CN114123257A - Day-ahead scheduling method considering energy storage power constraint - Google Patents

Day-ahead scheduling method considering energy storage power constraint Download PDF

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Publication number
CN114123257A
CN114123257A CN202111313961.4A CN202111313961A CN114123257A CN 114123257 A CN114123257 A CN 114123257A CN 202111313961 A CN202111313961 A CN 202111313961A CN 114123257 A CN114123257 A CN 114123257A
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energy storage
power
storage power
power station
peak
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Inventor
韩旭杉
王维洲
周强
吴悦
张彦琪
马志程
马彦宏
吕清泉
刘炽
申自裕
张尧翔
曾贇
曹钰
王佳浩
王定美
张金平
李津
张睿骁
韩小齐
庞清仑
刘淳
保承家
张健美
张珍珍
高鹏飞
杨美颖
张雯程
刘紫东
刘文颖
刘丽娟
郑翔宇
沈琛云
刘海伟
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STATE GRID GASU ELECTRIC POWER RESEARCH INSTITUTE
State Grid Corp of China SGCC
North China Electric Power University
State Grid Gansu Electric Power Co Ltd
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STATE GRID GASU ELECTRIC POWER RESEARCH INSTITUTE
State Grid Corp of China SGCC
North China Electric Power University
State Grid Gansu Electric Power Co Ltd
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Priority to CN202111313961.4A priority Critical patent/CN114123257A/en
Publication of CN114123257A publication Critical patent/CN114123257A/en
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    • 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
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06312—Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Electricity, gas or water supply
    • 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
    • H02J3/003—Load forecast, e.g. methods or systems for forecasting future load demand
    • 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
    • H02J3/004—Generation forecast, e.g. methods or systems for forecasting future energy generation
    • 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
    • H02J3/007—Arrangements for selectively connecting the load or loads to one or several among a plurality of power lines or power sources
    • H02J3/0075—Arrangements for selectively connecting the load or loads to one or several among a plurality of power lines or power sources for providing alternative feeding paths between load and source according to economic or energy efficiency considerations, e.g. economic dispatch
    • 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
    • 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
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/381—Dispersed generators
    • 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
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
    • 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
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • 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
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/22—The renewable source being solar energy
    • H02J2300/24—The renewable source being solar energy of photovoltaic origin
    • 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
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/28—The renewable source being wind 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
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/40—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation wherein a plurality of decentralised, dispersed or local energy generation technologies are operated simultaneously
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/50—Photovoltaic [PV] energy
    • Y02E10/56—Power conversion systems, e.g. maximum power point trackers
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/70—Wind energy
    • Y02E10/76—Power conversion electric or electronic aspects
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E70/00—Other energy conversion or management systems reducing GHG emissions
    • Y02E70/30—Systems combining energy storage with energy generation of non-fossil origin
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
    • Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications

Abstract

The invention provides a day-ahead scheduling method considering energy storage power constraint, which comprises the following steps: acquiring day-ahead prediction data of wind power, photovoltaic power and load power of a power grid, and calculating equivalent load power (algebraic sum of wind power, photovoltaic power and load power); calculating the peak load regulation requirement of the system; under the condition of considering energy storage power constraint, establishing an energy storage power station regulation model; and calculating the charging/discharging time period of the energy storage power station participating in system peak shaving. The energy storage power station is coordinated and dispatched with a conventional power supply to perform charging and discharging regulation, the energy storage power station is charged when wind power and photovoltaic power are in a large power generation state, and the energy storage power station is discharged when the wind power and the photovoltaic power are in a small power generation state so as to reduce the peak-valley difference of the system, stabilize the large fluctuation of the peak-valley of the system caused by the random fluctuation of the wind power and the photovoltaic power and achieve the purpose of improving the peak regulation capacity of the system. However, in the source-storage coordination scheduling process, the energy storage regulation characteristic, especially the energy storage power constraint, needs to be considered sufficiently to prevent the overcharge and the overdischarge of power, so as to prolong the service life of the energy storage battery.

