CN112085300A - Power supply classification-based power system total energy storage operation curve calculation method - Google Patents

Power supply classification-based power system total energy storage operation curve calculation method Download PDF

Info

Publication number
CN112085300A
CN112085300A CN202011121586.9A CN202011121586A CN112085300A CN 112085300 A CN112085300 A CN 112085300A CN 202011121586 A CN202011121586 A CN 202011121586A CN 112085300 A CN112085300 A CN 112085300A
Authority
CN
China
Prior art keywords
power station
power
total
curve
energy storage
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.)
Granted
Application number
CN202011121586.9A
Other languages
Chinese (zh)
Other versions
CN112085300B (en
Inventor
章坚民
黄江
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.)
Hangzhou Dianzi University
Original Assignee
Hangzhou Dianzi 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 Hangzhou Dianzi University filed Critical Hangzhou Dianzi University
Priority to CN202011121586.9A priority Critical patent/CN112085300B/en
Publication of CN112085300A publication Critical patent/CN112085300A/en
Application granted granted Critical
Publication of CN112085300B publication Critical patent/CN112085300B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION 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
    • G06Q10/00Administration; Management
    • G06Q10/04Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00Pattern recognition
    • G06F18/20Analysing
    • G06F18/24Classification techniques
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION 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
    • G06Q50/00Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/06Energy or water supply
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00Circuit arrangements for ac mains or ac distribution networks
    • H02J3/28Arrangements for balancing of the load in a network by storage of energy
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46Controlling of the sharing of output between the generators, converters, or transformers
    • YGENERAL 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
    • Y04INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04SSYSTEMS 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
    • Y04S10/00Systems supporting electrical power generation, transmission or distribution
    • Y04S10/50Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications

Landscapes

  • Engineering & Computer Science (AREA)
  • Business, Economics & Management (AREA)
  • Economics (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Strategic Management (AREA)
  • Human Resources & Organizations (AREA)
  • General Physics & Mathematics (AREA)
  • Tourism & Hospitality (AREA)
  • Health & Medical Sciences (AREA)
  • General Business, Economics & Management (AREA)
  • Data Mining & Analysis (AREA)
  • Marketing (AREA)
  • Power Engineering (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Public Health (AREA)
  • Water Supply & Treatment (AREA)
  • General Health & Medical Sciences (AREA)
  • Artificial Intelligence (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Primary Health Care (AREA)
  • Evolutionary Computation (AREA)
  • Evolutionary Biology (AREA)
  • General Engineering & Computer Science (AREA)
  • Development Economics (AREA)
  • Game Theory and Decision Science (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Operations Research (AREA)
  • Quality & Reliability (AREA)
  • Supply And Distribution Of Alternating Current (AREA)

Abstract

The invention discloses a power supply classification-based method for calculating a total energy storage operation curve of an electric power system. And classifying the power supplies according to types, and then calculating the total energy storage operation curve. The power supply is divided into an energy storage power station, a peak shaving power station and an output determining power station. Firstly, a power plant determined by output bears a total load curve, and the rest curve is used as a load curve to be conditioned; then the peak shaving power station bears the part below the average value of the load curve to be conditioned, so that a total energy storage daily operation curve for keeping the charging energy equal to the discharging energy is formed; and distributing the part above the average value of the composite curve to be conditioned to the power station with the built energy storage, and distributing the rest part to the newly-built energy storage power station, namely planning the position and the capacity of the newly-built energy storage power station according to the rest curve. The method is simple in calculation, various power stations are fully considered, overall planning is achieved, and resources are effectively saved.

