Abstract:With the increase of non-synchronous generators such as renewable energy and high voltage direct current transmission system, the inertia of power system has been reduced, which in turn leads significant changes to frequency characteristics of power system. Synchronous condensers as one type of synchronous machines has inertial responses, which provides short-time frequency support for the system. Firstly, the principle of inertial response of synchronous condensers and its interaction with synchronous generators are introduced. Secondly, taking the application of inertial response for synchronous condenser as entry point, the worldwide work on improving the inertial responses and frequency characteristics of power system is sorted out, including the synchronous inertia level of power system, the measurements to improve the synchronous inertia, the effect of synchronous inertia on frequency response in power system and so on. Finally, combined with the worldwide research experiences, the necessity for East China Power Grid to apply synchronous condensers to enhance the frequency support of power system is analyzed, and relevant suggestions are put forward.

Abstract:Integrated electricity-gas system (IEGS) based on bi-directional coupling of gas turbine and power to gas (P2G) is an important carrier to realize accommodation of high-proportion renewable energy and improve terminal energy utilization efficiency. Firstly, based on the comparison of transmission characteristics of power system and natural gas system, the connotation, characteristics and advantages of IEGS are described. Secondly, the technical principle and modeling method of P2G in IEGS are introduced. Furthermore, the research progress of relevant technology is emphatically summarized from two dimensions: solution of IEGS energy flow model and optimization of IEGS operation scheduling. In terms of research on optimal operation scheduling, it is discussed from five aspects, including basic scheduling model and consideration of system randomness, energy flow difference and market operation mechanism and non-linear processing method of model. Finally, the prospect of future research on IEGS modeling and operation optimization are proposed.

Abstract:The electricity-natural gas coupling system consisting of gas generation units and power to gas (P2G) facilities improves the interaction of different energy systems. In order to realize the safe and economic operation of the coupling system during planning year, an optimal planning method for electricity-gas coupling system considering P2G is proposed, which aims at minimizing the sum of annual investment cost and annual operation cost. This optimization method can obtain the construction state of gas generation units, P2G plants, power lines, gas pipelines and optimal output of typical daily gas generation units and P2G plants in the planning year. Then, based on the proposed method, 7-node natural gas and 9-node power system can be modeled and calculated in different scenarios. Finally, the results of immune algorithm show that the reasonable location planning for P2G plants can reduce the construction cost of natural gas network pipeline, and the output adjustment of gas generation units and P2G plants can reduce the operation cost of the system.

Abstract:Multi-port energy router is an effective topology structure of integrating photovoltaic, energy storage and charging pile of electric vehicle. When energy routing is performed at different ports, the energy router involves multiple operation modes. Therefore, seamless mode transition is a major difficulty. In the Energy Internet framework, hierarchical control of multi-port energy router enables coordinated operation to achieve seamless mode transition in power grid dispatching, grid-connected/off-grid conditions or in the condition that electric vehicle is integrated or cut off. The control layer of micro-network adopts centralized control to maintain the overall energy balance of the system with various operation modes, which interacts with the upper-level scheduling layer to respond to scheduling, communicates with the lower-level local control layer by sampling the state information of each port, and calculates the references current of energy storage and the charging pile. In the local control layer, ports of photovoltaic and voltage source converter adopt distributed control to reduce the communication bandwidth. Ports of energy storage and the charging pile adopt the proposed new droop control strategy based on current tracking to accurately transmit the required power and control the voltage stability of DC bus. Finally, the effectiveness of the proposed unified coordinated control strategy is verified by MATLAB simulation.

Abstract:For the complexity of operation mode of the power electronic transformer (PET) ports and their multiple combinations in hybrid AC/DC grid composed of several PETs, an optimal combination method of operation strategy for PETs based on generalized AC/DC droop control (GADDC) is proposed, the objective of which is to fully utilize the renewable energy while maintaining the stability operation of power system. The switching between different control modes of PET ports could be approximated by adjusting the coefficients of GADDC, which avoids importing integer variables in the non-linear programming model, thus effectively reducing the complexity of the proposed model. Based on this, a robust combined optimization model of PET operation strategy considering the uncertainty of renewable energy is established. Furthermore, a bi-level optimization method is adopted to solve the proposed model. Simulation results verify the effectiveness and feasibility of the proposed method.

