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07 August 2020, Volume 41 Issue 8
    

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  • LIU Sai, LIU Yu, GAO Shan, GUO Haomin SONG Tiancheng, JIANG Weiyi, LI Zheng, WANG Juncheng, XU Yimin
    ELECTRIC POWER CONSTRUCTION. 2020, 41(8): 1-8. https://doi.org/10.12204/j.issn.1000-7229.2020.08.001
    Abstract ( ) Download PDF ( )   Knowledge map   Save
    Non-intrusive load monitoring (NILM) acquires power consumption information in low cost. It can realize household load recognition and decomposition without affecting the normal power consumption. The installation of smart meters also provides data and technical support for NILM. Firstly, by researching power characteristics, current waveforms and harmonic characteristics of common household appliances, principal component analysis (PCA) is used to reduce the dimension of high-dimensional harmonic feature space and extract the main harmonic information. It is combined with basic power characteristics to form multi-feature objective function. Then, on the basis of integer linear programming (ILP) model, NILM method of PCA-ILP considering multi-feature objective function is established to realize load decomposition and recognition for different electrical appliances. Finally, case study indicates that the proposed method has a sound performance for load decomposition in different scenarios of household appliances under different signal-to-noise ratio (SNR).
  • ZHUANG Weijin, ZHANG Hong, FANG Guoquan, CHEN Zhong
    ELECTRIC POWER CONSTRUCTION. 2020, 41(8): 9-16. https://doi.org/10.12204/j.issn.1000-7229.2020.08.002
    Abstract ( ) Download PDF ( )   Knowledge map   Save
     With the combination of users smart meter and non-intrusive load monitoring, research on load disaggregation based on low-rate power data has become the latest trend. On the basis of this, a non-intrusive load disaggregation method based on the mining of operating states is proposed in this paper. Firstly, this method detects load events and extracts power characteristic around load events. In the characteristic plane, a clustering algorithm is used to obtain clusters that represent different types of load events. Finally, among clusters, the GSP algorithm is used to mine equipment operation states that are matched with load templates stored in database to realize load disaggregation. The results of example in this paper verifies the accuracy of event detection and load disaggregation, and also verifies that the introduction of circle operation energy consumption in state mining process has an optimized effect on load disaggregation of devices with similar rated power. Accordingly, it provides a novel idea for the research of non-intrusive load disaggregation technology based on low-rate power data.
  • TANG Zizhuo, LIU Yang, XU Lixiong, GUO Jiuyi
    ELECTRIC POWER CONSTRUCTION. 2020, 41(8): 17-24. https://doi.org/10.12204/j.issn.1000-7229.2020.08.003
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    The current user mode extraction technology is mainly based on the time-domain characteristics of load data. It cannot accurately distinguish load data with close Euclidean distance in time domain and different fluctuation characteristics in frequency domain, and the classification accuracy of imbalanced data is low. This paper proposes a user mode extraction model to solve the above problems. The model firstly processes the data set with class imbalance by SVM-SMOTE over-sampling method, secondly obtains the scale and wavelet coefficients which is used to form the characteristic matrix in frequency domain through overlapping discrete wavelet transform, finally inputs the characteristic matrix into the deep LSTM network for classification and obtains the typical user mode by calculating the centroid of each category. The experimental results show that the method can effectively process imbalanced data and increase classification accuracy.
  • ELECTRIC POWER CONSTRUCTION. 2020, 41(8): 25-31. https://doi.org/10.12204/j.issn.1000-7229.2020.08.004
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    With the increase of renewable energy generations integration, the dynamic behaviors of power system are affected. The inertia characteristic of power system is a critical factor reflecting the ability of resisting frequency disturbances. Based on the characteristics of electromechanical disturbance propagation, a mathematical model is established in this paper. To evaluate the frequency anti-disturbance ability of different buses in the grid, the inertia distribution identification method is proposed according to the relationship between propagation speed and inertia. Based on the inertia distribution results, the change of inertia characteristics of power system caused by the integration of renewable energy generation is further evaluated. Then, the IEEE 39 test system simulation validates the effectiveness of the approach and reveals the impact of new energy integration.
