Sponsored by State Power Economic Research Institute (SPERI) and China Electric Power Research Institute (CEPRI), which was founded in 1958, the journal of Electric Power Construction (EPC) is published in Chinese, and the corresponding titles, abstracts and references in English are given at the same time. All papers are reviewed by experts for the purpose of selecting better ones with the average publication period of five months, which greatly shortens the time for publication and guarantees articles be read when they are still fresh and valuable. It is published by Electric Power Construction Press and its online edition is published on China Knowledge Resource Integrated Database and WANFANG DATA platform. All papers are open and free to readers at our website of the journal.
In the context of the continuous deepening of energy Internet construction, the degree of coupling between information systems and energy supply systems is deepening. Current assessment of energy supply reliability does not include information system failures, and the impact of information component failures on the operational reliability of the system is not quantified. This paper proposes a new analysis method for energy supply reliability considering multi-information perturbation. Firstly, the cyber physical energy system is taken as the research object, and the typical architecture of the system is introduced. Secondly, the state model of the key equipment in the cyber physical energy system and the static connection and dynamic transmission model of the system are constructed. Thirdly, the evaluation indices and evaluation process of the operational reliability of the cyber physical energy system are proposed. Finally, the validity and practicability of the evaluation method proposed in this paper are verified by constructing practical cases, and the factors affecting reliability are further analyzed.
The high-speed railway station contains various loads such as cooling, heat and electricity, which is a typical application scenario of the integrated energy system （IES）. At the same time, compared with conventional industrial parks, a high-speed railway station as a giant cavity building has good energy storage characteristics. In view of the planning of a new high-speed railway station, this paper proposes an optimized planning method for integrated energy system considering the energy storage characteristics of buildings. Firstly, the energy supply framework of the integrated energy system is established. On this basis, considering the building characteristics and the controllability of the temperature inside the station, the model of the energy storage system is built, and the corresponding comfort cost is considered. Then the model is integrated into the integrated energy system framework. The overall planning takes the total annual cost as the optimization goal and the system is optimized by a two-layer optimization method. The simulation results show the effectiveness and rationality of the proposed method.
Aiming at the problem that the existing distribution network planning method fails to fully consider cooperative support for power supply reliability from primary and secondary equipment of distribution network under the ubiquitous power internet of things, a collaborative planning method for distribution network grid structure and distribution automation terminal is proposed. Firstly, an alternate optimization framework for primary and secondary collaborative planning of the distribution network is proposed, and a mathematical optimization model of the network structure planning layer and the automation terminal configuration layer is proposed. Secondly, to solve the reliability problem in the planning and configuration model, combining the types and communication methods of distribution automation terminals, the reliability evaluation method of distribution network considering distribution automation is proposed. Thirdly, the solution method of bi-layer model based on genetic algorithm and integer particle swarm algorithm is proposed. Among them, the efficient generation method for the initial network structure and the corresponding genetic coding method based on the idea of "avoiding the circle method" are proposed in the network structure planning layer. Finally, a certain 60-node city distribution network is used as an example to verify the effectiveness and rationality of the proposed method.
In view of the lack of evaluation methods and research methods for internal causes in current research of distribution system operation efficiency, this paper proposes a method based on Apriori algorithm and convolution neural network for mining the main influencial factors of distribution equipment operation efficiency. Firstly, according to the definition, the calculation method for daily operation efficiency of distribution equipment is proposed； Secondly, the reasons that may affect the operation efficiency are analyzed, and the method based on K-means clustering and Apriori algorithm for mining the main influencing factors of operation efficiency is proposed； Thirdly, the quantitative measurement method for the relationship between operation efficiency and main influencing factors is proposed on basis of convolution neural network； Finally, by using programming, the feasibility of this method is verified.
In order to study the interaction between the price of electricity in microgrid and the price of electricity sold in distribution network, and to realize the reasonable pricing of the interactive electricity quantity between the microgrid and the distribution network, this paper proposes a pricing method to maximize the benefits of both the microgrid and the distribution network. Through discussion on the impact of the construction and operation of microgrid on distribution network and microgrid operators, the cost-benefit model of microgrid and the comprehensive benefit model of distribution network are established to quantitatively evaluate each cost-benefit. Then the cost-benefit is divided into capacity cost-benefit and electricity cost-benefit, and the optimal benefit models of microgrid and distribution network are established, respectively. The optimal model obtains the influence of in-house price on the optimal benefit of microgrid and distribution network, and compares and analyses the reasonable range of interactive pricing between microgrid and distribution network under different in-house price of microgrid through a specific example of microgrid, which verifies the feasibility of the proposed model.