Description

Day-ahead scheduling method considering energy storage power constraint
Technical Field
The invention belongs to the technical field of source-storage peak shaving, and particularly relates to a day-ahead scheduling method considering energy storage power constraint.
Background
With the increasing of power consumers, the demand of power has a larger peak-to-valley difference in daytime, at night and in different seasons, and from the perspective of construction cost and resource protection, it is more and more difficult to meet the demand of peak load through newly added distribution, transmission and distribution equipment, and the demand of users on power supply reliability and peak regulation is higher and higher. Therefore, a large-scale energy storage power station which is economical and quick in response is established, the off-peak electric energy is converted into the peak electric energy, an effective way for realizing decoupling and load adjustment between power generation and power utilization is provided, and the premise of marketization of the power industry is provided. The energy storage power station can store electric energy in a large wind-solar power generation period and serve as a power supply in the large wind-solar power generation period, and the purposes of peak clipping and valley filling are achieved. The energy storage power station participates in peak regulation scheduling of the power grid, power fluctuation of the power system can be effectively improved, stability of power is guaranteed, and accordingly the integral peak regulation capacity of the power grid is improved.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to provide a day-ahead scheduling method considering energy storage power constraint, which has small calculated amount and is close to practical engineering application.
The day-ahead scheduling method considering the energy storage power constraint comprises the following steps:
s1: acquiring day-ahead prediction data of wind power, photovoltaic and load power of a power grid, and calculating equivalent load of the system;
s2: calculating the peak load regulation requirement of the system;
s3: under the condition of considering energy storage power constraint, establishing an energy storage power station regulation model;
s4: calculating the charging/discharging time period of the energy storage power station participating in system peak regulation;
s5: the energy storage power station and a conventional power supply perform source-storage coordination scheduling, and the system peak regulation capacity is improved.
The S1 includes the steps of:
s101: calculating the equivalent load of the system (the equivalent load is the algebraic sum of the wind power, the photovoltaic power and the load power) according to the predicted day-ahead wind power, photovoltaic power and load power prediction data, and drawing a system equivalent load curve;
s102: and calculating the peak value of the equivalent load curve and the valley value of the equivalent load curve.
The S2 includes the steps of:
s201: and calculating the peak regulation requirement of the system based on the peak value of the equivalent load curve and the valley value of the equivalent load curve.
The S3 includes the steps of:
s301: determining an electrical power constraint of the energy storage power station;
s302: the charge state of the energy storage power station is restrained;
s303: and establishing an energy storage power station regulation model.
The S4 includes the steps of:
s401: setting step length PkMake a horizontal straight line P1＝Plmin+kPkIntersecting the predicted daily load curve at a point t1，t2…t2n-1，t2n；
S402: the charging time t needed by the energy storage power station at the time is obtainedc；
S403: if the maximum charging time is greater than tcIf k is k +1, repeating the operation;
s404: if maximum charging is requiredElectricity time less than tcIf so, the energy storage power station operates in a charging mode at a set power;
s405: setting step length PrMake a horizontal straight line P2＝Plmax-rPrAnd intersects with the predicted daily load curve at point t'1，t′2…t′2n-1，t′2n；
S406: the required discharge time t of the energy storage power station at the time is obtainedf；
S407: if the maximum discharge time is greater than tfIf r is r +1, repeating the operation;
s408: if the maximum discharge time is less than tfAnd the energy storage power station operates in a discharging mode at the set power.
The S5 includes the steps of:
s501: calculating the load peak-valley difference before and after the energy storage power station participates in regulation;
s502: and calculating the peak regulation capacity of the system before and after the energy storage power station participates in regulation.
The invention provides a day-ahead scheduling method considering energy storage power constraint, which comprises the following steps: acquiring day-ahead prediction data of wind power, photovoltaic and load power of a power grid, and calculating equivalent load of the system; based on this, calculating the peak load demand of the system; then, under the condition of considering energy storage power constraint, establishing an energy storage power station regulation model; calculating the charging/discharging time period of the energy storage power station participating in system peak regulation; and finally, the energy storage power station and a conventional power supply perform source-storage coordination scheduling, so that the peak regulation capacity of the system is improved. And the energy storage power constraint is considered in the source storage coordination scheduling process, so that the service life of the battery energy storage system can be effectively prolonged.
