CN110676863A - Energy storage optimal configuration method and system - Google Patents
Energy storage optimal configuration method and system Download PDFInfo
- Publication number
- CN110676863A CN110676863A CN201911007302.0A CN201911007302A CN110676863A CN 110676863 A CN110676863 A CN 110676863A CN 201911007302 A CN201911007302 A CN 201911007302A CN 110676863 A CN110676863 A CN 110676863A
- Authority
- CN
- China
- Prior art keywords
- energy storage
- power station
- storage power
- price
- determining
- 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
Links
- 238000004146 energy storage Methods 0.000 title claims abstract description 321
- 238000000034 method Methods 0.000 title claims abstract description 44
- 230000005611 electricity Effects 0.000 claims description 26
- 238000005457 optimization Methods 0.000 claims description 16
- 238000012545 processing Methods 0.000 claims description 15
- 238000012423 maintenance Methods 0.000 claims description 12
- 238000004590 computer program Methods 0.000 claims description 10
- 238000007599 discharging Methods 0.000 claims description 9
- 239000013256 coordination polymer Substances 0.000 claims description 4
- 230000003203 everyday effect Effects 0.000 claims description 3
- 238000011084 recovery Methods 0.000 claims description 3
- 230000007246 mechanism Effects 0.000 abstract description 7
- 230000008901 benefit Effects 0.000 abstract description 4
- 238000004891 communication Methods 0.000 description 9
- 230000002354 daily effect Effects 0.000 description 6
- 238000010586 diagram Methods 0.000 description 3
- 230000006870 function Effects 0.000 description 3
- 238000010276 construction Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 238000004422 calculation algorithm Methods 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000004069 differentiation Effects 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000002452 interceptive effect Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 239000002245 particle Substances 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 239000004576 sand Substances 0.000 description 1
- 230000000087 stabilizing effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Images
Classifications
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06313—Resource planning in a project environment
-
- 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
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
- Y02E40/70—Smart grids as climate change mitigation technology in the energy generation sector
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- General Physics & Mathematics (AREA)
- Tourism & Hospitality (AREA)
- Health & Medical Sciences (AREA)
- Theoretical Computer Science (AREA)
- Entrepreneurship & Innovation (AREA)
- General Business, Economics & Management (AREA)
- Physics & Mathematics (AREA)
- Marketing (AREA)
- Life Sciences & Earth Sciences (AREA)
- Biodiversity & Conservation Biology (AREA)
- Operations Research (AREA)
- Development Economics (AREA)
- Game Theory and Decision Science (AREA)
- Power Engineering (AREA)
- Educational Administration (AREA)
- Quality & Reliability (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Supply And Distribution Of Alternating Current (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention provides an energy storage optimal configuration method and system, wherein the energy storage optimal configuration method comprises the following steps: determining the peak time period discharge price of the energy storage power station, determining the valley time period charge price of the energy storage power station, and determining the auxiliary service compensation price of the energy storage power station participating in peak regulation; determining the maximum net gain of the energy storage power station based on the peak time period discharge price of the energy storage power station, the valley time period charge price of the energy storage power station and the auxiliary service compensation price of the energy storage power station participating in peak shaving; and determining the capacity configuration of the energy storage power station based on the maximum net income and the constraint conditions of the energy storage power station. According to the energy storage optimal configuration method, the system, the electronic equipment and the storage medium, the energy storage power station is optimally configured based on the price mechanism, and the optimal capacity configuration of the energy storage power station can be determined, so that the benefit of the energy storage power station can be maximized, and the large-scale application of the energy storage power station is facilitated.
Description
Technical Field
The present invention relates to the field of energy storage, and more particularly, to an energy storage optimal configuration method, system, electronic device, and storage medium.
Background
In recent years, with the annual increase of the total power consumption, the peak-valley difference of the user load is increasingly increased, the staged power peak is obviously improved, meanwhile, the diversification of the power consumption load types in the power distribution network, the differentiation and the individuation of the user requirements are realized, the requirement of the user on the power supply quality is continuously improved, and the high requirement on environmental protection is met, the requirement on the diversification of the electric energy of the user is met while the high-efficiency utilization of clean energy is improved, however, the utilization rate of the clean renewable energy is low, the user lacks the response to a market mechanism, the load peak-valley difference is large, and the lack of an efficient interactive operation mechanism and the like are still ubiquitous problems.
