CN114530871A - Energy storage optimal configuration method and device - Google Patents
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Abstract
The invention provides an energy storage optimal configuration method and device, and relates to the technical field of energy storage data processing. The method comprises the following steps: establishing an optimization target by taking the minimum of a normalized energy storage cost calculation model of energy storage as a target function, establishing a complementary optimization configuration model containing the energy storage by taking the minimum total cost of a complementary system as a target, establishing a constraint condition, generating configuration capacity of various power supplies of the complementary system, and guiding planning and production of various complementary power supplies in actual production according to a determined capacity configuration result. The device performs the above method. The energy storage optimal configuration method and the device provided by the embodiment of the invention can effectively solve the problem that the new energy station and the new energy collecting station are difficult to plan and put into production due to too high cost, optimize the resource configuration and improve the utilization rate of new energy of the system.
Description
Technical Field
The invention relates to the technical field of energy storage data processing, in particular to an energy storage optimal configuration method and device.
Background
The energy storage application scene is diversified, and the energy storage application scene can be divided into a power generation side, a power grid side and a user side according to different positions, and mainly comprises the functions of improving renewable energy consumption, tracking planned output, frequency modulation, peak regulation, black start and peak clipping and valley filling (user time-of-use electricity price management and user basic electricity charge management) according to function classification, and certainly has the functions of serving as a standby power supply (improving user power supply reliability), improving electric energy quality, providing reactive power support and the like. The energy storage application scenarios can be divided into an energy storage application scenario and a power storage application scenario according to the requirements of specific electric quantity and specific power, for example, participating in frequency modulation, reactive power support, tracking planned output, improving electric energy quality and being biased to the power storage application scenario, while peak regulation, peak clipping requirements and load regulation requirements are biased to the energy storage application scenario.
The levelled Cost of Electricity (LCOE) refers to the reduced power generation Cost per kilowatt hour of a power supply project in a full life cycle, and is a widely accepted power generation Cost calculation method with high transparency.
The energy storage is a special carrier which can be charged and discharged, namely a power supply and a load, and the cost per degree of electricity discharged by the energy storage is not proper in name by using the standardized electricity consumption cost LCOE, but the method for converting the cost of the energy storage into the cost per degree of electricity or per power mileage is feasible, namely the standardized energy storage cost LCOS is formed.
Along with the diversified development of energy storage technologies in recent years, the energy storage technology is gradually expanded from traditional pumped storage and electrochemical energy storage to generalized energy storage technologies capable of realizing unidirectional or bidirectional storage between electric power and energy such as heat energy and chemical energy, such as energy storage and power generation, electricity-to-gas conversion and electric power hydrogen production; the adaptability of different energy storage technologies is different according to the application requirements of a new energy base on various scenes such as smooth output, tracking plan, system frequency modulation, peak clipping and valley filling. Therefore, there is a need to fully analyze the technical and economic characteristics of multi-type energy storage for future adaptation to high-proportion new energy delivery systems. The method and the device facilitate the comprehensive consideration of the operating characteristics of different energy storage devices, the application scene application requirements, the comprehensive benefits of the new energy delivery system, the comprehensive economy of the system and other factors during the planning and design stage of the power system. And a reference basis is provided for subsequent multi-element energy storage distribution, capacity and type selection.
Disclosure of Invention
For solving the problems in the prior art, embodiments of the present invention provide an energy storage optimal configuration method and apparatus, which can at least partially solve the problems in the prior art.
In one aspect, the present invention provides an energy storage optimal configuration method, including:
acquiring energy storage data, regional resource data, system basic technical data and complementary system planning data of a new energy station and a new energy collection station;
analyzing the capacity characteristic and the electric quantity characteristic of the energy storage facing to the planning based on the energy flow relation and the technical index of the energy storage power station;
establishing an optimization target by taking the minimum normalized energy storage cost calculation model of the energy storage as an objective function, constructing a constraint condition, and calculating the scale configuration of each subsystem of the energy storage power station according to the energy storage capacity and the energy storage hours obtained by simulation calculation; the leveling energy storage cost calculation model comprises a cycle degradation parameter and a calendar degradation parameter;
and constructing an energy storage-containing complementary optimization configuration model by taking the lowest total cost of the complementary system as a target, constructing constraint conditions, generating configuration capacity of various power supplies of the complementary system, and guiding planning and production of various complementary power supplies in actual production according to a determined capacity configuration result.