Drawings
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Fig. 1 is a flowchart of a day-ahead scheduling method considering energy storage power constraints according to the present invention.
Fig. 2 is a graph of equivalent load of the energy storage power station participating in peak shaving scheduling.
FIG. 3 is a diagram of the charging and discharging power of the energy storage power station provided by the invention.
Fig. 4 is a daily equivalent load curve chart before and after the energy storage power station provided by the invention participates in peak shaving scheduling.
Detailed Description
In order to clearly understand the technical solution of the present invention, a detailed structure thereof will be set forth in the following description. It is apparent that the specific implementation of the embodiments of the present invention is not limited to the specific details familiar to those skilled in the art. Exemplary embodiments of the invention are described in detail below, and other embodiments in addition to those described in detail are possible.
The present invention will be described in further detail with reference to the accompanying drawings and examples.
Example 1
Fig. 1 is a flow chart of a method of day-ahead scheduling that takes into account energy storage power constraints. In fig. 1, a flowchart of a day-ahead scheduling method considering energy storage power constraint provided by the present invention includes:
s1: acquiring day-ahead prediction data of wind power, photovoltaic and load power of a power grid, and calculating equivalent load of the system;
s2: calculating the peak load regulation requirement of the system;
s3: under the condition of considering energy storage power constraint, establishing an energy storage power station regulation model;
s4: calculating the charging/discharging time period of the energy storage power station participating in system peak regulation;
s5: the energy storage power station and a conventional power supply perform source-storage coordination scheduling, and the system peak regulation capacity is improved. The S1 includes the steps of:
s101: drawing a day equivalent load curve according to the predicted and calculated day-ahead equivalent load data;
the S2 includes the steps of:
s202: the peak value p of the statistical equivalent load curvelmaxValley p of equivalent load curvelminAnd calculating the peak load regulation requirement of the system.
ΔPl＝plmax-plmin (1)
The S3 includes the steps of:
s301: determining an electrical power constraint of the energy storage power station;
charging and discharging power P of energy storage power stationbIn which P isbThe following formula is satisfied:
Figure BDA0003343050560000041
in the formula, when P isbWhen the power station is more than 0, the energy storage power station operates in a discharge mode when P isbWhen the voltage is less than 0, the energy storage power station operates in a charging mode; pb，maxThe maximum value of the discharge power of the energy storage power station; pb，minAnd the maximum value of the charging power of the energy storage power station is obtained.
S302: to the state of charge SOC of the energy storage power stationtAnd (4) carrying out constraint:
Figure BDA0003343050560000051
SOCmin≤SOCt≤SOCmax (4)
in the formula, SOCtThe state of charge of the energy storage power station at the moment t; enRated capacity for the energy storage power station; etThe capacity of the energy storage power station at the moment t; SOCminIs the minimum value of the state of charge, SOC, of the energy storage systemmaxIs the maximum value of the state of charge of the energy storage system.
S303: and establishing an energy storage power station regulation model.
Charging and discharging power P of energy storage power stationbMaximum charge-discharge time T under constraint:
Figure BDA0003343050560000052
the S4 includes the steps of:
s401: setting step length PkMake a horizontal straight line P1＝Plmin+kPkIntersecting the predicted daily load curve at a point t1，t2…t2n-1，t2n；
S402: the charging time t needed by the energy storage power station at the time is obtainedc：
tc＝t2n-t2n-1+…+t2-t1 (6)
S403: if the maximum charging time T is greater than TcIf k is k +1, repeating the operation;
s404: if the maximum charging time T is less than TcThen the energy storage power station to set power PbOperating in a charging mode.
S405: setting step length PrMake a horizontal straight line P2＝Plmax-rPrAnd intersects with the predicted daily load curve at point t'1，t′2…t′2n-1，t′2n；
S406: the required discharge time t of the energy storage power station at the time is obtainedf：
tf＝t′2n-t′2n-1+…+t′2-t′1 (7)
S407: if the maximum discharge time T is greater than TfIf r is r +1, repeating the operation;
s408: if the maximum discharge time T is less than TfThen the energy storage power station to set power PbOperating in a discharge mode.
The S5 includes the steps of:
s501: calculating the absolute peak-valley difference delta P of equivalent load before and after the energy storage power station participates in adjustmentl：
ΔPl＝plmax-plmin (8)