With the increasing proportion of distributed photovoltaic （DPV） power in distribution network， the fluctuation of its power output will become a non-negligible uncertain factor in power grid dispatch and operation. On the basis of the correlation of photovoltaic power generation in one region， a prediction method for distributed photovoltaic output is proposed on the basis of spatial correlation. Firstly， the historical data of centralized and distributed photovoltaic output in the same region are normalized to uncovered coefficient which represents the randomness of photovoltaic output. Then， the weather conditions are classified by K-means clustering. According to Copula theory， the correlation model of photovoltaic output under various weather conditions is established. Finally， the distributed photovoltaic output is predicted according to the information of centralized photovoltaic output. The validity of the proposed method is verified by using an example of a photovoltaic power station in a city of northern China.
More distributed power supplies are connected to the grid. This trend has made distributed power sources more and more influential to the operational vulnerability of the grid. To solve this problem， firstly， the operational vulnerability of the power grid is studied， and then a comprehensive vulnerability index that can comprehensively evaluate the operation vulnerability of the power grid is proposed. Combined with the commonly used economic power consumption loss index and the static voltage stability index considering voltage quality， a multi-objective optimization configuration model considering the grid operation vulnerability index is established. The improved quantum particle swarm optimization algorithm is used to solve the model. The simulation example finally achieves the optimal configuration of the distributed power supply in terms of capacity and position. The results show that comparing with the traditional optimized configuration model， not only the grid economy and voltage quality can be guaranteed， but the grid operation vulnerability will be improved as well， thus the superiority of the proposed model being verified.
With the access of high-proportion distributed power supply， higher requirement of the optimization of distribution network voltage and network loss is made. However， traditional centralized control lacks enough measurement and communication equipment， which leads to incomplete data acquisition and inaccurate optimization model， and makes it difficult to meet the operation requirements of large-scale photovoltaic power accessing to grid. In this paper， a double-layer optimization model is constructed to make up for the shortcomings of traditional centralized control. On the basis of the electrical distance matrix of probability optimization， ant colony clustering is used for effective partition and dominant node selection. Traditional secondary control of distribution network is introduced into the first layer model， and then the PSO-ELM neural network is used to mine and fit the functional relationship among the distribution network parameter data， and iteratively corrects the first-layer control model. Finally， the simulation results of IEEE 33-node system verify the effectiveness of the model for voltage and photovoltaic output control of distribution network.
Energy storage system connected with the end of distribution network， which is used for auxiliary services such as system voltage regulation， can effectively deal with the problem of voltage fluctuation caused by intermittent distributed renewable energies and the fluctuation of load demand. In this paper， the operation of energy-storage battery is modeled as a Markov Decision Making process. Considering its subsequent regulation ability， an intelligent control strategy based on deep reinforcement learning （DRL） is proposed. By embedding a Q deep neural network to approach the optimal action value， the problem of too large state space can be solved. The state vector composed of the state of charge （SOC）， the predicted output of renewable energy and the load level is used as the input of Q network， and the optimal discrete charge and discharge action is output， which is trained by replay strategy. Compared with the traditional method， the proposed method is based on learning without explicit uncertainty model， and the calculation efficiency is high. Finally， the IEEE 33-node distribution network system is analyzed by using MATPOWER in TtensorFlow， and the effectiveness of the proposed method is proved.
Virtual power plant （VPP） is an effective means to solve the problem of regulation and operation of abundant distributed generation （DG） access to power grid regulation and operation. DGs participation in the auxiliary service market of power system through VPPs， provides auxiliary services such as peak shaving and frequency regulation for power grid， and is benefited from them， to realize win-win between power grid and DG users. On the basis of fully distributed coordination control mode based on sparse communication and point-to-point information interaction， an economic primary frequency control method for VPP applying distributed control method based on sub-gradient projection is proposed. On the premise of minimizing its own operation cost of VPP， this method can improve its grid-connected friendliness and frequency support level for power grid. Compared with traditional droop control， this method not only achieves optimal power allocation， but also avoids competitive control， and can better deal with the power limit problem of DGs compared with the common distributed sub-gradient method. It also has better adaptability to communication delay.