Abstract:The control objective of DC microgrid is to ensure the accuracy of current distribution and reduce the deviation of DC bus voltage, so as to maintain the power balance of the system. These two control objectives cannot be achieved simultaneously by the traditional droop control. By using the distributed secondary control framework, this paper proposes an improved control strategy for DC microgrid based on discrete time interaction, including continuous-voltage control and discrete-current control, which can ensure the accuracy of current distribution and reduce the voltage deviation of DC bus simultaneously. Different from other proposed control methods, the proposed method in this paper only needs to sample the average current information at discrete times, which reduces the communication burden. The system model is built in MATLAB/Simulink to verify the effectiveness of the proposed control strategy.

Abstract:The fluctuation of wind power may lead to the change of operation point in power system. In order to effectively improve the adaptability of subsynchronous oscillation damping control, a subsynchronous oscillation robust damping controller is designed by using the additional control method of direct-drive wind turbines. Firstly, based on the linearized state space model, the mixed H ₂/H _∞ control with regional pole placement is used to suppress the power system subsynchronous oscillation caused by random disturbance. The convex polytope model is constructed by using different operation points as the vertices of the convex polytope to adapt to the wide variation of system operation points caused by wind power output fluctuations and improve the robustness of the controller. Secondly, a linear matrix inequality is applied to solve the state feedback matrix and design a subsynchronous oscillation robust damping controller. Finally, a four-machine two-area system with two direct-drive wind turbines is used as the test system for time domain simulation. The simulation results show that the robust damping controller based on convex polytope can provide sufficient damping for the subsynchronous oscillation modes, and the controller also has good control effect when the outputs of wind power change over a wide range.

Abstract:With the increasing penetration rate of renewable energy in power system， the system ability of supporting frequency is getting worse and worse. Configuring virtual inertia for power system is an effective way to solve this problem. To effectively allocate the virtual inertia， the Voronoi diagram interpolation method is proposed to optimize the virtual inertia distribution. The mathematical model of virtual inertia in power system is established. The stability of the system is judged by Lyapunov direct method and the 2-norm of the decision matrix is used as comprehensive evaluation performance indicators. The stability of the system frequency is analyzed when multiple influence factors interact. The Voronoi diagram and center of gravity interpolation method is used to find the optimal solution of the inertia. The optimization results are verified by simulation. Compared with other traditional methods， simulation results show that the virtual inertia is configured based on the method. The result is more accurate and the calculation speed is faster， and it could use virtual inertia more effectively to improve system frequency stability.

Abstract:In order to scientifically determine the number and location of energy stations and the distribution of energy supply pipelines in regional integrated energy system, the planning method of energy stations and pipelines considering topological characteristics of regional integrated energy system is proposed. Firstly, the topological characteristics of regional integrated energy system are summarized. According to the urban planning scheme and geographic information system, the optional energy station sites and pipeline channels are obtained. Secondly, a topological description model of energy system is established based on energy flow balance constraints and heating network characteristics. To minimize the cost of initial construction and later operation, the layout planning model of energy station and energy supply pipeline is established, and orthogonal polynomial approximation is used to simplify the optimization model. The simulation results show that the proposed method could obtain a more economical planning scheme.

Abstract:Taking long-distance large-scale wind farms connected to the grid as the research background, and considering the synchronization effect of environmental factors on the current-carrying law of the transmission line and its mechanical performance degradation, electro-thermal coordination theory and line aging failure model are organically combined. Based on the electro-thermal coupling and life-cycle cost, the maximum allowable temperature assessment model for renewable transmission lines is proposed, which provides an evaluation basis for the renewable energy consumption capacity and operation performance of the grid. The model continuously processes the environmental variable values according to various setting schemes of maximum allowable temperature, and simulates annual variations of electrical and physical state parameters of the line based on the thermal inertia equation of the overhead conductor.Then, the duration of each temperature interval is calculated and the life-cycle performance of line is predicted based on the aging failure model of transmission line. The life-cycle cost of the line can be obtained according to the failure rate model, the annual average profit of investment for transmission line and analytic function expression of the maximum allowable temperature for transmission line on the premise that the access income of unit wind power is fixed, thereby achieving the goal of maximizing the annual average profit. Finally, effectiveness of the proposed model and its effect on improving the economic and safety of the system operation are verified by the actual case study.

