CN113344427A - Method, system, equipment and storage medium for determining variable capacity demand curve - Google Patents

Method, system, equipment and storage medium for determining variable capacity demand curve Download PDF

Info

Publication number
CN113344427A
CN113344427A CN202110721009.1A CN202110721009A CN113344427A CN 113344427 A CN113344427 A CN 113344427A CN 202110721009 A CN202110721009 A CN 202110721009A CN 113344427 A CN113344427 A CN 113344427A
Authority
CN
China
Prior art keywords
capacity
unit
demand curve
price
peak
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.)
Pending
Application number
CN202110721009.1A
Other languages
Chinese (zh)
Inventor
单茂华
谢毅
曹媛媛
曹阳
严春华
张豪
田伟
陈广娟
李宏杰
李晓嘉
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.)
Shanxi Electric Power Trading Center Co ltd
China Electric Power Research Institute Co Ltd CEPRI
Original Assignee
Shanxi Electric Power Trading Center Co ltd
China Electric Power Research Institute Co Ltd CEPRI
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 Shanxi Electric Power Trading Center Co ltd, China Electric Power Research Institute Co Ltd CEPRI filed Critical Shanxi Electric Power Trading Center Co ltd
Priority to CN202110721009.1A priority Critical patent/CN113344427A/en
Publication of CN113344427A publication Critical patent/CN113344427A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • 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
    • G06Q10/0635—Risk analysis of enterprise or organisation activities
    • 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
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0201—Market modelling; Market analysis; Collecting market data
    • G06Q30/0203—Market surveys; Market polls
    • 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—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Energy or water supply
    • 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
    • Y04S50/00—Market activities related to the operation of systems integrating technologies related to power network operation or related to communication or information technologies
    • Y04S50/14—Marketing, i.e. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards

Landscapes

  • Business, Economics & Management (AREA)
  • Engineering & Computer Science (AREA)
  • Strategic Management (AREA)
  • Human Resources & Organizations (AREA)
  • Economics (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Development Economics (AREA)
  • General Business, Economics & Management (AREA)
  • Accounting & Taxation (AREA)
  • Finance (AREA)
  • Marketing (AREA)
  • Theoretical Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Physics & Mathematics (AREA)
  • Tourism & Hospitality (AREA)
  • Game Theory and Decision Science (AREA)
  • Health & Medical Sciences (AREA)
  • Quality & Reliability (AREA)
  • Operations Research (AREA)
  • Data Mining & Analysis (AREA)
  • Educational Administration (AREA)
  • Public Health (AREA)
  • Water Supply & Treatment (AREA)
  • General Health & Medical Sciences (AREA)
  • Primary Health Care (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The invention provides a method, a system, equipment and a storage medium for determining a variable capacity demand curve, wherein the method comprises the following steps: obtaining historical load data, calculating the system target capacity b of the capacity delivery yearx(ii) a Obtaining system capacity supply cxAnd capacity requirement axCalculating a system tolerance value (c)x‑ax) (ii) a Setting a capacity price b corresponding to a target capacity of a system based on fixed cost of marginal units operated at peak time of the systemyAnd price cap ay(ii) a Obtaining three coordinate points on the variable capacity demand curve: a (a)x，ay)，b(bx，by)，c(cx，cy) And establishing a variable capacity demand curve based on three coordinate points. The invention can avoid the price fluctuation brought by the vertical capacity demand curveThe profit of the power generation enterprise is highly uncertain, and the investment risk of the power generation enterprise is reduced.