Description

Power supply classification-based power system total energy storage operation curve calculation method
Technical Field
The invention belongs to the field of power system planning, and particularly relates to a method for calculating an operation curve of an energy storage power station in a power system according to a power supply classification result.
Background
With the development of economy, the peak power load of a power grid is increased day by day, the problem of peak-valley difference is obvious, and great challenges are brought to power grid dispatching. In addition, in recent years, renewable energy sources begin to be connected to the grid on a large scale and become effective substitutes of traditional energy sources, but the inherent intermittency and randomness of the renewable energy sources aggravate the difficulty in power grid deployment. The energy storage battery system is a key technology for realizing the space-time transfer of power supply and demand, and has attracted extensive attention because of the functions of realizing peak clipping and valley filling, improving the quality of electric energy, absorbing new energy and the like.
With the continuous development of energy storage technology, the condition that commercial operation and large-scale centralized energy storage power stations are merged into a main network is gradually mature, and the function of the energy storage power stations in the main network of the power system is increasingly displayed; in the face of large-scale centralized energy storage power station grid connection, the optimized operation of the energy storage power station in the prior art lacks consideration on the influence of a regional comprehensive energy system, and the type of energy is not brought into the optimized consideration range.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a power supply classification-based power system total energy storage operation curve calculation method.
A method for calculating a total energy storage operation curve of a power system based on power classification specifically comprises the following steps:
step 1, collecting a total load curve of a system;
selecting the day with the maximum power consumption in the year as a representative day, and taking the total load curve P of the representative dayr(t) as a planned annual representative curve.
Step 2, power classification;
the power supply is classified according to whether the daily load bearing large fluctuation can be taken as a standard, and the specific classification method comprises the following steps:
virtualizing all types of energy storage power stations including the energy storage power stations which are put into operation and to be planned into a total energy storage power station;
secondly, virtualizing all types of units and power plants which bear peak regulation into a total peak regulation power station, and setting the maximum power of the total peak regulation power station as Ppcm0
And thirdly, determining the power plant by considering all other power sources as output power.
Step 3, calculating output to determine system load born by the power plant;
1) a total photovoltaic power station is virtualized, and a representative daily total output curve is calculated;
2) a total wind power station is virtualized, and a representative total daily output curve is calculated;
3) according to the predicted hydropower station output of the incoming water, a total hydropower station is virtualized, and a representative daily total output curve is calculated;
4) calculating a representative sunrise curve of the external power according to a plan;
5) other conventional power plants are fully developed according to their maximum output.
After the prearranged spare capacity is removed, the total load curve of the system is shared according to the representative daily total output curve of the power supply to bear the base load; setting the residual load curve after the power supply bears as Pps(t), the load curve to be conditioned, the average of which is:
Figure 833065DEST_PATH_IMAGE001
(1)
wherein, TdayAre time intervals.
Step 4, calculating a load curve of the peak shaving power station;
the total energy storage power station and the total peak regulation power station in the power system share the load curve P to be regulatedps(t)。
1) If Ppcm0≥PpsIf the maximum power of the total peak shaving power station is larger than the average value of the load curves to be conditioned, the daily operation curve of the peak shaving power station is arranged as follows:
Figure 435691DEST_PATH_IMAGE002
(2)
wherein, c1For the output coefficient, eta, of the peak shaving power station in this cased、ηcThe charging and discharging efficiencies of the total energy storage power station are respectively.
At this time, the peak shaving residual capacity of the total peak shaving power station is as follows:
