CN113011030A - CPS 1-based frequency modulation capacity allocation method and device and storage medium - Google Patents

CPS 1-based frequency modulation capacity allocation method and device and storage medium Download PDF

Info

Publication number
CN113011030A
CN113011030A CN202110311652.7A CN202110311652A CN113011030A CN 113011030 A CN113011030 A CN 113011030A CN 202110311652 A CN202110311652 A CN 202110311652A CN 113011030 A CN113011030 A CN 113011030A
Authority
CN
China
Prior art keywords
frequency modulation
capacity
energy storage
traditional
load sequence
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
CN202110311652.7A
Other languages
Chinese (zh)
Other versions
CN113011030B (en
Inventor
李广凯
洪骁
谷裕
刘志学
郑金
段力勇
柳勇军
谢明磊
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.)
China Southern Power Grid Co Ltd
Research Institute of Southern Power Grid Co Ltd
Original Assignee
China Southern Power Grid Co Ltd
Research Institute of Southern Power Grid Co Ltd
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 China Southern Power Grid Co Ltd, Research Institute of Southern Power Grid Co Ltd filed Critical China Southern Power Grid Co Ltd
Priority to CN202110311652.7A priority Critical patent/CN113011030B/en
Publication of CN113011030A publication Critical patent/CN113011030A/en
Application granted granted Critical
Publication of CN113011030B publication Critical patent/CN113011030B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00Computer-aided design [CAD]
    • G06F30/20Design optimisation, verification or simulation
    • 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
    • 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
    • G06Q10/06Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063Operations research, analysis or management
    • G06Q10/0631Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • 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
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F2111/00Details relating to CAD techniques
    • G06F2111/04Constraint-based CAD
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F2111/00Details relating to CAD techniques
    • G06F2111/08Probabilistic or stochastic CAD
    • 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
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02EREDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E40/00Technologies for an efficient electrical power generation, transmission or distribution
    • Y02E40/70Smart grids as climate change mitigation technology in the energy generation sector
    • 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)
  • Human Resources & Organizations (AREA)
  • Economics (AREA)
  • Strategic Management (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Marketing (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Tourism & Hospitality (AREA)
  • General Business, Economics & Management (AREA)
  • Development Economics (AREA)
  • Operations Research (AREA)
  • Quality & Reliability (AREA)
  • Health & Medical Sciences (AREA)
  • Game Theory and Decision Science (AREA)
  • General Health & Medical Sciences (AREA)
  • Geometry (AREA)
  • General Engineering & Computer Science (AREA)
  • Evolutionary Computation (AREA)
  • Computer Hardware Design (AREA)
  • Primary Health Care (AREA)
  • Water Supply & Treatment (AREA)
  • Public Health (AREA)
  • Educational Administration (AREA)
  • Supply And Distribution Of Alternating Current (AREA)

Abstract

The invention provides a CPS 1-based frequency modulation capacity allocation method, which comprises the steps of establishing a relation between conventional generated power and energy storage capacity and a relation between stored energy generated power and energy storage capacity, to meet the CPS1 standard under random load variation and model the above constraint relationship in a mixed integer linear programming model, wherein the mixed integer linear programming model aims at minimizing the total cost of the energy storage frequency modulation capacity and the traditional frequency modulation capacity, then, by solving the mixed integer linear programming model, the traditional frequency modulation capacity and the energy storage frequency modulation capacity are distributed and scheduled, the uncertainty of the power systems of the two regions and the load fluctuation is considered, so that the power dispatching center mechanism of the single region can reasonably distribute and dispatch the traditional power generation resources and energy storage resources, and the frequency modulation performance of the regional power grid is greatly improved. The invention also correspondingly provides a frequency modulation capacity distribution device based on the CPS1 and a storage medium.

