CN113315148A - Capacity configuration method and system of energy storage system in frequency modulation of unit system - Google Patents
Capacity configuration method and system of energy storage system in frequency modulation of unit system Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/24—Arrangements for preventing or reducing oscillations of power in networks
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/12—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load
- H02J3/14—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load by switching loads on to, or off from, network, e.g. progressively balanced loading
- H02J3/144—Demand-response operation of the power transmission or distribution network
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
- H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/381—Dispersed generators
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
- H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
- H02J2300/20—The dispersed energy generation being of renewable origin
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
- H02J2300/40—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation wherein a plurality of decentralised, dispersed or local energy generation technologies are operated simultaneously
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- 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
- Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y02B70/00—Technologies for an efficient end-user side electric power management and consumption
- Y02B70/30—Systems integrating technologies related to power network operation and communication or information technologies for improving the carbon footprint of the management of residential or tertiary loads, i.e. smart grids as climate change mitigation technology in the buildings sector, including also the last stages of power distribution and the control, monitoring or operating management systems at local level
- Y02B70/3225—Demand response systems, e.g. load shedding, peak shaving
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- 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
- Y04S20/00—Management or operation of end-user stationary applications or the last stages of power distribution; Controlling, monitoring or operating thereof
- Y04S20/20—End-user application control systems
- Y04S20/222—Demand response systems, e.g. load shedding, peak shaving
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Abstract
The invention discloses a capacity configuration method and a capacity configuration system of an energy storage system in frequency modulation of a set system, wherein the method comprises the following steps of firstly, obtaining depreciation cost, operation and maintenance cost, loss cost and frequency modulation compensation income of the energy storage system; secondly, establishing an objective function according to depreciation cost, operation and maintenance cost, energy storage system loss cost and frequency modulation compensation income of the energy storage system; then, determining a frequency modulation constraint condition, and obtaining an energy storage capacity optimization model according to the target function and the frequency modulation constraint condition; and finally, solving an energy storage capacity optimization model by taking the highest comprehensive income as a target to obtain capacity configuration information of the energy storage system. The method can ensure that the comprehensive yield of the unit system is highest, and effectively realizes energy management of the energy storage system.
Description
Technical Field
The invention relates to the technical field of electric power, in particular to a capacity configuration method and system of an energy storage system in frequency modulation of a unit system.
Background
For grid technology, energy supply and demand imbalance and system emergencies are inherent characteristics of power system operation. In the conventional energy structure, the energy imbalance of the power grid in a short time is adjusted by a conventional unit (mainly, in China, the power grid and the hydropower grid) by responding to an Automatic Generation Control (AGC) signal. With the grid connection of new energy, the energy imbalance of a power grid in a short time is aggravated by the fluctuation and randomness of wind and light, and the traditional energy (especially thermal power) cannot meet the newly increased demand because the frequency modulation speed is low and the traditional energy has hysteresis in responding signals.
Particularly for thermal power plants, the impact of the conditioning service by AGC mainly includes the impact of the cost of the conditioning service, including the loss cost of thermal efficiency, increased operational and maintenance costs, opportunity costs, etc., as well as the impact on the life of the power generation equipment. Because the thermal efficiency is reduced and the required fuel quantity is increased by frequently adjusting the power of the generator set compared with the state of constant output of the generator set; meanwhile, the hemp damage of the generator set parts can be increased, the ordinary maintenance workload can be increased, the maintenance period of the generator set can be greatly shortened, and the cost for replacing the worn parts can be increased. Certain components of the generator set are not replaceable, and long and frequent adjustments of the power of the generator set cause wear to these components, which can result in shortening the overall life of the generator set. In addition to the above direct costs, the provision of the conditioning services by the units also results in indirect costs, for example, reserved fm reserve capacity will lose the opportunity to gain profit in the main power market, the more fm reserve capacity, the more electricity is lost, and the higher the opportunity cost.
In summary, the introduction of the energy storage system in the frequency modulation of the unit system can adjust the small and frequent load fluctuation adjustment, so how to configure the capacity of the energy storage system becomes an urgent technical problem to be solved.
Disclosure of Invention
Based on this, it is necessary to provide a capacity configuration method and system for an energy storage system in a frequency modulation of a set system, aiming at the problem of the capacity of the energy storage system.