Description

Method, system, equipment and storage medium for determining variable capacity demand curve
Technical Field
The present invention relates to the field of power scheduling, and in particular, to a method, a system, a device, and a storage medium for determining a variable capacity demand curve.
Background
The vertical demand curve in the capacity market mechanism has certain advantages in calculation and formulation, but the price is lack of elasticity, the vertical price fluctuation can bring high uncertainty for power generation enterprises, the investment construction of a guide power supply is not facilitated, and the price guide effect of the capacity price is not obvious. And the price of the variable demand curve has elasticity, so that the investment risk of power generation enterprises can be reduced. Therefore, the design of the variable capacity demand curve needs to be considered, so that a certain guiding effect is played for the investment construction of the power supply.
Disclosure of Invention
The method for determining the variable capacity demand curve based on the capacity market mechanism can avoid the high uncertainty of the profit of the power generation enterprise caused by the price fluctuation of the vertical capacity demand curve, and reduce the investment risk of the power generation enterprise.
In order to achieve the purpose, the invention adopts the following technical scheme:
a method for determining a variable capacity demand curve comprises the following steps:
obtaining historical load data, calculating the system target capacity b of the capacity delivery yearx；
Obtaining system capacity supply cxAnd capacity requirement axCalculating a system tolerance value (c)x-ax)；
Setting a capacity price b corresponding to a target capacity of a system based on fixed cost of marginal units operated at peak time of the systemyAnd price cap ay；
Obtaining three coordinate points on the variable capacity demand curve: a (a)x，ay)，b(bx，by)，c(cx，cy) And establishing a variable capacity demand curve based on three coordinate points.
As a further refinement of the invention, the historical load data is load data for a period of time prior to the year of delivery of the capacity.
As a further improvement of the invention, the system target capacity b of the capacity delivery yearxThe method specifically comprises the following steps:
bx＝RelReq＝Lp×(1+IRM)×(1-S)-FRR
in the formula, Lp, IRM, S and FRR are respectively the load peak value, the standby rate, the forced shutdown rate and the load self-supply capacity of each partition of the system.
As a further improvement of the present invention, the determination of the forced outage rate of the system is based on historical data, specifically:
equivalent forced outage rate EFOR equal to all units planned to be put into service in year of deliverydAccording to the weighted average value of the unit capacity and the service hours; the specific calculation method comprises the following steps:
Figure BDA0003136526500000021
Figure BDA0003136526500000022
EFDH＝EFOH-FOH
Figure BDA0003136526500000023
Figure BDA0003136526500000024
Figure BDA0003136526500000025
Figure BDA0003136526500000026
Figure BDA0003136526500000027
wherein, EFORdThe equivalent forced outage rate of the unit; pmaxThe capacity of the unit; SH is the service hours of the unit; f. offAnd fpF coefficient and p coefficient when the computer unit is equivalent to the forced outage rate respectively; AH is the number of available hours; FOH is the number of hours of forced shutdown of the unit; EFDH is equivalent planned derating hours of the unit; EFOH is the equivalent forced outage hours of the unit; r, T and D are respectively the average forced outage time, the average call interval time and the average running time; RSH is standby down time.
As a further improvement of the present invention, the spare rate is determined based on a system historical load model and a capacity model, and specifically includes:
generating a weekly peak-to-peak load distribution based on historical load data, generating a weekly available power generation capacity distribution based on historical unit shutdown events, performing convolution operation on the weekly peak-to-peak load distribution and the available power generation capacity distribution, wherein the area corresponding to the area with the power supply margin smaller than 0 is LOLP, and adding the LOLPs of each week to obtain annual LOLPs; when the annual LOLP meets the system requirements, then the utilization IRM is equal to the installed capacity divided by the peak annual load at that time.
As a further development of the invention, the system capacity supply cxAnd capacity requirement axThe specific calculation method comprises the following steps:
Figure BDA0003136526500000031
Figure BDA0003136526500000032
wherein, the IRM is the standby rate of each partition of the system, and a 'and c' are constants.
As a further development of the invention, the capacity price byAnd price cap ayThe method specifically comprises the following steps:
Figure BDA0003136526500000033
Figure BDA0003136526500000034
in the formula, CONE is the annual fixed cost of the marginal unit operated at the peak time of the system; the E & AS is the average annual revenue value obtained by marginal units operating at peak times of the system from the electric energy market and the ancillary services market before the year of capacity delivery.
A variable capacity demand curve determination system comprising:
a first calculating unit for acquiring the historical load data and calculating the system target capacity b of the capacity delivery yearx；
A second calculation unit for acquiring system capacity supply cxAnd capacity requirement axCalculating a system tolerance value (c)x-ax)；
A third calculating unit for setting a capacity price b corresponding to the target capacity of the system based on the fixed cost of the marginal unit operated at the peak time of the systemyAnd price cap ay；
The curve establishing unit is used for obtaining three coordinate points on the variable capacity demand curve: a (a)x，ay)，b(bx，by)，c(cx，cy) And establishing a variable capacity demand curve based on three coordinate points.
An electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the variable capacity demand curve determination method when executing the computer program.
A computer-readable storage medium, storing a computer program which, when executed by a processor, implements the steps of the variable capacity demand curve determination method.