Wherein the equivalent load absolute peak-to-valley difference Δ PlCharacterizing the maximum absolute deviation of the load and the absolute peak-to-valley difference delta P of the load under a certain time scalelThe smaller the absolute deviation of the maximum load is;
s502: calculating the peak regulation capacity of the system before and after the energy storage power station participates in regulation:
ΔP＝ΔPl0-ΔPl1 (9)
wherein, the delta P represents the participation of the energy storage power station in the regulation front-back systemThe degree of improving the peak regulation capability is improved, and the larger the delta P is, the stronger the function exerted after the energy storage participates in the peak regulation scheduling is. Delta Pl1Indicating the system peak shaver demand, Δ P, before energy storage participates in regulationl0And the peak regulation requirement of the system after the energy storage participates in regulation is shown.
Example 2
The method selects a place in Gansu province as a research place, and takes Dunhuang load data and a Bujilong energy storage power station as a basis, and the day-ahead scheduling method considering energy storage power constraint provided by the invention comprises the following steps:
s1: acquiring day-ahead prediction data of wind power, photovoltaic and load power of a power grid, acquiring a day-ahead power generation plan of a conventional power supply, and calculating the equivalent load of the system.
And (3) drawing an equivalent load curve of the energy storage power station before participating in peak shaving dispatching according to day-ahead prediction data of wind power, photovoltaic and load power of a certain day in the region of Gansu province, as shown in fig. 2.
S2: computing system peak shaver requirements
Counting the equivalent load peak value P before daylmax843.552MW, pre-day load trough plminIs 659.286 MW. The peak shaver requirement of the computing system is 184.266 MW.
S3 establishing energy storage power station adjusting model
The power regulation constraint of a blonde energy storage plant (60MW/240MWh) is: maximum permissible discharge power Pb，maxIs +60000KW, maximum allowable charging power Pb，minIs-60000 KW, minimum state of charge SOCminAt 20%, maximum state of charge SOCmaxSet the discharge power P to 80%bIs +40MW, discharge power PbThe maximum charging time T is 3.6h when the SOC of the energy storage power station is 20% in the early morning of the day at-40 MW.
S4: calculating charge/discharge periods of an energy storage plant
(1) Calculating a charging period of an energy storage power station
Setting step length PkStarting with a horizontal line P, 1MW, 1 k1＝Plmin+kPkIntersects the predicted daily load curve at a point t1，t2…t2n-1，t2nCalculating tc＝t2n-t2n-1+…+t2-t1Judgment of tcIf T is greater than T, if T iscIf the value is less than T, k is made to be 2, and a horizontal straight line P is made again1＝Plmin+kPkCalculating new tcComparing the sizes of the two, if the two do not meet the requirement, iterating until tcGreater than T, then at TcPower per power P of internal energy storage power stationbThe charging operation is performed for a total charging time T. In this example, the iteration is cut off until k equals 34, at which time tc＝3.67h>3.6h and a horizontal straight line P1Two intersection points are arranged between the charging time and the daily load curve, so that only one charging time is 03: 10-06: 50. Therefore, the charging time period of the energy storage power station can be 03: 15-06: 50.
(2) Calculating the discharge period of an energy storage power station
Setting step length PrStarting with a horizontal line P, 1MW, 1 r2＝Plmax-rPrAnd intersects the predicted daily load curve at a point t'1，t′2…t′2n-1，t′2nCalculating tf＝t′2n-t′2n-1+…+t′2-t′1Judgment of tfIf T is greater than T, if T isfIf the value is less than T, let r be 2, and make horizontal straight line P again2＝Plmax-rPrCalculating new tfComparing the sizes of the two, if the two do not meet the requirement, iterating until tfGreater than T, then at TfPower per power P of internal energy storage power stationbThe charging operation is performed for a total charging time T. In this example, the iteration is cut off until r is 24, at which time tf＝3.67h>3.6h and a horizontal straight line P24 intersection points are formed between the daily load curve and the charging time period, the corresponding charging time period is two, the number of the intersection points is 09: 50-11: 25, the number of the corresponding charging time period is 15: 25-17: 40, and the charging time period of the energy storage power station is selected as follows: 09: 50-11: 20 and 15: 25-17: 40.
S5: system peak shaving capacity improved after energy storage power station participates in peak shaving scheduling
The absolute peak-valley difference of the equivalent load is 184.266MW before the energy storage power station participates in adjustment, the absolute peak-valley difference of the equivalent load is 123.332MW after the energy storage power station participates in adjustment, and the peak regulation capability of the system before and after the energy storage power station participates in adjustment improves 60.934 MW.
Finally, it should be noted that: although the present invention has been described in detail with reference to the above embodiments, those skilled in the art can make modifications and equivalents to the specific embodiments of the invention without departing from the spirit and scope of the invention, which is set forth in the claims appended hereto.