A capacity configuration method of an energy storage system in frequency modulation of a set system comprises the following steps:
acquiring depreciation cost, operation and maintenance cost, energy storage system loss cost and frequency modulation compensation income of the energy storage system;
establishing an objective function according to depreciation cost, operation and maintenance cost, energy storage system loss cost and frequency modulation compensation income of the energy storage system;
determining a frequency modulation constraint condition, and obtaining an energy storage capacity optimization model according to the target function and the frequency modulation constraint condition;
and solving an energy storage capacity optimization model by taking the highest comprehensive income as a target to obtain capacity configuration information of the energy storage system.
In one embodiment, the step of obtaining the depreciation cost, the operation and maintenance cost, the energy storage system loss cost, and the fm compensation profit of the energy storage system further includes the following steps:
obtaining the initial investment cost of the energy storage system according to the power unit price, the capacity unit price, the rated power and the rated capacity of the energy storage system;
obtaining the investment recovery coefficient of the energy storage system according to the depreciation rate and the operation age limit of the energy storage system;
and obtaining depreciation cost of the energy storage system according to the initial investment cost, the investment recovery coefficient and the annual frequency modulation duration of the energy storage system.
In one embodiment, the step of obtaining depreciation cost, operation and maintenance cost, energy storage system loss cost and fm compensation profit of the energy storage system comprises the following steps:
obtaining the operation and maintenance cost of the energy storage system according to the rated capacity of the energy storage system, the operation and maintenance cost of unit capacity and the annual frequency modulation duration
In one embodiment, the step of obtaining depreciation cost, operation and maintenance cost, energy storage system loss cost and fm compensation profit of the energy storage system comprises the following steps:
and obtaining the loss cost of the energy storage system according to the frequency modulation times of the energy storage system, the power price of the power grid during the frequency modulation of the energy storage system, the charging and discharging efficiency of the energy storage system, the energy storage power during the ith frequency modulation of the energy storage system and the duration time during the ith frequency modulation of the energy storage system.
In one embodiment, the step of obtaining depreciation cost, operation and maintenance cost, energy storage system loss cost and fm compensation profit of the energy storage system comprises the following steps:
and obtaining the compensation benefit of the frequency modulation system based on the frequency modulation depth of the energy storage system at the ith time period according to the frequency modulation times of the energy storage system, the on-line electricity price of the unit system at the ith time period, the comprehensive frequency modulation performance index of the frequency modulation system at the ith time period, the frequency modulation depth of the energy storage system at the ith time period, the adjustment precision coefficient of the frequency modulation system, the response time coefficient of the frequency modulation system and the response speed index of the frequency modulation system.
In one embodiment, the constraint on frequency modulation comprises the following constraints:
the method comprises the following steps of unit output restraint, unit climbing restraint, energy storage running power restraint, energy storage running SOC restraint and energy storage running state restraint.
In one embodiment, the step of solving energy storage capacity optimization to obtain the capacity configuration information of the energy storage system with the highest comprehensive profit as the target includes the following steps:
and solving energy storage capacity optimization by adopting a particle swarm optimization algorithm with the highest comprehensive yield as a target to obtain capacity configuration information of the energy storage system.
In one embodiment, the capacity configuration information of the energy storage system includes a rated power and a rated capacity of the energy storage system.
In one embodiment, the energy storage system is a lithium ion battery.
A capacity allocation system of energy storage system in frequency modulation of a set system comprises,
the acquisition module is used for acquiring depreciation cost, operation and maintenance cost, energy storage system loss cost and frequency modulation compensation income of the energy storage system;
the establishing module is used for establishing an objective function according to depreciation cost, operation and maintenance cost, loss cost of the energy storage system and frequency modulation compensation income of the energy storage system;
the determining module is used for determining a frequency modulation constraint condition and obtaining an energy storage capacity optimization model according to the target function and the frequency modulation constraint condition; and
and the solving module is used for solving the energy storage capacity optimization model by taking the highest comprehensive income as a target to obtain the capacity configuration information of the energy storage system.
The capacity configuration method of the energy storage system in the frequency modulation of the unit system can ensure that the comprehensive benefit of the unit system is the highest, and effectively realizes energy management of the energy storage system. In addition, the operation of the energy storage system reduces the fuel consumption of a power grid, correspondingly reduces the pollutant emission and the treatment cost thereof, and has clean production and definite environmental benefit.
Drawings
FIG. 1 is a schematic flow chart of a capacity configuration method of an energy storage system in frequency modulation of a unit system;
fig. 2 is a schematic structural diagram of a capacity configuration system of an energy storage system in frequency modulation of a unit system.
