In response to the increasing pressures of frequency regulation and peak shaving in high-penetration renewable energy power system, we propose a day-ahead scheduling model that incorporates the auxiliary role of energy storage systems in supporting frequency regulation and peak shaving operations. First, we derive the constraints related to steady-state power imbalance, transient frequency excursion risk, and quasi-steady-state frequency recovery risks associated with the participation of energy storage in these ancillary services. Then, we analyze in detail the compatibility between the regulation requirements at various stages of system operation and the corresponding actions of energy storage systems. Based on this analysis, we develop a comprehensive day-ahead active power and frequency security scheduling model to improve the economic efficiency and stability of high-penetration renewable energy power system. The improved IEEE 30-bus system was used as a case study to validate the effectiveness and necessity of the proposed model, which considers the entire dynamic peak shaving and frequency regulation process. Although the associated costs increased by 8.32%, 10.5%, and 2.55% compared to Scenario 1, Scenario 2, and Scenario 3, respectively, the model significantly enhanced the system's frequency stability. Additionally, the role of energy storage resources in the overall dynamic peak shaving and frequency regulation process was confirmed. Furthermore, the superiority of the proposed day-ahead scheduling method in enhancing system kinetic energy and minimizing the lowest frequency point was also verified.

To balance power supply and demand under extreme weather events with constrained renewable energy sources (RESs) outputs, this paper proposes a novel energy storage sources (ESSs) capacity planning method based on the timescale of typical day timescale and extreme weather events. The extreme weather event is defined according to duration of RES low output. Based on the number and duration of extreme weather events for a typical year, a novel model of ESSs capacity planning is established to minimize costs with integrated load demand. The particle swarm optimization (PSO) is adopted to find a global solution for ESSs capacity planning. Numerical simulations are conducted on an actual 34-bus power system to verify the feasibility and effectiveness of the proposed algorithm.

The northwest region of China is rich in wind and photovoltaic resources, and large-scale energy bases and high-voltage direct current transmission channels are developing rapidly. However, the increase in energy abandonment rate of energy bases and the serious dependence of AC power grids on thermal power still exist. To achieve the scientific consumption of new energy in a large-scale energy base and the clean energy consumption of the sending-end AC power grid, a coordinated optimal dispatching method for the sending-end AC power grid and the energy base with multiple DC transmission channels is proposed. Firstly, a scheduling framework is constructed for multi-DC transmission channels that couple the AC power grid and the energy base, and the energy flow within this framework is studied. Then, a coordinated optimal scheduling model considering the thermal power operation cost, wind and photovoltaic abandonment cost, equipment operation and maintenance cost, and flexible response cost is established, taking into account both economic and environmental considerations. The example results show that the proposed coordinated optimization scheduling method can improve the new energy consumption capacity, reduce the dependence on thermal power units, and achieve efficient energy transmission.

To enhance wind power integration capability and voltage regulation performance in renewable energy-dominated sending-end power systems, this paper investigates a coordinated two-stage transient voltage stability control strategy combining wind farms with energy storage systems. In the first stage, an optimal power flow (OPF) model is formulated for grid steady-state operation, aiming to minimize the operational costs associated with energy storage utilization and wind power curtailment. The interior point method is implemented to solve the convex optimization framework and obtain the optimal steady-state operating condition. In the second stage, during the transient voltage stability control phase, a dynamic constraint-satisfaction model incorporating transient voltage security margins is developed to regulate post-optimization power flow deviations. The particle swarm and beetle antennae search technique are subsequently adopted to iteratively refine the operating point through intelligent swarm-based parameter adjustment. The effectiveness of the proposed two-stage preventive control framework is validated through electromagnetic transient simulations on a modified Nordic test system integrated with high-penetration wind generation, demonstrating measurable improvements in renewable energy accommodation capacity and transient voltage security indices under contingency scenarios.