Wherein obtaining the cyclic degradation parameter comprises:
and calculating the cycle degradation parameter according to the cycle life and the preset percentage.
Wherein obtaining the calendar degradation parameter comprises:
and calculating the calendar degradation parameter according to the degradation time parameter and a preset percentage.
Wherein, the establishment of the normalized energy storage cost calculation model comprises the following steps:
and establishing the leveling energy storage cost calculation model according to the discharge capacity index parameter, each cost item required for leveling energy storage cost calculation, the discount rate, the time point of the specific operating year and the service life of the energy storage technology.
The leveling energy storage cost calculation model comprises a discharge capacity index parameter discount corresponding to the discharge capacity index parameter.
Wherein, the calculation of the discharge capacity index parameter discount comprises the following steps:
and calculating the discharge amount index parameter according to annual cycle, nominal energy storage capacity, discharge depth, conversion efficiency, cycle degradation parameter, calendar degradation parameter, external discharge rate and technical construction time, time point of specific operating year and service life of the energy storage technology.
Wherein the cost items required for flattening energy storage cost calculations include:
initial investment cost, operation and maintenance cost, charging cost and scrapping cost of energy storage.
In one aspect, the present invention provides an energy storage optimal configuration apparatus, including:
the system comprises an acquisition unit, a storage unit and a management unit, wherein the acquisition unit is used for acquiring energy storage data, regional resource data, system basic technical data and complementary system planning data of a new energy station and a new energy collection station;
the analysis unit is used for analyzing the capacity characteristic and the electric quantity characteristic of the energy storage surface for planning based on the energy flow relation and the technical index of the energy storage power station;
the building unit is used for building an optimization target by taking the minimum normalized energy storage cost calculation model of the energy storage as an objective function, building a constraint condition and calculating the scale configuration of each subsystem of the energy storage power station according to the energy storage capacity and the energy storage hours obtained by simulation calculation; the leveling energy storage cost calculation model comprises a cycle degradation parameter and a calendar degradation parameter;
and the configuration unit is used for constructing an energy storage-containing complementary optimization configuration model by taking the lowest total cost of the complementary system as a target, constructing constraint conditions, generating the configuration capacity of various power supplies of the complementary system, and guiding the planning and the production of various complementary power supplies in actual production according to the determined capacity configuration result.
Wherein the construction unit is specifically configured to:
and calculating the cycle degradation parameter according to the cycle life and the preset percentage.
Wherein the construction unit is specifically configured to:
and calculating the calendar degradation parameter according to the degradation time parameter and a preset percentage.
Wherein the construction unit is further specifically configured to:
and establishing the leveling energy storage cost calculation model according to the discharge capacity index parameter, each cost item required for leveling energy storage cost calculation, the discount rate, the time point of the specific operating year and the service life of the energy storage technology.
In another aspect, an embodiment of the present invention provides an electronic device, including: a processor, a memory, and a bus, wherein,
the processor and the memory are communicated with each other through the bus;
the memory stores program instructions executable by the processor, the processor invoking the program instructions to perform a method comprising:
acquiring energy storage data, regional resource data, system basic technical data and complementary system planning data of a new energy station and a new energy collection station;
analyzing the capacity characteristic and the electric quantity characteristic of the energy storage facing to the planning based on the energy flow relation and the technical index of the energy storage power station;
establishing an optimization target by taking the minimum normalized energy storage cost calculation model of the energy storage as an objective function, constructing a constraint condition, and calculating the scale configuration of each subsystem of the energy storage power station according to the energy storage capacity and the energy storage hours obtained by simulation calculation; the leveling energy storage cost calculation model comprises a cycle degradation parameter and a calendar degradation parameter;
and constructing an energy storage-containing complementary optimization configuration model by taking the lowest total cost of the complementary system as a target, constructing constraint conditions, generating configuration capacity of various power supplies of the complementary system, and guiding planning and production of various complementary power supplies in actual production according to a determined capacity configuration result.