  • TANG Jihong, ZHANG De, CONG Fanchao, TIAN Guoliang, WU Guihong, LI Yujun, YU Haifeng
    ELECTRIC POWER CONSTRUCTION. 2020, 41(8): 32-39. https://doi.org/10.12204/j.issn.1000-7229.2020.08.005
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     With the increasing of the penetration rate of new energy power generation and DC transmission, and resulted effective inertia decreasing, the transient stability of multi-terminal DC systems (MTDC) based on voltage source converters (VSC) has become particularly prominent. In order to solve the rotor-angle stability problem caused by the decrease of the effective inertia and the reduction of the effective damping of the MTDC system, an optimal power adjustment scheme for MTDC system, which is based on linear quadratic optimal control, is proposed. Firstly, the linearization model of the AC-DC hybrid system is obtained by linearizing the MTDC model near the stable equilibrium point. The design scheme of optimal power controller for MTDC system is obtained by using linearization model and adopting the linear quadratic optimal control theory, which uses the minimum rotor speed difference among generators as the control target. The simulations of a 3-generator 9-bus AC-DC hybrid system have demonstrated that the proposed method can suppress the first swing effectively and restore the rotor-angle difference among the generators quickly during disturbances, which can improve the transient stability of AC-DC hybrid system.
  • WANG Liang, GAI Zhengyu, JIANG Weiyong, SHI Yuxin, MENG Qingmeng
    ELECTRIC POWER CONSTRUCTION. 2020, 41(8): 40-47. https://doi.org/10.12204/j.issn.1000-7229.2020.08.006
    Abstract ( ) Download PDF ( )   Knowledge map   Save
     It may be unstable that isolated island operation mode occurs passively in the delivering side of UHVDC system, which belongs to a weak system. At present, the recommended solutions are blocking DC link, cutting off AC filters and cutting off generators. The coordination problem of the above strategies caused by action sequence remains to be studied. ±800 kV Yan-Huai UHVDC is taken as the research object. Its max transmission power is 4 300 MW when Hu-Guan line Ⅰ is uncharged. The isolated island operation process is calculated through the electromagnetic transient simulation. It is found that once the isolated island operation mode occurs, the voltage and power will fluctuate disorderly. The frequency falls into the operation range of low-frequency protection. Different time series of solutions action is analyzed. If the strategy of blocking DC link is earlier than cutting off generators, twice of rated voltage will attack the delivering-side power grid immediately. If blocking DC by low-voltage protection after cutting off generators, power shortage impact on the receiving side will continue for 2.00 s and the frequency reduces 0.2 Hz. It is suggested that when receiving the signal of isolated island, control and protection system blocks DC after a certain delay. So generators will be cut off firstly and overvoltage is eliminated significantly. Cooperative control system can execute the command of power modulation in time.
  • ZHANG Weiguo, CHEN Liangliang, CHENG Haisheng, FU Rong, JI Juan
    ELECTRIC POWER CONSTRUCTION. 2020, 41(8): 48-56. https://doi.org/10.12204/j.issn.1000-7229.2020.08.007
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    Considering the adverse impact of the disorderly access of flexible loads such as electric vehicles (EVs) and air conditioning loads on the power grid, an elastic optimal scheduling method for load in supply region is proposed, which takes into account the situation analysis of EV power supply resources. Firstly, the probability prediction of the charging demand of EVs is carried out. Through quantitative analysis of the characteristic indicators of EV loads, a situation awareness model for regional EV power supply resources is proposed, and the situation assessment of power supply resources is performed through  training of integrated learning algorithms. Then, according to the situational awareness result, this paper proposes an optimal scheduling strategy that flexibly controlling the charging demand of EVs. It takes the charging demand of EVs and the reduction amount of air conditioning load as control amounts, establishes a multi-objective scheduling optimization model with elastic constraints, and improves multi-objective particle swarm optimization. The algorithm is solved to obtain the optimal scheduling plan. Finally, the analysis of regional examples verifies that the proposed optimal scheduling method can achieve peak regulation of the power load, coordinately resolve the conflicts between the demand for flexible loads and idle resources, orderly dispatch   EVs charging  and air-conditioning   load to maximize the utilization of power supply resources.
  • WU Dingjie, LI Xiaolu
    ELECTRIC POWER CONSTRUCTION. 2020, 41(8): 57-67. https://doi.org/10.12204/j.issn.1000-7229.2020.08.008
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    Existing research on charging load prediction of electric vehicle (EV) lacks accurate descriptions of user travel behaviors and traffic conditions. Therefore, a spatio-temporal graph attention network is constructed to learn and predict the spatio-temporal distribution of travel demand considering urban points of interest and road traffic flow, taking into account the effect of date type, weather temperature and traffic events. The Dijkstra algorithm based on the travel time index (TTI) is used to obtain the shortest travel time. An EV energy consumption model that takes into account the impact of traffic conditions and air temperature, and a charging station selection decision model that considers distance and comprehensive charging cost, are both established. According to the actual travel demand and traffic data of the second ring area in Xian, the charging demand of electric vehicles for private cars, taxis and internet-hailed vehicles is predicted, and the changes in travel demand are analyzed for charging stations in various grid spaces in the city. The EV charging load prediction provides a reference and basis for the planning of charging facilities.