Abstract:In the coordinated planning process of distributed generator (DG) and network structure of active distribution system, it is difficult to consider their interaction in the operation process simutaneously. To solve this problem, a mathematical model and solving algorithm for multi-agent balance of interest considering planning and operation alternative optimization are proposed. Firstly, considering demand response and operation strategy, a tri-level optimization framework and mathematical model based on the optimal cost-effectiveness of distribution network and DG are established. Secondly, the network simplification method based on topological equivalence principle is presented. Based on the in-depth analysis of the topological structure variation in the network structure generation process, a rapid generation strategy for link and loop network based on broken circle method is proposed. Then an encoding/decoding scheme of particle swarm optimization is developed. Thirdly, based on the load characteristics and demand response willingness of customers, an optimization method and operation strategy for dynamic time-of-use price are proposed, and coordinated planning solution process of the source and network considering the operation optimization is presented. Finally, the efficiency and practicability of the method are demonstrated on a practical system.

Abstract:Domestic electric water heater (EWH) has great potential in the demand response (DR) market because its power consumption is highly correlated with daily load patterns and it accounts for a high proportion of the household consumption. Recognizing load patterns of residential EWHs and quantifying their flexibility in DR help grid operators develop reasonable regulatory strategies. Firstly, probability statistic models are established for load patterns (the start time, the end time and the duration of the power event) of residential EWH with different time types. Secondly, a training-less non-intrusive load extracting (NILE) algorithm based on load signatures and power block extremum is proposed, which can automatically separate EWH loads with different rated power levels. Finally, an incentive price-based DR model is established to optimize load patterns of EWH, and flexibility of EWH is quantified based on changes in their usage behavior before and after optimization. Furthermore, the validity of the proposed algorithm is verified with an actual dataset, and the flexibility of EWH participating DR in different conditions is quantified based on the separated load data.

Abstract:Large-scale aggregated air-conditioning load can change its aggregated power through demand response, which plays an important role in peak shaving, balancing fluctuations of renewable energy and providing auxiliary service. For the dispatching of power grid, it has a practical meaning to establish a model to describe the characteristics of aggregated air-conditioning loads. Compared with the extensive researches on independent model for air-conditioning loads, there are few researches on aggregated model for air-conditioning loads which requires accurate parameters in modeling. Based on the method of adjusting the temperature setting of air-conditioning, this paper proposes a simplified aggregated power model for air-conditioning loads considering outdoor environment temperature variations and the stochastic adjustment behaviors of the consumers. In addition, the proposed model is simplified based on the state queuing model, which can effectively reduce computation burden and real-time communication pressure during dispatching. The accuracy and feasibility of the proposed model are verified through simulation analysis.

Abstract:A charging demand forecasting method of electric vehicle based on empirical mode decomposition-fuzzy entropy and ensemble learning is proposed. This method decomposes the time series of charging demand for electric vehicle into relatively simple components by empirical mode decomposition. In order to avoid the cumbersome calculation and error accumulation caused by excessive components, firstly, the complexity of each component is calculated by using fuzzy entropy. The components are superimposed and combined to obtain a series of sub-sequences to reduce the number of components. Secondly, long short-term memory (LSTM) neural networks and supported vector regression (SVR) are used as the base learner for prediction of sub-sequences with different frequencies. Finally, the prediction result of base learner, the weather data and time series data of the pre-decomposed charging demand are combined to form the feature set by the Stacking integrated learning strategy. Final forecasting results are obtained through a fully connected neural network. Single-step and multi-step prediction experiments are carried out based on real data of charging demand for electric vehicle in a certain area of a certain city in Southwest China, and the comparison with other algorithms is made， which shows the reliability of the proposed method..