The energy storage power station incorporated into the power distribution network has application functions of improving the influence of high-permeability distributed energy on a grid-connected point, solving the problems of wind abandoning, light abandoning and water abandoning, stabilizing the output fluctuation of the distributed power supply, clipping peaks and filling valleys, improving the power supply quality and the like, so that the energy storage power station becomes an important component for supporting the construction of a smart power grid and an energy internet in the future. Meanwhile, along with the improvement of the technical performance and the reduction of the cost of the energy storage power station, the economical efficiency of the battery energy storage power station technology with long service life, low cost and high energy conversion efficiency is gradually highlighted, and the application of the energy storage power station technology is gradually shifted from project demonstration to commercial operation.
However, in the related art, the capacity configuration of the energy storage power station is difficult to design, especially, the capacity configuration of part of the energy storage power stations is too large, so that the investment cost is high, the equipment is idle, and the capacity configuration of part of the energy storage power stations is too small, so that the matching requirements are difficult to meet, and the application of the energy storage power stations is restricted.
Disclosure of Invention
Embodiments of the present invention provide a solution to, or at least partially solve, the above problems.
In a first aspect, an embodiment of the present invention provides an energy storage optimization configuration method, including: determining the peak time period discharge price of the energy storage power station, determining the valley time period charge price of the energy storage power station, and determining the auxiliary service compensation price of the energy storage power station participating in peak regulation; determining the maximum net gain of the energy storage power station based on the peak time period discharge price of the energy storage power station, the valley time period charge price of the energy storage power station and the auxiliary service compensation price of the energy storage power station participating in peak shaving; and determining the capacity configuration of the energy storage power station based on the maximum net income and the constraint conditions of the energy storage power station.
In some embodiments, the maximum net gain of the energy storage power station is determined based on the high-storage low-discharge arbitrage of the energy storage power station, the auxiliary service compensation of the energy storage power station participating in peak shaving, the daily investment cost and the daily operation and maintenance cost of the energy storage power station.
In some embodiments, the maximum net profit of the energy storage power station is determined based on high storage and low discharge arbitrage of the energy storage power station, auxiliary service compensation of the energy storage power station participating in peak shaving, investment cost and operation and maintenance cost of the energy storage power station reduced to daily, and the method includes: using formulas
Determining a maximum net gain of the energy storage power station, wherein f is the net gain of the energy storage power station, f1The method is characterized in that the method is used for high-storage low-discharge arbitrage of an energy storage power station, T is a scheduling period, T is a time interval, Cr(t) the price of electricity in the corresponding time period, Ps(t) is the electricity price of the energy storage power station in the corresponding time period, f2Auxiliary service compensation for energy storage stations participating in peak shaving, CPLCompensating prices for peak shaving in energy storage power stations, Pwloss,tThe abandoned electricity quantity per hour before configuration of the energy storage power station is P'wloss,tElectricity discard per hour after configuration for energy storage power station, f3Investment costs and operational maintenance costs reduced to everyday for energy storage power stations, fcFor capital recovery factor, r is annual rate, TEFor the actual service time, alpha, of the energy storage plant in its life cyclesPower unit price, beta, reduced to annuity for energy storage power stationssReduced to annual capacity unit price, P, for energy storage power stationscapFor rated charge-discharge power of energy-storage power stations, ScapFor rated capacity of energy storage power station, fEFor unit investment cost of energy storage power station, fOMIs the unit operating maintenance cost, and epsilon is the proportion of the cost.
In some embodiments, the constraints include: the power and the charge state of the energy storage power station are restricted, and the charge and discharge state of the energy storage power station is restricted.
In some embodiments, the power and state of charge constraints of the energy storage power plant include: using formulas
Is determined in which Ps,tFor the charging and discharging power of the energy-storing power station at time t, SSOC,tFor the state of charge, P, of the energy-storing power station at time tmax,tAnd SoCmax,tThe maximum value of the charging and discharging power and the maximum value of the state of charge of the energy storage power station at the moment t are respectively.
In some embodiments, the energy storage power station charge-discharge state constraints include: using formulas
Determination of λtFor charging or discharging status signs of energy-storing power stations, wherein λt0 denotes that the energy storage station is in an idle float state, λt1 is charged state, λt-1 is in the discharged state.