peak=Ppcm0-c1Pps (3)
the operating curve of the total energy storage power station is:
Pesse(t)=Pps(t)-Ppc1(t) (4)
substituting equation (2) into equation (4) yields:
Figure 153112DEST_PATH_IMAGE003
(5)
wherein when P isps(t)>PpsIndicating that the peak shaving power station is in a discharging state, and the rest time is in a charging state; to satisfy the daily balance of the total stored energy, i.e. the charged energy is equal to the discharged energy, it must be satisfied:
c1Tc+Tddc= Tc+Td (6)
wherein, TcFor the charging time of the day, TdFor the discharge time within the day, the deformation for (6) yields:
c1=1+Td*(1-ηdc)/ Tc (7)
and because of 1-etadc> 0, so c1>1。
So the charging energy A of the total energy storage power stationesse(+) and discharge energy Aesse(-) is:
Figure 469692DEST_PATH_IMAGE004
(8)
the peak shaving residual capacity is:
peak=Ppcm0-Pps- Pps* Td*(1-ηdc)/ Tc (9)。
2) if Ppcm0<PpsI.e. low maximum power of the total peak shaving stationAnd arranging the daily operation curve of the peak shaving power station as follows according to the average value of the load curve to be conditioned:
Figure 221748DEST_PATH_IMAGE005
(10)
at this point, the peak shaver station will have become fully operational at base charge.
The maximum power of the base load unit needing to be increased is as follows:
Ppc2,max=Pps-Ppcm0 (11)
the daily operating curves for the added load units are arranged as follows:
Figure 529364DEST_PATH_IMAGE006
(12)
wherein, c2The output coefficient of the peak shaver power station under the condition; analyzing (10) and (12), combining the peak shaving power stations into a new peak shaving power station, and substituting (12) to obtain a daily operation mode of the new peak shaving power station as follows:
Figure 468501DEST_PATH_IMAGE007
(13)
the operating curve of the total energy storage power station is:
Pesse(t)=Pps(t)-Ppc(t) (14)
substituting (13) into (14) yields:
Figure 854352DEST_PATH_IMAGE008
(15)
wherein when P isps(t)>PpsIndicating that the peak shaving power station is in a discharging state, and the rest time is in a charging state; to satisfy the daily balance of the total stored energy, i.e. the charged energy is equal to the discharged energy, it must be satisfied:
Tc*(Ppcm0+c2(Pps-Ppcm0))+Td*Ppsdc= (Tc+Td)*Pps (16)
namely, it is
c2=(( Tc+Td*(1-ηdc))*Pps- Tc*Ppcm0)/( Tc*(Pps- Ppcm0))
=((1+ Td*(1-ηdc)/ Tc)- Ppcm0/ Pps)/(1- Ppcm0/ Pps) (17)
And because of 1-etadc> 0 and 1+ Td*(1-ηdc)/ Tc> 1, so c2>1。
So the maximum power requirement of the added load unit can meet the following requirements:
P pc2,max=c2(Pps-Ppxm0)
=(( 1+ Td*(1-ηdc)/ Tc)- Ppcm0/ Pps)*( Pps- Ppcm0)/(1- Ppcm0/ Pps) (18)
so the charging energy A of the total energy storage power stationesse(+) and discharge energy Aesse(-) is:
Figure 460913DEST_PATH_IMAGE009
(19)。
step 5, load sharing of the total energy storage power station
1) Arranging the built energy storage power station according to the operation curve of the total energy storage power station calculated in the step 4, and carrying out load sharing according to the limits of the maximum energy, the maximum output, the minimum charge state and the like of the built energy storage power station;
2) and planning and designing new energy storage power station resources according to the residual operation curves after the built energy storage power stations are allocated.
The invention has the following beneficial effects:
1. the storage of various power generation resources in the planning year and the power generation resources to be planned are fully considered, and after the power supplies are classified according to types, the operation curves are calculated and distributed, so that the resources are effectively saved;
2. the method is simple, high in operability and convenient to calculate, and can quickly calculate the load curve meeting the typical daily load of a planning year;
3. the calculation result of the method can be used as a reference for further addressing and capacity fixing schemes of the energy storage power station.
Detailed Description
The invention is further illustrated by the following specific examples.
Step 1, collecting a total load curve of a system;
will represent the total load curve P of the dayr(t) Total load Curve P as the planned annual representative Curver(t) the following:
Figure 188698DEST_PATH_IMAGE011
step 2, power classification;
the power supply is classified according to whether the daily load bearing large fluctuation can be taken as a standard, and the specific classification method comprises the following steps:
virtualizing all types of energy storage power stations including the energy storage power stations which are put into operation and to be planned into a total energy storage power station;
secondly, virtualizing all types of units and power plants which bear peak regulation into a total peak regulation power station, and setting the maximum power of the total peak regulation power station as Ppcm0