Under the background of the new power system, there have been significant changes in the forms of the grid side, power source side, and load side. Clarifying the construction process and investment structure changes of the new power system from a development perspective is the key to discovering investment change patterns, guiding efficient investment of funds, and discovering and improving the investment efficiency of power grid infrastructure. This article first constructs a new power system evaluation index system and a new power system construction evaluation method from four dimensions: macro policies, power structure, grid structure, and terminal demand. Secondly, based on the higher demand for system regulation capability in the development stage of the power grid, as well as the urgent need to further improve power supply reliability, transaction flexibility, and diversity of power supply forms, an analysis of the investment direction of the power grid is conducted. Then, considering the changes in the demand for power grid investment functions, a power grid investment demand system that adapts to the new power system is constructed, including building a power grid investment demand calculation model based on project requirements at the project level, coordinating execution and planning, and considering factors such as load growth to construct a power grid investment demand calculation model that takes into account multiple factors. The power grid investment demand is calculated by combining bottom-up and top-down approaches. Finally, taking X province as an example, empirical calculations are conducted to verify the usability of the model.

China needs to build a massive new energy transmission infrastructure if it hopes to meet its carbon peaking and carbon neutrality targets as well as promote coordinated development in both its eastern and western regions. Ensuring the transmission base operates economically and reliably requires the efficient allocation of diverse new energy sources and energy storage capacity. This paper proposes a capacity allocation method for new energy transmission based on the confidence probability of wind and solar resources. First, an improved K-means clustering method is introduced to optimize the transmission power of the DC channel, taking into account the load curve at the receiving end. Next, a transmission confidence probability index is suggested, which evaluates whether the transmission base's output power can satisfy the DC channel's transmission requirements. The ideal model for the distribution of wind energy and energy storage capacities is constructed with this confidence probability index as a constraint, and it is solved using a stochastic planning technique. In order to verify the efficacy of the suggested allocation model, we lastly examine a case study involving a resource supplier in western China and a recipient region in eastern China.

In this paper, the mathematical model of hydrogen production from alkaline electrolyzed water and storage and transportation is constructed mainly from the point of view of hydrogen production station, and the scheduling method of short-distance storage and transportation is studied. A set of mathematical models covering four modules of hydrogen production, compression, storage and transportation is constructed for the rapidly developing hydrogen energy market demand. The model is based on hydrogen production from lye, compression at 32 MPa, hydrogen storage in type II bottles, and road transportation in 20 MPa long-tube trailers, and the mathematical model is constructed by quantifying the performance indexes of each link using the data of China in 2023. This paper innovatively proposes a storage and transportation strategy that determines whether hydrogen needs to be stored at the source and the number of hydrogen carriers required based on the matching relationship between the hydrogen production rate and the refilling rate of hydrogen carriers. The model is also used to carry out calculations to analyze the configuration scheme of short-haul transportation with transport distance related to the scale of hydrogen production from alkaline electrolytic water.

As the fossil energy depletion and environmental pollution problem is increasingly serious, pv, fan and other renewable power will occupy the main position in the future power ratio, how to dig in electric power system and use the multi-types resource flexibility, further planning and cost saving, reduced the wind light, is currently the focus of the high proportion of renewable energy power planning problem. First, the overall framework of power supply planning is established. Secondly, based on the analysis of various flexible resources, a storage-load flexible resource scheduling model based on energy storage batteries, electric vehicles and demand response was proposed. On this basis, the investment construction cost and operation cost are integrated, and the power planning-operation model is established. Finally, the effectiveness of the proposed model is verified by an example analysis.

As the existing U-HVDC(（ultra-high voltage direct current）control strategy does not consider the inter station communication delay,the influence of inter communication delay on commutation failure and recovery characteristics are analyzed based on CIGRE HVDC model. The influencing factors of commutation failure are analyzed. It is concluded that the main factors causing commutation failure are the decrease of AC system voltage and the rise of DC current at the inverter side.After analysing the influence of inter station communication delay on commutation failure,it is concluded that inter station communication delay will increase the risk of commutation failure. Three typical operating conditions are obtained by analysing the relationship between the current command values on the rectifier side and the inverter side under different communication delays,and the impact of communication delays on commutation failure and recovery characteristics under three different operating conditions is analyzed in detail. A CIGRE HVDC standard testing system is built based on PSCAD/EMTDC simulation software to simulate and analyze the impact of different communication delays on commutation failure and recovery characteristics under different fault resistors.