The invention has the beneficial effects that:
compared with a fixed demand curve, the variable capacity demand curve based on the capacity market mechanism is established, the variable capacity demand curve is considered, the price risk caused by a vertical demand curve can be avoided, the investment construction of a power supply is effectively guided, the capacity clearing price of each subarea is higher than the price corresponding to the target capacity, the investment construction can be accelerated, and the investment construction pace is slowed down if the capacity clearing price of each subarea is lower than the price corresponding to the target capacity. The power generation enterprise can be better helped to judge whether investment for building a new power supply is needed or not through market means, and price signals brought by a variable demand curve can better guide power supply investment.
Drawings
FIG. 1 is a schematic diagram of a variable capacity demand curve according to the present invention;
FIG. 2 is a flow chart illustrating a method for determining a variable capacity demand curve according to a preferred embodiment of the present invention;
FIG. 3 is a schematic diagram of a system for determining a variable capacity demand curve according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of an electronic device according to a preferred embodiment of the invention.
Detailed Description
The present invention will be described in detail below with reference to the embodiments with reference to the attached drawings. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
The following detailed description is exemplary in nature and is intended to provide further details of the invention. Unless otherwise defined, all technical terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the invention.
The price lacks elasticity to fixed demand curve, and the vertically price fluctuation can bring high uncertainty for the power generation enterprise, is unfavorable for the investment construction of guide power, and the price guide effect that the capacity price played is not obvious, and the price of the variable demand curve has elasticity, can reduce the investment risk of power generation enterprise. Therefore, the design of the variable capacity demand curve needs to be considered, so that a certain guiding effect is played for the investment construction of the power supply. The invention provides a variable capacity demand curve determining method based on a capacity market mechanism.
The noun explains:
variable capacity demand curve: the generating capacity is changed along with the change of the capacity price.
The method thus comprises: (1) determining a System target Capacity for a Capacity delivery year bx(ii) a (2) Determining a tolerance value (c)x-ax) (ii) a (3) Setting a capacity price b corresponding to a target capacity based on fixed cost of marginal unit operated at peak time of systemyAnd price cap ay. The method can avoid the high uncertainty of the profit of the power generation enterprise caused by the price fluctuation of the vertical capacity demand curve, and reduce the investment risk of the power generation enterprise.
The method specifically comprises the following steps:
the invention discloses a variable capacity demand curve determining method based on a capacity market mechanism, which comprises the following steps: (1) determining a System target Capacity for a Capacity delivery year bx(ii) a (2) Determining a tolerance value (c)x-ax) (ii) a (3) Setting a capacity price b corresponding to a target capacity based on fixed cost of marginal unit operated at peak time of systemyAnd price cap ay. The method can avoid the high uncertainty of the profit of the power generation enterprise caused by the price fluctuation of the vertical capacity demand curve, and reduce the investment risk of the power generation enterprise.
The invention is described in detail below with reference to figures 1 and 2:
(1) determining a System target Capacity for a Capacity delivery year bx；
The system target capacity b of the capacity delivery year in the step (1)xThe method specifically comprises the following steps:
bx＝RelReq＝Lp×(1+IRM)×(1-S)-FRR
in the formula, Lp, IRM, S and FRR are respectively the load peak value, the standby rate, the forced shutdown rate and the load self-supply capacity of each partition of the system.
Wherein the determination of the forced outage rate S of the system is based on historical 5-year data: equivalent forced outage rate EFOR equal to all units planned to be put into service in year of deliverydAccording to a weighted average of the unit capacity and the number of service hours.
Figure BDA0003136526500000061
Figure BDA0003136526500000062
EFDH＝EFOH-FOH
Figure BDA0003136526500000063
Figure BDA0003136526500000064
Figure BDA0003136526500000065
Figure BDA0003136526500000066
Figure BDA0003136526500000067
Wherein, EFORdThe equivalent forced outage rate of the unit; pmaxThe capacity of the unit; SH is the service hours of the unit; f. offAnd fpF coefficient and p coefficient when the computer unit is equivalent to the forced outage rate respectively; AH is the number of available hours; FOH is the number of hours of forced shutdown of the unit; EFDH is equivalent planned derating hours of the unit; EFOH is the equivalent forced outage hours of the unit; r, T and D are respectively the average forced outage time, the average call interval time and the average running time; RSH is standby down time.
The system standby rate IRM is determined based on a system load model and a capacity model. A weekly peak-to-day load profile is generated based on historical load data from the previous 5 years, and a weekly available generation capacity profile is generated based on unit outage events from the previous 5 years. Convolution operation is performed for the daily peak-to-load distribution and the available power generation capacity distribution for each week, the area corresponding to the region where the power supply margin is less than 0 is a low, and the LOLPs for each week are added to obtain an annual LOLP. When the annual LOLP meets the system requirements, then the utilization IRM is equal to the installed capacity divided by the peak annual load at that time.
(2) Determining a tolerance value (c)x-ax)；
The tolerance value (c)x-ax) The method specifically comprises the following steps:
Figure BDA0003136526500000071
Figure BDA0003136526500000072
the system tolerances depend specifically on the system supply and demand, and are determined by the market operator. a isx,cxThe constants a and c in the numerator in the expression can be set according to system requirements, such as: if the system capacity is sufficient, in order to avoid the capacity price from being too low, a larger c '(c' belongs to (0, 1)); if the system capacity is insufficient, a' e (0,1) can be set smaller to attract the power investment construction.
(3) Setting a capacity price b corresponding to a target capacity based on fixed cost of marginal unit operated at peak time of systemyAnd price cap ay。
Capacity price b corresponding to the target capacityyAnd price cap ayThe method specifically comprises the following steps:
Figure BDA0003136526500000073
Figure BDA0003136526500000074
in the formula, CONE is the annual fixed cost of the marginal unit operated at the peak time of the system; the E & AS is the average annual revenue value obtained from the electric energy market and the auxiliary service market 5 years before the year of capacity delivery for marginal units operating at peak times of the system.
Examples
The following description will be made by taking a specific example, and a method of determining a variable capacity demand curve will be explained based on the following data. FIG. 1 is a schematic diagram of a variable demand curve according to the present invention.
1) Determining a System target Capacity for a Capacity delivery year bx。
Assuming that the system has only 4 units, the technical parameters of the units, the equivalent forced outage rate, the service hours and other data are shown in table 1. The forced outage rate S of the system is 7.5956%.
TABLE 1
Figure BDA0003136526500000081
Assuming that the system load peak value is 400MW, the standby rate is 15% and the load self-supply capacity is 50.8MW, the target capacity is bx＝RelReq＝374.2602MW。
2) Determining a tolerance value (c)x-ax)。
The system supply and demand can be known through the set parameters and peak load in the step (1). Considering that the supply and demand of the system are larger, the speed of power supply investment construction is expected to be slowed down, and therefore a larger positive fluctuation range is set. The forward and reverse fluctuation ranges were set to 8.8% for c 'and 1.2% for a', respectively. The abscissa corresponding to the coordinates of the other two key points on the variable capacitance curve is
Figure BDA0003136526500000082
Figure BDA0003136526500000083
3) Setting a capacity price b corresponding to a target capacity based on fixed cost of marginal unit operated at peak time of systemyAnd price cap ay。
Assuming that the marginal unit at the peak time of the system is the unit 4, the annual fixed cost is shown in table 2. The capacity price corresponding to the target capacity is by＝1948，ay＝4800。
TABLE 2
Figure BDA0003136526500000084
To this end, the variable capacity demand curve is shown in fig. 2, and the coordinates of 3 key points are: point a (370.3549,4800), point b (374.2602,1948), and point c (402.8992, 0).
Therefore, the variable-capacity demand curve is considered, the price risk caused by the vertical demand curve can be avoided, the investment construction of the power supply is effectively guided, the capacity clearing price of each subarea is higher than the price corresponding to the target capacity, the investment construction plant can be accelerated, and the investment construction plant pace is slowed down if the capacity clearing price of each subarea is lower than the price corresponding to the target capacity. The power generation enterprise can be better helped to judge whether investment for building a new power supply is needed or not through market means, and price signals brought by a variable demand curve can better guide power supply investment.
As shown in fig. 3, another objective of the present invention is to provide a system for determining a demand curve of variable capacity, comprising:
a first calculating unit for acquiring the historical load data and calculating the system target capacity b of the capacity delivery yearx；
A second calculation unit for acquiring system capacity supply cxAnd capacity requirement axCalculating a system tolerance value (c)x-ax)；
A third calculating unit for setting a capacity price b corresponding to the target capacity based on the fixed cost of the marginal unit operated at the peak time of the systemyAnd price cap ay；
The curve establishing unit is used for obtaining three coordinate points on the variable capacity demand curve: a (a)x，ay)，b(bx，by)，c(cx，cy) And drawing a variable capacity demand curve based on a capacity market mechanism based on three coordinate punctuations.
A third object of the present invention is to provide an electronic device, which includes a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the variable capacity demand curve determining method when executing the computer program.
The method for determining the variable capacity demand curve comprises the following steps:
obtaining historical load data, calculating the system target capacity b of the capacity delivery yearx；
Obtaining system capacity supply cxAnd capacity requirement axCalculating a system tolerance value (c)x-ax)；
Setting a capacity price b corresponding to a target capacity based on fixed cost of marginal unit operated at peak time of systemyAnd price cap ay；
Obtaining three coordinate points on the variable capacity demand curve: a (a)x，ay)，b(bx，by)，c(cx，cy) And drawing a variable capacity demand curve based on a capacity market mechanism based on three coordinate punctuations.
A fourth object of the present invention is to provide a computer-readable storage medium storing a computer program which, when executed by a processor, implements the steps of the variable capacity demand curve determination method.
The method for determining the variable capacity demand curve comprises the following steps:
obtaining historical load data, calculating the system target capacity b of the capacity delivery yearx；
Obtaining system capacity supply cxAnd capacity requirement axCalculating a system tolerance value (c)x-ax)；
Setting a capacity price b corresponding to a target capacity based on fixed cost of marginal unit operated at peak time of systemyAnd price cap ay；
Obtaining three coordinate points on the variable capacity demand curve: a (a)x，ay)，b(bx，by)，c(cx，cy) And drawing a variable capacity demand curve based on a capacity market mechanism based on three coordinate punctuations.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.