And thirdly, determining the power plant by considering all other power sources as output power.
Step 3, calculating output to determine system load born by the power plant;
1) a total photovoltaic power station is virtualized, and a representative daily total output curve is calculated;
2) a total wind power station is virtualized, and a representative total daily output curve is calculated;
3) according to the predicted hydropower station output of the incoming water, a total hydropower station is virtualized, and a representative daily total output curve is calculated;
4) calculating a representative sunrise curve of the external power according to a plan;
5) other conventional power plants are fully developed according to their maximum output.
After the prearranged spare capacity is removed, the total load curve of the system is shared according to the representative daily total output curve of the power supply to bear the base load; calculating and determining the system load P (t) borne by the power plant as follows:
Figure 198871DEST_PATH_IMAGE013
calculating and determining the residual load curve P after the output power plant undertakesps(t), the load curve to be conditioned, is shown in the following table:
Figure 670304DEST_PATH_IMAGE015
calculating to obtain the average value P of the load curve to be conditionedps=68 MW. When P is presentps(t)>PpsIndicating that the peak shaving power station is in a discharging state and the rest of the time is in a charging state, so the charging time of the total energy storage power stationTc=14, discharge timeTd=10。
Step 4, calculating a load curve of the peak shaving power station;
the total energy storage power station and the total peak regulation power station in the power system share the load curve P to be regulatedps(t) of (d). Wherein the charge-discharge efficiency eta of the total energy storage power stationdc=0.9, charging timeTc=14, discharge timeTd=10。
1) When peak shaving the maximum power P of the power stationpcm0=80MW, i.e. Ppcm0≥PpsAnd the maximum power of the total peak shaving power station is larger than the average value of the load curve to be conditioned.
In order to meet the daily balance of the total stored energy, namely the charged energy is equal to the discharged energy, the output coefficient of the peak shaving power station and the charge-discharge efficiency and the charge-discharge time of the total stored energy power station are required to meet the following requirements:
c1Tc+Tddc= Tc+Td
and calculating the output coefficient c1=1.1357 of the peak shaver power station at the moment.
The daily operation curve of the peak shaving power station is arranged as follows:
Figure 662531DEST_PATH_IMAGE016
(20)
according to formula Pesse(t)=Pps(t)-Ppc1(t) calculating to obtain the operation curve of the total energy storage power station as shown in the following table:
Figure 13747DEST_PATH_IMAGE018
the energy storage power station load is a negative value to indicate that the energy storage power station is in a charging state, and a positive value to indicate that the energy storage power station is in a discharging state.
2) When the maximum power of the peak shaving power station Pcpcm 0=60MW, namely Pcpcm 0 < Pps, the maximum power of the total peak shaving power station is smaller than the average value of the load curve to be conditioned.
The daily operation curve of the peak-shaving power station is obtained by calculation as follows:
Figure 193055DEST_PATH_IMAGE019
(21)
the maximum power of the load group to be added is:
Ppc2,max=Pps-Ppcm0=8 MW (11)
the daily operating curves for the added load units are arranged as follows:
Figure 953332DEST_PATH_IMAGE020
(22)
wherein, c2The output coefficient of the peak shaver power station in this case.
Will be provided withP pc1 AndP pc2 merging the two into a new peak regulation power station, wherein the daily operation mode of the new peak regulation power station is as follows:
Figure 534486DEST_PATH_IMAGE021
(23)
in order to meet the daily balance of the total stored energy, namely the charged energy is equal to the discharged energy, the output coefficient of the peak shaving power station and the charge-discharge efficiency and the charge-discharge time of the total stored energy power station are required to meet the following requirements:
Tc*(Ppcm0+c2(Pps-Ppcm0))+Td*Ppsdc= (Tc+Td)*Pps (24)
and calculating to obtain the output coefficient c2=2.1536 of the peak shaver power station.
According to formula Pesse(t)=Pps(t)-Ppc(t) calculating to obtain the operation curve of the total energy storage power station as shown in the following table:
Figure 791024DEST_PATH_IMAGE022
the maximum power requirement of the added base load unit is met:
P pc2,max=c2(Pps-Ppxm0)
=(( 1+ Td*(1-ηdc)/ Tc)- Ppcm0/ Pps)*( Pps- Ppcm0)/(1- Ppcm0/ Pps)=17.23 MW (25)。