针对新能源高渗透系统灵活性需求激增的问题,文中提出一种新能源高渗透系统灵活性供给能力评价方法.首先,基于净负荷时序波动特性建立新能源高渗透系统灵活性需求模型,根据灵活性改造火电机组、需求响应和储能的运行特性,构建源荷储侧灵活性资源供给能力模型,精确计算新能源高渗透系统的灵活性需求量;其次,采用节点运行灵活性的思想建立灵活性资源供给能力评价指标;然后,基于协同优化的思想构建新能源高渗透系统灵活性评价指标计算模型,并通过Yalmip调用CPLEX对模型进行求解;最后,基于改进的IEEE 39节点系统进行仿真算例分析.结果表明,所提出的灵活性评价方法通过源、荷、储灵活性资源协调优化,能够在实现系统整体灵活性供给能力优化的同时使系统经济性更优.

针对共享储能的集中式与分布式投资方式及电量共享与容量共享运营模式,分别建立了考虑可再生能源发电及用户负荷季节差异性的多场景优化模型,并采用基于供需比的定价机制对系统内的电力交易进行经济结算.为评估系统内用户负荷灵活性对储能规划及系统总成本的影响,对用户灵活性负荷进行了建模及敏感性分析.最后结合真实历史数据,通过仿真算例对不同投资及共享模式进行了多角度的分析对比,并针对峰谷电价差及规模投资效应对储能投资运营的影响进行了进一步分析.结果表明,采用集中式储能投资并进行电量共享的运营模式更具经济性.

海上风电是新型电力系统的重要支撑,其集电系统需要大量昂贵海缆,占总成本比重较高,优化规划较为困难.为此,提出适宜集电系统的含网损线性潮流模型,基于决策变量构建潮流约束.考虑开关的优化配置,将可靠性综合成本引入模型,并对场景进行解耦,基于网络流模型构建故障功率流变量实现具有可靠性的数学约束化建模分析.综合多方面成本建立集电系统规划模型,将风机聚类后,进行集中式优化得到最优的拓扑设计.同时,提出标准成本的概念以综合评判设计方案与求解模型的优劣.最后,通过该方法与现有方法的算例对比,说明该方法得到的方案具有更低的标准成本,该模型具有更好的计算精度.综上,所提出的模型及方法更适宜于集电系统的规划分析问题.

由社会资本投资的大量分布式电源(Distribution Generation,DG)接入配电网势必对配电网稳定与经济运行带来诸多挑战.为了对DG进行合理规划,以我国电力改革的实际情况为背景,从配电公司(Distribution System Company,DISCO)和分布式电源运营商(Distributed Generation Owners,DGOs)的利益角度出发,构建基于主从博弈的DISCO配电网扩展规划的双层优化模型.上层决策以DISCO的成本最小化为目标,综合考虑各年配电网运行约束和DG渗透率约束;而下层决策则由多个DGO的子优化问题组成,以各DGO的收益最大作为优化目标,计及各年并网容量约束.采用粒子群算法求解该双层优化模型,得到以年为单位的最优配电网扩展规划方案.基于IEEE-33节点系统进行仿真实验,验证了所提模型的有效性与先进性.

针对高压直流系统首次换相失败后在故障恢复期间的后续换相失败问题,提出一种变斜率动态电流偏差控制方法.该方法基于瞬时电压实时检测换流母线电压幅值,根据换流母线电压跌落量自适应提高曲线斜率和关断角最大增量,增大故障恢复过程中的实际关断角裕度,有效降低后续换相失败的发生概率.最后,在PSCAD/EMTDC中搭建CIGRE标准模型对所提策略进行仿真测试,不同交流故障类型下的测试结果验证了所提变斜率动态电流偏差控制方法的有效性.

Aiming at the transient overvoltage problem of high proportion new energy multi direct current (DC) transmission system caused by DC blocking fault, the interaction mechanism between multiple DC lines is analyzed firstly and the multi-outfeed voltage infection factor is introduced, which reveals the fundamental reason of transient overvoltage of other sound DC near area alternating current (AC) systems caused by DC blocking. Secondly, based on the quantitative relationship between reactive power output of the synchronous condenser in different time scales and rectifier side commutation bus voltage and improved rectifier side control of DC system, the capacity of the synchronous condenser installed on the rectifier side bus is configured and the required investment capacity is reduced. Thirdly, based on the above strategy, integrating the reactive power regulation capability of the synchronous condenser and rectifier, a transient overvoltage suppression strategy with coordinated cooperation of multi DC and multi reactive power equipment is proposed. Finally, a double-circuit DC transmission system model is built in PSCAD simulation platform to verify the suppression effect of the proposed coordination strategy on transient overvoltage and the configuration effect of condenser capacity.

