[go: up one dir, main page]

WO2023108384A1 - Procédé de commande de commutation d'application multi-scénario de stockage d'énergie basé sur un indice d'identification complet - Google Patents

Procédé de commande de commutation d'application multi-scénario de stockage d'énergie basé sur un indice d'identification complet Download PDF

Info

Publication number
WO2023108384A1
WO2023108384A1 PCT/CN2021/137684 CN2021137684W WO2023108384A1 WO 2023108384 A1 WO2023108384 A1 WO 2023108384A1 CN 2021137684 W CN2021137684 W CN 2021137684W WO 2023108384 A1 WO2023108384 A1 WO 2023108384A1
Authority
WO
WIPO (PCT)
Prior art keywords
energy storage
transient
regulation
planning
frequency
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
PCT/CN2021/137684
Other languages
English (en)
Chinese (zh)
Inventor
郑军
王雪燕
朱优优
尹绍杰
林鹏
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Taizhou Institute of Zhejiang University
Original Assignee
Taizhou Institute of Zhejiang University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Taizhou Institute of Zhejiang University filed Critical Taizhou Institute of Zhejiang University
Priority to PCT/CN2021/137684 priority Critical patent/WO2023108384A1/fr
Publication of WO2023108384A1 publication Critical patent/WO2023108384A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

Links

Images

Classifications

    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for AC mains or AC distribution networks
    • H02J3/12—Circuit arrangements for AC mains or AC distribution networks for adjusting voltage in AC networks by changing a characteristic of the network load
    • H02J3/16—Circuit arrangements for AC mains or AC distribution networks for adjusting voltage in AC networks by changing a characteristic of the network load by adjustment of reactive power
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for AC mains or AC distribution networks
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for AC mains or AC distribution networks
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means