In some embodiments, the determining the energy storage plant peak period discharge price comprises: using formulas
Determining the peak period discharge price of the energy storage power station, wherein CPFor peak period discharge price of energy storage power station, CtSelling the electricity price for the common electricity consumption of the user side, and taking the Delta R as the total investment cost and the running cost of the energy storage power stationAnd, TEFor the actual time of use, P, in the life cycle of the energy-storing power stationWRated active power for energy storage power stations, CGSubsidizing the cost for the energy storage power station;
or, the determining the charging price of the energy storage power station in the valley period comprises: using formulas
Determining the energy storage power station valley period charging price, wherein CTOCharging price for energy storage station in valley period, CtSelling the electricity price for the common electricity consumption of the user side, wherein Delta R is the sum of the investment cost and the operation cost of the energy storage power station, TEFor the actual time of use, P, in the life cycle of the energy-storing power stationWRated active power for energy storage power stations, CGSubsidizing the cost for the energy storage power station;
or, the determining the auxiliary service compensation price of the energy storage power station participating in peak shaving includes: using formulas
CPL＝CG+Ca，
Determining an auxiliary service compensation price for the energy storage power station participating in peak shaving, wherein CPLCompensating prices for auxiliary services participating in peak shaving in energy storage plants, CGSubsidizing costs for energy storage power stations, CaThe marginal cost of the energy storage power station participating in peak shaving is provided.
In a second aspect, an embodiment of the present invention provides an energy storage optimal configuration system, including: the first processing unit is used for determining the peak period discharge price of the energy storage power station; the second processing unit is used for determining the charging price of the energy storage power station in the valley period; the third processing unit is used for determining the auxiliary service compensation price of the energy storage power station participating in peak shaving; the fourth processing unit is used for determining the maximum net gain of the energy storage power station based on the peak time interval discharge price of the energy storage power station, the valley time interval charge price of the energy storage power station and the auxiliary service compensation price of the energy storage power station participating in peak regulation; and the fifth processing unit is used for determining the configuration of the energy storage power station based on the maximum net income and the constraint conditions of the energy storage power station.
In a third aspect, an embodiment of the present invention provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the method provided in the first aspect when executing the program.
In a fourth aspect, an embodiment of the present invention provides a non-transitory computer readable storage medium, on which a computer program is stored, which when executed by a processor, implements the steps of the method as provided in the first aspect.
According to the energy storage optimal configuration method, the energy storage optimal configuration system, the electronic equipment and the storage medium, the energy storage power station is optimally configured based on the price mechanism, and the optimal capacity configuration of the energy storage power station can be determined, so that the benefit of the energy storage power station can be maximized, and the large-scale application of the energy storage power station is facilitated.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
Fig. 1 is a flowchart of an energy storage optimization configuration method according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of an energy storage optimization configuration system according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, 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 some, but not all, embodiments of the present invention. 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.
An energy storage optimization configuration method according to an embodiment of the present invention is described below with reference to fig. 1, and the energy storage optimization configuration method can be used for determining capacity configuration of an energy storage power station.
As shown in fig. 1, the energy storage optimization configuration method according to the embodiment of the present invention includes the following steps:
step S100, determining the peak time period discharge price of the energy storage power station, determining the valley time period charge price of the energy storage power station, and determining the auxiliary service compensation price of the energy storage power station participating in peak shaving.
It should be noted that the energy storage power station is in a discharge operation mode during the peak period of power consumption, and discharges to the power grid, the peak period discharge price of the energy storage power station represents the selling price of the energy storage power station, the peak period of power consumption may be 9-13 points, 19-21 points, and the like, and the peak period of power consumption may be determined according to seasons.
In order to encourage the building of the energy storage power station, generally, when the energy storage power station participates in peak shaving, price arc compensation is provided, and the auxiliary service compensation price of the energy storage power station participating in peak shaving is the subsidy price of the energy storage power station participating in peak shaving.
The energy storage power station is in a charging working mode at the electricity consumption valley period, that is, the electric energy of the power grid is consumed and stored, for example, the electric energy can be converted into heat energy through the energy storage device for storage, the charging price at the energy storage power station valley period is the electricity purchasing price of the energy storage power station, and the electricity purchasing price is usually lower than the electricity selling price.
And S200, determining the maximum net profit of the energy storage power station based on the peak time period discharge price of the energy storage power station, the valley time period charge price of the energy storage power station and the auxiliary service compensation price of the energy storage power station participating in peak shaving.
