With the rapid increase of wind power intergration, wind turbines such as doubly-fed induction generator (DFIG), are required to participate in active power balance and frequency stability of power system. Therefore, it is necessary to determine the active reserve capacity range of DFIGs. A method is proposed to determine the range of active reserve capacity of DFIGs in overspeed mode. The power flow model of grid-connected DFIGs is established,which takes into account speed and rotor-side converter (RSC) capacity constraints, and determines the lower limit of DFIG steady-state active power. Under this operation mode, the eigenvalue analysis to the power system is performed to find the dangerous modes. Since the slip rate affects the initial value and the state matrix, the Jacobian matrix is extended to establish the analytical expression of the sensitivities of the dangerous mode to slip rate. Based on the above sensitivity, power flow for hazard modes strongly related to slip rate is screened, and adjust PI parameters or/and slip rate are adjusted to eliminate the dangerous mode. Finally, the range of DFIG active reserve capacity is determined based on the slip rate value. The simulation results of the example verify the correctness and control effectiveness of the proposed algorithm.

To cut down the ride-through cost when the near-area AC short-circuit fault occurs at the receiving-end converter(hereinafter called receiving-end AC fault) of the flexible high voltage direct current (HVDC) system integrated with wind farms, this paper proposes a fault ride-through strategy where the adaptive nearest level modulation(ANLM) strategy and the chopper resistances in wind turbines work together. After the fault occurs, the sending-end converter cooperates with the chopper resistances within wind turbines to quickly realize the aim of wind farm load reduction. Before a significant load reduction in the wind farm, the ANLM strategy increases the equivalent capacitance of the converter station by reducing the number of sub-module inputs, absorbs the accumulated unbalanced energy of the flexible HVDC power grid, limits DC overvoltage, and strives for sufficient time for wind farm load reduction. The unbalanced energy stored in the converter is gradually released after the wind farm completes load reduction. The proposed strategy can reduce the ride-through cost only by using the regulation potential of the system. Finally, based on the simulation model of PSCAD software, the effectiveness of the proposed strategy is verified by taking the most serious receiving-end AC fault scenario as an example.

The fault modeling and analysis method of renewable energy stations is the basis of fault characteristics and protection research in wind power and photovoltaic centralized grid connected areas. However, the widely used single machine equivalent model cannot accurately reflect the short-circuit current characteristics of the stations. Based on the fault characteristics of the permanent magnet wind turbine, the dq axis currents before and after the equivalence are reduced, and the analytical relationship between the short-circuit current error caused by the equivalence and the electrical quantity boundary of the unit is obtained. According to the required equivalence accuracy, the cluster boundary for establishing the multi-machine equivalent model is given to realize the multi machine modeling of the permanent magnet wind farm. A simulation model is built with a typical actual station topology as an example. The simulation results show that the fault current characteristics of the proposed model and the detailed model are basically the same, and its accuracy is greatly improved compared with the single machine equivalent model, which verifies the rationality of the clustering criterion proposed in this paper.

In recent years, the construction of long-distance and large-capacity offshore wind farms are developing very fast. The VSC-HVDC based on the modular multilevel converter (MMC) is the preferred option for the future long-distance offshore wind power interconnection. It will improve reliability and transmission power of offshore wind farm interconnection via bipolar MMC-HVDC system. Firstly, the bipolar MMC-HVDC system for offshore wind farm interconnection is introduced in this paper, and the improved control strategy of the bipolar MMC-HVDC system is designed detaily to realize the bipolar power balance and non-error control of the voltage and frequency of AC system. Finally, the offline simulation model is built on PSCAD/EMTDC platform to verify the effectiveness and feasibility of the above control strategies.

In the AC/DC hybrid transmission system of sending-terminal power grid containing a high proportion of new energy, the commutation failure （CF） will cause power flow transfer of AC/DC hybrid system, and lead to overload phenomenon of AC transmission system. This paper proposes an AC/DC active power coordination control strategy considering wind turbine （WT） regulation potential. Firstly, based on K-means clustering algorithm, the discrimination model of WT operation states classifies its operation states, and characteristic data are collected to train self-organizing map （SOM） network, minimum quantization error （MQE） is used to evaluate WT regulation potential. Secondly, the DC subsequent CF is suppressed by adjusting DC transmission power, and the active power output of WTs with regulation potential is reduced based on the active power control principle of WTs, which can reduce the overload harm of AC transmission system. Finally, the SOM-MQE based evaluation model of WT regulation potential based on actual WT operaiton data is built, and the effectiveness of the proposed strategy is verified on the simulation platform.