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.
Referring to fig. 1, an embodiment of the present invention provides a method for configuring capacity of an energy storage system in frequency modulation of a battery system, including the following steps:
and S100, obtaining depreciation cost of the energy storage system, operation and maintenance cost of the energy storage system, loss cost of the energy storage system and frequency modulation compensation income.
Specifically, the energy storage system is a lithium battery system for assisting the unit to perform frequency modulation, and the lithium battery has higher energy storage density and can realize high-capacity energy storage; and because the power density of the lithium battery is low, large-current continuous and quick discharge can not occur, and the lithium battery is the battery type which is most suitable for auxiliary frequency modulation in the electrochemical energy storage technology. In addition, in the aspect of output characteristics of the lithium battery, the unit system is suitable for large-amplitude, continuous and unidirectional lifting loads, and is difficult to accurately track frequent frequency modulation power command signals; and the speed of the battery energy storage responding to the power instruction is in millisecond level, so that the method is more suitable for adjusting small and frequent load fluctuation. Therefore, for the unit system only adopting AGC frequency modulation, due to the problems of low climbing rate and the like of the unit system, the energy storage system with smaller capacity is adopted to replace the unit system with larger capacity for frequency modulation, and the maximization of comprehensive benefits can be realized. Preferably, the power unit system comprises an energy storage system and a thermal power unit system.
More specifically, the depreciation cost C of the energy storage system is obtainedeThe method comprises the following steps:
firstly, according to the power unit price c of the energy storage systempCapacity unit price ceRated power PENAnd rated capacity EENObtaining the initial investment cost C of the energy storage system0，
Then, obtaining the investment recovery coefficient f of the energy storage system according to the depreciation rate r and the operation age N of the energy storage systemcr；
Finally, according to the initial investment cost C of the energy storage system0Investment recovery factor fcrAnd the annual frequency modulation duration T (in hours) to obtain the depreciation cost C of the energy storage systeme。
Namely, the depreciation cost of the energy storage system satisfies the following formula:
wherein 8760 is the total hours of a year.
Obtaining the operation and maintenance cost C of the energy storage systemopIn particular according to the rated capacity E of the energy storage systemENOperation and maintenance cost per unit volume (MW) CopAnd the annual frequency modulation duration T, i.e. the operation and maintenance cost C of the energy storage systemopThe following formula is satisfied:
wherein T is an integer, T > 0, and T is expressed in units of hours (h); 8760 is the total hours when the frequency modulation duration is one whole year,
obtaining a loss cost C of an energy storage systemlThe loss cost of the lithium battery is obtained, the charge and discharge efficiency of the lithium battery can reach more than 95%, and in the long term, the upward frequency modulation and the downward frequency modulation of the unit system tend to be normally distributed. Therefore, the cost based on the frequency modulation of the energy storage system is mainly the system loss during the charging and discharging of the energy storage system. Thereby the loss cost C of the energy storage systemlAccording to the frequency modulation times n of the energy storage system, the online electricity price P of the power grid when the energy storage system performs frequency modulation, the charging and discharging efficiency eta of the energy storage system, and the energy storage power P when the energy storage system performs ith frequency modulationeiAnd duration ti of the energy storage system at the ith frequency modulation, i.e. loss cost C of the energy storage systemlThe following formula is satisfied:
wherein i is greater than 0 and i is an integer.
Further, currently, most areas perform AGC compensation according to a frequency modulation depth, and because the whole unit system includes an energy storage system and a thermal power unit system, in a frequency modulation process, frequency modulation of the frequency modulation system refers to that the thermal power unit and the energy storage are considered together to perform AGC frequency modulation, but in a frequency modulation process of the frequency modulation system, parameters of the energy storage system are mainly considered, but some basic limitations of the unit are also considered. The frequency modulation compensation income R is the online electricity price p of the unit system unit power in the ith time period according to the frequency modulation times n of the energy storage systemiAnd the comprehensive frequency modulation performance index K of the frequency modulation system in the ith time periodpiFrequency modulation depth P of energy storage system in ith time periodei+Pgi-PagciAdjusting precision coefficient K of frequency modulation system1Response time coefficient K of frequency modulation system2Andresponse speed index K of frequency modulation system3And (4) obtaining the product. The frequency modulation system is based on the compensation benefit of the frequency modulation depth of the energy storage system in the ith period.