An embodiment of the present invention provides a non-transitory computer-readable storage medium, including:
the non-transitory computer readable storage medium stores computer instructions that cause the computer to perform a method comprising:
acquiring energy storage data, regional resource data, system basic technical data and complementary system planning data of a new energy station and a new energy collection station;
analyzing the capacity characteristic and the electric quantity characteristic of the energy storage facing to the planning based on the energy flow relation and the technical index of the energy storage power station;
establishing an optimization target by taking the minimum normalized energy storage cost calculation model of the energy storage as an objective function, constructing a constraint condition, and calculating the scale configuration of each subsystem of the energy storage power station according to the energy storage capacity and the energy storage hours obtained by simulation calculation; the leveling energy storage cost calculation model comprises a cycle degradation parameter and a calendar degradation parameter;
and constructing an energy storage-containing complementary optimization configuration model by taking the lowest total cost of the complementary system as a target, constructing constraint conditions, generating configuration capacity of various power supplies of the complementary system, and guiding planning and production of various complementary power supplies in actual production according to a determined capacity configuration result.
The energy storage optimization configuration method and the device provided by the embodiment of the invention establish an optimization target by taking the minimum normalized energy storage cost calculation model of the energy storage as a target function, establish an energy storage-containing complementary optimization configuration model by taking the minimum total cost of a complementary system as a target, establish constraint conditions, generate the configuration capacity of various power supplies of the complementary system, guide the planning and production of various complementary power supplies in actual production according to the determined capacity configuration result, effectively solve the problem that the new energy station and the new energy gathering station are difficult to plan production due to too high cost, optimize resource configuration and improve the utilization rate of new energy of the system.
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, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts. In the drawings:
fig. 1 is a schematic flow chart 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 apparatus 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 more apparent, the embodiments of the present invention are further described in detail below with reference to the accompanying drawings. The exemplary embodiments and descriptions of the present invention are provided to explain the present invention, but not to limit the present invention. It should be noted that the embodiments and features of the embodiments in the present application may be arbitrarily combined with each other without conflict.
Fig. 1 is a schematic flow chart of an energy storage optimization configuration method according to an embodiment of the present invention, and as shown in fig. 1, the energy storage optimization configuration method according to the embodiment of the present invention includes:
step S1: and acquiring energy storage data, regional resource data, system basic technical data and complementary system planning data of the new energy station and the new energy collection station.
Step S2: and analyzing the capacity characteristic and the electric quantity characteristic of the energy storage facing the planning based on the energy flow relation and the technical indexes of the energy storage power station.
Step S3: establishing an optimization target by taking the minimum normalized energy storage cost calculation model of the energy storage as an objective function, constructing a constraint condition, and calculating the scale configuration of each subsystem of the energy storage power station according to the energy storage capacity and the energy storage hours obtained by simulation calculation; the normalized energy storage cost calculation model comprises a cycle degradation parameter and a calendar degradation parameter.
Step S4: and constructing an energy storage-containing complementary optimization configuration model by taking the lowest total cost of the complementary system as a target, constructing constraint conditions, generating configuration capacity of various power supplies of the complementary system, and guiding planning and production of various complementary power supplies in actual production according to a determined capacity configuration result.
In step S1, the device obtains the energy storage data, the regional resource data, the system basic technology data, and the complementary system planning data of the new energy station and the new energy collecting station. The apparatus may be a computer device that performs the method, the regional resource data comprising historical wind speed data, historical lighting data, and historical water inflow data; the basic technical data of the system comprise load data, technical and economic data of various power supplies, tie line data and environmental and economic data; the energy storage power station planning data comprises annual design utilization hours AUH of the energy storage power stationCSPConfidence capacity of energy storage power station
The minimum power generation time Tmin of the energy storage power station and the maximum power generation ratio x of the backup system; the complementary system planning data comprises a system standby rate D, a minimum utilization rate gamma of a connecting line, a minimum proportion of the new energy generated energy of the system and a proportion epsilon of the maximum allowable outgoing power conversion amount in unit time to the transmission capacity.