Definitions

  • the invention relates to an energy storage control method, in particular to an energy storage multi-scenario application switching control method based on comprehensive identification indicators.
  • the demand of the power grid in each time period may be different.
  • the invention is oriented to the demand of the power grid and solves the actual power grid problem through a single energy storage.
  • the specific solution provided is as follows:
  • a method for switching control of energy storage multi-scenario applications based on comprehensive identification indicators comprising the following steps:
  • the predictable and planned demand scenarios described in S2 may be: peak shaving, steady-state voltage regulation, and steady-state frequency regulation; the unpredictable and planned demand scenarios may specifically be: transient voltage regulation, Transient FM.
  • S3 is specifically, dividing the day into a main peak-shaving period and a main pressure-regulating period on a time scale, with daytime being the main peak-shaving period and night-time being the main pressure-regulating period.
  • S4 is specifically, wherein, in the main peak shaving period, peak shaving is the main one, the PCS capacity first meets the peak shaving, and the energy storage active output curve is obtained after determining the peak shaving line and the valley filling line through the load forecasting curve, And the reactive power margin curve of energy storage used for voltage regulation is obtained through the energy storage plan; in the main voltage regulation period, the voltage regulation is the main one, and the PCS first meets the voltage regulation.
  • the energy storage constant low power is first set Charging until the end of the main voltage regulation period is just completed, and a constant reactive power margin is obtained according to the remaining capacity of the PCS.
  • the energy storage alone undertakes the task of voltage regulation; if the required reactive power output is greater than the reactive power margin, the required reactive power output is first compared with the unit capacitor capacity Judging whether the ratio of the remaining value to the unit capacitor capacity exceeds the set threshold, if it is, it means that the capacitor voltage regulation will cause overshoot or overshoot due to the limitation of the unit capacitor capacity, and the energy storage auxiliary capacitor is used for fine voltage regulation. Otherwise, it means that the capacitor voltage regulation is sufficient to achieve voltage regulation accuracy, and the capacitor alone undertakes the voltage regulation work.
  • transient frequency modulation and transient voltage regulation are transient frequency modulation and transient voltage regulation.
  • the identification index of transient frequency modulation exceeds a certain threshold, it is identified as transient frequency modulation. If the index exceeds a certain threshold, it will be identified as a transient voltage regulation; the identification index can specifically be:
  • the identification index of transient frequency modulation includes the comprehensive frequency modulation identification index ⁇ F t :
  • ⁇ f is the frequency deviation
  • ⁇ f i is the frequency deviation corresponding to the real-time power deviation
  • all three are per unit values
  • K G is the unit regulation power of the unit
  • K D is the frequency regulation effect coefficient of the load
  • ⁇ p is the real-time power deviation
  • the advantage of the integrated frequency modulation identification index is that the conventional identification index will cause a series of misoperations such as frequency overshoot and reverse adjustment of the adaptive energy storage control due to the small time scale of frequency change and the large system delay.
  • the indicator introduces a real-time power deviation ⁇ p to make up for the frequency deviation caused by the power deviation outside the day-ahead plan, which can prevent malfunctions during frequency modulation, including late actions and over-actions;
  • the identification index of transient voltage regulation can be the voltage deviation ⁇ u in the conventional identification method, or the following comprehensive voltage regulation identification index ⁇ U t :
  • u(t) is the real-time voltage value of grid-connected point
  • u PCCN is the rated value of grid-connected voltage
  • ⁇ u i is the cumulative change of voltage
  • ⁇ u, ⁇ u i All are per unit values.
  • the present invention proposes a multi-scenario application switching control method, aiming to adapt energy storage to different power grids through energy storage access.
  • the access of energy storage and built-in control methods can solve as many problems as possible in the current power grid. Additional aspects and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
  • Fig. 1 is a flow chart of the steps of the energy storage multi-scenario application switching control method based on the comprehensive identification index according to the embodiment of the present invention
  • Fig. 2 is a time period arrangement and planning diagram of the peak regulation and the steady-state voltage regulation on a typical day in the embodiment of the present invention
  • Fig. 3 is the specific flowchart of S4 in the embodiment of the present invention.
  • Fig. 4 is the specific flowchart of S6 in the embodiment of the present invention.
  • Fig. 5 is the specific flowchart of S8 in the embodiment of the present invention.
  • Fig. 6 is a diagram of energy storage SOC calibration and recovery at set time intervals in an embodiment of the present invention.
  • a comprehensive identification index-based energy storage multi-scenario application switching control method provided by the embodiment of the present invention includes the following steps:
  • the predictable and planned demand scenarios described in S2 can specifically be: peak shaving, steady-state voltage regulation, and steady-state frequency regulation; the unpredictable and planned demand scenarios can be specifically: transient voltage regulation, temporary State FM.
  • the grid demand scenarios determined by the actual grid data in preset S1 of the embodiment include: peak regulation, steady voltage regulation, transient voltage regulation and transient frequency regulation. According to the above S2, it can be seen that the peak regulation and steady-state voltage regulation scenarios are predictable and planned demand scenarios, and the transient voltage regulation and transient frequency regulation are unpredictable and planned demand scenarios.
  • the S3 specifically may be:
  • the changing law of the total regional load is consistent with the changing law of the substation load.
  • the load size shows an upward trend in the morning (6:00-11:00), a downward trend in the evening (20:00-4:00), and a downward trend in the noon (11:00-12:00) and evening (18:00 ⁇ 20:00) there is a big peak and a small peak respectively, and there is a big trough in the early morning (2:00 ⁇ 5:00). Therefore, there is no essential difference between the energy storage installed on the 10kV bus of the substation for peak-shaving and valley-filling of the total regional load and the peak-shaving and valley-filling of the substation load, and the same effect can be achieved.
  • the changing law of the load is basically opposite to that of the bus voltage. In the morning (6:00-11:00) the voltage drops when the load increases, and in the evening (20:00-4:00) the voltage rises when the load decreases.
  • the voltage is basically at a low level, but when the load is at a high level, it has crossed the peak clipping line many times and the maximum value is higher than the peak clipping line by a certain distance, while the voltage is basically not low at a low level
  • the upper limit and the voltage basically exceeds the limit in the valley filling area. Therefore, there is no need to consider steady-state voltage regulation when energy storage is in the peak-shaving area, but it needs to be considered when it is in the valley-filling area.
  • the voltage is at a high level and exceeds the limit for a long time when the load is low, which is caused by the lack of reactors in many substations in the power grid.
  • Excessive voltage will lead to: 1The transformer is over-excited, which greatly increases the loss of the iron core; 2Accelerates the aging of electrical equipment and reduces the service life; 3It leads to damage to industrial equipment and unqualified industrial products.
  • the switching control plan of the energy storage planned peak shaving/planned voltage regulation can specifically be:
  • the day is divided into the main peak-shaving period and the main pressure-regulating period according to the time scale.
  • the daytime is the main peak-shaving period
  • the night-time is the main pressure-regulating period.
  • the division of the specific time nodes is obtained according to the following data analysis, as shown in Table 1.