Claims (10)

1. A method for determining a variable capacity demand curve is characterized by comprising the following steps:
obtaining historical load data, calculating the system target capacity b of the capacity delivery yearx；
Obtaining system capacity supply cxAnd capacity requirement axCalculating a system tolerance value (c)x-ax)；
Setting a capacity price b corresponding to a target capacity of a system based on fixed cost of marginal units operated at peak time of the systemyAnd price cap ay；
Obtaining three coordinate points on the variable capacity demand curve: a (a)x，ay)，b(bx，by)，c(cx，cy) And establishing a variable capacity demand curve based on three coordinate points.
2. The method of claim 1,
the historical load data is load data for a period of time prior to the year of delivery of the capacity.
3. The method of claim 1,
system target capacity b of said capacity year of deliveryxThe method specifically comprises the following steps:
bx＝RelReq＝Lp×(1+IRM)×(1-S)-FRR
in the formula, Lp, IRM, S and FRR are respectively the load peak value, the standby rate, the forced shutdown rate and the load self-supply capacity of each partition of the system.
4. The method of claim 3,
the determination of the forced outage rate of the system is based on historical data, and specifically comprises the following steps:
equivalent forced outage rate EFOR equal to all units planned to be put into service in year of deliverydAccording to the weighted average value of the unit capacity and the service hours; the specific calculation method comprises the following steps:
Figure FDA0003136526490000021
Figure FDA0003136526490000022
EFDH＝EFOH-FOH
Figure FDA0003136526490000023
Figure FDA0003136526490000024
Figure FDA0003136526490000025
Figure FDA0003136526490000026
Figure FDA0003136526490000027
wherein, EFORdThe equivalent forced outage rate of the unit; pmaxThe capacity of the unit; SH is the service hours of the unit; f. offAnd fpF coefficient and p coefficient when the computer unit is equivalent to the forced outage rate respectively; AH is the number of available hours; FOH is the number of hours of forced shutdown of the unit; EFDH is equivalent planned derating hours of the unit; EFOH is the equivalent forced outage hours of the unit; r, T, D are respectively the mean time of forced outage, mean call interval, meanRunning time; RSH is standby down time.
5. The method of claim 2,
the standby rate is determined based on a system historical load model and a capacity model, and specifically comprises the following steps:
generating a weekly peak-to-peak load distribution based on historical load data, generating a weekly available power generation capacity distribution based on historical unit shutdown events, performing convolution operation on the weekly peak-to-peak load distribution and the available power generation capacity distribution, wherein the area corresponding to the area with the power supply margin smaller than 0 is LOLP, and adding the LOLPs of each week to obtain annual LOLPs; when the annual LOLP meets the system requirements, then the utilization IRM is equal to the installed capacity divided by the peak annual load at that time.
6. The method of claim 1, wherein:
said system capacity supply cxAnd capacity requirement axThe specific calculation method comprises the following steps:
Figure FDA0003136526490000031
Figure FDA0003136526490000032
wherein, the IRM is the standby rate of each partition of the system, and a 'and c' are constants.
7. The method of claim 1,
said volume price byAnd price cap ayThe method specifically comprises the following steps:
Figure FDA0003136526490000033
Figure FDA0003136526490000034
in the formula, CONE is the annual fixed cost of the marginal unit operated at the peak time of the system; the E & AS is the average annual revenue value obtained by marginal units operating at peak times of the system from the electric energy market and the ancillary services market before the year of capacity delivery.
8. A variable capacity demand curve determination system, comprising:
a first calculating unit for acquiring the historical load data and calculating the system target capacity b of the capacity delivery yearx；
A second calculation unit for acquiring system capacity supply cxAnd capacity requirement axCalculating a system tolerance value (c)x-ax)；
A third calculating unit for setting a capacity price b corresponding to the target capacity of the system based on the fixed cost of the marginal unit operated at the peak time of the systemyAnd price cap ay；
The curve establishing unit is used for obtaining three coordinate points on the variable capacity demand curve: a (a)x，ay)，b(bx，by)，c(cx，cy) And establishing a variable capacity demand curve based on three coordinate points.
9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the variable capacity demand curve determination method according to any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium storing a computer program which, when executed by a processor, implements the steps of the variable capacity demand curve determination method according to any one of claims 1 to 7.
CN202110721009.1A 2021-06-28 2021-06-28 Method, system, equipment and storage medium for determining variable capacity demand curve Pending CN113344427A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202110721009.1A CN113344427A (en) 2021-06-28 2021-06-28 Method, system, equipment and storage medium for determining variable capacity demand curve