The natural equivalent resistance of the DC yard equipment in hybrid multi-terminal HVDC (H-MTDC) system is small, so it is easy to cause resonance oscillation at the DC side of the system when the control system can't provide sufficient damping. This paper firstly deduces the DC-side output impedances of line commuted converter (LCC) and modular multilevel converter (MMC) stations. The impedance model of H-MTDC system is established in MATLAB and the stability criterion based on loop gain is given. Secondly, by quantitative analysis of the frequency domain sensitivity of controller parameters through calculating loop gain, their effect on loop gain curve has been quantitatively analyzed. The dominant factors affecting the resonance characteristics of the system are clarified, and a parameter adjustment scheme is formulated combining stability criteria. Thirdly, by feeding back the DC current from the converter station, the original constant current controller of LCC station is improved to a current damping controller and its parameters are designed. Finally, the effectiveness of the resonance suppression strategies are verified by time domain simulation in PSCAD/EMTDC.

The volume and cost of a modular multilevel converter (MMC) are mainly limited by the sub-module capacitor. Active injection of double-frequency circulating current or third-order harmonic voltage is an effective method of capacitance reduction. However, most of the existing harmonic injection strategies apply offline table lookup methods to calculate injection parameters. When the working conditions change, the injection parameters need to be recalculated, which are not suitable for scenarios with frequently changing operating conditions. In addition, there is still lack of analysis on the coupling effect of coordinated injection of the two methods. Firstly, the influence of coordinated second- and third-order harmonic injections on the voltage fluctuation of the sub-module capacitor is analyzed, and then the effect on the MMC operating characteristics is studied and the constraints of the injection parameters are given. Secondly, based on the voltage fluctuation of the sub-module capacitor, the optimization results of the coordinated harmonic injection parameters are given. Finally, the simulation model of MMC is built in PSCAD, and the proposed strategy is simulated and verified. The results show that the coordinated harmonic injection strategy can effectively suppress the capacitor voltage fluctuation of the sub-module.

In order to improve the control performance of inverter, voltage and current double closed loop control strategy is often used. Firstly, the mechanism and parameter design of the inductor current control inner loop with the proportional controller are analyzed. The mathematical model of the voltage outer loop based on the quasi proportional integral resonance （PIR） control and the controller design method are discussed in detail. The stability analysis of the dual loop control system is given. Secondly, the reason why the dual loop control cannot suppress the inverter output DC bias is analyzed, and the DC bias detection circuit and suppression strategy are designed to reduce the negative impact of DC bias on the inverter load. Finally, taking a 10 kW single-phase inverter as an example, the proposed control strategy and design method are verified by simulation and experiment, and the results show that the proposed control scheme is correct.

Distributed protection is an important research direction for active distribution network with high permeability distributed generation. This paper proposes a distributed intelligent backup protection scheme. And this scheme uses dynamic thresholds to form the start-up criterion of backup protection without the need for complex delay setting. The backup protections at each ring network node can effectively locate the fault section and determine the action smartly with coordination, with the help of the information exchange with its neighbors. The proposed backup protection can provide effective protection under various abnormal conditions, such as communication failure, smart unit failure, breaker miss-tripping and so on. The performance effectiveness of backup protection is verified by the failure simulation examples of active distribution network

In the context of the construction of new power systems, it is an important technical issue to consider the composite functions and application scenarios of new energy storage, and to demonstrate the planning and configuration scale and coordination of energy storage from the overall perspective of the system. This paper takes the coordination planning and layout of new energy storage for complex AC and DC power grids as the background, proposes a new system-level energy storage layout planning two-stage method. In the first stage, the optimization goal is to improve the new energy consumption capacity of the system, ensure the lowest overall cost of system planning and comprehensive operating cost, and preliminarily determine the overall energy storage configuration scale of the system. In the second stage, overall consideration is given to solving the consumption problems of new energy collection areas and delivery capacity of external delivery channels, network blockage in load-intensive areas, and system transient stability, the installation location and layout scale of new energy storage is optimized, and relevant models and processes of the method are provided. Finally, based on the complex AC and DC power grid planning of a province in 2025, a case study is carried out on the configuration scale and layout of energy storage in a compound scenario, which verifies the effectiveness of the model and method.

Aiming at low reliability and long time-consuming of existing system power deficit estimation algorithms, a fast power deficit estimation algorithm based on local frequency information is proposed. Firstly, it is proved that local frequency deviation is composed of the linear component and n-1 electro-mechanical （EM） modes via solving the initial value problem of ordinary differential equations. Furthermore, the linear component of each local frequency deviation is identical to the center of inertia （COI） frequency deviation in the early stages of system disturbance. Based on this property, a remote-communication-independent system power deficit estimation method is proposed. In the proposed method, the center of inertia （COI） frequency can be estimated via extracting the linear component of local frequency based on least-squares fitting. Then, the system power deficit is estimated by combining system inertia level. Finally, New England 39-bus system is built in PSCAD/EMTDC to verify the correctness of the property and the effectiveness of the proposed power deficit estimation method.