Wherein i is greater than 0 and i is an integer.
Step S200, according to depreciation cost C of the energy storage systemeAnd operation and maintenance cost C of energy storage systemopLoss cost C of energy storage systemlAnd frequency modulation compensation gain R to establish an objective function.
The objective function meets the optimization target of highest comprehensive income, specifically, the rated power PENAnd rated capacity EENBoth are optimized to obtain the optimal capacity allocation value, so that the objective function can be expressed as:
maxJ(PEN，EEN)＝R-(Ce+Cop+Cl)
the optimal power and capacity configuration value is obtained by optimizing and selecting the power and capacity of the stored energy, so that the energy management of the battery energy storage system is realized, and simultaneously, a series of power data for the auxiliary AGC control of the battery energy storage system, namely the rated power P of the energy storage system can be obtainedENAnd rated capacity EEN。
And step S300, determining a frequency modulation constraint condition, and obtaining an energy storage capacity optimization model according to the objective function and the frequency modulation constraint condition. The frequency modulation constraints include the following constraints: the method comprises the following steps of unit output restraint, unit climbing restraint, energy storage running power restraint, energy storage running SOC restraint and energy storage running state restraint.
Specifically, the unit output constraint is as follows:
The unit climbing restraint is as follows:
in the formula, Pu、PdThe ramp up and down rates for the unit.
The energy storage operation power constraint is as follows:
in the formula, Pe,maxFor storing the upper limit value of charging and discharging power of the energy storage system,
the discharge and charge powers of the energy storage system during the ith period are respectively.
The energy storage operation SOC constraint is as follows:
in the formula, SOCiThe state of charge of the energy storage system in the ith period; SOC0The initial moment charge state of the energy storage system; xt、YtIn the charge-discharge state of the energy storage system, Xt、YtAll values of (a) are 0 or 1; deltaeThe energy storage charge-discharge efficiency.
The energy storage running state constraint is as follows:
SOCmin≤SOCi≤SOCmax
in the formula, SOCmax、SOCminThe maximum and minimum values of the energy storage state of charge.
And S400, solving an energy storage capacity optimization model by taking the highest comprehensive income as a target to obtain capacity configuration information of the energy storage system. If the rated power of the energy storage system is taken as the maximum value of the instruction power, the required energy storage capacity can be calculated, but the cost of the lithium battery energy storage is considered to be high, the power and the capacity of the energy storage system are optimized, and the optimal power and capacity configuration value is selected and obtained.
Further, with the highest comprehensive income as a target, solving energy storage capacity optimization to obtain capacity configuration information of the energy storage system comprises solving an energy storage capacity optimization model by adopting a particle swarm optimization algorithm with the highest comprehensive income as a target to obtain the capacity configuration information of the energy storage system. Specifically, the energy storage capacity optimization model is input into the particle swarm optimization model, and then capacity configuration information of the energy storage system when the comprehensive profit is the highest is finally output through the particle swarm optimization algorithm, namely the rated power and the rated capacity of the energy storage system.
Referring to fig. 2, the embodiment of the present invention further provides a capacity allocation system of an energy storage system in a frequency modulation of a unit system, for performing the above method, the capacity allocation system of the energy storage system in the frequency modulation of the unit system includes an obtaining module 110, an establishing module 120, a determining module 130, and a solving module 140, wherein,
the obtaining module 110 is configured to obtain depreciation cost, operation and maintenance cost, energy storage system loss cost, and frequency modulation compensation benefit of the energy storage system; the establishing module 120 is configured to establish an objective function according to depreciation cost, operation and maintenance cost, energy storage system loss cost, and frequency modulation compensation benefit of the energy storage system; the determining module 130 is configured to determine a frequency modulation constraint condition, and obtain an energy storage capacity optimization model according to a target function and the frequency modulation constraint condition; the solving module 140 is configured to solve the energy storage capacity optimization model to obtain capacity configuration information of the energy storage system, with the highest comprehensive profit as a target.
The capacity configuration system adopting the energy storage system to assist the frequency modulation of the traditional unit can ensure the highest comprehensive benefit of the unit system, and effectively realizes the energy management of the energy storage system. In addition, the operation of the energy storage system reduces the fuel consumption of a power grid, correspondingly reduces the pollutant emission and the treatment cost thereof, and has clean production and definite environmental benefit.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A capacity configuration method of an energy storage system in frequency modulation of a set system is characterized by comprising the following steps:
acquiring depreciation cost, operation and maintenance cost, energy storage system loss cost and frequency modulation compensation income of the energy storage system;
establishing an objective function according to depreciation cost, operation and maintenance cost, energy storage system loss cost and frequency modulation compensation income of the energy storage system;
determining a frequency modulation constraint condition, and obtaining an energy storage capacity optimization model according to the target function and the frequency modulation constraint condition;
and solving an energy storage capacity optimization model by taking the highest comprehensive income as a target to obtain capacity configuration information of the energy storage system.
2. The capacity allocation method for the energy storage system in the frequency modulation of the unit system according to claim 1, wherein the step of obtaining the depreciation cost, the operation and maintenance cost, the energy storage system loss cost and the frequency modulation compensation profit of the energy storage system further comprises the following steps:
obtaining the initial investment cost of the energy storage system according to the power unit price, the capacity unit price, the rated power and the rated capacity of the energy storage system;
obtaining the investment recovery coefficient of the energy storage system according to the depreciation rate and the operation age limit of the energy storage system;
and obtaining depreciation cost of the energy storage system according to the initial investment cost, the investment recovery coefficient and the annual frequency modulation duration of the energy storage system.
3. The capacity allocation method for the energy storage system in the frequency modulation of the unit system according to claim 1, wherein the step of obtaining the depreciation cost, the operation and maintenance cost, the energy storage system loss cost and the frequency modulation compensation profit of the energy storage system comprises the following steps:
and obtaining the operation and maintenance cost of the energy storage system according to the rated capacity of the energy storage system, the operation and maintenance cost of unit capacity and the annual frequency modulation duration.
4. The capacity allocation method for the energy storage system in the frequency modulation of the unit system according to claim 1, wherein the step of obtaining the depreciation cost, the operation and maintenance cost, the energy storage system loss cost and the frequency modulation compensation profit of the energy storage system comprises the following steps:
and obtaining the loss cost of the energy storage system according to the frequency modulation times of the energy storage system, the power price of the power grid during the frequency modulation of the energy storage system, the charging and discharging efficiency of the energy storage system, the energy storage power during the ith frequency modulation of the energy storage system and the duration time during the ith frequency modulation of the energy storage system.
5. The capacity allocation method for the energy storage system in the frequency modulation of the unit system according to claim 1, wherein the step of obtaining the depreciation cost, the operation and maintenance cost, the energy storage system loss cost and the frequency modulation compensation profit of the energy storage system comprises the following steps:
and obtaining the compensation benefit of the frequency modulation system based on the frequency modulation depth of the energy storage system at the ith time period according to the frequency modulation times of the energy storage system, the on-line electricity price of the unit system at the ith time period, the comprehensive frequency modulation performance index of the frequency modulation system at the ith time period, the frequency modulation depth of the energy storage system at the ith time period, the adjustment precision coefficient of the frequency modulation system, the response time coefficient of the frequency modulation system and the response speed index of the frequency modulation system.
6. The capacity allocation method for the energy storage system in the frequency modulation of the unit system according to claim 1, wherein the constraint condition of frequency modulation comprises the following constraints:
the method comprises the following steps of unit output restraint, unit climbing restraint, energy storage running power restraint, energy storage running SOC restraint and energy storage running state restraint.
7. The capacity configuration method of the energy storage system in the frequency modulation of the unit system according to claim 1, wherein the step of solving the energy storage capacity optimization with the highest comprehensive profit as a target to obtain the capacity configuration information of the energy storage system comprises the following steps:
and solving energy storage capacity optimization by adopting a particle swarm optimization algorithm with the highest comprehensive yield as a target to obtain capacity configuration information of the energy storage system.
8. The method for configuring the capacity of the energy storage system in the frequency modulation of the unit system according to claim 7, wherein the capacity configuration information of the energy storage system comprises a rated power and a rated capacity of the energy storage system.
9. The capacity configuration method for the energy storage system in the frequency modulation of the unit system according to any one of claims 1 to 8, wherein the energy storage system is a lithium ion battery.