In step S2, the device analyzes the capacity characteristic and the electric quantity characteristic of the energy storage plane based on the energy flow relationship and the technical index of the energy storage power station.
Based on the energy flow relation and the technical indexes of the energy storage power station, the capacity characteristic and the electric quantity characteristic of the energy storage facing the planning are analyzed, and the economy, the reliability, the flexibility and the environmental protection of the energy storage facing the planning can also be analyzed.
Capacity characteristic
The method is used for evaluating the capacity of the power supply to provide output, and specifically comprises the following steps:
the parameters of the above formula are conventional technical parameters in the field, and the calculation process is also conventional in the field, and are not described again.
Electric quantity characteristic: annual energy production E of power supplyCSPThe method is used for the electric quantity balance analysis of system planning, and specifically comprises the following steps:
ECSP＝CapCSPAUHCSP
the parameters of the above formula are conventional technical parameters in the field, and the calculation process is also conventional in the field, and are not described again.
The economic efficiency is as follows: evaluating the economy by using a normalized energy storage cost calculation model of energy storage, wherein a specific calculation formula is as follows:
in which LCOS is the leveling energy storage cost, Cinvest、CO&M、CchargeAnd CendCollectively referred to as the cost terms required for normalizing the energy storage cost calculations.
Cinvest、CO&M、CchargeAnd CendThe initial investment cost, the operation and maintenance cost, the charging cost and the scrapping cost of the stored energy are respectively.
QdisIs a discharge capacity index parameter. r is the discount rate, N is the time point of the specific operating year, and N is the service life of the energy storage technology.
Calculating the discharge capacity index parameter according to the following formula:
wherein CycpaFor annual cycle, Capnom,ENominal energy storage capacity, DoD depth of discharge, etaRTTo conversion efficiency, CycDegAs a cyclic degradation parameter, TDegAs a calendar degradation parameter, etaoutFor external discharge rate, TCThe technology construction time is shortened.
The preset percentage can be set autonomously according to the actual situation, and can be 75% optionally, which represents the proportion corresponding to the preset scrapping value, and the preset scrapping value is the nominal energy storage capacity multiplied by 75%.
For cycle life CyclifeComprises the following steps:
wherein CyclifeThe actual service life of the battery is determined according to the rated service life of the battery, and it can be understood that the actual service life of the battery is different due to different objective conditions such as a use mode and a use environment in the process of continuous recycling of the battery, and the actual service life of the battery is different from the rated service life of the battery.
Further, the historical use data and the historical use data of the batteries with the same type can be usedThe actual service life and other data calculate the cycle life Cyclife。
According to the formula, the method comprises the following steps:
for calendar degradation parameter T in the same wayDegThe method comprises the following steps:
wherein, TlifeAs a parameter of the degradation time, is a general term of art.
External discharge rate etaoutThe calculation can be made according to the following formula:
wherein DD is discharge duration ηself,idleIs daily self-discharge, Cyc in idle statepaIs an annual cycle.
Initial investment cost CinvestCan be calculated according to the following formula:
wherein, Capnom,PIs nominal power, CpIs specific power cost, CESpecific capacity cost, CprTo replace cost, TrInterval time, rep is the number of replacements over the technical life cycle.
Operation maintenance cost CO&MIncluding power specific operation and maintenance cost Cp-OMAnd energy specific operation and maintenance cost CE-OM。
And calculating the operation and maintenance cost discount according to the following formula:
the parameters of the formula can be referred to the above description.
The ratio of the discounted cost of charging the stored energy to the discounted parameter of the discharge capacity is equal to the price of electricity PelAnd conversion efficiency ηRTThe ratio of:
according to the formula, the charge cost discount of energy storage can be calculated
Calculating the scrap cost discount according to the following formula:
wherein, FEOLIs the scrap cost factor.