The profit of energy storage power station is derived from high-storage low-discharge arbitrage and supplementary service subsidy, and this step can calculate the biggest net profit of energy storage power station through above-mentioned price, and this biggest net profit is relevant with the capacity configuration of energy storage power station, if capacity configuration is too big, can cause investment cost big, and equipment is idle, if capacity configuration undersize, can cause and be difficult to the demand of matching.
And S300, determining the capacity configuration of the energy storage power station based on the maximum net income and the constraint conditions of the energy storage power station.
Based on the maximum net gain of the energy storage power station, under the condition that constraint conditions are met, the configuration of the energy storage power station and the configuration of the energy storage power station can be solved, wherein the configuration of the energy storage power station comprises the capacity configuration of the energy storage power station, and the capacity configuration mainly refers to the capacity of an energy storage device of the energy storage power station.
That is, when designing the capacity configuration, both satisfying the constraint adjustment and enabling the energy storage plant to achieve the maximum net gain.
According to the energy storage optimal configuration method, the energy storage power station is optimally configured based on the price mechanism, and the optimal capacity configuration of the energy storage power station can be determined, so that the benefit of the energy storage power station can be maximized, and the large-scale application of the energy storage power station is facilitated.
In some embodiments, the determining the energy storage plant peak period discharge price in step S100 includes: using formulas
Determining the peak period discharge price of the energy storage power station, wherein CPFor peak period discharge price of energy storage power station, CtSelling the electricity price for the common electricity consumption of the user side, wherein Delta R is the sum of the investment cost and the operation cost of the energy storage power station, TEFor the actual time of use, in particular T, in the life cycle of the energy storage power stationEFor hours, P, used in the life cycle of the energy storage power stationWRated active power for energy storage power stations, CGThe cost is subsidized for the energy storage power station.
In some embodiments, the determining the energy storage valley time charging price in step S100 includes: using formulas
Determining the charging price of the energy storage power station in the valley period, wherein CTOFor energy-storage power stationsCharging price at off-peak time, CtSelling the electricity price for the common electricity consumption of the user side, wherein Delta R is the sum of the investment cost and the operation cost of the energy storage power station, TEFor the actual time of use, in particular T, in the life cycle of the energy storage power stationEFor hours, P, used in the life cycle of the energy storage power stationWRated active power for energy storage power stations, CGThe cost is subsidized for the energy storage power station.
In some embodiments, the determining the auxiliary service compensation price for the energy storage power station participating in peak shaving in step S100 includes: using formulas
CPL＝CG+Ca，
Determining an auxiliary service compensation price for the energy storage power station participating in peak shaving, wherein CPLCompensating prices for auxiliary services participating in peak shaving in energy storage plants, CGSubsidizing costs for energy storage power stations, CaThe marginal cost of the energy storage power station participating in peak shaving is provided.
In some embodiments, the maximum net gain of the energy storage power station is determined based on the high-storage low-discharge arbitrage of the energy storage power station, the auxiliary service compensation of the energy storage power station participating in peak shaving, the investment cost and the operation and maintenance cost of the energy storage power station reduced to daily.
In other words, the respective major costs of the energy storage power stations and the major revenue sources are comprehensively analyzed, and the maximum net profit of the energy storage power stations is determined, and is related to the capacity configuration of the energy storage power stations.
In some embodiments, the determination of the maximum net gain of the energy storage power station for the high-storage low-discharge arbitrage based on the energy storage power station, the auxiliary service compensation of the energy storage power station participating in peak shaving, the daily investment cost and the daily operation and maintenance cost of the energy storage power station comprises: using formulas
And determining the maximum net gain of the energy storage power station, wherein f is the net gain of the energy storage power station.
f1The method is characterized in that the method is used for high-storage low-discharge arbitrage of an energy storage power station, T is a scheduling period, T is a time interval, Cr(t) is the corresponding time period electricity price, such as at peak time period Cr(t)＝CPAt the valley period Cr(t)＝CTO，PsAnd (t) is the electricity price of the energy storage power station in a corresponding time period.
f2Auxiliary service compensation for energy storage stations participating in peak shaving, CPLCompensating prices for peak shaving in energy storage power stations, Pwloss,tThe abandoned electricity quantity per hour before configuration of the energy storage power station is P'wloss,tAnd the electricity discard amount per hour after the configuration of the energy storage power station.
f3Investment costs and operational maintenance costs reduced to everyday for energy storage power stations, fcFor capital recovery factor, r is annual rate, e.g. r is 0.1, TEFor the actual service time, alpha, of the energy storage plant in its life cyclesThe unit price of power for the energy storage power station is reduced to annual power unit price.
