning function of the fault diagnosis system. Finally, the results of the test cases of the fault diagnosis show that the proposed model is feasible and efficient. 
     
  • ZHAO Jianpeng, SONG Jieying, ZHAO Chengyong, LU Feng, XU Jianzhong, SONG Fangfang, LIU Yun
    Electric Power Construction. 2017, 38(7): 139. https://doi.org/10.3969/j.issn.1000-7229.2017.07.017
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     ABSTRACT:  This paper proposes an electromechanical transient modeling method of static synchronous series compensator (SSSC) for large-scale power system transient stability analysis. Through reasonable assumptions, according to the mathematical model and electromechanical transient characteristics of SSSC, this method establishes the electromechanical transient model of SSSC with considering the DC voltage dynamic process of SSSC. Firstly, we construct the AC-side model of SSSC according to the external features of SSSC, and then, construct the DC-side model according to the own constraints of SSSC. On this basis, we implement the modular design of its controller model and modulation model. The simulation results show that this model presents the dynamic characteristics of SSSC effectively, and is appropriate for the influence analysis of SSSC access into large-scale power system on the transient stability of power system. 
     
  • JIAO Xiaopeng,LIU Qing
    Electric Power Construction. 2017, 38(7): 146. https://doi.org/10.3969/j.issn.1000-7229.2017.07.018
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     ABSTRACT:  Modular multilevel converter (MMC) has a widely application and research because of its advantages of high output level, low switching frequency and good waveform quality, etc. The voltage balance of sub-module capacitor is one of the key research directions of MMC. While traditional voltage balancing method will greatly increase the frequency loss of switching element and controller operation with the increasing of the number of sub-modules. This paper puts forward an optimized capacitor voltage balancing strategy for MMC based on improved quick sort algorithm, which can trigger or maintain control scheduling module by real-time monitoring the voltage of sub-module capacitor, setting the discrete degree index of sub-modules voltage. At the same time, through the optimization of the sorting algorithm, the calculation efficiency of controller in multi-modules is greatly increased and the hardware requirements is reduced. Finally, this paper builds the MMC-HVDC model in PSCAD/EMTDC simulation platform to simulate and verify the algorithm. The simulation results show that the improved voltage balancing control method can significantly improve the running speed and reduce the switching frequency of sub-module without noticeablly influencing the system performance.