  • the area where the time node for switching between the main voltage regulation period and the main peak shaving period is located is 9:00-10:15, and the corresponding appropriate point in the area is selected as the time node for switching.
  • the S4 can specifically be:
  • the peak shaving is the main one.
  • the PCS capacity first meets the peak shaving. After determining the peak shaving line and the valley filling line through the load forecasting curve, the energy storage active output curve is obtained, and the output of the energy storage plan is obtained.
  • the energy storage alone undertakes the task of voltage regulation; if the required reactive power output is greater than the reactive power margin, the required reactive power output is first compared with the unit capacitor capacity Judging whether the ratio of the remaining value to the unit capacitor capacity exceeds the set threshold, if it is, it means that the capacitor voltage regulation will cause overshoot or overshoot due to the limitation of the unit capacitor capacity, so the energy storage auxiliary capacitor is used for fine voltage regulation , otherwise it means that the capacitor voltage regulation is sufficient to achieve voltage regulation accuracy, so the capacitor alone undertakes the voltage regulation work.
  • the demand scenarios for unpredictable planning described in S5 are transient frequency modulation and transient voltage regulation.
  • the identification index of transient frequency modulation exceeds a certain threshold, it is identified as transient frequency modulation.
  • the identification index of transient voltage regulation exceeds A certain threshold value is identified as a transient voltage regulation; the identification index can be specifically:
  • the frequency modulation identification index can be the frequency deviation ⁇ f in the conventional identification method, and can also be the following comprehensive frequency modulation identification index ⁇ F t :
  • ⁇ f is the frequency deviation
  • ⁇ f i is the frequency deviation corresponding to the real-time power deviation
  • all three are per unit values
  • K G is the unit regulation power of the unit
  • K D is the frequency regulation effect coefficient of the load
  • ⁇ p is the real-time power deviation.
  • the advantage of the integrated frequency modulation identification index is that the conventional identification index will cause a series of misoperations such as frequency overshoot and reverse adjustment of the adaptive energy storage control due to the small time scale of frequency change and the large system delay.
  • the indicator introduces a real-time power deviation ⁇ p to make up for the frequency deviation caused by the power deviation outside the day-ahead plan, which can prevent misoperation during frequency modulation, including late action and over action.
  • the voltage regulation identification index can be the voltage deviation ⁇ u in the conventional identification method, or the following comprehensive voltage regulation identification index ⁇ U t :
  • u(t) is the real-time voltage value of grid-connected point
  • u PCCN is the rated value of grid-connected voltage
  • ⁇ u i is the cumulative change of voltage
  • ⁇ u, ⁇ u i All are per unit values.
  • the advantage of the comprehensive voltage regulation identification index is the same as that of the comprehensive frequency modulation identification index.
  • the handover index described in S6 is used to judge whether the handover is completed, and the handover index may include impact factors on other scenarios and result factors of energy storage participating in the scene.
  • the switching index can be specifically shown in the following formula:
  • ⁇ 1 and ⁇ 2 are the weights of the result factor and the impact factor respectively;
  • R fro-bac and I fro-bac are the result weight and the impact factor respectively;
  • ⁇ x bac-fro is the weight of the original scene target parameter x before and after the energy storage scene switch
  • ⁇ x fro is the deviation of the original scene target parameter x before the energy storage switch;
  • ⁇ y bac-fro is the change of the next scene target parameter y before and after the energy storage switch;
  • ⁇ y fro is the next field experience before the energy storage switch The deviation of the target parameter y.
  • the impact factor is the impact of the exit of the previous scene and the addition of this scene on the target parameters of the previous scene, that is, the previous The amount of change of the target parameter of a scene before and after switching;
  • the result factor is the impact of the energy storage on the result of the target parameter of the scene after participating in the scene, that is, the change of the target parameter of the scene before and after switching.
  • the determination of the weights of ⁇ 1 and ⁇ 2 can be specifically as follows:
  • the urgency index is an index established to measure the degree of deviation of the target quantity of the scene, and to reflect the severity of the current scene.
  • the importance index is to measure the importance of pairwise comparisons between scenarios, for example, it is known that the importance index of the frequency modulation scenario should be higher than that of the voltage regulation scenario.
  • the definition formula of the comprehensive index is as follows, which is the product of the urgency index and the importance index.
  • the demand scenario of unpredictable planning is identified. If a single scenario is identified, it is judged whether the energy storage is currently being applied to the demand scenario of predictable planning, and if not, it directly enters the identified demand scenario. Unpredictable planned demand scenarios, if so, calculate the switching index and compare it with the set threshold to choose whether to switch the scenario;
  • the two demand scenarios of transient voltage regulation and transient frequency regulation are identified, it is judged whether the energy storage is currently being applied in the predictable and planned demand scenario, and if not, the transient voltage regulation and transient frequency regulation are calculated.
  • the switching index of the two demand scenarios of transient frequency modulation and compare the size of the two switching indexes choose to enter one of the two demand scenarios of transient voltage regulation and transient frequency modulation, and if so, calculate the The switching index of the two demand scenarios of transient voltage regulation and transient frequency modulation and compare the two switching indexes with the set threshold value, and select whether to switch and switch to the transient voltage regulation scenario or the transient frequency modulation scenario.
  • the size of the comparison handover index described in S8 can be specifically selected to enter the scene as follows:
  • the present invention proposes the following two methods to solve the power conservation problem:
  • Method 1 Divide the energy storage capacity into virtual planning capacity and virtual scheduling capacity, where the virtual planning capacity is used to determine the output of the peak-shaving plan, and determine the peak-shaving line and valley-filling line of the peak-shaving scenario according to the divided virtual planning capacity;
  • the virtual dispatching capacity is used to increase or decrease active power in the frequency modulation scenario. If the virtual dispatching capacity is 0 and the frequency modulation scenario requires energy storage and discharge, the energy storage will not participate in the frequency modulation scenario; if the virtual dispatching capacity is at its maximum value, the frequency modulation scenario requires energy storage and charging , the energy storage does not participate in the frequency modulation scenario.
  • Method 2 Set a time interval to restore the SOC of the energy storage. As shown in Figure 6, it can be specifically:
  • the power consumption of the frequency adjustment scene will be charged at a constant power in the energy recovery area, as shown in the area 1 in the figure.
  • the calculation of the charging power is as follows.
  • the charging time is from It starts at t 1 and ends at t 1 + ⁇ t; if the previous frequency modulation is aimed at the sudden increase in frequency, then the power is stored in the frequency modulation scene, and the stored energy is discharged at constant power in the power recovery area, as shown in area 2 in the figure , the discharge power is as follows, the discharge time starts from t 2 - ⁇ t and ends at t 2 .
  • ⁇ t is the duration of constant power electric quantity recovery
  • t 1 is the start time of the energy storage non-action area between the main voltage regulation area and the peak-shaving area
  • t 2 is the energy storage non-action area between the main voltage regulation area and the The end time between the peak shaving areas
  • P peak is the energy storage peak shaving line
  • P valley is the energy storage valley filling line.