Reliability: establishing a model based on the long-term statistical characteristics of the stored energy, and specifically calculating as follows:
the parameters of the above formula are conventional technical parameters in the field, and the calculation process is also conventional in the field, and are not described again.
Flexibility: the operation interval, the climbing speed and the start and stop of the unit are specifically calculated as follows:
the parameters of the above formula are conventional technical parameters in the field, and the calculation process is also conventional in the field, and are not described again.
Environmental protection property: the emission cost and the emission discharge amount of pollutants of the energy storage power station are slight, and the specific calculation is as follows:
wherein x is a capacity factor of the energy storage power station; capCSPThe rated capacity of the energy storage power station; CRF is the capital recovery factor;
the investment cost of the energy storage power station is reduced;
the annual operation and maintenance cost of the energy storage power station is saved; y is a state probability function of the energy storage power station; xCSPThe output state variable of the energy storage power station;
for the ith output state of the energy storage power station:
the probability of the energy storage power station in the ith output state is given;
the state variable of the energy storage power station at the moment h is represented as l, the table is in operation, and 0 represents the outage;
respectively representing the minimum output and the maximum output of the energy storage power station;
for energy storage power station h hourForce of engraving; RDCSP，RUCSPMaximum downward climbing speed and maximum upward climbing speed of the energy storage power station are respectively set; x is the type of contaminant; rhoxThe discharge cost per unit mass of the pollutant x;
is the emission equivalent of the pollutant x.
In the step S3, the device establishes an optimization target with the normalized energy storage cost calculation model of energy storage as the minimum objective function, constructs constraint conditions, and calculates the scale configuration of each subsystem of the energy storage power station according to the energy storage capacity and the energy storage hours obtained by simulation calculation; the normalized energy storage cost calculation model comprises a cycle degradation parameter and a calendar degradation parameter.
Establishing an optimization target min f by taking the minimum normalized energy storage cost calculation model of the energy storage power station as an objective function:
min f＝LCOS
the LCOS is a leveling energy storage cost calculation model.
The constructed constraint conditions comprise resource constraint of the energy storage power station; operation constraints of the energy storage power station; external characteristic constraints of the energy storage power station;
the resource constraint of the energy storage power station is as follows:
wherein A isSFThe area is the use area of the energy storage power station;
the area of the energy storage power station is planned;
the operation constraint of the energy storage power station is as follows:
wherein the content of the first and second substances,
electric energy transmitted by the energy storage power station at the moment h is as follows: n is the energy storage conversion efficiency; DNIhElectric power at time h:
the electric quantity is discarded at the moment h;
the energy transmitted to the power generation system by the energy storage system at the moment h,
the electric energy transferred to the power generation system by the energy storage system at h moment
Storing the electric energy of the energy storage system at the moment h; etaHeatThe loss coefficient of the energy storage system; etaSTThe energy storage efficiency of the energy storage system; etaPBEfficiency of the power generation system; etaTPThe discharge efficiency of the energy storage system;
the electric energy is provided for the backup system at the h moment;
external characteristic constraints of energy storage power stations include the following:
the confidence capacity constraint is:
the annual energy production is constrained as follows:
the reliability constraints are:
the environmental protection constraints are:
wherein tau is the peak load time period; t isτIs the duration of the peak load period; t is the simulation duration; x is a capacity factor of the energy storage power station; k is the maximum power generation ratio of the backup system: t isminThe minimum power generation time of the energy storage power station is set; AUHCSPDesigning the utilization hours for the year of the energy storage power station;
the confidence capacity of the energy storage power station is obtained; eCSPIs the annual energy production of the energy storage power station.
The scale configuration of each subsystem of the energy storage power station is calculated as follows:
CapSF＝SMSFCapCSP/ηPB
wherein, CapSFIs the capacity of the energy storage system;
capacity of the energy storage subsystem; SMSFThe ratio of the photoelectric capacity of the energy storage power station; hTESThe number of energy storage hours; etaPBEfficiency of the power generation system; etaTPThe heat release efficiency of the energy storage system; etaHeatThe loss coefficient of the energy storage system; capCSPThe rated capacity of the energy storage power station.
In the step S4, the device constructs an energy storage complementary optimal configuration model with the goal of minimizing the total cost of the complementary system, constructs constraint conditions, generates configuration capacities of various power sources of the complementary system, and guides planning and production of various complementary power sources in actual production according to the determined capacity configuration result.
The objective function for constructing the energy storage power station complementary optimization configuration model by taking the lowest complementary system total cost as the target is as follows:
wherein N is the type number of the complementary power supply; knThe number of the units of the nth power supply is as follows:
the investment cost of the nth power supply single unit is as follows:
the operation and maintenance cost of the nth type power supply unit is obtained;
and
the output and input power of the tie line at the h moment; ρ is a unit of a gradientSEAnd ρBEElectricity prices for selling and buying, respectively: cspillThe cost is abandoned for new energy.
The constraint conditions for constructing the configuration capacity of various power supplies in the complementary system comprise system power reserve and balance constraint, operation constraint of various power supplies, system resource constraint, system new energy power generation capacity ratio constraint and system external area power transmission constraint.
The system power backup and balance constraints are:
wherein x isnCapacity factor for class n power supply: capnRated capacity of the nth type power supply; omegaRAnd ΩCThe new energy and the conventional energy are respectively integrated as follows:
a maximum load;
and respectively representing the load power at the h moment and the power of the nth power supply;
intermittent power sources such as wind power, photovoltaic and the like are as follows:
wherein, P is the output of the intermittent power supply at the moment h; kw/sThe number of intermittent units; zhThe output at the moment h of a single unit:
discarding power for the intermittent power source at the h moment;
the operating constraints of a conventional power supply are:
wherein the content of the first and second substances,
the number of conventional units in transit is as follows:
the minimum maximum power of the conventional unit;
the output of the conventional unit at the h moment is obtained; RU (RU)C、RDCRespectively representing the up-down climbing rate of the conventional unit;
system resource constraints are;
wherein the content of the first and second substances,
respectively representing the minimum and maximum configuration numbers of the nth power supply;
the new energy generated energy is constrained by the following ratio:
the delivery electrical constraint of the system outer region is:
wherein, CaplineIs the transmission capacity of the junctor.
Configuration capacity II of nth power supply in complementary systemnThe following were used:
Пn＝KnCapn
wherein, KnThe number of the units of the nth power supply; capnThe rated capacity of the nth type power supply.
It can be understood that the method is based on the use of the normalized energy storage cost calculation model and is used as a universal model adapted to a power type energy storage application scene and an electric quantity type energy storage application scene, and the method has the advantages of conveniently acquiring the normalized energy storage cost data and improving the efficiency of acquiring the normalized energy storage cost data.
The energy storage optimization configuration method provided by the embodiment of the invention establishes an optimization target by taking the minimum normalized energy storage cost calculation model of energy storage as an objective function, establishes an energy storage-containing complementary optimization configuration model by taking the minimum total cost of a complementary system as a target, establishes a constraint condition, generates the configuration capacity of various power supplies of the complementary system, guides the planning and the production of various complementary power supplies in actual production according to a determined capacity configuration result, can effectively solve the problem that the new energy field station and the new energy collection station are difficult to plan and put into production due to too high cost, optimizes resource configuration and improves the utilization rate of new energy of the system.
Further, obtaining the cycle degradation parameter includes:
and calculating the cycle degradation parameter according to the cycle life and the preset percentage. The above description of the embodiments can be referred to, and are not repeated.
Further, obtaining the calendar degradation parameter comprises:
and calculating the calendar degradation parameter according to the degradation time parameter and a preset percentage. The above description of the embodiments can be referred to, and are not repeated.
Further, the establishing of the normalized energy storage cost calculation model comprises:
and establishing the leveling energy storage cost calculation model according to the discharge capacity index parameter, each cost item required for leveling energy storage cost calculation, the discount rate, the time point of the specific operating year and the service life of the energy storage technology. The above description of the embodiments can be referred to, and are not repeated.