In view of the low automation level of distribution network, the changes of node electrical data and topology structure cannot be fully monitored in real time, which makes the line loss calculation difficult. This paper proposes an online calculation method of distribution network line loss based on random forest （RF） and kernel ridge regression （KRR）. Firstly, the typical operation modes under different topologies are determined according to the historical operation conditions of the distribution network. Secondly, by the power flow calculation of distribution systems with different operation modes, the training sets are constructed respectively. Through the training of KRR model, the mapping relationship between branch line loss power and distribution network state is fully explored. Finally, the operation mode of distribution network is judged based on the RF classification method, then the online calculation of distribution network line loss is realized by the KRR model of the corresponding operation mode. The example analysis results of IEEE 33-bus distribution network show that this method has higher accuracy and better robustness.

In order to effectively measure the management level of regional power grid construction and quantitatively evaluate the regional reliability level differentiatedly, a method for evaluating the reliability level of distribution network power supply based on GRA-K-means++ algorithm is proposed. Firstly, both external factors and power grid factors are taken into account, the set of reliability influencing factors of regional distribution network is constructed. The correlation between reliability influencing factors and power supply reliability is analyzed based on grey relational analysis （GRA）, combined with the regional power supply range. Next, the regional weighted clustering model is proposed based on the external factors, the information entropy and correlation with reliability of external factors are used as the index comprehensive weight, and the weighted K-means++ algorithm is combined to cluster the regions with the same external conditions. The reliability deviation index is proposed as the evaluation index of regional reliability level. Then, based on the reliability correlation degree of power grid factors, the key factors leading to low regional reliability are identified, and the direction of construction and management for improving the reliability of power grid is put forward. The algorithm is verified by actual distribution network data, and the results show that the proposed method can effectively realize the reliability level evaluation of distribution network, and provide a certain theoretical basis for decision about reliability improvement methods.

This paper proposes an electric vehicle(EV) charging and discharging scheduling strategy that takes into account the user responsiveness in the scheduling process of traditional EV clusters, which fails to fully consider the impact of user responsiveness and its influencing factors on the schedulable capacity. Firstly, the charging load model of EV clusters based on user travel data is built. Secondly, an EV user responsiveness model is established based on Weber-Fechner's law, and the influence of the charging and discharging price set by the aggregator and the vehicle state of charge (SOC) on user charging and discharging responsiveness is comprehensively considered. Finally, the charging and discharging price set by aggregators and the charging and discharging power of EVs are taken as decision variables. Overall considering of the benefit of the power grid, aggregators and EV users, the EV charging and discharging optimal scheduling strategy model is designed to minimize the load fluctuation of the distribution network and the charging cost of the user, maximize the revenue of the aggregator. And the optimal problem is solved by particle swarm optimization(PSO) algorithm. The example results show that the model can achieve peak-shaving and valley-filling while ensuring the benefits of aggregators and EV users.

In recent years, the penetration rate of electric vehicles in the distribution network has gradually increased, which leads to the increasingly obvious difference of power flow distribution in the distribution network. The congestion management of the distribution network is a necessary link of the smart grid. In this paper, considering the elasticity of flexible loads, a decentralized scheduling strategy for electric vehicles based on virtual aggregation and AC optimal power flow （ACOPF） is proposed. Firstly, starting from the synergistic relationship of multiple market entities, a framework for flexible load participation of electric vehicles in distribution network scheduling is designed. Secondly, a virtual aggregation model of electric vehicles is established based on the charging sequence relationship in the electric vehicle station. Then considering the load elasticity, the two-layer optimization model of market economy safety dispatching and in-station electric vehicle dispatching is established based on ACOPF. Finally, the simulation results show that the proposed strategy can improve the power flow distribution of the distribution network and improve the solution efficiency. What’s more, the node marginal electricity price can be used as a fair price signal to guide electric vehicles charging in an orderly manner, enabling decentralized dispatching of electric vehicles and reducing costs.

As a new operation mode, shared energy storage can effectively reduce the investment cost and use cost. Therefore, a shared energy storage operation optimization strategy based on user point-to-point energy transaction is proposed. Participating users can give priority to using their own distributed energy for point-to-point energy transaction, fill the energy gap and reduce the cost of using energy storage. In the collaborative optimization of users and shared energy storage, the load regulation characteristics of users are considered, and appropriate regulation is carried out according to electricity price, transaction and other information to realize economic operation. Using historical data for simulation verification, the results show that the proposed method can effectively use the regulation characteristics of various loads of users, reduce the operation cost of users, reduce the service cost of using shared energy storage and the power purchase cost of power grid through user energy point-to-point transaction, and realize the win-win situation of users.