Landscapes

  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Supply And Distribution Of Alternating Current (AREA)

Abstract

Est divulgué un procédé de commande de commutation d'application multi-scénario de stockage d'énergie basé sur un indice d'identification complet, consistant : à analyser des scénarios de demande de réseau électrique selon des données de réseau électrique réelles ; à diviser les scénarios de demande en scénarios de demande de planification prévisibles et en scénarios de demande de planification imprévisibles ; à déterminer, au moyen de données historiques et d'une analyse de données de la veille, l'aménagement de période de temps et la planification du jour des scénarios de demande de planification prévisibles ; à déterminer un procédé de calcul pour la sortie de puissance active réelle et la sortie de puissance réactive du stockage d'énergie dans une période de temps de chaque scénario de demande de planification prévisible ; à établir un indice d'identification pour achever l'identification d'un scénario de demande de planification imprévisible ; et à établir un indice de commutation pour déterminer s'il faut achever la commutation du scénario de demande de planification imprévisible. Sur la base d'une politique de commande d'une pluralité de scénarios d'application d'un réseau électrique d'accès au stockage d'énergie actuel et par combinaison d'une analyse de demande de réseau électrique réelle, la présente invention concerne un procédé de commande de commutation d'application multi-scénario, et vise à réaliser l'objectif de satisfaire pleinement les demandes de différents réseaux électriques au moyen d'un accès au stockage d'énergie et par la réalisation d'une transformation adaptative qui convient à différents réseaux électriques sur ces derniers.
PCT/CN2021/137684 2021-12-14 2021-12-14 Procédé de commande de commutation d'application multi-scénario de stockage d'énergie basé sur un indice d'identification complet Ceased WO2023108384A1 (fr)