Claims (5)

1. a method for calculating a total energy storage operation curve of a power system based on power classification is characterized by comprising the following steps: the method specifically comprises the following steps:
step 1, collecting a total load curve of a system;
selecting the day with the maximum power consumption in one year as a representative day and the total representative dayLoad curve Pr(t) as a planned annual representative curve;
step 2, power classification;
classifying power supplies by taking the daily load capable of bearing large fluctuation as a standard, and dividing the power supplies into output power determining power plants with the maximum power Pcom0The total peak regulation power station and the total energy storage power station to be calculated;
step 3, calculating output to determine system load born by the power plant
Calculating output to determine the representative daily total output curve of the power plant, sharing the total load curve of the system, bearing the base load, and obtaining the residual load curve Pps(t) is the load curve to be conditioned, and the average value is:
Figure 231386DEST_PATH_IMAGE002
(1)
wherein, TdayIs a time interval;
step 4, load curve calculation of peak shaving power station
Load curve P to be conditionedps(t) the total peak regulation power station and the total energy storage power station share the same load, and daily operation curves of the peak regulation power station and operation curves of the total energy storage power station are calculated according to conditions;
(1) when P is presentpcm0≥PpsNamely, the maximum power of the total peak shaving power station is larger than the average value of the load curves to be conditioned, the daily operation curves of the total peak shaving power station and the total energy storage power station are calculated, and when P isps(t) is greater than PpsDischarging the peak shaving power station, and charging the energy storage power station by the peak shaving power station at the rest time; according to the daily balance principle of the total energy storage power station, namely the charging capacity is equal to the discharging energy, calculating the charging energy and the discharging energy of the total energy storage power station and the residual capacity of the peak shaving power station;
(2) when P is presentpcm0<PpsThe maximum power of the total peak shaving power station is larger than the average value of the load curve to be conditioned, the peak shaving power station base load operation is arranged, and the daily operation curve of the total peak shaving power station is calculated; calculating the daily operation curve of the base load unit needing to be added, and combining the daily operation curve with the original peak regulation power station to obtain a new onePeak shaving power stations; calculating the operation curve of the new peak shaving power station when Pps(t) is greater than PpsWhen the power station is charged, the new peak shaving power station is charged; and calculating the charging energy and the discharging energy of the total energy storage power station according to a daily balance principle of the total energy storage power station, namely that the charging capacity is equal to the discharging energy.
2. The method for calculating the total energy storage operating curve of the power system based on the power classification as claimed in claim 1, wherein: the specific method for classifying the power supply in the step 2 comprises the following steps:
virtualizing all types of energy storage power stations including the energy storage power stations which are put into operation and to be planned into a total energy storage power station;
virtualizing all types of units and power plants which bear peak regulation into a total peak regulation power station;
and thirdly, determining the power plant by considering all other power sources as output power.
3. The method for calculating the total energy storage operating curve of the power system based on the power classification as claimed in claim 1, wherein: and 3, the method for determining the system load born by the power plant by calculating the output comprises the following steps:
1) a total photovoltaic power station is virtualized, and a representative daily total output curve is calculated;
2) a total wind power station is virtualized, and a representative total daily output curve is calculated;