In order to reduce the impact of natural disasters and other human factors on power system， a post-disaster recovery strategy of resilient distribution network considering the interactive optimization of mobile energy storage system and network reconfiguration is proposed in this paper. Considering the maximization of load recovery， this strategy firstly estimates the network after the disaster， analyzes the number of micro-grid formation， and carries out network reconstruction. Secondly， according to network reconstruction results， the access location of mobile energy storage system is optimized， and the removal of mobile energy storage follows the principle of the shortest time. Finally， a new network reconfiguration of the distribution network is carried out to meet the requirements. The strategy proposed in this paper can minimize the load loss and maximize the use of renewable energy on the basis of security operation of isolated islands. It reduces the impact of disasters on power system and greatly increases the resilience and economy of the distribution network. Finally， this paper takes IEEE 33-node system as an example to simulate disaster recovery in different scenarios， and verifies the effectiveness and practicability of the proposed strategy.
As an important development direction of the future distribution network， AC/DC hybrid distribution network is still in the initial research stage， and the research on the configuration characteristics and application mode of the future AC/DC distribution network is not comprehensive. This paper firstly summarizes the research on typical topologies of DC distribution network， and expounds the principles that influence the selection of topology. Secondly， the basic characteristics of the key equipment connecting AC and DC distribution network， including converter， soft open point and power electronic transformer， are briefly described. Thirdly， from the perspective of networking of these AC/DC conversion devices， the paper studies the configuration characteristics of AC/DC distribution network and the suitable application mode. Finally， the differences in equipment configuration and structure development of AC/DC distribution networks based on three different interconnection devices are compared. It provides a reference for constructing a new AC/DC distribution network.
In recent years， distribution network is developing rapidly from current to future advanced form. Under the tendency， this article puts forward a new AC and DC distribution network technology based on flexible substation. This technology is firstly launched in research， design， equipment manufacturing and engineering construction， etc. There is no mature design experience and complete theory. In this paper， system scheme and design method based on flexible substation are given systematically for the first time. And design of system scheme， parameters of key equipment， control and protection system are researched and discussed in depth. All of the research results above are adopted in the first demonstration project of AC and DC distribution network based on flexible substation for system design. The study results will provide theoretical and experimental experience for system design in the future AC and DC distribution network projects.
In order to improve renewable energy utilization and power supply economy， promote the combination of renewable energy and energy storage projects， and realize the local accommodation of renewable energy， this paper proposes a bi-level two-stage robust optimal operation strategy for AC and DC hybrid distribution network with photovoltaic and energy storage （PAES） considering source-load uncertainty. The first level of the strategy takes the maximum accommodation of renewable energy as the constraints， and the minimum electricity purchase cost required to access PAES nodes as the optimization objective； the second level takes the minimum operation cost of AC and DC hybrid distribution network as the optimization objective， including power purchase cost， network loss cost， operation and maintenance cost and life loss cost of energy storage station. The second-order cone relaxation method is adopted to handle nonlinear constraints. The strategy proposed in this paper realizes the maximum accommodation of renewable energy， solves the problem of large gap between peak and valley of load curve， and achieves the economic operation of AC and DC distribution network on the basis of ensuring the robustness of optimization strategy. Finally， this paper takes an AC and DC distribution network with the modified IEEE 33 nodes as an example to analysis， and verifies the correctness and effectiveness of the proposed strategy.
A flexible DC power distribution system operates in various ways and the source-load power fluctuations have high-frequency randomness. In order to solve the problems of low power quality， unreasonable power distribution and unsatisfactory dynamic voltage regulation under traditional droop control， a dual-objective optimal droop control strategy considering both economic performance and converter power margin is proposed. Firstly， the power flow optimization is analyzed when the system running loss is minimum， the droop coefficient of economic distribution is derived， and the power of each station is optimized. In order to avoid over-limit of the converter station parameters and reduce the static deviation of DC voltage， it is proposed to adaptively adjust the droop coefficient by considering the voltage margin and the real-time maximum power margin of the converter station. Finally， according to the DC voltage deviation when the system power fluctuates， the selection method for optimizing the droop coefficient is proposed. The simulation model of double-ended flexible DC power distribution system is built in PSCAD. The simulation results of different operating conditions verify the effectiveness of the strategy.
State Grid Corporation of China
State Power Economic Research Institute
Copyright @ ELECTRIC POWER CONSTRUCTION Editorial Office
Address: Tower A225, SGCC, Future Science & Technology Park,Beijing, China
Telephone: +86-(0)10-66602697 Fax:+86-(0)10-66602711
Technical support: Beijing Magtech Co.firstname.lastname@example.org