A shutdown strategy for a low-cost hybrid DC converter based on diode rectifier is studied. The shut-down process of the auxiliary converter is divided into an energy feedback stage and an energy dissipation stage. At the energy feedback stage, part of the energy stored in the capacitors of sub-modules is fed back to grid through the DC transmission line under the active control. At the energy dissipation stage, the resonant capacitor and the capacitors of sub-modules are discharged in sequence through a discharging resistor. The calculation methods for the discharging cur-rent, capacitance voltage, and discharging time are derived, and the design method for the discharging resistor is also given. The capacitors of the auxiliary converter can be discharged quickly and efficiently under the proposed shutdown strategy without a high-voltage and large-capacity discharging resistor, which is conducive to the realization in engineer-ing projects. Finally, a simulation model is constructed in Matlab/Simulink, and the validity of the shutdown strategy is verified by simulation results.

Aimed at the problem that the existing incentive pricing compensation mechanism cannot meet the differentiated needs of multiple types of load, a compensation method for interruptible load is proposed in the form of sectional compensatory price. Meanwhile, a two-dimensional alternating function of load transferable time and load transferable power is introduced to establish a transferable load compensation model to quantify the cost of load transfer. A model of multi-type demand response participating in the optimal operation of distribution network considering uncertainties in interruptible load is established. Aimed at the non-convex nonlinearity constraint of the model, it is transformed into a mixed integer second-order cone programming model by the second-order cone relaxation method, which is further solved by the CPLEX solver. In addition, the contribution degree and confidence degree are introduced to evaluate the user responsiveness. Simulation results show that the novel compensation mechanism can more reasonably guide users to adjust the power load, smooth the load curve, and improve the operating economy of distribution network.

In view of the high fluctuation and randomness of wind turbine output, which affects the safe and stable operation of power system as well as the accuracy of wind power prediction, a wind power prediction method based on the fluctuation characteristics of wind power is proposed. First, the fluctuation characteristics of wind power are analyzed in terms of time scale and unit scale, and the appropriate wind power data is selected for wind power prediction. Then, a wind turbine short-term power prediction model based on least squares-support vector machine (LS-SVM) is established. The adaptive variational mode decomposition (AVMD) is used to decompose the wind power data to achieve frequency division, and the improved particle swarm optimization(IPSO) is used to optimize the model parameters affecting the re-gression prediction in the LS-SVM model. Experimental results show that the prediction model has strong adaptability, and the effectiveness of the prediction method can be proved by prediction error evaluation indexes.

The optimal configuration of source-storage in micro energy grid(MEG) is a primary challenge at the early stage of its construction since there exist complicated energy flows. In addition, the uncertainties (especially the stochastic fluctuations of wind, solar, and multi-energy load power) in MEG are difficult to describe and overcome. To address these problems, the uncertainties of renewable energy and load demand are described as intervals, the minimization of annual converted investment cost is taken as the objective, and a linear AC power flow model is coupled. The constraints of cool/heat/electric power balance, node voltage static security, line capacity and heat pipe transmission power are taken into account, and the indeterministic constraints are transformed into deterministic ones based on the interval linear pro-gramming theory, thereby constructing an interval-based optimal planning model of MEG with the consideration of source-load uncertainties. The feasibility and superiority of this model are verified by case studies and analyses, indicat-ing that the planning scheme can adapt to different uncertain scenarios and ensure the system's stable operation.

The development of the flexible DC fault line selection technology plays an important role for DC distri-bution network. In this paper, a novel algorithm is proposed to solve the problem that there is less available fault infor-mation about the existing flexible DC fault, which makes full use of the advantages of ensemble empirical mode decom-position (EEMD), principal component analysis (PCA) and the correlation coefficient algorithm. First, the transient cur-rent sample signal is extracted, and the data matrix represented by the orthogonal basis function is obtained by EEMD. Then, the feature vector of the matrix element is transformed into the principal component based on PCA, and the sam-ple signal is projected into the principal component space to realize coordinate transformation, so as to obtain the clus-tering and identification results of the sample data. Finally, fault line identification is performed based on the correlation coefficient. The EEMD of the proposed algorithm reveals the internal variation law of the original historical data, while PCA can effectively select the effective fault features. A large num-ber of experiments show that the novel algorithm is accurate and effective. Compared with other existing methods, it has ad-vantages in the cases of unclear fault information and different transition resistances.