3) according to the predicted hydropower station output of the incoming water, a total hydropower station is virtualized, and a representative daily total output curve is calculated;
4) calculating a representative sunrise curve of the external power according to a plan;
5) other conventional power plants are fully developed according to their maximum output.
4. The method for calculating the total energy storage operating curve of the power system based on the power classification as claimed in claim 1, wherein: the method for calculating the daily operation curve of the peak regulation power station and the operation curve of the total energy storage power station according to the situation comprises the following steps:
1) if it isPpcm0≥PpsIf the maximum power of the total peak shaving power station is larger than the average value of the load curves to be conditioned, the daily operation curve of the peak shaving power station is arranged as follows:
Figure 513463DEST_PATH_IMAGE004
(2)
wherein, c1For the output coefficient, eta, of the peak shaving power station in this cased、ηcRespectively the charging efficiency and the discharging efficiency of the total energy storage power station;
at this time, the peak shaving residual capacity of the total peak shaving power station is as follows:
peak=Ppcm0-c1Pps (3)
the operating curve of the total energy storage power station is:
Pesse(t)=Pps(t)-Ppc1(t) (4)
substituting equation (2) into equation (4) yields:
Figure 463971DEST_PATH_IMAGE005
(5)
wherein when P isps(t)>PpsIndicating that the peak shaving power station is in a discharging state, and the rest time is in a charging state; to satisfy the daily balance of the total stored energy, i.e. the charged energy is equal to the discharged energy, it must be satisfied:
c1Tc+Tddc= Tc+Td (6)
wherein, TcFor the charging time of the day, TdFor the discharge time within the day, the deformation for (6) yields:
c1=1+Td*(1-ηdc)/ Tc (7)
and because of 1-etadc> 0, so c1>1;
So the charging energy A of the total energy storage power stationesse(+) and dischargeEnergy Aesse(-) is:
Figure 173301DEST_PATH_IMAGE007
(8)
wherein, Ω (T)d) Is a collection of charging times.
5. The peak shaving residual capacity is:
peak=Ppcm0-Pps- Pps* Td*(1-ηdc)/ Tc (9)
2) if Ppcm0<PpsIf the maximum power of the total peak shaving power station is smaller than the average value of the load curve to be conditioned, the daily operation curve of the peak shaving power station is arranged as follows:
Figure 75004DEST_PATH_IMAGE009
(10)
at the moment, the peak shaving power station is completely changed into base load operation;
the maximum power of the base load unit needing to be increased is as follows:
Ppc2,max=Pps-Ppcm0 (11)
the daily operating curves for the added load units are arranged as follows:
Figure 160772DEST_PATH_IMAGE011
(12)
wherein, c2The output coefficient of the peak shaver power station under the condition; analyzing (10) and (12), combining the peak shaving power stations into a new peak shaving power station, and substituting (12) to obtain a daily operation mode of the new peak shaving power station as follows:
Figure 716518DEST_PATH_IMAGE013
(13)
the operating curve of the total energy storage power station is:
Pesse(t)=Pps(t)-Ppc(t) (14)
substituting (13) into (14) yields:
Figure 846017DEST_PATH_IMAGE014
(15)
wherein when P isps(t)>PpsIndicating that the peak shaving power station is in a discharging state, and the rest time is in a charging state; to satisfy the daily balance of the total stored energy, i.e. the charged energy is equal to the discharged energy, it must be satisfied:
Tc*(Ppcm0+c2(Pps-Ppcm0))+Td*Ppsdc= (Tc+Td)*Pps (16)
namely, it is
c2=(( Tc+Td*(1-ηdc))*Pps- Tc*Ppcm0)/( Tc*(Pps- Ppcm0))
=((1+ Td*(1-ηdc)/ Tc)- Ppcm0/ Pps)/(1- Ppcm0/ Pps) (17)
And because of 1-etadc> 0 and 1+ Td*(1-ηdc)/ Tc> 1, so c2>1;
So the maximum power requirement of the added load unit can meet the following requirements:
P pc2,max=c2(Pps-Ppxm0)
=(( 1+ Td*(1-ηdc)/ Tc)- Ppcm0/ Pps)*( Pps- Ppcm0)/(1- Ppcm0/ Pps) (18)
so the charging energy A of the total energy storage power stationesse(+) and discharge energy Aesse(-) is:
Figure 487214DEST_PATH_IMAGE016
(19)。
CN202011121586.9A 2020-10-20 2020-10-20 Power supply classification-based power system total energy storage operation curve calculation method Active CN112085300B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202011121586.9A CN112085300B (en) 2020-10-20 2020-10-20 Power supply classification-based power system total energy storage operation curve calculation method