Description

CPS 1-based frequency modulation capacity allocation method and device and storage medium
Technical Field
The invention belongs to the technical field of electric power, and particularly relates to a CPS 1-based frequency modulation capacity allocation method, a CPS 1-based frequency modulation capacity allocation device and a storage medium.
Background
Unlike conventional power generation resources (such as coal and hydroelectric power plants), Energy storage systems (Energy storage systems) have limited Energy and cannot maintain power supply for a long time. However, such constant supply is necessary in order to satisfy high power matching under various system conditions, such as when a large number of loads are connected (early morning hours) or disconnected. At present, the power market still takes the traditional frequency modulation resources as the main part and takes the energy storage frequency modulation resources as the auxiliary part to participate in the frequency modulation service, and if the traditional power generation resources and the energy storage resources cannot be reasonably distributed and scheduled, the stability of frequency regulation is not facilitated, and the stable operation of a system is influenced.
Disclosure of Invention
Various aspects of the embodiment of the invention provide a CPS 1-based frequency modulation capacity allocation method, a CPS 1-based frequency modulation capacity allocation device and a CPS 1-based frequency modulation capacity allocation storage medium, so that a single-region power dispatching center mechanism can reasonably allocate traditional power generation resources and energy storage resources, and further the frequency modulation performance of a regional power grid is improved.
The frequency modulation capacity allocation method based on CPS1 provided by the embodiment of the invention comprises the following steps:
acquiring a maximum available traditional frequency modulation capacity group and a maximum available energy storage frequency modulation capacity group from a resource pool;
performing discrete processing on the maximum available energy storage frequency modulation capacity group to obtain an energy storage capacity group;
constructing a frequency response simulation model of the two-region interconnected power grid, wherein the simulation model is analyzed in a first region and realizes automatic power generation control under the condition that an oscillation or transmission system between machines is not considered;
inputting the energy storage capacity group, the maximum available traditional frequency modulation capacity group and the load sequence set into the simulation model to obtain the CF1The traditional frequency modulation capacity group corresponding to each load sequence is less than or equal to 1, and the energy storage frequency modulation capacity group corresponding to each load sequence;
obtaining an energy storage frequency modulation expected capacity group according to the probability of each load sequence and the energy storage frequency modulation capacity group corresponding to each load sequence;
obtaining a traditional frequency modulation expected capacity group according to the probability of each load sequence and the traditional frequency modulation capacity group corresponding to each load sequence;
establishing a mixed integer linear programming model by taking the minimum total cost of the rated energy storage frequency modulation capacity and the traditional frequency modulation capacity of a system as a target, wherein the mixed integer linear programming model considers the relation constraint between the traditional generating power and the energy storage capacity, the relation constraint between the energy storage frequency modulation capacity and the energy storage frequency modulation expected capacity group and the relation constraint between the traditional frequency modulation capacity and the traditional frequency modulation expected capacity group;
and solving the mixed integer linear programming model to obtain a regional power grid dispatching scheme, and distributing the traditional frequency modulation capacity and the energy storage frequency modulation capacity according to the regional power grid dispatching scheme.
Preferably, the maximum available energy storage frequency modulation capacity group is subjected to discrete processing to obtain an energy storage capacity group, and specifically:
performing discrete processing on all available energy storage frequency modulation capacity data contained in the maximum available energy storage frequency modulation capacity group to obtain a plurality of energy storage capacity combination data, wherein the energy storage capacity combination data is any one available energy storage frequency modulation capacity data or the sum of any plurality of available energy storage frequency modulation capacity data;
obtaining an energy storage capacity group according to the data of the plurality of energy storage capacity combinations, namely:
Figure BDA0002987852750000021
wherein, Pess,regIs a set of energy storage capacity and has
Figure BDA0002987852750000022
Pess,maxIs the maximum available energy storage capacity.
Preferably, the load sequence set is obtained by:
acquiring historical power load data, and obtaining an initial load sequence set through Gaussian random distribution under the condition that the mean value and the variance are known;
and reducing the initial load sequence set to obtain a load sequence set, wherein the load sequence set comprises a plurality of representative load sequences.
Preferably, the energy storage capacity group, the maximum available conventional frequency modulation capacity group and the load sequence set are input into the simulation model to obtain the CF1Each load sequence is less than or equal to 1 and corresponds to a conventional FM capacity group and each load sequenceThe energy storage frequency modulation capacity group specifically comprises:
acquiring a load sequence in the load sequence set, and inputting the acquired load sequence, the energy storage capacity group and the maximum available traditional frequency modulation capacity group into the simulation model for calculation;
based on the load sequence scenario of the current input, each energy storage capacity combination data in the energy storage capacity group is calculated in the simulation model in turn such that CF1The traditional power generation capacity corresponding to the requirement is less than or equal to 1, and each traditional power generation capacity corresponding to the currently input load sequence is obtained;
determining each energy storage power generation capacity corresponding to the currently input load sequence according to each traditional power generation capacity corresponding to the currently input load sequence;
according to each traditional power generation capacity corresponding to the currently input load sequence, obtaining a traditional frequency modulation capacity group corresponding to the currently input load sequence;
according to each energy storage power generation capacity corresponding to the currently input load sequence, obtaining an energy storage frequency modulation capacity group corresponding to the currently input load sequence;
and repeating all the steps, and calculating all the rest load sequences in sequence to obtain a traditional frequency modulation capacity group corresponding to each load sequence and an energy storage frequency modulation capacity group corresponding to each load sequence.
Preferably, each energy storage capacity combination data in the energy storage capacity group is calculated in the simulation model in turn based on the load sequence scenario currently input, so that CF is calculated1The traditional power generation capacity corresponding to the requirement less than or equal to 1 is obtained, and each traditional power generation capacity corresponding to the currently input load sequence is specifically:
based on the currently input load sequence scene, sequentially judging whether each energy storage capacity combination data in the energy storage capacity group receives each traditional frequency modulation capacity data in the maximum available traditional frequency modulation capacity group or not, wherein the receiving condition is that the energy storage capacity combination data and the traditional frequency modulation capacity data are currently input in the negative frequency modulation capacity groupEnable CF in a load sequence scenario1Less than or equal to 1;
and accumulating all the traditional frequency modulation capacity data meeting the receiving condition received by each energy storage capacity combination data respectively, and taking the accumulated result as the traditional power generation capacity corresponding to each energy storage capacity combination data.