βsReduced to annual capacity unit price, P, for energy storage power stationscapFor rated charge-discharge power of energy-storage power stations, ScapFor rated capacity of energy storage power station, fEFor unit investment cost of energy storage power station, fOMIs the unit operating maintenance cost, and epsilon is the proportion of the cost.
In some embodiments, the constraints include: the power and the charge state of the energy storage power station are restricted, and the charge and discharge state of the energy storage power station is restricted.
Specifically, power and state of charge constraints of energy storage power stations include: using formulas
Is determined in which Ps,tFor the charging and discharging power of the energy-storing power station at time t, SSOC,tFor the state of charge, P, of the energy-storing power station at time tmax,tAnd SoCmax,tThe maximum value of the charging and discharging power and the maximum value of the state of charge of the energy storage power station at the moment t are respectively.
Specifically, the energy storage power station charge-discharge state constraint includes: using formulas
Determination of λtFor charging or discharging status signs of energy-storing power stations, wherein λt0 denotes that the energy storage station is in an idle float state, λt1 is charged state, λt-1 is in the discharged state.
According to the energy storage optimal configuration method, the set price mechanism of the energy storage power station is brought into the objective function, and the particle swarm algorithm is adopted to carry out solving calculation, so that the optimal configuration of the energy storage power station is obtained.
In summary, the energy storage optimal configuration method provided by the invention formulates an energy storage power station operation price mechanism by considering the technical and economic current situation of the energy storage power station, establishes an objective function with the maximum comprehensive income of the energy storage power station, realizes the capacity configuration of the energy storage power station, and can guide the construction of the energy storage power station.
The energy storage optimization configuration system provided by the embodiment of the invention is described below, and the energy storage optimization configuration system described below and the energy storage optimization configuration method described above can be referred to correspondingly.
As shown in fig. 2, the energy storage optimization configuration system according to the embodiment of the present invention includes: the first processing unit is used for determining the peak period discharge price of the energy storage power station; the second processing unit is used for determining the charging price of the energy storage power station in the valley period; the third processing unit is used for determining the auxiliary service compensation price of the energy storage power station participating in peak shaving; the fourth processing unit is used for determining the maximum net profit of the energy storage power station based on the peak time period discharge price of the energy storage power station, the valley time period charge price of the energy storage power station and the auxiliary service compensation price of the energy storage power station participating in peak shaving; and the fifth processing unit is used for determining the configuration of the energy storage power station based on the maximum net income and the constraint conditions of the energy storage power station.
Fig. 3 illustrates a physical structure diagram of an electronic device, which may include, as shown in fig. 3: a processor (processor)810, a communication Interface 820, a memory 830 and a communication bus 840, wherein the processor 810, the communication Interface 820 and the memory 830 communicate with each other via the communication bus 840. The processor 810 may call logic instructions in the memory 830 to perform the energy storage optimization configuration method according to the above embodiment, the method includes: determining the peak time period discharge price of the energy storage power station, determining the valley time period charge price of the energy storage power station, and determining the auxiliary service compensation price of the energy storage power station participating in peak regulation; determining the maximum net gain of the energy storage power station based on the peak time period discharge price of the energy storage power station, the valley time period charge price of the energy storage power station and the auxiliary service compensation price of the energy storage power station participating in peak shaving; and determining the configuration of the energy storage power station based on the maximum net income and the constraint conditions of the energy storage power station.
It should be noted that, when being implemented specifically, the electronic device in this embodiment may be a server, a PC, or other devices, as long as the structure includes the processor 810, the communication interface 820, the memory 830, and the communication bus 840 shown in fig. 3, where the processor 810, the communication interface 820, and the memory 830 complete mutual communication through the communication bus 840, and the processor 810 may call the logic instructions in the memory 830 to execute the above method. The embodiment does not limit the specific implementation form of the electronic device.
In addition, the logic instructions in the memory 830 may be implemented in software functional units and stored in a computer readable storage medium when the logic instructions are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
Further, an embodiment of the present invention discloses a computer program product, the computer program product includes a computer program stored on a non-transitory computer readable storage medium, the computer program includes program instructions, when the program instructions are executed by a computer, the computer can execute the energy storage optimization configuration method as described above in the embodiment, the method includes: determining the peak time period discharge price of the energy storage power station, determining the valley time period charge price of the energy storage power station, and determining the auxiliary service compensation price of the energy storage power station participating in peak regulation; determining the maximum net gain of the energy storage power station based on the peak time period discharge price of the energy storage power station, the valley time period charge price of the energy storage power station and the auxiliary service compensation price of the energy storage power station participating in peak shaving; and determining the configuration of the energy storage power station based on the maximum net income and the constraint conditions of the energy storage power station.
In another aspect, an embodiment of the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored, where the computer program is implemented to perform the energy storage optimization configuration method according to the above embodiment when executed by a processor, where the method includes: determining the peak time period discharge price of the energy storage power station, determining the valley time period charge price of the energy storage power station, and determining the auxiliary service compensation price of the energy storage power station participating in peak regulation; determining the maximum net gain of the energy storage power station based on the peak time period discharge price of the energy storage power station, the valley time period charge price of the energy storage power station and the auxiliary service compensation price of the energy storage power station participating in peak shaving; and determining the configuration of the energy storage power station based on the maximum net income and the constraint conditions of the energy storage power station.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. An energy storage optimal configuration method is characterized by comprising the following steps: determining the peak time period discharge price of the energy storage power station, determining the valley time period charge price of the energy storage power station, and determining the auxiliary service compensation price of the energy storage power station participating in peak regulation; determining the maximum net gain of the energy storage power station based on the peak time period discharge price of the energy storage power station, the valley time period charge price of the energy storage power station and the auxiliary service compensation price of the energy storage power station participating in peak shaving; and determining the capacity configuration of the energy storage power station based on the maximum net income and the constraint conditions of the energy storage power station.
2. The energy storage optimal configuration method according to claim 1, wherein the maximum net profit of the energy storage power station is determined based on high storage low discharge profit of the energy storage power station, auxiliary service compensation of the energy storage power station participating in peak shaving, investment cost and operation and maintenance cost of the energy storage power station reduced to each day.
3. The energy storage optimal configuration method according to claim 2, wherein the maximum net profit of the energy storage power station is determined based on high storage low discharge profit of the energy storage power station, auxiliary service compensation of the energy storage power station participating in peak shaving, investment cost and operation and maintenance cost of the energy storage power station reduced to each day, and the method comprises the following steps: using formulas
Determining a maximum net gain of the energy storage power station, wherein f is the net gain of the energy storage power station, f1The method is characterized in that the method is used for high-storage low-discharge arbitrage of an energy storage power station, T is a scheduling period, T is a time interval, Cr(t) the price of electricity in the corresponding time period, Ps(t) is the electricity price of the energy storage power station in the corresponding time period, f2Auxiliary service compensation for energy storage stations participating in peak shaving, CPLCompensating prices for peak shaving in energy storage power stations, Pwloss,tThe abandoned electricity quantity per hour before configuration of the energy storage power station is P'wloss,tElectricity discard per hour after configuration for energy storage power station, f3Investment costs and operational maintenance costs reduced to everyday for energy storage power stations, fcFor capital recovery factor, r is annual rate, TEFor the actual service time, alpha, of the energy storage plant in its life cyclesPower unit price, beta, reduced to annuity for energy storage power stationssReduced to annual capacity unit price, P, for energy storage power stationscapFor rated charge-discharge power of energy-storage power stations, ScapFor rated capacity of energy storage power station, fEFor unit investment cost of energy storage power station, fOMIs the unit operating maintenance cost, and epsilon is the proportion of the cost.
4. The energy storage optimization configuration method according to claim 1, wherein the constraint condition includes: the power and the charge state of the energy storage power station are restricted, and the charge and discharge state of the energy storage power station is restricted.
5. The energy storage optimal configuration method of claim 4, wherein the power and state of charge constraints of the energy storage power station comprise: using formulas
Is determined in which Ps,tFor the charging and discharging power of the energy-storing power station at time t, SSOC,tFor the state of charge, P, of the energy-storing power station at time tmax,tAnd SoCmax,tThe maximum value of the charging and discharging power and the maximum value of the state of charge of the energy storage power station at the moment t are respectively.
6. The energy storage optimal configuration method according to claim 4, wherein the energy storage power station charge-discharge state constraint comprises: using formulas
Determination of λtFor charging or discharging status signs of energy-storing power stations, wherein λt0 denotes that the energy storage station is in an idle float state, λt1 is charged state, λt-1 is in the discharged state.
7. The energy storage optimal configuration method according to any one of claims 1-6, wherein the determining the peak period discharge price of the energy storage power station comprises: using formulas
Determining the peak period discharge price of the energy storage power station, wherein CPFor peak period discharge price of energy storage power station, CtSelling the electricity price for the common electricity consumption of the user side, wherein Delta R is the sum of the investment cost and the operation cost of the energy storage power station, TEFor the actual time of use, P, in the life cycle of the energy-storing power stationWRated active power for energy storage power stations, CGFor storing energySubsidy cost of the power station;
or, the determining the charging price of the energy storage power station in the valley period comprises: using formulas
Determining the energy storage power station valley period charging price, wherein CTOCharging price for energy storage station in valley period, CtSelling the electricity price for the common electricity consumption of the user side, wherein Delta R is the sum of the investment cost and the operation cost of the energy storage power station, TEFor the actual time of use, P, in the life cycle of the energy-storing power stationWRated active power for energy storage power stations, CGSubsidizing the cost for the energy storage power station;
or, the determining the auxiliary service compensation price of the energy storage power station participating in peak shaving includes: using formulas
CPL＝CG+Ca，
Determining an auxiliary service compensation price for the energy storage power station participating in peak shaving, wherein CPLCompensating prices for auxiliary services participating in peak shaving in energy storage plants, CGSubsidizing costs for energy storage power stations, CaThe marginal cost of the energy storage power station participating in peak shaving is provided.
8. An energy storage optimal configuration system, comprising:
the first processing unit is used for determining the peak period discharge price of the energy storage power station;
the second processing unit is used for determining the charging price of the energy storage power station in the valley period;
the third processing unit is used for determining the auxiliary service compensation price of the energy storage power station participating in peak shaving;
the fourth processing unit is used for determining the maximum net gain of the energy storage power station based on the peak time interval discharge price of the energy storage power station, the valley time interval charge price of the energy storage power station and the auxiliary service compensation price of the energy storage power station participating in peak regulation;
and the fifth processing unit is used for determining the configuration of the energy storage power station based on the maximum net income and the constraint conditions of the energy storage power station.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the energy storage optimization configuration method according to any one of claims 1 to 7 when executing the program.
10. A non-transitory computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the energy storage optimization configuration method according to any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911007302.0A CN110676863B (en) | 2019-10-22 | 2019-10-22 | Energy storage optimal configuration method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911007302.0A CN110676863B (en) | 2019-10-22 | 2019-10-22 | Energy storage optimal configuration method and system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110676863A true CN110676863A (en) | 2020-01-10 |
| CN110676863B CN110676863B (en) | 2021-07-27 |
Family
ID=69083492
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911007302.0A Active CN110676863B (en) | 2019-10-22 | 2019-10-22 | Energy storage optimal configuration method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110676863B (en) |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111539620A (en) * | 2020-04-21 | 2020-08-14 | 中国电力科学研究院有限公司 | Energy storage operation method and system for providing energy service |
| CN111539619A (en) * | 2020-04-21 | 2020-08-14 | 中国电力科学研究院有限公司 | Energy storage power station operation method and system for providing auxiliary service |
| CN112132638A (en) * | 2020-10-22 | 2020-12-25 | 云南电网有限责任公司电力科学研究院 | Energy storage internet pricing system and method |
| CN112350350A (en) * | 2020-10-26 | 2021-02-09 | 清华四川能源互联网研究院 | Operation control method and device for battery energy storage and hydrogen production equipment and electronic equipment |
| CN112769156A (en) * | 2020-12-28 | 2021-05-07 | 南昌大学 | Source network load storage coordinated operation method considering large-scale offshore wind power grid connection |
| CN113315148A (en) * | 2021-07-08 | 2021-08-27 | 傲普(上海)新能源有限公司 | Capacity configuration method and system of energy storage system in frequency modulation of unit system |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108808659A (en) * | 2018-06-05 | 2018-11-13 | 国网吉林省电力有限公司 | The coordination optimization of wind electricity digestion integrated energy system controls and economic evaluation method |