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202110721009.1A CN113344427A (en) 2021-06-28 2021-06-28 Method, system, equipment and storage medium for determining variable capacity demand curve

Publications (1)

Publication Number Publication Date
CN113344427A true CN113344427A (en) 2021-09-03

Family

ID=77479219

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202110721009.1A Pending CN113344427A (en) 2021-06-28 2021-06-28 Method, system, equipment and storage medium for determining variable capacity demand curve

Country Status (1)

Country Link
CN (1) CN113344427A (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113344636A (en) * 2021-06-28 2021-09-03 中国电力科学研究院有限公司 Method, system, equipment and storage medium for clearing power capacity market partition

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113344636A (en) * 2021-06-28 2021-09-03 中国电力科学研究院有限公司 Method, system, equipment and storage medium for clearing power capacity market partition

Similar Documents

Publication Publication Date Title
CN108132839B (en) Resource scheduling method and device
CN113344427A (en) Method, system, equipment and storage medium for determining variable capacity demand curve
CN105656025A (en) Method of increasing wind power absorption capability
CN111832824A (en) Electric power frequency modulation market trading clearing and settlement method, device and system
CN109193802A (en) A kind of Demand-side resource regulating method and system considering new energy prediction error
CN110472871A (en) A kind of investigation method for management line loss abnormal cause
CN109040793A (en) A kind of playback method and device
CN116544999A (en) Method, device, equipment and medium for determining installed capacity of energy storage system
CN111478373A (en) Active control method and system for new energy in consideration of medium-long-term transaction and real-time replacement
CN116822954A (en) Evaluation method and device for power generation project, electronic equipment and storage medium
CN112712440A (en) Demand response market resource allocation method and device for power spot market
JP7205669B1 (en) Energy supply and demand operation guidance device and its system, optimization calculation server device and program for optimization calculation server device, guidance terminal device and program for guidance terminal device, and energy supply and demand operation method and energy supply and demand operation program in business establishment
CN113078688B (en) Day-ahead thermal power starting optimization method and system for preventing and controlling standby shortage risk
CN111582720B (en) Monitoring processing method and device based on power supplier and storage medium
CN110244096B (en) Method for automatically discovering and processing electric meter full code in electric energy metering system
CN113420991A (en) Power supply energy storage joint planning method and system considering expected power shortage linearization
CN115879676A (en) Method and device for regulating and controlling cold chain to participate in power auxiliary service market
CN112101642A (en) Coal consumption cost offset method for improving marginal cost algorithm of thermal power plant
CN111724056B (en) Direct current planning method and system for preferentially absorbing clean energy
CN113344636B (en) Method, system, equipment and storage medium for clearing power capacity market partition
CN113065682B (en) Method and device for dispatching gas-electricity comprehensive energy system
CN112467801B (en) Method and system for optimizing new energy station daily power generation plan
CN117559434A (en) Method and device for clearing capacity market considering energy storage and new energy
CN116937602A (en) Operation control method and device of ammonia production unit, electronic equipment and storage medium
CN109903093A (en) Communicate marketing method and platform

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