Priority Applications (1)

Application Number Priority Date Filing Date Title
PCT/CN2021/137684 WO2023108384A1 (fr) 2021-12-14 2021-12-14 Procédé de commande de commutation d'application multi-scénario de stockage d'énergie basé sur un indice d'identification complet

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/CN2021/137684 WO2023108384A1 (fr) 2021-12-14 2021-12-14 Procédé de commande de commutation d'application multi-scénario de stockage d'énergie basé sur un indice d'identification complet

Publications (1)

Publication Number Publication Date
WO2023108384A1 true WO2023108384A1 (fr) 2023-06-22

Family

ID=86774956

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2021/137684 Ceased WO2023108384A1 (fr) 2021-12-14 2021-12-14 Procédé de commande de commutation d'application multi-scénario de stockage d'énergie basé sur un indice d'identification complet

Country Status (1)

Country Link
WO (1) WO2023108384A1 (fr)

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117424255A (zh) * 2023-11-28 2024-01-19 广东电网有限责任公司广州供电局 一种改进下垂综合控制的用户侧构网型储能快速调频控制方法
CN117439133A (zh) * 2023-12-21 2024-01-23 山东省科学院能源研究所 基于负荷预测算法的公共建筑可再生能源多能互补系统
CN119738611A (zh) * 2024-12-24 2025-04-01 许昌开普检测研究院股份有限公司 一种储能型功率测试平台的配置及能量管理方法
CN120341859A (zh) * 2025-06-18 2025-07-18 国网冀北电力有限公司经济技术研究院 一种基于多场景融合的灵活性资源适应性配置方法
CN120414574A (zh) * 2025-07-03 2025-08-01 国网内蒙古东部电力有限公司通辽供电公司 一种基于负荷控制公平有效性考量的非固定式负荷精准切除方法

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20160079778A1 (en) * 2013-04-29 2016-03-17 Welsengen Limited Apparatus and method for managing stored energy
CN105449701A (zh) * 2016-01-18 2016-03-30 华北电力科学研究院有限责任公司 一种储能系统参与电网频率控制的方法及装置
CN105490292A (zh) * 2016-01-18 2016-04-13 华北电力科学研究院有限责任公司 一种储能系统参与电网二次频率控制的方法及装置
CN110264110A (zh) * 2019-07-08 2019-09-20 国网湖南省电力有限公司 基于配电网多应用场景的储能电站选址定容方法
CN110311397A (zh) * 2019-07-26 2019-10-08 国网湖南省电力有限公司 基于自适应识别的储能电站多场景协同控制方法
CN110401211A (zh) * 2019-07-26 2019-11-01 国网湖南省电力有限公司 基于特征提取的储能电站工作场景识别方法
CN111162547A (zh) * 2020-01-03 2020-05-15 浙江大学台州研究院 一种储能多场景应用切换控制方法

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20160079778A1 (en) * 2013-04-29 2016-03-17 Welsengen Limited Apparatus and method for managing stored energy
CN105449701A (zh) * 2016-01-18 2016-03-30 华北电力科学研究院有限责任公司 一种储能系统参与电网频率控制的方法及装置
CN105490292A (zh) * 2016-01-18 2016-04-13 华北电力科学研究院有限责任公司 一种储能系统参与电网二次频率控制的方法及装置
CN110264110A (zh) * 2019-07-08 2019-09-20 国网湖南省电力有限公司 基于配电网多应用场景的储能电站选址定容方法
CN110311397A (zh) * 2019-07-26 2019-10-08 国网湖南省电力有限公司 基于自适应识别的储能电站多场景协同控制方法
CN110401211A (zh) * 2019-07-26 2019-11-01 国网湖南省电力有限公司 基于特征提取的储能电站工作场景识别方法
CN111162547A (zh) * 2020-01-03 2020-05-15 浙江大学台州研究院 一种储能多场景应用切换控制方法
CN112952848A (zh) * 2020-01-03 2021-06-11 浙江大学台州研究院 一种基于综合识别指标的储能多场景应用切换控制方法