  • ZHAO Erdong , WANG Hao , LIN Hongyang
    ELECTRIC POWER CONSTRUCTION. 2020, 41(8): 68-71. https://doi.org/10.12204/j.issn.1000-7229.2020.08.009
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     It is an inevitable trend for thermal power enterprises to enter the power spot market, and market mechanisms such as electricity bidding, green certificates, quotas and carbon trading are bound to increase the competitive pressure of thermal power enterprises. In order to make thermal power enterprises better adapt to market changes, this paper puts forward a ladder bidding strategy model based on improved genetic algorithm and evolutionary game according to the bidding and clearing rules in the spot market of electric power, so as to make auxiliary decision for thermal power enterprises in different power market supply and demand situations. By setting a classic example, we simulated the bidding strategies of thermal power enterprises with different technical levels and sizes under three supply and demand conditions: standard supply and demand, tight supply and demand and loose supply and demand. We found that the bidding strategy based on evolutionary game theory can assist the enterprises to find a ladder quotation suitable for the current background and gain advantages in market competition. It shows that the bidding strategy based on evolutionary game theory has strong applicability, which provides valuable strategic reference for thermal power enterprises to enter the spot market.
  • GAO Jianwei, LANG Yutong, GAO Fangjie, GUO Guiyu , LIANG Pengcheng
    ELECTRIC POWER CONSTRUCTION. 2020, 41(8): 78-86. https://doi.org/10.12204/j.issn.1000-7229.2020.08.010
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    Considering both economic value and adequacy risk of peak load regulation for the coordination of wind farm clusters and conventional units, this paper proposes an invrestment timing decision method for wind farms clusters. Firstly, we establish an economic value assessment model with option theory to measure the economic value of wind farm clusters investment. Secondly, in order to study the influence of wind speed correlation on peaking adequacy risk, and consider risk preference of investors, by using the Copula function to describe the correlation of wind speed, a UCVaR index based on modified value function in prospect theory is proposed. Then we construct a bi-level programming model that integrates investment economy and peaking adequacy risk. The Monte Carlo simulation and genetic algorithm are used to solve the model. Finally, the example gives the optimal timing scheme in six scenarios. The calculation results show that the correlation of wind speed, the investors risk preference, and the selection of risk index have considerable influence on the timing planning for investment of wind farm clusters. 
  • WANG Hanlin, LIU Yang, XU Lixiong, CHEN Xianbang, TAN Siwei
    ELECTRIC POWER CONSTRUCTION. 2020, 41(8): 87-98. https://doi.org/10.12204/j.issn.1000-7229.2020.08.011
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    With the continuous deepening of the reform of the power market, it is of great significance to study the energy transaction among multiple microgrids on the distribution side to improve regional economy. To reduce the economic cost of microgrid operation, promote the consumption of renewable energy, and reduce the adverse impact of large-scale microgrid access on distribution network operation, taking the energy trading among multiple microgrids in the adjacent range as the research object, this paper establishes a hierarchical coordinated energy optimization management model for multi-microgrid system applying cooperative game. The upper layer of the model is the unified pricing of the management center, and the lower layer is the autonomous optimization of each microgrid. In the autonomous optimization scheduling of each microgrid, the demand response of different types of loads is considered, and a coordinated operation with users is formed through the signing of an agreement. The non-convex non-linear programming problem with power flow constraints is transformed into a second-order cone optimization problem that can be effectively solved by using the second-order cone relaxation technology, and the original bi-level programming model is transformed into an easy-to-solve single-level linear programming model by using decomposition theory such as dual theory and Big M method. The upper management center formulates the electricity price and conducts multiple volume and price interactions with the microgrids to find the equilibrium state of the coordinated operation of the regional multi-microgrid system. And then the income of the regional multi-microgrid alliance is distributed through the income distribution method based on the Shapley value. Finally, an example is given to verify the effectiveness of the model for improving the benefits of microgrids and promoting the consumption of renewable energy.
  • ZHU Xu, YANG Jun, LI Gaojunjie, DONG Xuzhu, LIU Shouwen
    ELECTRIC POWER CONSTRUCTION. 2020, 41(8): 99-110. https://doi.org/10.12204/j.issn.1000-7229.2020.08.012
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    Transferring loads across time periods, energy storage device plays an important role in the economic and stable operation of multi-energy system. But construction cost of energy storage device is high, which makes it difficult to apply energy storage device on a large scale. From the perspective of electric energy and heat energy, this paper proposes an optimal scheduling strategy for regional integrated energy system (RIES) considering virtual energy storage (VES) system, which can also transfer energy loads across time periods. According to the electric vehicle charging management method and building heat storage characteristics, virtual electric energy and thermal energy storage model is developed. The virtual energy storage system is integrated into the RIES optimal dispatching model. By arranging the charging of electric vehicles and adjusting indoor temperature within the temperature comfort range rationally, charging/discharging power management of virtual energy storage system can be realized. Finally, different energy supply modes under the summer refrigeration scenario are simulated to demonstrate the effectiveness of the proposed optimal dispatching method. Simulation results show that the proposed strategy can improve the economy and stability of the multi-energy system while guarantee the customer temperature comfort and meet regional energy demands.
  • SHANG Huiyu, LIN Hongji, LI Zhonghui, ZHAO Hongwei, CHEN Minghui, YANG Zeng, WEN Fushuan
    ELECTRIC POWER CONSTRUCTION. 2020, 41(8): 111-119. https://doi.org/10.12204/j.issn.1000-7229.2020.08.013
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    Establishing an electric power emergency response mechanism is of great significance for improving the emergency support capability of a power system. Efficiently dispatching mobile emergency power sources in the event of a power outage is an important part of the emergency response, and can reduce the losses caused by the power outage. There are some uncertain factors associated with a power outage event and the corresponded emergency response procedure, such as the travelling time of mobile emergency power sources and the power shortage value of important users during a power outage event. These uncertain factors have not yet been systematically taken into consideration by most of the existing related publications. Given this background, a robust optimal scheduling method for mobile emergency power sources considering uncertainties is proposed. Firstly, the interval number is used to represent the uncertain factors, and an optimization model is established with the objective formulated as the minimization of the total outage losses of important users. Then, the nonlinear terms in the optimization model are linearized by introducing auxiliary decision variables, and the model is thus transformed into a mixed integer linear programming problem. Next, a robust optimization method based on the fluctuation range of the acceptable solution is proposed to attain a more reasonable solution compared with the pessimistic solutions which are conservative in most scenarios. Finally, numerical results are carried out to demonstrate that the uncertain factors in the optimal dispatch of mobile emergency power sources can be well considered by the proposed model and then an effective scheduling scheme attained.
  • ZHENG Huiping, ZENG Peng, LIU Xinyuan, CHENG Xueting, BO Liming, YANG Weiwei, ZHANG Yifan, CUI Yang
    ELECTRIC POWER CONSTRUCTION. 2020, 41(8): 120-128. https://doi.org/10.12204/j.issn.1000-7229.2020.08.014
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    With the increase of wind power penetration rate, the problems of predictability and poor schedulability of wind farms have become prominent. Aiming at the problem that the above-mentioned factors lead to the reduction of wind power consumption level, this paper proposes an active-power layered control strategy combined with error feedforward prediction for wind power clusters. Firstly, an error-feedforward prediction model considering wind power variation trend is proposed, which is combined with wavelet packet decomposition and persistence method prediction model to form an ultra-short-term power prediction model, and the error feedforward limit is given according to the training situation of historical data. Secondly, on the basis of this prediction model, a  multiple temporal and spatial scales  active-power layered control strategy is proposed. The strategy divides the control layer  into cluster layer, farm group layer and sub-farm layer under the premise of existing scheduling instructions.  It realizes coordinated control of various wind farms. Finally, on the basis of the actual operation data of a wind power in Northeast China, simulation analysis is carried out by MATLAB and CPLEX. The results show that the proposed method improves the wind power accommodation level and the coordination output of wind farms energy storage.
  • TAN Qinliang, DING Yihong, LI Yu, LI Rui
    ELECTRIC POWER CONSTRUCTION. 2020, 41(8): 129-136. https://doi.org/10.12204/j.issn.1000-7229.2020.08.015
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    The combined dispatching and operation of wind-solar-thermal power system is an effective way to promote the development of renewable energy, which puts forward new requirements for power generation dispatching strategy. In this paper, under the principle of economic-environmental equilibrium, a multi-objective optimization model for combined dispatching of wind-solar-thermal power is constructed with the objectives of minimum power purchase cost, maximum renewable energy generation, and minimum fluctuation of renewable energy output. The main objective priority method is used to transform the model into single objective programming and then solved by Lingo software. The model is applied to the matching power supply of Tianzhong HVDC transmission project. Through the comparative analysis of typical daily dispatching results in four seasons, the role of the proposed optimization model in promoting renewable energy consumption, energy saving, and emission reduction is verified. In addition, the inclusion of auxiliary service fees into power purchase costs makes the load distribution of thermal power units more evenly.