风电的高比例渗透削弱了电力系统的惯性与调频容量，储能凭借响应迅速、出力稳定等特点被广泛应用于电网的惯量支撑及频率调节工作。首先以双馈风机额定转速与有功出力为约束条件，基于转子超速控制设置最适功率预留系数，划分风机参与系统调频的风速范围。在此基础上，考虑系统频率支撑能力，提出一种风电机组与储能协调配合的调频方法。通过对储能有功出力与系统稳态恢复过程的分析，刻画了虚拟同步机控制策略下储能系统的动态频率调节特性，由此实现储能在应对系统不同工况与不同支撑需求下控制参数的最优配置。仿真结果表明，所提方法能够在保证系统调频需求的同时充分利用风电自身的调频容量，优化储能系统参数的配置结果，实现储能出力的平滑输出，提高系统的频率支撑能力。

The high proportion penetration of the wind power weakens the inertia and frequency regulation capacity of the power system. The energy storage system (ESS) is widely used in the inertia support and frequency regulation of the power grid with the characteristics of rapid response and stable output. Firstly, the rated speed and active power output of the doubly fed induction generator (DFIG) were taken as constraint conditions, and the optimal power reservation coefficient was set based on the rotor overspeed control to divide the wind speed range of the DFIG participating in the system frequency modulation. On this basis, considering the frequency support capacity of the system, a coordinated frequency modulation method of the DFIG and the ESS was proposed. Based on the analysis of the ESS active power output and system steady-state recovery process, the dynamic frequency regulation characteristics of the ESS under the control strategy of the virtual synchronous machine were described, so as to realize the optimal configuration of the control parameters of the ESS under different working conditions and different support requirements. Simulation results show that the proposed method can make full use of the frequency modulation capacity of the DFIG while ensuring the frequency modulation requirements of the system, optimize the configuration results of the ESS parameters, realize the smooth output of the ESS, and improve the frequency support ability of the system.

In isolated operation, DC microgrids require multiple distributed energy storage units (DESUs) to accommodate the variability of distributed generation (DG). The traditional control strategy has the problem of uneven allocation of load current when the line impedance is not matched. As the state-of-charge (SOC) balancing proceeds, the SOC difference gradually decreases, leading to a gradual decrease in the balancing rate. Thus, an improved SOC droop control strategy is introduced in this paper, which uses a combination of power and exponential functions to improve the virtual impedance responsiveness to SOC changes and introduces an adaptive acceleration factor to improve the slow SOC balancing problem. We construct a sparse communication network to achieve information exchange between DESU neighboring units. A global optimization controller employing the consistency algorithm is designed to mitigate the impact of line impedance mismatch on SOC balancing and current allocation. This approach uses a single controller to restore DC bus voltage, effectively reducing control connections and alleviating the communication burden on the system. Lastly, a simulation model of the DC microgrid is developed using MATLAB/Simulink R2021b. The results confirm that the proposed control strategy achieves rapid SOC balancing and the precise allocation of load currents in various complex operational scenarios.

在预估光伏－制氢系统运行备用容量需求时，受光伏－制氢系统运行数据不确定性的影响，预估结果的误差偏大，为此，提出基于最近邻聚类的光伏－制氢系统运行备用容量需求预估模型。引入最近邻聚类中的不确定自然最近邻机制，以近邻数数量为基础，按稠密点、稀疏点、噪声点的分类标准，将数据集中的不确定光伏－制氢系统运行数据对象进行划分处理；在使用不确定自然邻域搜索算法获取到不确定的自然稳定状态输出结果后，根据特征值的差异性去除噪声点，借助不确定自然邻域密度因子对光伏－制氢系统运行数据进行聚类；在预估模型构建阶段，将径向对称的高斯径向基函数(radial basis function，RBF)作为核函数，并将所有的RBF输出结果映射到同一个空间中，得到光伏－制氢系统运行备用容量需求结果。测试结果表明，所提方法对最大备用容量需求预估结果的偏差始终稳定在250 MW以内，对最小备用容量需求预估结果的偏差始终稳定在150 MW以内，有效降低了能量管理的成本开销。

When estimating the spare capacity requirement for the operation of photovoltaic-hydrogen systems, the estimation error is relatively large due to the uncertainty of operation data of photovoltaic-hydrogen production system. Therefore, a prediction model based on nearest neighbor clustering is proposed for estimating the spare capacity requirement for the operation of photovoltaic-hydrogen systems. In this model, the uncertain natural nearest neighbor mechanism in the nearest neighbor clustering is introduced to classify the data points based on their density, sparsity, and noise. The data set is divided into different groups of uncertain photovoltaic-hydrogen production system operation data objects. After obtaining the uncertain natural stable state output results using the uncertain natural neighbor search algorithm, the noise points are removed based on the difference of eigenvalues. Then, the photovoltaic-hydrogen production system operation data is clustered using the uncertain natural neighbor density factor. In the construction phase of the estimation model, the radial symmetric Gaussian radial basis function (RBF) is used as the kernel function, and all RBF output results are mapped to the same space to obtain the photovoltaic-hydrogen production system operational reserve capacity requirement results. The testing results show that the proposed method has a maximum estimation error of less than 250 MW for the maximum reserve capacity requirement and a minimum estimation error of less than 150 MW for the minimum reserve capacity requirement, effectively reducing the energy management cost.

In view of the peak shaving problem caused by high proportion of renewable energy connected to the grid, this paper proposes a trading mode in which the distributed energy storage aggregator participates in the peak shaving auxiliary service market, analyzes the operation mode of DSAP participating in peak shaving auxiliary service, and puts forward the optimization model and scheduling strategy of DSAP participating in peak shaving. The feasibility and effectiveness of DSAP participating in peak shaving auxiliary service are verified by numerical simulation.

随着新型电力系统建设的推进，用户侧小型储能装置愈发受到重视。然而无序的充放电管理模式既给电网带来安全运行隐患，又造成资源浪费。基于此，提出一种通过储能聚合商云服务平台实现用户侧小储能装置联合调度的运行模式。建立综合考虑储能运营商、储能装置投资者和电网等各参与主体的最优运行模型，然后基于纳什均衡理论建立各参与主体在约束条件下的合作博弈模型。通过算例仿真分析，对模型求解得出最优共享储能定价方案。结果表明：多主体合作最优定价方案达到了削峰填谷、节约资源的目的，同时实现了电网、储能聚合商、储能装置投资者的多方共赢。提出的定价机制被验证具有一定的可行性和科学性。

With the advancement of the construction of new power systems， small energy storage devices on the user side have become increasingly important. However， their disorder charging and discharging behaviors not only pose safety hazards to the power grid， but also cause resource waste. Based on this， a joint scheduling mode for small energy storage devices on the user side is proposes，which are integrated on an energy storage aggregator cloud service platform. The optimal operation models for energy storage operators， energy storage device investors， and the power grid are established. Based on Nash equilibrium theory， a cooperative game model for all participating entities under their constraints is established. In a numerical simulation analysis，the optimal pricing scheme for shared energy storage devices is obtained by model solving. The results indicate that the optimal pricing scheme can not only achieve the goals of peak load regulation and resources saving， but also lead to a win-win situation among the three participating entities. The feasibility and scientificity of the proposed pricing mechanism have been proven.

在聚合商管理模式下，对大规模插电式电动汽车(electric vehicles, EV)调节容量的高效利用可降低系统运行成本，助力可再生能源(renewable energy resources, RES)消纳。同时，随着EV快速充电设施的普及，相较于慢充而言，快充模式下EV参与电网辅助服务时可能存在更多灵活性，但无疑也考验着电力系统承受能力。为充分利用需求侧灵活性资源，考虑将快速充电概念应用于电动汽车入网(vehicle to grid, V2G)场景中，即考虑双向的快速功率，提出考虑EV充放电模式灵活性的配电网日前经济调度方法，其包含2个模型：考虑充放电模式的EV聚合模型与配电网经济调度模型。通过算例分析验证了该策略可提升EV可调度区域灵活性，并能为配电网经济调度带来可观效益。

Under the aggregator management model, efficient utilization of the regulation capacity of large-scale electric vehicles (EV) can reduce system operating costs and facilitate the consumption of renewable energy resources (RES). At the same time, with the popularization of EV fast charging facilities, compared with slow charging, there may be more flexibility for EV to participate in grid auxiliary services under fast charging mode, but it is undoubted that the affordability of the power system is tested. To give full play to the advantages of resource flexibility on the demand side, this paper considers applying the fast charging concept to vehicle to grid (V2G) scenario i. e. considering the two-way fast power, and a day-ahead economic scheduling method for distribution networks considering the flexibility of EV charging and discharging modes is proposed. It includes two models: the EV aggregation model considering charging and discharging modes and the distribution network economic dispatch model. The results show that the strategy improves the flexibility of the dispatchable domain of EV and brings considerable benefits to the economic scheduling of the distribution network.

针对高比例分布式光伏接入配电网系统后引起的功率波动、电压越限以及配电网线路过载、线路损耗大等问题，提出了一种云储能模式下的配电网分布式光伏-储能无功优化方法。该方法基于无功补偿价格机制激励云储能参与配电网调压辅助服务，并深入挖掘分布式光伏、静止无功补偿器（SVC）、并联电容器（SC）、有载调压变压器（OLTC）的调压潜力。最后，以配电网运行成本和电压偏差最小为优化目标，建立基于云储能灵活调控的配电网多灵活性资源经济优化模型。仿真分析表明，云储能参与配电网系统有功无功联合优化有利于平抑配电网电压波动，并降低无功补偿装置调压压力和减少线路功率损耗，使配电网系统运行更加安全经济。

Aiming at the problems caused by the access of high-proportion distributed photovoltaic to distribution networks， such as power fluctuations， over-limit voltages， line overloads and excessive line losses， a distributed photovoltaic-energy storage reactive power optimization method for distribution networks taking cloud energy storage mode is proposed. The method takes reactive power compensation price mechanism to encourage cloud energy storage devices to participate in distribution network voltage regulation auxiliary services， and fully employs the voltage regulation capacities of distributed photovoltaic panels， static var compensators（SVCs）， shunt capacitors（SCs） and on-load tap changers（OLTCs）. Finally， taking the minimum operation cost and minimum voltage deviation of a distribution network as optimization objectives， an economic optimization model of the distribution network system based on the flexible multi- resources regulation of cloud energy storage devices is established. Simulation analysis shows that the participation of cloud energy storage in the joint optimization of active and reactive power is helpful to stabilize the voltage fluctuation of the distribution network， alleviate the voltage regulation pressure of the reactive power compensation device and reduce the line power loss， guaranteeing the safe and economic operation of the distribution network system.