10. A capacity allocation system of an energy storage system in frequency modulation of a machine set system is characterized by comprising,
the acquisition module is used for acquiring depreciation cost, operation and maintenance cost, energy storage system loss cost and frequency modulation compensation income of the energy storage system;
the establishing module is used for establishing an objective function according to depreciation cost, operation and maintenance cost, loss cost of the energy storage system and frequency modulation compensation income of the energy storage system;
the determining module is used for determining a frequency modulation constraint condition and obtaining an energy storage capacity optimization model according to the target function and the frequency modulation constraint condition; and
and the solving module is used for solving the energy storage capacity optimization model by taking the highest comprehensive income as a target to obtain the capacity configuration information of the energy storage system.
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Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103151797A (en) * | 2013-03-04 | 2013-06-12 | 上海电力学院 | Multi-objective dispatching model-based microgrid energy control method under grid-connected operation mode |
| CN108665188A (en) * | 2018-05-23 | 2018-10-16 | 国网天津市电力公司电力科学研究院 | A kind of garden multiple-energy-source main body synthesis matching method based on Optimized model |
| CN109347100A (en) * | 2018-11-26 | 2019-02-15 | 国网四川省电力公司经济技术研究院 | Promote the mixed energy storage system Optimal Configuration Method of wind power plant comprehensive performance |
| CN110676863A (en) * | 2019-10-22 | 2020-01-10 | 国网安徽省电力有限公司电力科学研究院 | Energy storage optimal configuration method and system |
| CN110970912A (en) * | 2019-12-09 | 2020-04-07 | 国网新疆电力有限公司 | Operation simulation method for new energy power system containing energy storage |
| CN110994646A (en) * | 2019-12-11 | 2020-04-10 | 国网河南省电力公司电力科学研究院 | Power grid AGC (automatic gain control) adjustment operation effect evaluation method and system and storage medium |
| CN111754361A (en) * | 2020-06-29 | 2020-10-09 | 国网山西省电力公司电力科学研究院 | Energy storage capacity optimal configuration method and computing device of wind-storage combined frequency modulation system |
| CN112465665A (en) * | 2020-11-17 | 2021-03-09 | 西安热工研究院有限公司 | Method for configuring capacity of gas turbine unit electric energy storage system for improving frequency modulation yield of power plant |
| CN112508287A (en) * | 2020-12-11 | 2021-03-16 | 国网重庆市电力公司营销服务中心 | Energy storage optimization configuration method based on user side BESS full life cycle |
| CN112821438A (en) * | 2021-03-16 | 2021-05-18 | 东北电力大学 | Optimal scheduling method and system of BSS-containing micro-grid combined system |
-
2021
- 2021-07-08 CN CN202110770960.6A patent/CN113315148A/en active Pending
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103151797A (en) * | 2013-03-04 | 2013-06-12 | 上海电力学院 | Multi-objective dispatching model-based microgrid energy control method under grid-connected operation mode |
| CN108665188A (en) * | 2018-05-23 | 2018-10-16 | 国网天津市电力公司电力科学研究院 | A kind of garden multiple-energy-source main body synthesis matching method based on Optimized model |
| CN109347100A (en) * | 2018-11-26 | 2019-02-15 | 国网四川省电力公司经济技术研究院 | Promote the mixed energy storage system Optimal Configuration Method of wind power plant comprehensive performance |
| CN110676863A (en) * | 2019-10-22 | 2020-01-10 | 国网安徽省电力有限公司电力科学研究院 | Energy storage optimal configuration method and system |
| CN110970912A (en) * | 2019-12-09 | 2020-04-07 | 国网新疆电力有限公司 | Operation simulation method for new energy power system containing energy storage |
| CN110994646A (en) * | 2019-12-11 | 2020-04-10 | 国网河南省电力公司电力科学研究院 | Power grid AGC (automatic gain control) adjustment operation effect evaluation method and system and storage medium |
| CN111754361A (en) * | 2020-06-29 | 2020-10-09 | 国网山西省电力公司电力科学研究院 | Energy storage capacity optimal configuration method and computing device of wind-storage combined frequency modulation system |
| CN112465665A (en) * | 2020-11-17 | 2021-03-09 | 西安热工研究院有限公司 | Method for configuring capacity of gas turbine unit electric energy storage system for improving frequency modulation yield of power plant |
| CN112508287A (en) * | 2020-12-11 | 2021-03-16 | 国网重庆市电力公司营销服务中心 | Energy storage optimization configuration method based on user side BESS full life cycle |
| CN112821438A (en) * | 2021-03-16 | 2021-05-18 | 东北电力大学 | Optimal scheduling method and system of BSS-containing micro-grid combined system |
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