| CN109948868A (en) * | 2019-04-17 | 2019-06-28 | 上海电力设计院有限公司 | High permeability distribution type renewable energy power generation cluster Method for optimized planning |
-
2019
- 2019-10-22 CN CN201911007302.0A patent/CN110676863B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108808659A (en) * | 2018-06-05 | 2018-11-13 | 国网吉林省电力有限公司 | The coordination optimization of wind electricity digestion integrated energy system controls and economic evaluation method |
| CN109948868A (en) * | 2019-04-17 | 2019-06-28 | 上海电力设计院有限公司 | High permeability distribution type renewable energy power generation cluster Method for optimized planning |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111539620A (en) * | 2020-04-21 | 2020-08-14 | 中国电力科学研究院有限公司 | Energy storage operation method and system for providing energy service |
| CN111539619A (en) * | 2020-04-21 | 2020-08-14 | 中国电力科学研究院有限公司 | Energy storage power station operation method and system for providing auxiliary service |
| CN111539620B (en) * | 2020-04-21 | 2022-08-05 | 中国电力科学研究院有限公司 | Energy storage operation method and system for providing energy service |
| CN112132638A (en) * | 2020-10-22 | 2020-12-25 | 云南电网有限责任公司电力科学研究院 | Energy storage internet pricing system and method |
| CN112132638B (en) * | 2020-10-22 | 2024-04-09 | 云南电网有限责任公司电力科学研究院 | Energy storage internet pricing system and method |
| CN112350350A (en) * | 2020-10-26 | 2021-02-09 | 清华四川能源互联网研究院 | Operation control method and device for battery energy storage and hydrogen production equipment and electronic equipment |
| CN112350350B (en) * | 2020-10-26 | 2022-02-08 | 清华四川能源互联网研究院 | Operation control method and device for battery energy storage and hydrogen production equipment and electronic equipment |
| CN112769156A (en) * | 2020-12-28 | 2021-05-07 | 南昌大学 | Source network load storage coordinated operation method considering large-scale offshore wind power grid connection |
| CN113315148A (en) * | 2021-07-08 | 2021-08-27 | 傲普(上海)新能源有限公司 | Capacity configuration method and system of energy storage system in frequency modulation of unit system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110676863B (en) | 2021-07-27 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110676863B (en) | Energy storage optimal configuration method and system | |
| CN110188950B (en) | Multi-agent technology-based optimal scheduling modeling method for power supply side and demand side of virtual power plant | |
| CN107464010B (en) | Virtual power plant capacity optimal configuration method | |
| Purvins et al. | Application of battery-based storage systems in household-demand smoothening in electricity-distribution grids | |
| CN113904385B (en) | New energy power generation side virtual power plant shared energy storage method, system and storage medium | |
| CN109995063B (en) | User side energy storage control strategy | |
| CN110852535A (en) | Day-ahead market clearing model considering medium-long term trading and wind power uncertainty | |
| CN110739690A (en) | Power distribution network optimal scheduling method and system considering electric vehicle quick charging station energy storage facility | |
| CN114156870B (en) | Energy storage system participation multi-application-field optimization scheduling method | |
| CN109873449A (en) | Light stores up capacity configuration optimizing method in a kind of family microgrid | |
| CN108805326A (en) | A kind of electricity price pricing method based on Multiple Time Scales demand response model | |
| CN113794224A (en) | Energy storage system optimal configuration method and device based on wind power plant application scene | |
| CN113488995A (en) | Energy storage cost-based shared energy storage capacity optimal configuration method and device | |
| CN116365507A (en) | Energy storage energy management method suitable for household light storage system | |
| CN116436048A (en) | Multi-target-driven micro-grid group cloud energy storage optimal configuration method and device | |
| CN117498416B (en) | Method and device for formulating discharge strategy of energy storage battery and electronic equipment | |
| CN113572165A (en) | Electric power spot market clearing mechanism considering water-light storage complementary power generation | |
| CN118174333A (en) | Energy storage capacity optimization method and system for household photovoltaic system | |
| CN116979619A (en) | Micro-grid energy storage configuration method and device, computer equipment and storage medium | |
| CN116914787A (en) | Regional power grid multi-time scale shared energy storage capacity planning method and system | |
| CN114039351B (en) | Energy storage capacity configuration method and device | |
| CN115441494A (en) | Converter station capacity optimal configuration method and device based on flexible direct current interconnection system | |
| CN112865101A (en) | Linear transaction method considering uncertainty of output of renewable energy | |
| CN114629105A (en) | Power distribution network voltage reactive power optimization control method considering multi-party benefit balance | |
| CN117674300B (en) | Virtual power plant resource scheduling method and device, terminal equipment and storage medium |
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 |