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202011121586.9A CN112085300B (en) 2020-10-20 2020-10-20 Power supply classification-based power system total energy storage operation curve calculation method

Publications (2)

Publication Number Publication Date
CN112085300A true CN112085300A (en) 2020-12-15
CN112085300B CN112085300B (en) 2023-09-08

Family

ID=73730573

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202011121586.9A Active CN112085300B (en) 2020-10-20 2020-10-20 Power supply classification-based power system total energy storage operation curve calculation method

Country Status (1)

Country Link
CN (1) CN112085300B (en)

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109560562A (en) * 2018-12-28 2019-04-02 国网湖南省电力有限公司 Energy-accumulating power station peak regulation control method based on ultra-short term
CN111598295A (en) * 2020-04-13 2020-08-28 中国电建集团贵阳勘测设计研究院有限公司 Power system pumped storage power station installation optimization method for promoting wind power consumption

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109560562A (en) * 2018-12-28 2019-04-02 国网湖南省电力有限公司 Energy-accumulating power station peak regulation control method based on ultra-short term
CN111598295A (en) * 2020-04-13 2020-08-28 中国电建集团贵阳勘测设计研究院有限公司 Power system pumped storage power station installation optimization method for promoting wind power consumption

Also Published As

Publication number Publication date
CN112085300B (en) 2023-09-08

Similar Documents

Publication Publication Date Title
CN102694391B (en) Day-ahead optimal scheduling method for wind-solar storage integrated power generation system
CN112270433B (en) Micro-grid optimization method considering renewable energy uncertainty and user satisfaction
CN115936244A (en) Virtual power plant optimal scheduling method considering renewable energy power generation uncertainty
CN111160636B (en) CCHP type micro-grid scheduling optimization method
CN115173453A (en) Energy storage auxiliary power grid peak regulation optimal configuration method
CN113708365A (en) Virtual power plant energy management and control optimization method and system based on end edge cloud architecture
CN114914943B (en) Hydrogen energy storage optimal configuration method for green port shore power system
CN110084465A (en) Wind generator system cost/Reliability Estimation Method based on energy storage
CN112488378A (en) Cost modeling method for renewable energy driven reverse osmosis seawater desalination technology
CN110535187A (en) A kind of the energy dispatching method and system of the composite energy storage capacity of active distribution network
CN111762057B (en) Intelligent charging and discharging management method for V2G electric vehicle in regional microgrid
CN114169211A (en) Multi-station fusion energy storage optimization configuration model based on improved particle swarm optimization
CN115001046A (en) Double-layer optimization control method for participating in peak shaving and frequency modulation of multi-energy-storage power station
CN115062985A (en) Offshore island microgrid operation strategy considering user comfort requirement side management
CN118412929A (en) Virtual power plant operation control method considering scheduling response capability
CN112269966B (en) Communication base station virtual power plant power generation capacity measurement method considering standby demand
CN110739710A (en) Method and device for coordinated scheduling of multiple energy types based on optimization algorithm
CN112307603A (en) Hybrid energy storage capacity optimal configuration method and system considering large-scale wind power access
CN112036735A (en) Energy storage capacity planning method and system for energy storage system of photovoltaic power station
CN112653195A (en) Method for configuring robust optimization capacity of grid-connected micro-grid
CN116131303A (en) Comprehensive energy system collaborative optimization method based on energy storage, energy storage and photovoltaic cell
CN117013522A (en) Comprehensive energy system scheduling optimization method considering distributed power supply and gas-electricity cooperation
CN108683211B (en) Virtual power plant combination optimization method and model considering distributed power supply volatility
CN116316844A (en) Construction and operation layered optimization design method of power generation side energy storage power station
CN116613801A (en) Day-ahead optimal scheduling method for wind-solar storage battery hybrid hydrogen energy storage power generation system

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant