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01 December 2019, Volume 40 Issue 12
    

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  • WANG Bingyu, YAN Yong, WEN Fushuan, ZHOU Ziqiang, LIN Shaowa, CHEN Xingying
    Electric Power Construction. 2019, 40(12): 3-10. https://doi.org/10.3969/j.issn.1000-7229.2019.12.001
    Abstract ( ) Download PDF ( )   Knowledge map   Save
    With the rapid development of photovoltaic (PV) power generation and the gradual downward subsidies, the advantages of satisfying load demand by local generation supply are becoming more and more significant, and market trading for distributed generation (MTDG) is then promoted. In MTDG, both power generation and load demand are located at the end of the utility grid, with some features exhibited including numerous participating entities, small transaction sizes, and point-to-point transactions. The traditional centralized transaction model suffers some problems such as low transparency, high cost, low efficiency, and untrustworthy data, and is not suitable for MTDG. Blockchain technology has the characteristics of decentralization, non-tampering, and anonymity, and can well meet the needs of MTDG for improved security, autonomy and transparency of electricity transactions. Given this background, the blockchain technology is applied in MTDG, and the corresponding trading mechanism, settlement mechanism and reward and punishment mechanism are developed considering the characteristics of MTDG. Finally, an example is employed to demonstrate the developed MTDG mechanism.
  • YANG Wentao, WEN Fushuan, ZHANG Xian, CHEN Hao, GAO Bo, LI Xuesong
    ELECTRIC POWER CONSTRUCTION. 2019, 40(12): 11-21. https://doi.org/10.3969/j.issn.1000-7229.2019.12.002
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    The development of distributed renewable energy generation could make an electricity user act as an electric power provider as well, i.e. the so-called prosumer. A prosumer can benefit through energy trading. Apart from electricity, natural gas and heat are also widely used as major energy resources in the demand side. With the fast development and commercialization of energy conversion technologies, e.g., the organic Rankine cycle (ORC) and power-to-gas, energy conversion among multiple kinds of energy and decentralized transaction become feasible solutions for improving energy consumption efficiency and promoting social welfare. Given this background, a decentralized transaction mechanism for multiple kinds of energy at the demand side is presented by employing an ORC system. An energy hub framework with an ORC system embedded is firstly presented, and the steady-state mathematical model of the ORC system is developed. The conventional centralized transaction model is then briefly described, and two kinds of decentralized trading mechanisms are presented with respect to the cases with and without a trusted third party involved in the trading process. Trading optimization models are presented on the basis of the developed decentralized trading mechanisms, and the well-established optimization method namely alternating direction method of multipliers (ADMM) is employed to solve the optimization models. Finally, the IEEE 123-node distribution system is employed to demonstrate the presented decentralized trading mechanisms, the economic benefits and technical requirements of energy conversion among multiple kinds of energy through the ORC system are investigated, and comparisons between two decentralized trading mechanisms are carried out.
  • LIU Dunnan, LI Pengfei,GE Rui, HAN Jinshan
    Electric Power Construction. 2019, 40(12): 22-29. https://doi.org/10.3969/j.issn.1000-7229.2019.12.003
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    Cross-regional interconnection can effectively promote the accommodation of clean energy, but cross-regional interconnection will have an impact on the spare capacity of units within the region and the line transmission margin, thereby bringing challenges to the safe and stable operation of the power grid. With the development of ubiquitous power internet of things, the demand response of user-side load continues to deepen, and distributed power generation and energy storage technologies also develop rapidly, providing more effective ways to solve the problem of regional interconnection reserve. At the same time, with the increased complexity of the grid structure under the ubiquitous power internet of things, the traditional centralized algorithm is faced with problems of information storage, data exchange and information protection. Therefore, on the basis of distributed algorithm, this paper studies the cross-region interconnection collaborative scheduling problem with the participation of energy storage and controllable load. Firstly, a multi-region dispatching scenario considering storage and adjustable load is established. Then, taking the minimum total operating cost of the multi-region system as the objective function and considering the robust equivalent constraints under uncertainty, a multi-region optimal scheduling model is established, and the distributed algorithm is adopted to solve the problem. Finally, the effectiveness of robust equivalent constraints is verified by example analysis, and the effectiveness of energy storage and adjustable load for relieving standby pressure of unit is analyzed.
  • JIANG Lichao, LIU Yang, SHEN Xiaodong, YANG Junfeng, LI Min, ZHANG Hongtu, WANG Changhao
    Electric Power Construction. 2019, 40(12): 30-37. https://doi.org/10.3969/j.issn.1000-7229.2019.12.004
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    Reasonable monthly power unit commitment (UC) can further expand the space of wind power absorption in a longer time scale, but the strong uncertainty caused by large-scale wind power will bring great challenges to power unit commitment. In addition, because the implementation of monthly contract power dispatch based on proportional distribution method is difficult, this paper presents a monthly combined model of thermal power units which combines with improved monthly contract power decomposition method and the uncertainty of source and load. The historical data of wind power is applied to monthly unit commitment decision-making, and the data-driven distributed robust method combined with stochastic optimization technology is used to solve the unit commitment and power decomposition scheme. The calculation results show that the model can effectively reduce the amount of abandoned wind power and improve the load rate of thermal power units.
  • GAO Tianle,LI Jiaxu,WANG Ying,XU Yin
    Electric Power Construction. 2019, 40(12): 38-44. https://doi.org/10.3969/j.issn.1000-7229.2019.12.005
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    After a blackout caused by an extreme event, the local power sources in the distribution network can be used for service restoration to critical infrastructure loads to quickly restore some or all functions of critical infrastructure. However, the infrastructure interdependency is complicated and difficult to model. When making decisions on restoration strategy for critical loads, insufficient consideration of the infrastructure interdependency may result in the abnormal operation of infrastructures even if the power service is restored. To tackle the issue, this paper firstly explores the interdependency of critical infrastructures and establishes the interdependency models that can be analytically expressed. Considering the interdependency models, a mixed integer second-order cone program (MISOCP) for restoration decision-making is proposed to maximize the critical infrastructure functions and restored loads. The MISOCP model can be solved efficiently by off-the-shelf optimization solvers. Finally, the proposed decision-making method is demonstrated on a test case and the effectiveness of the proposed method is validated.
  • WANG Xi, GOU Jing, SU Yunche, YANG Xinting, OUYANG Xuetong, LI Ao, FAN Jinzhu, LI Huaqiang
    Electric Power Construction. 2019, 40(12): 45-54. https://doi.org/10.3969/j.issn.1000-7229.2019.12.006
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     In order to meet the trend of large-scale integration of renewable energy to power grid, it is urgent to plan a grid structure with high adaptability to improve the systems capability to accept renewable energy. Applying the united weighted entropy theory, a series of adaptive indexes for power grid planning is proposed to analyze the security of power grid after renewable energy integration. In uncertain operation environment, the indexes consider the security and stability of power flow distribution, the balance and rationality of nodes and branches. By analyzing the actual state and electrical structure of the power grid, the security of the grid with renewable energy is evaluated. Then, a multi-objective programming model of transmission network is established on the basis of the adaptability indexes, and the data envelope analysis model with analytic hierarchy process restraint cone is used to make comprehensive decision on Pareto solution set. Finally, an example of Garver 18-node system is simulated to verify the rationality and effectiveness of the indexes and the planning model.
  • ZHAO Yanjun, LONG Fei, WANG Qian, CHENG Xue, LIU Yao, WANG Hongtao
    Electric Power Construction. 2019, 40(12): 55-60. https://doi.org/10.3969/j.issn.1000-7229.2019.12.007
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     Extreme weather events happen more frequently in recent years, which make the black-start units become the key to the fast restoration after a blackout. For most regional power grids with few pumped-storage aggregates and hydropower units, this paper proposes an optimal allocation of black-start power sources which come from the modified gas-steam combined cycle units. In this paper, combined with the influence of extreme weather on the power grid, the risk of line recovery is defined, and a bi-objective optimization model of black-start power source allocation with the goal of minimizing the recovery time and risk of the guaranteed power grid is established. The improvement of TOPSIS method is applied to solve this model on the basis of the non-inferior solution. The effectiveness of this method is verified by an example of Dongguan regional power grid.
  • JIANG Yefeng, XIONG Hao, HU Yu, LIU Yu
    Electric Power Construction. 2019, 40(12): 61-69. https://doi.org/10.3969/j.issn.1000-7229.2019.12.008
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    Aiming at the rapid growth of multi-type loads represented by electricity and heat load in distribution network, and the coordinated scheduling of distributed energy such as controllable units, energy storage devices and fans, an optimal scheduling model of virtual power plant (VPP) considering multi-type load comprehensive demand response is proposed. Firstly, wind turbines, cogeneration system, various energy storage devices, electric boilers and electric heating load are integrated into a virtual power plant. On the user side, a comprehensive demand response model for electric heating load is established on the basis of the combination of electricity price type and incentive demand response measures. Then, aiming at maximizing the operating profit of the virtual power plant, the opportunity constraint model is used to describe the uncertainty of the wind turbine, load forecasting and internal power balance, and the operational constraints and network security constraints of each unit are considered. Scheduling scheme is generated on the basis of reasonable control and coordination of the output of each component. The quantum particle swarm optimization algorithm with adaptive inertia weight adjustment is used to solve the model. In the example, the effects of different demand response schemes on load curve optimization results, network security and virtual power plant economy are compared. The dispatching results of virtual power plant under different confidence levels are compared. Therefore, the feasibility of the model is verified.
  • LI Linghao, QIU Xiaoyan, ZHANG Kai, LIU Mengyi, ZHAO Changshu
    Electric Power Construction. 2019, 40(12): 70-79. https://doi.org/10.3969/j.issn.1000-7229.2019.12.009
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    Demand response (DR) has been an important mean for peaking adjustment, operation economy raising and wind curtailment reduction. Considering the time characteristics of wind power and demand-side resources, as well as the stackelberg game between power grid dispatch and load aggregators (LAs), this paper establishes a two-stage hierarchical dispatch model. In this paper, a fuzzy chance constraint programming is used to deal with the uncertainties of wind power, loads and demand-side resources. Aiming at hierarchical distributed intra-day model with multiple load aggregators, this paper adopts analytical target cascading (ATC) in model decoupling, and the parallel solution of each part is realized. The test results show that the costs of power system has been decreased to 95.5% and 94% by dispatching DR and LAs, respectively, while each LA earnings have been increased more than 8%, which means the proposed strategy can enhance economy of power system and take all load aggregators earnings into account, and promote wind power accommodation as well.
  • LI Qin,ZHANG Huifang, LIU Yi,XU Zhiqiang,LU Jun, WANG Xingxing, HU Zesheng
    Electric Power Construction. 2019, 40(12): 80-85. https://doi.org/10.3969/j.issn.1000-7229.2019.12.010
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    Load shedding control is one of the key technologies in the stable operation and efficiency optimization control of power system. Aiming at the optimization problem of load over-cut rate in the optimal control of minute-level accurate load-cutting efficiency, in this paper, a precise control method for load cutting is presented, which takes into account the granularity of users response load. Firstly, the granularity of user response load is taken as the starting point, and the strategy of demand response is adopted to reduce the granularity of user response load. Secondly, the optimal model of the minimum load over-cut rate is constructed by load classification modeling. Finally, a numerical example is given to show that the proposed method can reduce the load over-cut effectively compared with the traditional minimum over-cut control method. The validity of the proposed method is verified by the reduced over-cut rate and its volatility.
  • GENG Qi, HU Yan, HE Jianzong, ZHOU Yongyan, ZHAO Wei
    Electric Power Construction. 2019, 40(12): 86-95. https://doi.org/10.3969/j.issn.1000-7229.2019.12.011
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    Microgrids are important parts of smart grids. They can integrate a variety of distributed renewable energy sources to satisfy the local loads. However, the intermittence of renewable energy sources limits the reliable operation of microgrids. Installation of energy storage systems and diesel generators can solve the intermittent problem of renewable energy sources, and the power sharing of microgrids is also an effective measure to ensure the reliable operation of microgrids. This paper firstly presents an offline algorithm that can produce optimal operation solutions of dual-microgrid system, assuming that the information of renewable energy sources and loads is known in advance. On this basis, the influence of power sharing and energy storage system on power purchasing cost of microgrids is studied. Then this paper develops online strategies that do not require any future information and are easier to be implemented in the actual smart grids. The simulation results show that the online strategies can obtain suboptimal solutions close to the optimal solutions of the offline algorithm. Finally, an online clustering strategy for multi-microgrid system is proposed on the basis of the online strategy of dual-microgrid system.
  • FU Shouqiang, CHEN Xiangyu, WANG Chang, YANG Lin
    Electric Power Construction. 2019, 40(12): 96-103. https://doi.org/10.3969/j.issn.1000-7229.2019.12.012
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    With the development of power electronics technology, it has become a new development trend to build hybrid AC/DC distribution network which can realize large-scale interconnection by power electronic transformer (PET). Firstly, for the application scenario of multi-PET in hybrid AC/DC distribution network, the flexible regulation function is analyzed. Secondly, considering the uncertainty of the day-ahead forecast output of distributed power supply, the day-ahead optimal scheduling model of the multi-PET interconnected hybrid AC/DC distribution network based on opportunity constraint programming is constructed. Thirdly, Monte Carlo method is used to simulate the uncertainty of distributed power supply output, and particle swarm optimization algorithm is used to solve the proposed optimization model. Finally, on the basis of the improved IEEE 33-node calculation example, the proposed optimization model is analyzed, and the validity and correctness of the proposed model are verified by comparing with the deterministic operation optimization model.
  • SHI Pengjia, LEI Yong, ZHANG Linyao, WANG Qiulin, LIU Xin, TANG Yingqi, DONG Shufeng
    Electric Power Construction. 2019, 40(12): 104-112. https://doi.org/10.3969/j.issn.1000-7229.2019.12.013
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    This paper mainly studies the problem of frame planning in distribution network planning. A new planning method for distribution network is proposed on the basis of Steiner Minimum Tree, which is to solve the problems with no consideration in the introduction of intermediate nodes and searching the best solution in the feasible areas in the planning of the previous research. Firstly, this paper establishes a mathematical model of distribution network planning using the path description method. Then it converts the mathematical model into a Euclidean Steiner Minimum Tree problem and uses the simulated annealing algorithm to solve it. By heuristically searching the Steiner point in the algorithm, we have made searching for intermediate nodes in feasible regions possible and we have expanded the selection range of intermediate nodes. In addition, we have also increased the probability of searching for a global optimal solution. Finally, the performance and effectiveness of the algorithm are verified by example analysis.
  • JIANG Wenchao, ZHANG Xing, XIE Dong, LI Ming
    Electric Power Construction. 2019, 40(12): 113-119. https://doi.org/10.3969/j.issn.1000-7229.2019.12.014
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    With the increasing scale of photovoltaic power station and the impact of grid-connected photovoltaic systems on the original power supply network, islanding detection has become a problem that PV power station must study in depth. Aiming at the deficiencies of the existing islanding detection methods, a novel passive islanding detection method based on wavelet transform and BP neural network is proposed. The method obtains the characteristic information of the signal before and after islanding through wavelet transform, and then the BP neural network implements islanding detection and islanding protection behavior according to this characteristic information. The simulation results show that the new passive islanding detection method described in this paper has high detection speed and small no-detection zone. In the case of multiple load quality factors and harmonics, no misjudgment of islanding detection will occur.
  • QIN Yujie, HU Jian, JIAO Ticao
    Electric Power Construction. 2019, 40(12): 120-128. https://doi.org/10.3969/j.issn.1000-7229.2019.12.015
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    One of the goals of building ubiquitous power internet of things is to promote the accommodation of renewable energy. However, distributed renewable energies (DREs) have some problems, such as difficulty in dispatching by power grids and high cost of absorption. On the basis of the idea of ubiquitous power internet of things, DREs represented by wind power and photovoltaic power, conventional gas turbine, energy storage system, controllable load are incorporated into peak-shaving resources in the form of virtual power plant, and a peak-shaving model for DREs accommodated rationally is built. The improved IEEE 30-node system is selected, membrane computing based on distribution estimation is used to calculate the operation cost of peak-shaving system and DREs absorption degree under three different combination modes, and then a comparative analysis is made. The results show that peak-shaving resources are used more efficiently, and a win-win situation of the absorption of renewable energies and the economy of peak-shaving system is realized, when the peak-shaving mode for DREs absorbed rationally is used.