Abstract:The paper proposes a mode identification method for low frequency oscillations in power systems based on exact mode order-exponentially damped sinusoids neural network (EMO-EDSNN). Firstly, the mode order is estimated via singular value decomposition. An EMO method is employed to solve the key problem of order determination. It comprehensively considers the variation laws of singular values change and the values themselves, thus overcoming shortages of artificial thresholds and enhancing the accuracy of order determination. Secondly, the EDSNN is constructed to translate the parameter estimation into an optimization problem. After training the neural network via the self-adaptive Levenberg-Marquardt algorithm aiming for a minimum square error between output and real signals, all the mode parameters can be obtained simultaneously. Finally, simulations of numerical signals, EPRI-36 system and actual signals are carried out. The results show that the proposed method can identify the mode parameters in an accurate and reliable manner.

Abstract:Due to the particularity of power industry, the reliability of power communication network carrying its business transmission has been paid more and more attention. With the continuous improvement of the communication network structrue, the network gradually presents the characteristics of vertical layering, which makes cross-layer joint protection possible. A cross-layer protection based on network coding (CLPBNC) strategy is proposed for power communication network. In IP layer, network coding is used to protect links. In optical transmission network, preconfigured cycle (P-cycle) is used to recover link failure. And conditions of cross-layer joint protection are studied to improve protection efficiency. The simulation results show that CLPBNC can effectively reduce the redundancy of protection, improve the efficiency of protection and optimize the overall performance of the network.

Abstract:Pumped-storage power station has the auxiliary service function of phase modulation, which provides reliable supporting for stable operation of power grid. Firstly, in view of the current situation that no compensation analysis is made for phase modulation service of pumped-storage power station in electricity market environment, this paper designs a compensation mechanism for the phase modulation service with “two-part system” price of reactive power in order to objectively measure the quality of the phase modulation service of pumped-storage power station and balance the benefits between power grid enterprise and pumped-storage power station. Secondly, based on Stackelberg game theory, a compensation model of pumped-storage power station is constructed and the existence and uniqueness of Nash equilibrium solution are proved. Finally, simulation analysis of Liyang pumped-storage power station in Jiangsu Province of China is carried out to obtain the benefits of both sides of the game with the equilibrium solution. The example shows that the reactive power compensation cost of power grid enterprise is related to the type of phase modulation service. Through the draft of reactive power price, the benefits of both pumped-storage power station and power grid enterprise can be increased, and the pumped-storage power station can be encouraged to provide the phase modulation service. Also, suggestions on reactive power bidding and compensation mechanism of the phase modulation are given.

Abstract:Accurate faults prediction and potential risk scanning of distribution network through flexible analysis and application of multi-source heterogeneous data are meaningful to realize efficient and accurate operation analysis decision of distribution network. The overall structure and function design of a distribution network operation analysis system based on mass data are introduced, and the functions and analysis results of each module are demonstrated by an application example. The system integrates data such as geographic information system (GIS), marketing business application and distribution automation. By using improved machine learning algorithm and weak point identification method, the functions of data correlation analysis, fault risk level prediction and weak point identification of target distribution network are extended. It is beneficial for relevant departments to propose corresponding technologies and management methods to carry out the operation and maintenance of distribution network, improve the scientific and practicality of the existing distribution network analysis system, and ultimately lay the foundation for the informatization, intellectualization and leanization of distribution network operation analysis.

Abstract:The low-voltage distribution network is the most core area of the application of electric power Internet of Things (EPIoT). It is necessary to extend the smart low-voltage distribution network to EPIoT in nature. Present data acquisition and automation system for low-voltage distribution network needs to be developed into the cloud-edge node-edge device system architecture. As a core edge node, distribution transformer terminal unit (TTU) should have a quick iteration capability to realize the edged fusion and cloud-edge coordination of various old/new businesses. To meet such technique requirements, the key technologies such as container technology to support edge node are analyzed firstly. Secondly, the key implementation technologies to make TTU becoming a containerized edge node are proposed including hardware platform, software architecture, container deployment and interaction, container management, coordination between cloud and edge. Finally, by adding a new low-voltage circuit terminal unit (CTU), the application scenario for TTU is designed and its necessity to become a containerized edge node is demonstrated.