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
RUO LI, LI XINRAN, TAN ZHUANGXI, HUANG JIYUAN, MA ZHIHUI: "Integrated Control Strategy Considering Energy Storage Battery Participating in Secondary Frequency Regulation", AUTOMATION OF ELECTRIC POWER SYSTEMS, vol. 42, no. 8, 25 April 2018 (2018-04-25), pages 74 - 82, XP093072164 *

Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117424255A (zh) * 2023-11-28 2024-01-19 广东电网有限责任公司广州供电局 一种改进下垂综合控制的用户侧构网型储能快速调频控制方法
CN117424255B (zh) * 2023-11-28 2024-04-19 广东电网有限责任公司广州供电局 一种改进下垂综合控制的用户侧构网型储能快速调频控制方法
CN117439133A (zh) * 2023-12-21 2024-01-23 山东省科学院能源研究所 基于负荷预测算法的公共建筑可再生能源多能互补系统
CN117439133B (zh) * 2023-12-21 2024-05-03 山东省科学院能源研究所 基于负荷预测算法的公共建筑可再生能源多能互补系统
CN119738611A (zh) * 2024-12-24 2025-04-01 许昌开普检测研究院股份有限公司 一种储能型功率测试平台的配置及能量管理方法
CN120341859A (zh) * 2025-06-18 2025-07-18 国网冀北电力有限公司经济技术研究院 一种基于多场景融合的灵活性资源适应性配置方法
CN120414574A (zh) * 2025-07-03 2025-08-01 国网内蒙古东部电力有限公司通辽供电公司 一种基于负荷控制公平有效性考量的非固定式负荷精准切除方法

Similar Documents

Publication Publication Date Title
CN112952848B (zh) 一种基于综合识别指标的储能多场景应用切换控制方法
WO2023108384A1 (fr) Procédé de commande de commutation d'application multi-scénario de stockage d'énergie basé sur un indice d'identification complet
CN111416367B (zh) 一种储能多场景应用协同控制方法
CN106972516B (zh) 一种适用于微网的多类型储能多级控制方法
US12074443B2 (en) Source-grid-load-storage networked collaborative frequency control method
CN105529793B (zh) 一种同时作为应急供电源的电动汽车群充电微网的控制方法
CN107480833B (zh) 一种风电发电系统调峰能力评估方法
CN107834567A (zh) 特高压直流换流站与近区发电厂的无功电压协调控制方法
CN108565887A (zh) 储能环节维持微电网母线电压分区曲线动态下垂控制方法
CN108418255A (zh) 一种适用于含高渗透率新能源的特高压直流外送电网规划方法及系统
CN103997052B (zh) 一种多储能电站的有功功率控制的方法
CN103545814B (zh) 一种交直流混合电力系统协调电压控制方法
CN112928769B (zh) 一种兼顾补偿预测误差和平抑波动的光伏混合储能控制方法
CN119070326B (zh) 一种低压配电台区电能质量网格化区域协同综合治理方法及装置
CN110994626B (zh) 基于电压趋势预测的500-220kV区域电网自动电压控制方法
Saleh et al. One-node method to implement smart grid functions using a battery storage system
CN110535119A (zh) 适应电网调峰调频的储能电站时段电量滚动控制方法
CN115663791A (zh) 基于运行环境时变性的智能配电网多目标自适应调度方法
CN117081177B (zh) 一种孤岛模式下水电主调机组微电网运行功率控制方法
CN118572835A (zh) 一种微电网分布式储能系统及其电池soc均衡控制方法
CN107579530A (zh) 一种电网的低频减载方法及低频减载控制系统
CN117495186A (zh) 一种虚拟智能电网的稳定运行评估方法
CN110429614A (zh) 模拟低频减载控制模式的分布式储能装置频率控制方法
CN115693753A (zh) 一种基于负荷虚拟储能的多区域协调控制方法
CN115549158A (zh) 一种含有时间因子的电化学储能电站发电预测方法及系统

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 21967525

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 21967525

Country of ref document: EP

Kind code of ref document: A1