Compared with 4G communication, 5G communication uses key technologies such as large-scale antennas, ultra-dense networking, and high-frequency communication to greatly improve its performance, resulting in increased power consumption of single 5G base stations and multiple sites. As a result, the power supply requirements are also changed. At present, there are two kinds of power supply forms which can meet the new power supply requirements, i.e., near supply and HVDC remote supply. Aimed at the HVDC remote supply, the power supply architecture and key technology are sorted out, and a feasible operation mode is proposed by comprehensively considering the operating investment cost in the economic mode of peak-shaving and valley-filling, the busy and idle periods of 5G base station service load, and the peak-valley time-of-use electricity price. On the basis of the construction which has already been invested under the HVDC remote supply scheme, the investment cost is small, and the economic benefit is obtained by using the time-of-use electricity price difference between peak and valley periods, thus reducing the power consumption cost of base stations to a certain degree. Finally, the development of 5G base station power supply is forecasted, providing reference for the research or design of its power supply.

As a commonly used islanding detection method, the active detection method can reduce the non-detection zone by increasing the disturbance intensity, but it will also increase the degree of harmonic pollution to the grid at the same time. Aimed at this problem, a hybrid fuzzy low-harmonic islanding detection method without non-detection zone is proposed in this paper. First, the non-detection zone is judged, and the passive islanding detection method which has no harmonic pollution to the grid is used preferentially. If this zone is within the non-detection zone of the passive detection method, then a fuzzy low-harmonic islanding detection method with fuzzy disturbance control is used to disturb the output current in its second and fourth quarter periods. Finally, the corresponding simulation model is built to verify the effectiveness of the proposed method.

Aimed at the problem that the power quality control equipment in distribution network is lack of collaborative allocation, an optimal allocation strategy for the control equipment of harmonics, reactive power and three-phase imbalance is proposed, which is based on the multi-objective particle swarm optimization (MOPSO) algorithm. The active power filter (APF) is used to suppress harmonics, the intelligent capacitor is used to compensate reactive power, and the phase-change switch is used to reduce three-phase imbalance. The control effect and operating cost about each power quality issue are taken as optimization objects, and the relevant power quality standards are considered as constraints. Through the MOPSO algorithm, an optimal allocation scheme for the allocation nodes and relevant access capacity of control equipment can be obtained. Furthermore, a power quality assessment model is built, and a simulation model based on an improved IEEE 18-node distribution system is also constructed. The harmonics, reactive power and three-phase imbalance loads are separately connected to simulate power quality issues, and simulation results verify the feasibility of the proposed strategy and its advantages compared with the traditional scheme for power quality control equipment.

Monitoring the power quality of power supply system is an effective method for ensuring the safe operation of power system and user-side equipment. To ensure the power quality of power supply system, a monitoring method for its power quality stability is studied. Based on the Hilbert-Huang transform (HHT) algorithm, the harmonic frequency and amplitude of the power quality signal frame of power supply system are monitored, and the disturbance time amplitude and frequency of the power quality disturbance signal are detected, so as to realize the power quality stability of monitoring system. The frame loss rate, accuracy and transmission delay of the monitored power quality signals under different pressures (with different numbers of power quality signal frames) were tested by experiments, and results show that the proposed method can realize the monitoring of power quality.

Aimed at problems such as the setup of an additional excitation source required by active magnetic shielding and the expensive magnetic shielding materials used in passive magnetic shielding, a wireless power transmis-sion (WPT) coupling mechanism with magnetic shielding based on Halbach effect is proposed on the basis of the tradi-tional DD coil structure. First, the topology of WPT coupling mechanism with magnetic shielding effect is proposed, and the principle for the magnetic shielding effect is analyzed theoretically based on the corresponding equivalent magnetic circuit model. Second, the expression for the magnetic field intensity of the coupling mechanism on any plane in the space is derived using the micro-element method. Finally, an experimental platform was built to verify the WPT perfor-mance and magnetic shielding effect of the proposed coupling mechanism. Results show that the Halbach effect coil can effectively weaken the magnetic field intensity outside the coupling mechanism and improve the magnetic shielding ef-fect while ensuring that the power transmission efficiency is basically the same as that of the DD coil.