Claims (6)

1. A day-ahead scheduling method considering energy storage power constraint is characterized in that the source-storage coordination scheduling method for energy storage to participate in peak shaving comprises the following steps:
s1: acquiring day-ahead prediction data of wind power, photovoltaic and load power of a power grid, and calculating equivalent load of the system;
s2: calculating the peak load regulation requirement of the system;
s3: under the condition of considering energy storage power constraint, establishing an energy storage power station regulation model;
s4: calculating the charging/discharging time period of the energy storage power station participating in system peak regulation;
s5: the energy storage power station and a conventional power supply perform source-storage coordination scheduling, and the system peak regulation capacity is improved.
2. The method for day-ahead scheduling considering energy storage power constraint according to claim 1, wherein the S1 comprises the following steps:
s101: and calculating the equivalent load of the system according to the predicted day-ahead wind power, photovoltaic and load power prediction data, and drawing a system equivalent load curve.
3. The method for day-ahead scheduling considering energy storage power constraint according to claim 1, wherein the S2 comprises the following steps:
s201: peak value p based on equivalent load curvelmaxValley p of equivalent load curvelminAnd calculating the peak regulation requirement of the system according to the day-ahead output curve of the conventional power supply.
4. The method for day-ahead scheduling considering energy storage power constraint according to claim 1, wherein the S3 comprises the following steps:
s301: determining an electrical power constraint of the energy storage power station;
s302: the charge state of the energy storage power station is restrained;
s303: and establishing an energy storage power station regulation model.
5. The method for day-ahead scheduling considering energy storage power constraint according to claim 1, wherein the S4 comprises the following steps:
s401: setting step length PkMake a horizontal straight line P1＝Plmin+kPkIntersecting the predicted daily equivalent load curve at a point t1，t2…t2n-1，t2n；
S402: the charging time t needed by the energy storage power station at the time is obtainedc；
S403: if the maximum charging time is greater than tcIf k is k +1, repeating the operation;
s404: if the maximum charging time is less than tcAnd the energy storage power station operates in the charging mode at the set power.
S405: setting step length PrMake a horizontal straight line P2＝Plmax-rPrAnd intersects with the predicted daily load curve at point t'1，t′2…t′2n-1，t′2n；
S406: the required discharge time t of the energy storage power station at the time is obtainedf；
S407: if the maximum discharge time is greater than tfIf r is r +1, repeating the operation;
s408: if the maximum discharge time is less than tfAnd the energy storage power station operates in a discharging mode at the set power.
6. The method for day-ahead scheduling considering energy storage power constraint according to claim 1, wherein the S5 comprises the following steps:
s501: calculating the load peak-valley difference before and after the energy storage power station participates in regulation;
s502: and calculating the peak regulation capacity of the system before and after the energy storage power station participates in regulation.
CN202111313961.4A 2021-11-08 2021-11-08 Day-ahead scheduling method considering energy storage power constraint Pending CN114123257A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114977251A (en) * 2022-07-28 2022-08-30 湖南华大电工高科技有限公司 Control method for stabilizing wind power fluctuation of energy storage system

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114977251A (en) * 2022-07-28 2022-08-30 湖南华大电工高科技有限公司 Control method for stabilizing wind power fluctuation of energy storage system
CN114977251B (en) * 2022-07-28 2022-11-01 湖南华大电工高科技有限公司 Control method for stabilizing wind power fluctuation of energy storage system

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