Abstract:Because there are many types of equipment in the substation, the wiring is complex and each place has its own wiring graph drawing habits, it is difficult to automatically generate high-availability substation wiring graphs that meet users’ drawing habits. A topological analysis method based on the graphic description specification for electric power system CIM/G is proposed, which is used to identify and extract the features of the inventory graphs, to establish the graphic feature database, and to realize the automatic generation of the substation wiring graph by using the graphic features. This paper presents a case of generating a 220 kV substation graph in Lianyungang, Jiangsu Province of China, and verifies the correctness and effectiveness of the automatic generation of substation wiring graph based on the topological analysis of inventory graphs.

Abstract:The grid-connected control based on inductor current on the side of converter in synchronous rotating coordinate system is widely applied in the grid-connected converter with LCL-filter. However, the axe-cross-coupling exist in the dq models of LCL filter and digital delay, which constrains the grid-connected performance and becomes worse as the switching frequency decreases. To address this issue, based on the complex vector modeling of grid-connected converter with LCL-filter, this paper analyzes the coupling characteristics of the grid-connected converter and the conventional decoupling scheme. Aiming at the shortcomings of the existing control strategies, this paper proposes an improved control strategy of the grid-connected converter with LCL-filter based on phase compensation and virtual impedance optimization. Then, the effect of virtual impedance on system coupling and system damping characteristics is analyzed in detail through the zero-pole plots. And the method for determining optimization values of three parameters are given. Finally, the simulation and experimental results show that the proposed strategy can achieve independent control of system coupling degree and damping characteristics, while effectively realize decoupling and improve system dynamic performance.

Abstract:The derivation of the traditional modulation strategy for unipolar and bipolar single-phase inverters is based on the assumption that the DC bus voltage is an ideal constant DC parameter. However, due to the DC/AC power coupling, the DC bus voltage of the single-phase inverter contains a large amount of ripple component of double AC voltage frequency in the practical single-phase inverter. With the traditional modulation strategy, the second-order ripple component causes the increase of the third-order harmonic on the AC side, and impacts the power quality of AC output voltage. By means of the double Fourier transform method, the harmonic characteristics of output voltage are theoretically evaluated. Then, this paper proposes a harmonic reduction modulation strategy of single-phase inverter with a high second-order ripple rate of voltage on the DC side. Based on the third-order generalized integrator, the second-order ripple component in the DC bus voltage is extracted by the enhanced phase-locked loop (PLL). By injecting the opposite second-order components into the modulation coefficient, the third harmonic and the total harmonic distortion (THD) of the output voltage have been reduced. Finally, the rationality and feasibility of the active modulation strategy are verified by experiments.

Abstract:In the data acquisition and communication applications of smart grid based on wireless sensor network (WSN) , communication reliability is a key technical indicator of WSN. Increasing the transmit power improves the signal strength and reliability of the communication, but simultaneously degrades the mutual interference between the nodes. To solve this contradiction, this paper studies the optimization of WSN transmit power in the smart grid based on the adaptive model predictive control method. The main factors affecting the signal-to-noise ratio (SNR) of wireless communication in the smart grid are analyzed based on the wireless communication link path loss model, and the system state space model is constructed. By real-time estimation of the lower bound of stochastic fluctuation confidence interval of SNR, the compensation is performed and the algorithm based on the model predictive control is used to optimize the transmit power of the node. Finally, the proposed algorithm is compared with the adaptive transmission power control (ATPC) and potential feedback control (PFC) algorithms by simulation software, and the algorithm is tested by WSN hardware platform. The adaptive model predictive control algorithm can reduce the mutual interference between nodes caused by too high transmit power under the condition of ensuring the reliability of smart grid wireless communication.

Abstract:The energy-gaining power supply of current transformer has the heating problem when the bus current is high, which affects the service life of power supply. For this reason, this paper proposes a design method of the energy-gaining power supply for the current transformer based on self-adaptive power output control. Based on the analysis of the power acquiring principle of current transformer, the load equivalent model of energy-gaining coil of the current transformer is established, and the relationship between the output power of the coil and the bus current is derived. By controlling the on-off state of the bidirectional thyristor, the purpose of controlling the power output of energy-gaining coil is achieved, and it is ensured that the power supply does not heat up at a large current. An implementation form of self-adaptive power output control circuit is given. By establishing its equivalent model, the relationship between the conduction angle and the bus current is derived. Finally, the experiment shows that the power prototype made according to the proposed design method can work in a low heat consumption state in a wide current range, which verifies the feasibility of the proposed method.