综合能源环境下的配网规划复杂性强,分布式电源数量众多,为使配电网规划具有一定的简便性,提出无差异模式规划(简称无差异规划)的概念,即负荷需求(指负荷密度及供电可靠性)相似的分区内各类设备容量的近似一致性规划,且设备数量与分区面积近似成正比关系.无差异规划以牺牲准确性为代价,换取规划的简便性,在复杂环境下的配电网规划类问题中具有一定优势.研究了配电系统、热力系统及分布式电源耦合环境下的配电网无差异规划问题,各主体均可以选择自身的行为模式.通过算例,验证了无差异规划的可行性,并分析了综合能源环境下各主体不同的行为模式对配电网无差异规划的影响及修正方法,验证了其在综合能源环境下的适用性.

作为"碳达峰,碳中和"目标实现的重要部分,电力系统的低碳化转型始终是中国能源行业的关键问题.为了更好地实现能源资源的优化配置和低碳目标的顺利实现,建立了基于多阶段随机规划和多区域电源结构规划的中国未来电源结构发展规划模型.模型以规划期内总成本的期望值最小为目标,计及电力电量平衡、调峰平衡、区域互联等多方面约束条件,并引入了序贯决策所需的非预期约束条件使得规划结果集在多个不确定场景下分别达到最优,更好地模拟未来发展决策过程.考虑中国未来负荷和用电量增长的不确定性,文章对2020-2060年中国电源装机结构和发电结构进行规划,预测和分析了中国未来电源的发展和演进情况.

This paper examines the path of new energy development in China against the backdrop of carbon maximum and carbon neutralization, and studies the risk of large scale new energy power transmission. In order to solve the complex uncertainty challenges of renewables power and power grid expansion planning, this paper studies and proposes an optimal economic planning model, which includes the thermal power generation start-up and shutdown expenses during the operation, the hydro power generation expenses of surplus water of reservoir, and the curtail penalty cost of new energy output power, the investment of new planning lines. The model has also considered the constraints of balance for power generation and load consumption, the power change rate, and operation, which are calculated based on the time-series operation simulation of new energy power system. Based on the functions, the process of power grid planning technology has been proposed. The planning model proposed in this paper can consider the new energy power characteristics of generation, realize the optimal planning of different power grid schemes. According to the case study findings, the new transmission line can relieve the pressure of local new energy transmission, while also improving power flow distribution as well as the rate of new energy utilization.

The volatility and uncertainty of renewable energy sources aggravate the difficulties of power consumption balance in the new power system. One practical approach is to equip the grid with sufficient energy storage to reduce the operation risk. This paper focuses on a provincial grid with a heavy power outward delivery burden and its storage allocation problem. First, the optimization model with minimum storage allocation is established. Scenarios are constructed based on the typical set and the validation set. Second, a data-driven method is applied to build the typical set by k-means++. To describe the tolerance of wind and solar curtailed and delivery shedding, a chance-constrained approach is established and converted to linear constraints by big-M. The case study shows the power system needs considerable energy storage to ensure renewable energy consumption and delivery. With the lower tolerance, the allocated storage capacity will increase, and the lowest feasible tolerance is limited by scenarios with poor renewable output.

With the development of economy and society, the utilization rate of energy is getting higher and higher, and the energy problem is becoming more and more serious. Therefore, new energy has received extensive attention from all walks of life. New energy occupies a relatively high proportion of the power grid, which brings new challenges to the operation of the power grid, especially the power generation power system connected to the power grid by the inverter to regulate the power of the power grid. Under these conditions, this paper proposes to apply the dual-loop control algorithm simulation technology to the power regulation of the new energy grid, aiming to realize the rapid regulation of the power of the new energy grid. This article conducted a questionnaire survey on the impact of new energy grid output power on residential electricity consumption. The survey results showed that: Residents in the community have the highest annual electricity consumption in August, at 24880 KW/h, and less electricity consumption in a suitable weather month, at about 9100 KW/h; among the household appliances investigated, the air conditioner has the highest power, with an average use time of 4-8h/day, and the average use time of the hair dryer with the lowest power is 0.6 h/day; among the 300 users, 59% have higher requirements for the stability of the input electric energy, and only 0.5% have no requirements for the stability of the input electric energy.