Preferably, the obtaining of the conventional frequency modulation expected capacity group according to the probability of each load sequence and the conventional frequency modulation capacity group corresponding to each load sequence specifically includes:
Figure BDA0002987852750000041
wherein, IE (P)cg,reg) For conventional FM desired capacity groups, Pr(r) is the probability of the load sequence r,
Figure BDA0002987852750000042
and the load sequence R is a traditional frequency modulation capacity group corresponding to the load sequence R, and R is the total number of load sequences contained in the load sequence set.
Preferably, the obtaining of the energy storage frequency modulation expected capacity group according to the probability of each load sequence and the energy storage frequency modulation capacity group corresponding to each load sequence specifically includes:
Figure BDA0002987852750000043
wherein, IE (P)ess,reg) Frequency modulation of desired capacity group for energy storage, Pr(r) is the probability of the load sequence r,
Figure BDA0002987852750000044
and the load sequences are energy storage frequency modulation capacity groups corresponding to the load sequences R, and R is the total number of the load sequences contained in the load sequence set.
Preferably, the establishing of the mixed integer linear programming model with the minimum total cost of the system rated energy storage frequency modulation capacity and the conventional frequency modulation capacity as a target, the mixed integer linear programming model considering a relationship constraint between the conventional power generation and energy storage capacity, a relationship constraint between the energy storage frequency modulation capacity and the energy storage frequency modulation expected capacity set, and a relationship constraint between the conventional frequency modulation capacity and the conventional frequency modulation expected capacity set specifically includes:
(1) establishing and considering the relation constraint between the traditional generating power and the energy storage capacity:
constructing a first piecewise linear curve from each energy storage capacity combination data in the set of energy storage capacities and each element in the set of conventional fm expected capacities;
(2) establishing a relation constraint considering the energy storage power generation power and the energy storage capacity:
constructing a second piecewise linear curve according to each energy storage capacity combination data in the energy storage capacity group and each element in the energy storage frequency modulation expected capacity group;
(3) introducing a set of variables represented as
Figure BDA0002987852750000045
Such that λ is constrained by SOS2 and satisfies the following equation:
Figure BDA0002987852750000046
Figure BDA0002987852750000047
Figure BDA0002987852750000051
Figure BDA0002987852750000052
Figure BDA0002987852750000053
wherein the content of the first and second substances,
Figure BDA0002987852750000054
and
Figure BDA0002987852750000055
are two sets of indices defined by SOS2 constrained modeling, biIs an additional set of binary variables;
(4) establishing relation constraint between the energy storage frequency modulation capacity and the energy storage frequency modulation expected capacity group, and specifically comprising the following steps:
Pess,regλT≤Pess
Figure BDA0002987852750000056
wherein, PessAnd EessIs a variable of a mixed integer linear programming model, PessEnergy storage frequency modulation capacity representing the participation of energy storage in frequency modulation reporting, EessIs PessCapacity actually used for frequency modulation inside;
(5) establishing a relation constraint between a traditional frequency modulation capacity and the traditional frequency modulation expected capacity group, specifically comprising:
Figure BDA0002987852750000057
wherein, PcgIs another variable of the mixed integer linear programming model, representing the traditional frequency modulation capacity;
(6) establishing an objective function, specifically:
Figure BDA0002987852750000058
wherein, Cess,regCost of frequency modulation required for 1MW energy storage and power generation capacity per call, Ccg,regFrequency modulation required for conventional power generation capacity of 1MW per callAnd (4) cost.
Another aspect of the embodiments of the present invention provides a frequency modulation capacity allocation apparatus based on CPS1, including:
the system comprises a traditional and energy storage capacity acquisition module, a resource pool acquisition module and a resource management module, wherein the traditional and energy storage capacity acquisition module is used for acquiring a maximum available traditional frequency modulation capacity group and a maximum available energy storage frequency modulation capacity group from the resource pool;
the energy storage capacity discrete processing module is used for performing discrete processing on the maximum available energy storage frequency modulation capacity group to obtain an energy storage capacity group;
the simulation model establishing module is used for establishing a frequency response simulation model of the two-region interconnected power grid, and the simulation model is analyzed in the first region and realizes automatic power generation control under the condition that an oscillation or transmission system between machines is not considered;
a traditional and energy storage frequency modulation capacity calculation module for inputting the energy storage capacity group, the maximum available traditional frequency modulation capacity group and the load sequence set into the simulation model to obtain the CF1The traditional frequency modulation capacity group corresponding to each load sequence is less than or equal to 1, and the energy storage frequency modulation capacity group corresponding to each load sequence;
the energy storage frequency modulation expected capacity calculation module is used for obtaining an energy storage frequency modulation expected capacity group according to the probability of each load sequence and the energy storage frequency modulation capacity group corresponding to each load sequence;
the traditional frequency modulation expected capacity calculation module is used for obtaining a traditional frequency modulation expected capacity group according to the probability of each load sequence and the traditional frequency modulation capacity group corresponding to each load sequence;
the mixed integer linear programming model establishing module is used for establishing a mixed integer linear programming model by taking the minimum total cost of the rated energy storage frequency modulation capacity and the traditional frequency modulation capacity of a system as a target, wherein the mixed integer linear programming model considers the relation constraint between the traditional generating power and the energy storage capacity, the relation constraint between the energy storage frequency modulation capacity and the energy storage frequency modulation expected capacity group and the relation constraint between the traditional frequency modulation capacity and the traditional frequency modulation expected capacity group;
and the scheduling module is used for solving the mixed integer linear programming model to obtain a regional power grid scheduling scheme and distributing the traditional frequency modulation capacity and the energy storage frequency modulation capacity according to the regional power grid scheduling scheme.
Correspondingly, the embodiment of the invention also provides a storage medium, which comprises a stored computer program, wherein when the computer program runs, the device where the storage medium is located is controlled to execute the frequency modulation capacity allocation method based on the CPS 1.
Compared with the prior art, the invention has the following beneficial effects:
according to the frequency modulation capacity distribution method based on CPS1 provided by the embodiment of the invention, a maximum available traditional frequency modulation capacity group and a maximum available energy storage frequency modulation capacity group are obtained from a resource pool, the maximum available energy storage frequency modulation capacity group is subjected to discrete processing to obtain an energy storage capacity group, a frequency response simulation model of a two-region interconnected power grid is established, the energy storage capacity group, the maximum available traditional frequency modulation capacity group and a load sequence are input into the simulation model in a set mode to obtain a traditional frequency modulation capacity group corresponding to each load sequence and an energy storage frequency modulation capacity group corresponding to each load sequence, wherein CF1 is smaller than or equal to 1, so that relation constraint between traditional power generation power and energy storage capacity is constructed according to the energy storage frequency modulation capacity group and each energy storage capacity combination data in the energy storage capacity group, and a relation constraint between the energy storage power generation power and the energy storage capacity is constructed according to the traditional frequency modulation capacity group and each energy storage capacity combination data in the energy storage And system constraint, adding all the relation constraints into the mixed integer linear programming model for modeling, wherein the mixed integer linear programming model aims at minimizing the total cost of the rated energy storage frequency modulation capacity and the traditional frequency modulation capacity of the system, and finally solving the mixed integer linear programming model to obtain a regional power grid scheduling scheme, so that the traditional frequency modulation capacity and the energy storage frequency modulation capacity are distributed according to the regional power grid scheduling scheme, uncertainty of power systems of two regions and load fluctuation is considered, a power scheduling central mechanism of a single region can reasonably distribute and schedule the traditional power generation resources and the energy storage resources, and the frequency modulation performance of the regional power grid is greatly improved. The embodiment of the invention also correspondingly provides a CPS 1-based frequency modulation capacity allocation device and a storage medium.
Drawings
Fig. 1 is a schematic flow chart of a frequency modulation capacity allocation method based on CPS1 according to an embodiment of the present invention;
fig. 2 is a frequency response simulation model of a two-region interconnected power grid, which is constructed by the frequency modulation capacity allocation method based on CPS1 provided by the embodiment of the invention;
fig. 3 is a block diagram of an implementation process of step S4 of the frequency modulation capacity allocation method based on CPS1 according to the embodiment of the present invention;
fig. 4 is a block diagram of a frequency modulation capacity allocation apparatus based on CPS1 according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, it is a schematic flow chart of a frequency modulation capacity allocation method based on CPS1 according to an embodiment of the present invention.
The frequency modulation capacity distribution method based on CPS1 provided by the embodiment of the invention comprises the following steps S1-S8:
and step S1, acquiring the maximum available traditional frequency modulation capacity group and the maximum available energy storage frequency modulation capacity group from the resource pool.
Specifically, the maximum available conventional frequency modulation capacity group contains a plurality of available conventional frequency modulation capacity data, and the maximum available energy storage frequency modulation capacity group contains a plurality of available energy storage frequency modulation capacity data. During specific implementation, a plurality of available traditional frequency modulation capacity data and a plurality of available energy storage frequency modulation capacity can be obtained from data reported by a plurality of power generation enterprises.
And step S2, performing discrete processing on the maximum available energy storage frequency modulation capacity group to obtain an energy storage capacity group.
In an optional implementation manner, all available energy storage frequency modulation capacity data contained in the maximum available energy storage frequency modulation capacity group are subjected to discrete processing to obtain a plurality of energy storage capacity combination data, where the energy storage capacity combination data is any one available energy storage frequency modulation capacity data or the sum of any plurality of available energy storage frequency modulation capacity data;
obtaining an energy storage capacity group according to the data of the plurality of energy storage capacity combinations, namely:
Figure BDA0002987852750000081
wherein, Pess,regIs a set of energy storage capacity and has
Figure BDA0002987852750000082
Pess,maxIs the maximum available energy storage capacity. It is to be understood that the maximum available energy storage capacity is the sum of all available energy storage capacity data acquired.
And step S3, constructing a frequency response simulation model of the two-region interconnected network, wherein the simulation model analyzes and realizes automatic power generation control in the first region without considering the oscillation or transmission system between machines.
Referring to fig. 2, fig. 2 is a frequency response simulation model of a two-region interconnected power grid, which is constructed by the frequency modulation capacity allocation method based on CPS1 according to the embodiment of the present invention. The model establishes a power system of two regions, and aims to realize the optimized scheduling of the power system on the traditional power generation resources and energy storage frequency modulation resources, and analyze and realize automatic power generation control (AGC) in the first region. The model does not take into account the oscillation or transmission system between the machines, but is based on a linearization around an operating point, assuming coherent response of all generators in a region to changes in the system load, and using an equivalent inertia constant M1Is represented by a single generator. The model has a single damping constant D for the load damping effect1And (4) showing.
The load change in the first region is represented as Δ PLThe second region output power increase is expressed as Δ Ptie. The second region does not implement AGC, and furthermore, T12Is a synchronous torque coefficient for modeling a straight line and can be calculated by using a steady-state load flow solution. Each power dispatching center mechanism is mainly responsible for compensating load change in the area under the condition that other areas are not influenced, so that only the load change of the model in the first area is researched, and the load fluctuation of other areas is not considered. Selecting a shift factor B1 of the first region to obtain the frequency response characteristic
Figure BDA0002987852750000091
The influence of the selection of B1 on other zone load fluctuation is negligible, and R1 represents the frequency modulation equivalent reduction coefficient of the first zone power system and is determined by the system.
The simulation model calculates ACE every 2 seconds and uses a participation factor PF1And PF2The distribution between the traditional power generation resource and the energy storage frequency modulation resource is carried out, and the fractional gain of the distribution is proportional to the distribution capacity, such as PF in figure 21And PF2Expressed as:
Figure BDA0002987852750000092
wherein, PF1And PF2Respectively, the scale factors of the energy storage resource and the traditional power generation resource participating in frequency modulation in the power system of the first region.
Step S4, inputting the energy storage capacity group, the maximum available traditional frequency modulation capacity group and the load sequence set into the simulation model to obtain the CF1(the one-minute computer represents the standard frequency deviation coefficient per minute) less than or equal to 1, and the conventional fm capacity group corresponding to each load sequence and the energy storage fm capacity group corresponding to each load sequence.
In an alternative embodiment, the set of energy storage capacities, the set of maximum available conventional fm capacities, and the load orderColumn set input into the simulation model, resulting in CF1The traditional frequency modulation capacity group corresponding to each load sequence and the energy storage frequency modulation capacity group corresponding to each load sequence which are less than or equal to 1 specifically comprise:
acquiring a load sequence in the load sequence set, and inputting the acquired load sequence, the energy storage capacity group and the maximum available traditional frequency modulation capacity group into the simulation model for calculation;
based on the load sequence scenario of the current input, each energy storage capacity combination data in the energy storage capacity group is calculated in the simulation model in turn such that CF1The traditional power generation capacity corresponding to the requirement is less than or equal to 1, and each traditional power generation capacity corresponding to the currently input load sequence is obtained;
determining each energy storage power generation capacity corresponding to the currently input load sequence according to each traditional power generation capacity corresponding to the currently input load sequence;
according to each traditional power generation capacity corresponding to the currently input load sequence, obtaining a traditional frequency modulation capacity group corresponding to the currently input load sequence;
according to each energy storage power generation capacity corresponding to the currently input load sequence, obtaining an energy storage frequency modulation capacity group corresponding to the currently input load sequence;
and repeating all the steps, and calculating all the rest load sequences in sequence to obtain a traditional frequency modulation capacity group corresponding to each load sequence and an energy storage frequency modulation capacity group corresponding to each load sequence.
Further, in an optional embodiment, each energy storage capacity combination data in the energy storage capacity group is sequentially calculated in the simulation model based on the load sequence scenario of the current input, so that CF is calculated1The traditional power generation capacity corresponding to the requirement less than or equal to 1 is obtained, and each traditional power generation capacity corresponding to the currently input load sequence is specifically:
based on the currently input load sequence scene, each energy storage capacity combination data in the energy storage capacity group is in turnJudging whether to receive each conventional frequency modulation capacity data in the maximum available conventional frequency modulation capacity group, wherein the receiving condition is that the energy storage capacity combination data and the conventional frequency modulation capacity data can enable the CF under the current input load sequence scene1Less than or equal to 1;
and accumulating all the traditional frequency modulation capacity data meeting the receiving condition received by each energy storage capacity combination data respectively, and taking the accumulated result as the traditional power generation capacity corresponding to each energy storage capacity combination data.
In the embodiment of the invention, CPS1 index is adopted to measure the capacity planning of the energy storage system participating in frequency modulation. CPS1 can evaluate the influence of area ACE on the frequency deviation of the whole interconnected network in a period of time, and is a statistical measure of the ACE change condition. Since ACE represents the degree of balance between actual power generation and load in a control area, the CPS1 index reflects the comprehensive control performance of the area, including not only the real-time primary and secondary frequency modulation capabilities, but also the accuracy of day-ahead, day-in and real-time power generation planning of a fixed period, and the load management level on the power supply and demand sides. CPS1 can measure whether the root mean square value of the long-term frequency deviation of the power grid is within a limited range. In order to enable the AGC adjustment amount of the control area to maintain the stability of the power grid frequency, CPS1 is equal to or more than 100%.
In specific implementation, the energy storage capacity group, the maximum available traditional frequency modulation capacity group and the load sequence are input into a simulation model, and CF is calculated according to ACE and frequency offset1
Figure BDA0002987852750000111
Wherein the content of the first and second substances,<ACE>1min[n]represents the time step n of ACE calculation within 1min using the latest sample; Δ f represents the frequency offset (in Hz); b represents a frequency offset factor (MW/0.1Hz), typically a negative number, of the power dispatching center mechanism; epsilon1Representing a known constant.
Every hour and minute within 12 months before useClock acquisition CF1Calculates a CPS1 score and uses, on a rolling month basis:
CPS1score=(2-<CF1>12months)×100%,
according to the above formula, if CF1At each time step n less than 1, an average of 12 months less than 1 can be guaranteed, thereby guaranteeing a CPS1 score of greater than 100% per month.
Referring to fig. 3, fig. 3 is a block diagram of an implementation process of step S4 of the frequency modulation capacity allocation method based on CPS1 according to the embodiment of the present invention. In specific implementation, the algorithm 1 is repeatedly executed in the simulation model, and the algorithm 1 comprises an inner loop and an outer loop, wherein the outer loop is used for inputting the energy storage capacity group P in the simulation modeless,regEach of the energy storage capacity combination data
Figure BDA0002987852750000112
Performing iteration on the ith energy storage capacity combination data in the internal loop
Figure BDA0002987852750000113
Traverse the maximum available legacy FM capacity group Pcg,maxFinding the receivable overall frequency modulation capacity data by each traditional frequency modulation capacity data, and accumulating all the received traditional frequency modulation capacity data to obtain the corresponding traditional power generation capacity. When the data combined with the ith energy storage capacity is determined
Figure BDA0002987852750000114
And according to the traditional generating capacity, re-determining the energy storage generating capacity corresponding to the traditional generating capacity.
Whereby each of said energy storage capacity combination data is combined when the outer loop is executed
Figure BDA0002987852750000115
Can find the corresponding traditional generating capacity
Figure BDA0002987852750000116
And the energy storage and power generation capacity corresponding to the same
Figure BDA0002987852750000117
And finally, repeatedly executing the algorithm 1 by adopting different load sequences r to determine the traditional frequency modulation capacity group corresponding to each load sequence r
Figure BDA0002987852750000118
And energy storage frequency modulation capacity group
Figure BDA0002987852750000119
In an alternative embodiment, the load sequence is obtained by:
acquiring historical power load data, and obtaining an initial load sequence set through Gaussian random distribution under the condition that the mean value and the variance are known;
and reducing the initial load sequence set to obtain a load sequence set, wherein the load sequence set comprises a plurality of representative load sequences.
In particular implementations, a set of representative load sequences can be constructed by progressively selecting the initial load sequence with the smallest probability distance, where each load sequence has an associated probability.
And step S5, obtaining an expected capacity group of the energy storage frequency modulation according to the probability of each load sequence and the energy storage frequency modulation capacity group corresponding to each load sequence.
Specifically, the energy storage frequency modulation expected capacity group is obtained by calculating through the following formula:
Figure BDA0002987852750000121
wherein, IE (P)cg,reg) For conventional FM desired capacity groups, Pr(r) is the probability of the load sequence r,
Figure BDA0002987852750000122
and the load sequence R is a traditional frequency modulation capacity group corresponding to the load sequence R, and R is the total number of load sequences contained in the load sequence set.
And step S6, obtaining a traditional frequency modulation expected capacity group by the probability of each load sequence and the traditional frequency modulation capacity group corresponding to each load sequence.
Specifically, the traditional fm expected capacity group is calculated by the following formula:
Figure BDA0002987852750000123
wherein, IE (P)ess,reg) Frequency modulation of desired capacity group for energy storage, Pr(r) is the probability of the load sequence r,
Figure BDA0002987852750000124
and the load sequences are energy storage frequency modulation capacity groups corresponding to the load sequences R, and R is the total number of the load sequences contained in the load sequence set.
Step S7, establishing a mixed integer linear programming model by taking the minimum total cost of the rated energy storage frequency modulation capacity and the traditional frequency modulation capacity of the system as a target, wherein the mixed integer linear programming model considers the relation constraint between the traditional generating power and the energy storage capacity, the relation constraint between the energy storage frequency modulation capacity and the energy storage frequency modulation expected capacity group, and the relation constraint between the traditional frequency modulation capacity and the traditional frequency modulation expected capacity group.
As an optional implementation manner, the step S7 specifically includes:
(1) establishing and considering the relation constraint between the traditional generating power and the energy storage capacity:
constructing a first piecewise linear curve from each energy storage capacity combination data in the set of energy storage capacities and each element in the set of conventional fm expected capacities;
(2) establishing a relation constraint considering the energy storage power generation power and the energy storage capacity:
constructing a second piecewise linear curve according to each energy storage capacity combination data in the energy storage capacity group and each element in the energy storage frequency modulation expected capacity group;
(3) introducing a set of variables represented as
Figure BDA0002987852750000131
Such that λ is constrained by SOS2 and satisfies the following equation:
Figure BDA0002987852750000132
Figure BDA0002987852750000133
for each
Figure BDA0002987852750000134
Modeling SOS2 constraints as two sets of indices
Figure BDA0002987852750000135
And
Figure BDA0002987852750000136
and attaching a set of binary variables
Figure BDA0002987852750000137
And satisfies the following relationships:
Figure BDA0002987852750000138
Figure BDA0002987852750000139
Figure BDA00029878527500001310
ensuring, by the above constraints, that λ falls in a linear portion between two adjacent points of the first and second piecewise linear curves;
(4) establishing relation constraint between the energy storage frequency modulation capacity and the energy storage frequency modulation expected capacity group, and specifically comprising the following steps:
Pess,regλT≤Pess
Figure BDA00029878527500001311
wherein, PessAnd EessIs a variable of a mixed integer linear programming model, PessEnergy storage frequency modulation capacity representing the participation of energy storage in frequency modulation reporting, EessIs PessCapacity actually used for frequency modulation inside;
(5) establishing a relation constraint between a traditional frequency modulation capacity and the traditional frequency modulation expected capacity group, specifically comprising:
Figure BDA00029878527500001312
wherein, PcgIs another variable of the mixed integer linear programming model, representing the traditional frequency modulation capacity;
(6) establishing an objective function, specifically:
Figure BDA0002987852750000141
wherein, Cess,regCost of frequency modulation required for 1MW energy storage and power generation capacity per call, Ccg,regThe cost of frequency modulation required for each call of 1MW of conventional power generation capacity.
And step S8, solving the mixed integer linear programming model to obtain a regional power grid dispatching scheme, and distributing the traditional frequency modulation capacity and the energy storage frequency modulation capacity according to the regional power grid dispatching scheme.
According to the frequency modulation capacity distribution method based on CPS1 provided by the embodiment of the invention, a maximum available traditional frequency modulation capacity group and a maximum available energy storage frequency modulation capacity group are obtained from a resource pool, the maximum available energy storage frequency modulation capacity group is subjected to discrete processing to obtain an energy storage capacity group, a frequency response simulation model of a two-region interconnected power grid is established, the energy storage capacity group, the maximum available traditional frequency modulation capacity group and a load sequence are input into the simulation model in a set mode to obtain a traditional frequency modulation capacity group corresponding to each load sequence and an energy storage frequency modulation capacity group corresponding to each load sequence, wherein CF1 is smaller than or equal to 1, so that relation constraint between traditional power generation power and energy storage capacity is constructed according to the energy storage frequency modulation capacity group and each energy storage capacity combination data in the energy storage capacity group, and a relation constraint between the energy storage power generation power and the energy storage capacity is constructed according to the traditional frequency modulation capacity group and each energy storage capacity combination data in the energy storage And system constraint, adding all the relation constraints into the mixed integer linear programming model for modeling, wherein the mixed integer linear programming model aims at minimizing the total cost of the rated energy storage frequency modulation capacity and the traditional frequency modulation capacity of the system, and finally solving the mixed integer linear programming model to obtain a regional power grid scheduling scheme, so that the traditional frequency modulation capacity and the energy storage frequency modulation capacity are distributed according to the regional power grid scheduling scheme, uncertainty of power systems of two regions and load fluctuation is considered, a power scheduling central mechanism of a single region can reasonably distribute and schedule the traditional power generation resources and the energy storage resources, and the frequency modulation performance of the regional power grid is greatly improved. In addition, the regional power grid scheduling scheme obtained by the embodiment of the invention has the minimum scheduling total cost, can optimize and improve the minimum frequency modulation cost of the scheduling center layer of the regional power grid, and realizes the economic scheduling of the regional power grid.
Referring to fig. 4, fig. 4 is a block diagram of a frequency modulation capacity allocation apparatus based on CPS1 according to an embodiment of the present invention.
The frequency modulation capacity distribution device based on CPS1 provided by the embodiment of the invention comprises:
a legacy and energy storage capacity acquisition module 100, configured to acquire a maximum available legacy frequency modulation capacity group and a maximum available energy storage frequency modulation capacity group from a resource pool;
the energy storage capacity discrete processing module 101 is configured to perform discrete processing on the maximum available energy storage frequency modulation capacity group to obtain an energy storage capacity group;
the simulation model establishing module 102 is used for establishing a frequency response simulation model of the two-region interconnected power grid, and the simulation model is analyzed in a first region and realizes automatic power generation control under the condition that an oscillation or transmission system between machines is not considered;
a conventional and energy storage frequency modulation capacity calculation module 103, configured to input the energy storage capacity group, the maximum available conventional frequency modulation capacity group, and the load sequence set into the simulation model, so as to obtain a CF1The traditional frequency modulation capacity group corresponding to each load sequence is less than or equal to 1, and the energy storage frequency modulation capacity group corresponding to each load sequence;
the energy storage frequency modulation expected capacity calculation module 104 is configured to obtain an energy storage frequency modulation expected capacity group according to the probability of each load sequence and the energy storage frequency modulation capacity group corresponding to each load sequence;
a traditional frequency modulation expected capacity calculation module 105, which obtains a traditional frequency modulation expected capacity group according to the probability of each load sequence and the traditional frequency modulation capacity group corresponding to each load sequence;
a mixed integer linear programming model establishing module 106, configured to establish a mixed integer linear programming model with a goal of minimizing a total cost of a system rated energy storage frequency modulation capacity and a conventional frequency modulation capacity, where the mixed integer linear programming model considers a relationship constraint between a conventional power generation capacity and an energy storage capacity, a relationship constraint between an energy storage frequency modulation capacity and the energy storage frequency modulation expected capacity set, and a relationship constraint between a conventional frequency modulation capacity and the conventional frequency modulation expected capacity set;
and the scheduling module 107 is configured to solve the mixed integer linear programming model to obtain a regional power grid scheduling scheme, and allocate the conventional frequency modulation capacity and the energy storage frequency modulation capacity according to the regional power grid scheduling scheme.
Embodiments of the present invention further provide a storage medium including a stored computer program, wherein the apparatus on which the storage medium is located is controlled to execute steps S1 to S8 of the above-described frequency modulation capacity allocation method based on CPS1 when the computer program runs.
The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention.

Claims (10)

1. A CPS 1-based frequency modulation capacity allocation method is characterized by comprising the following steps:
acquiring a maximum available traditional frequency modulation capacity group and a maximum available energy storage frequency modulation capacity group from a resource pool;
performing discrete processing on the maximum available energy storage frequency modulation capacity group to obtain an energy storage capacity group;
constructing a frequency response simulation model of the two-region interconnected power grid, wherein the simulation model is analyzed in a first region and realizes automatic power generation control under the condition that an oscillation or transmission system between machines is not considered;
inputting the energy storage capacity group, the maximum available traditional frequency modulation capacity group and the load sequence set into the simulation model to obtain the CF1The traditional frequency modulation capacity group corresponding to each load sequence is less than or equal to 1, and the energy storage frequency modulation capacity group corresponding to each load sequence;
obtaining an energy storage frequency modulation expected capacity group according to the probability of each load sequence and the energy storage frequency modulation capacity group corresponding to each load sequence;
obtaining a traditional frequency modulation expected capacity group according to the probability of each load sequence and the traditional frequency modulation capacity group corresponding to each load sequence;
establishing a mixed integer linear programming model by taking the minimum total cost of the rated energy storage frequency modulation capacity and the traditional frequency modulation capacity of a system as a target, wherein the mixed integer linear programming model considers the relation constraint between the traditional generating power and the energy storage capacity, the relation constraint between the energy storage frequency modulation capacity and the energy storage frequency modulation expected capacity group and the relation constraint between the traditional frequency modulation capacity and the traditional frequency modulation expected capacity group;
and solving the mixed integer linear programming model to obtain a regional power grid dispatching scheme, and distributing the traditional frequency modulation capacity and the energy storage frequency modulation capacity according to the regional power grid dispatching scheme.
2. A frequency modulation capacity allocation method based on CPS1 as claimed in claim 1, wherein the discrete processing is performed on the maximum available energy storage frequency modulation capacity group to obtain an energy storage capacity group, specifically:
performing discrete processing on all available energy storage frequency modulation capacity data contained in the maximum available energy storage frequency modulation capacity group to obtain a plurality of energy storage capacity combination data, wherein the energy storage capacity combination data is any one available energy storage frequency modulation capacity data or the sum of any plurality of available energy storage frequency modulation capacity data;
obtaining an energy storage capacity group according to the data of the plurality of energy storage capacity combinations, namely:
Figure FDA0002987852740000021
wherein, Pess,regIs a set of energy storage capacity and has
Figure FDA0002987852740000022
Pess,maxIs the maximum available energy storage capacity.
3. A frequency modulation capacity allocation method based on CPS1 as claimed in claim 1, wherein the load sequence set is obtained by the steps of:
acquiring historical power load data, and obtaining an initial load sequence set through Gaussian random distribution under the condition that the mean value and the variance are known;
and reducing the initial load sequence set to obtain a load sequence set, wherein the load sequence set comprises a plurality of representative load sequences.
4. A frequency modulation capacity allocation method based on CPS1 as claimed in claim 1, wherein the input of the energy storage capacity group, the maximum available conventional frequency modulation capacity group and the load sequence set into the simulation model results in CF1The traditional frequency modulation capacity group corresponding to each load sequence and the energy storage frequency modulation capacity group corresponding to each load sequence which are less than or equal to 1 specifically comprise:
acquiring a load sequence in the load sequence set, and inputting the acquired load sequence, the energy storage capacity group and the maximum available traditional frequency modulation capacity group into the simulation model for calculation;
based on the load sequence scenario of the current input, each energy storage capacity combination data in the energy storage capacity group is calculated in the simulation model in turn such that CF1The traditional power generation capacity corresponding to the requirement is less than or equal to 1, and each traditional power generation capacity corresponding to the currently input load sequence is obtained;
determining each energy storage power generation capacity corresponding to the currently input load sequence according to each traditional power generation capacity corresponding to the currently input load sequence;
according to each traditional power generation capacity corresponding to the currently input load sequence, obtaining a traditional frequency modulation capacity group corresponding to the currently input load sequence;
according to each energy storage power generation capacity corresponding to the currently input load sequence, obtaining an energy storage frequency modulation capacity group corresponding to the currently input load sequence;
and repeating all the steps, and calculating all the rest load sequences in sequence to obtain a traditional frequency modulation capacity group corresponding to each load sequence and an energy storage frequency modulation capacity group corresponding to each load sequence.
5. A frequency modulated capacity allocation method based on CPS1 as claimed in claim 4, wherein based on the current input load sequence scenario, each energy storage capacity combination data in the energy storage capacity group is calculated in turn in the simulation model such that CF is calculated1The traditional power generation capacity corresponding to the requirement less than or equal to 1 is obtained, and each traditional power generation capacity corresponding to the currently input load sequence is specifically:
based on the currently input load sequence scene, sequentially judging whether to receive each conventional frequency modulation capacity data in the maximum available conventional frequency modulation capacity group or not by each energy storage capacity combination data in the energy storage capacity group, wherein the receiving condition is that the energy storage capacity combination data and the conventional frequency modulation capacity data can enable the CF to be in the currently input load sequence scene1Less than or equal to 1;
and accumulating all the traditional frequency modulation capacity data meeting the receiving condition received by each energy storage capacity combination data respectively, and taking the accumulated result as the traditional power generation capacity corresponding to each energy storage capacity combination data.
6. A frequency modulation capacity allocation method based on CPS1 as claimed in claim 1, wherein the conventional frequency modulation expected capacity set is obtained according to the probability of each load sequence and the conventional frequency modulation capacity set corresponding to each load sequence, specifically:
Figure FDA0002987852740000031
wherein, IE (P)cg,reg) For conventional FM desired capacity groups, Pr(r) is the probability of the load sequence r,
Figure FDA0002987852740000032
and the load sequence R is a traditional frequency modulation capacity group corresponding to the load sequence R, and R is the total number of load sequences contained in the load sequence set.
7. A frequency modulation capacity allocation method based on CPS1 as claimed in claim 1, wherein the obtaining of the energy storage frequency modulation expected capacity group according to the probability of each load sequence and the energy storage frequency modulation capacity group corresponding to each load sequence is specifically:
Figure FDA0002987852740000041
wherein, IE (P)ess,reg) Frequency modulation of desired capacity group for energy storage, Pr(r) is the probability of the load sequence r,
Figure FDA0002987852740000042
and the load sequences are energy storage frequency modulation capacity groups corresponding to the load sequences R, and R is the total number of the load sequences contained in the load sequence set.
8. The CPS 1-based fm capacity allocation method as claimed in claim 1, wherein the hybrid integer linear programming model is established with a goal of minimizing a total cost of a system-rated energy storage fm capacity and a conventional fm capacity, and the hybrid integer linear programming model considers a relationship constraint between a conventional generated power and an energy storage capacity, a relationship constraint between an energy storage fm capacity and the set of energy storage fm desired capacities, and a relationship constraint between a conventional fm capacity and the set of conventional fm desired capacities, and specifically includes:
(1) establishing and considering the relation constraint between the traditional generating power and the energy storage capacity:
constructing a first piecewise linear curve from each energy storage capacity combination data in the set of energy storage capacities and each element in the set of conventional fm expected capacities;
(2) establishing a relation constraint considering the energy storage power generation power and the energy storage capacity:
constructing a second piecewise linear curve according to each energy storage capacity combination data in the energy storage capacity group and each element in the energy storage frequency modulation expected capacity group;
(3) introducing a set of variables represented as
Figure FDA0002987852740000043
Such that λ is constrained by SOS2 and satisfies the following equation:
Figure FDA0002987852740000044
Figure FDA0002987852740000045
Figure FDA0002987852740000046
Figure FDA0002987852740000047
Figure FDA0002987852740000048
wherein the content of the first and second substances,
Figure FDA0002987852740000049
and
Figure FDA00029878527400000410
are two sets of indices defined by SOS2 constrained modeling, biIs an additional set of binary variables;
(4) establishing relation constraint between the energy storage frequency modulation capacity and the energy storage frequency modulation expected capacity group, and specifically comprising the following steps:
Pess,regλT≤Pess
Figure FDA0002987852740000051
wherein, PessAnd EessIs a variable of a mixed integer linear programming model, PessEnergy storage frequency modulation capacity representing the participation of energy storage in frequency modulation reporting, EessIs PessCapacity actually used for frequency modulation inside;
(5) establishing a relation constraint between a traditional frequency modulation capacity and the traditional frequency modulation expected capacity group, specifically comprising:
Figure FDA0002987852740000052
wherein, PcgIs another variable of the mixed integer linear programming model, representing the traditional frequency modulation capacity;
(6) establishing an objective function, specifically:
Figure FDA0002987852740000053
wherein, Cess,regRequired for 1MW energy storage and power generation capacity per callCost of frequency modulation of Ccg,regThe cost of frequency modulation required for each call of 1MW of conventional power generation capacity.
9. A frequency modulation capacity allocation apparatus based on CPS1, comprising:
the system comprises a traditional and energy storage capacity acquisition module, a resource pool acquisition module and a resource management module, wherein the traditional and energy storage capacity acquisition module is used for acquiring a maximum available traditional frequency modulation capacity group and a maximum available energy storage frequency modulation capacity group from the resource pool;
the energy storage capacity discrete processing module is used for performing discrete processing on the maximum available energy storage frequency modulation capacity group to obtain an energy storage capacity group;
the simulation model establishing module is used for establishing a frequency response simulation model of the two-region interconnected power grid, and the simulation model is analyzed in the first region and realizes automatic power generation control under the condition that an oscillation or transmission system between machines is not considered;
a traditional and energy storage frequency modulation capacity calculation module for inputting the energy storage capacity group, the maximum available traditional frequency modulation capacity group and the load sequence set into the simulation model to obtain the CF1The traditional frequency modulation capacity group corresponding to each load sequence is less than or equal to 1, and the energy storage frequency modulation capacity group corresponding to each load sequence;
the energy storage frequency modulation expected capacity calculation module is used for obtaining an energy storage frequency modulation expected capacity group according to the probability of each load sequence and the energy storage frequency modulation capacity group corresponding to each load sequence;
the traditional frequency modulation expected capacity calculation module is used for obtaining a traditional frequency modulation expected capacity group according to the probability of each load sequence and the traditional frequency modulation capacity group corresponding to each load sequence;
the mixed integer linear programming model establishing module is used for establishing a mixed integer linear programming model by taking the minimum total cost of the rated energy storage frequency modulation capacity and the traditional frequency modulation capacity of a system as a target, wherein the mixed integer linear programming model considers the relation constraint between the traditional generating power and the energy storage capacity, the relation constraint between the energy storage frequency modulation capacity and the energy storage frequency modulation expected capacity group and the relation constraint between the traditional frequency modulation capacity and the traditional frequency modulation expected capacity group;
and the scheduling module is used for solving the mixed integer linear programming model to obtain a regional power grid scheduling scheme and distributing the traditional frequency modulation capacity and the energy storage frequency modulation capacity according to the regional power grid scheduling scheme.
10. A storage medium characterized by comprising a stored computer program, wherein the apparatus on which the storage medium is located is controlled to execute the frequency modulation capacity allocation method based on CPS1 according to any one of claims 1 to 8 when the computer program is run.
CN202110311652.7A 2021-03-23 2021-03-23 CPS 1-based frequency modulation capacity allocation method and device and storage medium Active CN113011030B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202110311652.7A CN113011030B (en) 2021-03-23 2021-03-23 CPS 1-based frequency modulation capacity allocation method and device and storage medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202110311652.7A CN113011030B (en) 2021-03-23 2021-03-23 CPS 1-based frequency modulation capacity allocation method and device and storage medium