Abstract:The transmission line plays an important part in power transmission task, so it is of great significance to identify its defects for the maintenance, and the severe power accidents can be avoided or decreased. For the background of images captured by unmanned aerial vehicle is very complex and difficult to be detected, a radial basis probabilistic neural network based fault location identification method for transmission lines is proposed. Firstly, the weighted color difference method, maximum interclass variance method and morphological filtering are sequentially adopted to realize the accurate segmentation of transmission lines in complicated background. Secondly, the segmented line area is equally divided into 10 line sub-images, 40 texture enhancement sub-images at 8 angles and 5 dimensions of transmission lines are obtained by Gabor filter, and the roughness, contrast and orientation of each sub-image are also extracted. By the feature variance, 10 strong texture features are selected and adopted as the input parameters to the radial basis probabilistic neural network for the defect identification of transmission line. The results show that both the rapid segmentation of transmission lines and the accurate identification of the defects based on the images in the complex background can be achieved by the proposed method, which provides a new idea for the operation state detection of transmission line in unmanned aerial vehicle inspection.

Abstract:At present, the traditional control mode is commonly used in China’s running HVDC projects, which may lead to frequent action of DC discrete voltage regulation equipment with a fluctuation of DC power and voltage, and directly affect the HVDC project operation reliability. In view of the technical requirement for reducing the action frequency of DC discrete voltage regulating equipment, this paper firstly analyzes the action influencing factors of discrete voltage regulation equipment. Based on this, the HVDC traditional constant extinction angle and constant DC voltage control modes are respectively improved considering the coordination of tap-changer, AC filter and dynamic reactive compensation. And DC operating voltage varies with DC power within selected power range is proposed. Then the impact of the proposed strategy is analyzed and the corresponding optimization suggestions are given. Finally, the above analysis is verified based on DC main loop calculation and electromagnetic transient simulation. The results show that the proposed strategy can effectively reduce the action frequency of DC discrete voltage regulating equipment.

Abstract:Aiming at the problem of how to realize the efficient transformation of rural electric power grid through precise investment, a lean transformation method for rural electric power grid is put forward based on cascaded combination scoring. Firstly, the main problems existing in the current rural electric power grid are sorted out, and the corresponding evaluation indices are defined. The calculation formulas for matching each evaluation index are given. The severity of each problem is graded, and the cascaded evaluation criteria for each evaluation index is set up. An evaluation index system is constructed, which can fully reflect the weak links of rural electric power grid and its severity. Secondly, according to the index value, the equipment that needs to be transformed is determined and taken as the evaluation object. According to the evaluation index evaluation criteria, the evaluation object is scored. The weight of each evaluation index is determined by criteria importance through intercriteria correlation (CRITIC) method, the comprehensive score of evaluation object is calculated and the cascaded combination score of the evaluation objects is then completed. Finally, the evaluation objects are arranged in the descending order according to the size of the comprehensive score and the top ranking equipment should be given priority to be reformed first. The example analysis proves the correctness and effectiveness of the method.

Abstract:The concept of situation awareness was first proposed in the fields of space and cyber security, and then involved in the field of power systems. In recent years, the global scholars have extensively discussed the application of situation awareness technologies in power systems. In this background, the real-time operation state identification, the operation trend prediction, and the situation visualization technologies of power systems are respectively mapped to the three elements of situation awareness defined by Endsley (i.e. “perception”, “comprehension”, and “prediction”). And the wide-area control and risk dispatching are mapped to the “decision action” in situation awareness. The event detection, event identification, risk prediction, situation visualization technology, wide-area control, and risk dispatching of power systems are reviewed and analyzed. The ideas of existing methods are described. Finally, the deficiencies of existing research on situation awareness of power transmission systems are pointed out, and the artificial intelligence and big data technologies are regarded as the future research direction to solve the issues in situation awareness of power systems.