Publications (2)

Publication Number Publication Date
CN113011030A true CN113011030A (en) 2021-06-22
CN113011030B CN113011030B (en) 2022-12-06

Family

ID=76405856

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202110311652.7A Active CN113011030B (en) 2021-03-23 2021-03-23 CPS 1-based frequency modulation capacity allocation method and device and storage medium

Country Status (1)

Country Link
CN (1) CN113011030B (en)

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110417012A (en) * 2019-08-01 2019-11-05 国电南瑞科技股份有限公司 Power grid energy accumulation capacity configuration and system under a kind of constraint of frequency security
CN110994703A (en) * 2019-11-30 2020-04-10 江苏省电力有限公司电力科学研究院 Frequency modulation capacity demand allocation method considering multiple frequency modulation resources
CN112531792A (en) * 2020-12-03 2021-03-19 江苏方天电力技术有限公司 Frequency control method and system for interconnected power system containing energy storage resources

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110417012A (en) * 2019-08-01 2019-11-05 国电南瑞科技股份有限公司 Power grid energy accumulation capacity configuration and system under a kind of constraint of frequency security
CN110994703A (en) * 2019-11-30 2020-04-10 江苏省电力有限公司电力科学研究院 Frequency modulation capacity demand allocation method considering multiple frequency modulation resources
CN112531792A (en) * 2020-12-03 2021-03-19 江苏方天电力技术有限公司 Frequency control method and system for interconnected power system containing energy storage resources

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
穆永强等: "考虑系统负荷规模的CPS1标准修正方法", 《水利水电技术》 *
陈浩等: "基于CPS指标评估的不同场景调频储能容量配置", 《太原理工大学学报》 *

Also Published As

Publication number Publication date
CN113011030B (en) 2022-12-06

Similar Documents

Publication Publication Date Title
US11757404B2 (en) Coordinated control of renewable electric generation resource and charge storage device
CN105046395B (en) Method for compiling day-by-day rolling plan of power system containing multiple types of new energy
US10680445B2 (en) Power generation control device, power generation apparatus, control device, control system, control method, and recording medium
CN110535183A (en) A kind of dispatching method and system of virtual plant
CN110535119A (en) Adapt to the energy-accumulating power station period electricity scroll control method of peak load regulation network frequency modulation
CN111969613A (en) Demand response optimization scheduling method and system
WO2023167631A1 (en) An electrical power system and a multi-timescale coordinated optimization scheduling method therefor
Pilz et al. Selfish energy sharing in prosumer communities: A demand-side management concept
Yang et al. Control performance based dynamic regulation reserve allocation for renewable integrations
Mohamed et al. Stacking battery energy storage revenues in future distribution networks
Martinez-Rico et al. Sizing a battery energy storage system for hybrid renewable power plants based on optimal market participation under different market scenarios
CN107947246B (en) Wind power generation index distribution and increased power evaluation method considering frequency modulation and increased power
CN113011030B (en) CPS 1-based frequency modulation capacity allocation method and device and storage medium
CN112531703A (en) Optimization method for providing multi-market and local service by multi-energy virtual power plant
US11921482B2 (en) Method of controlling a microgrid, power management system, and energy management system
Zhang et al. Optimal day-ahead large-scale battery dispatch model for multi-regulation participation considering full timescale uncertainties
Han et al. Joint investment and operation optimization of a distribution system in a market environment
CN115842354A (en) Wind power energy storage configuration method for improving wind power prediction correlation coefficient
CN114936798A (en) Method and device for determining electric quantity scheduling scheme in target area
US20160328809A1 (en) Method and device for the provision of aggregate offers of electrical energy
CN111900740B (en) Power system frequency modulation method and system based on demand response equipment
Talari et al. Coordinated scheduling of demand response aggregators and customers in an uncertain environment
CN110676886A (en) Power system scheduling method and device, computer equipment and storage medium
Chhabra et al. Frequency regulation and economic dispatch using integrated storage in a hybrid renewable grid
Deng et al. Community energy storage management for welfare optimization using a Markov decision process

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