Further, the normalized energy storage cost calculation model comprises a discharge capacity index parameter discount corresponding to the discharge capacity index parameter. The above description of the embodiments can be referred to, and are not repeated.
Further, the calculation of the discharge amount index parameter discount comprises the following steps:
and calculating the discharge amount index parameter according to annual cycle, nominal energy storage capacity, discharge depth, conversion efficiency, cycle degradation parameter, calendar degradation parameter, external discharge rate and technical construction time, time point of specific operating year and service life of the energy storage technology. The above description of the embodiments can be referred to, and are not repeated.
Further, the cost items required for smoothing the energy storage cost calculation include:
initial investment cost, operation and maintenance cost, charging cost and scrapping cost of energy storage. The above description of the embodiments can be referred to, and are not repeated.
Fig. 2 is a schematic structural diagram of an energy storage optimization configuration device according to an embodiment of the present invention, and as shown in fig. 2, the energy storage optimization configuration device according to the embodiment of the present invention includes an obtaining unit 201, an analyzing unit 202, a constructing unit 203, and a configuring unit 204, where:
the acquiring unit 201 is configured to acquire energy storage data, regional resource data, system basic technology data, and complementary system planning data of the new energy station and the new energy collecting station; the analysis unit 202 is configured to analyze a capacity characteristic and an electric quantity characteristic of the energy storage plane for planning based on an energy flow relationship and a technical index of the energy storage power station; the construction unit 203 is configured to establish an optimization target by using the minimum normalized energy storage cost calculation model of energy storage as an objective function, construct a constraint condition, and calculate the scale configuration of each subsystem of the energy storage power station according to the energy storage capacity and the energy storage hours obtained through simulation calculation; the leveling energy storage cost calculation model comprises a cycle degradation parameter and a calendar degradation parameter; the configuration unit 204 is configured to construct an energy storage-containing complementary optimal configuration model with the goal of lowest total cost of the complementary system as a target, construct constraint conditions, generate configuration capacities of various power supplies of the complementary system, and guide planning and production of various complementary power supplies in actual production according to a determined capacity configuration result.
Specifically, the acquiring unit 201 in the device is configured to acquire energy storage data, regional resource data, system basic technology data, and complementary system planning data of the new energy station and the new energy collecting station; the analysis unit 202 is configured to analyze a capacity characteristic and an electric quantity characteristic of the energy storage plane for planning based on an energy flow relationship and a technical index of the energy storage power station; the construction unit 203 is configured to establish an optimization target by using the minimum normalized energy storage cost calculation model of the energy storage as an objective function, construct a constraint condition, and calculate the scale configuration of each subsystem of the energy storage power station according to the energy storage capacity and the energy storage hours obtained through simulation calculation; the leveling energy storage cost calculation model comprises a cycle degradation parameter and a calendar degradation parameter; the configuration unit 204 is configured to construct an energy storage-containing complementary optimal configuration model with the goal of lowest total cost of the complementary system as a target, construct constraint conditions, generate configuration capacities of various power supplies of the complementary system, and guide planning and production of various complementary power supplies in actual production according to a determined capacity configuration result.
Further, the constructing unit 203 is specifically configured to:
and calculating the cycle degradation parameter according to the cycle life and the preset percentage.
Further, the constructing unit 203 is specifically configured to:
and calculating the calendar degradation parameter according to the degradation time parameter and a preset percentage.
Further, the constructing unit 203 is further specifically configured to:
and establishing the leveling energy storage cost calculation model according to the discharge capacity index parameters, all cost items required for leveling energy storage cost calculation, the discount rate, the time point of the specific operating year and the service life of the energy storage technology.
The energy storage optimization configuration device provided by the embodiment of the invention establishes an optimization target by taking the minimum normalized energy storage cost calculation model of energy storage as an objective function, establishes an energy storage-containing complementary optimization configuration model by taking the minimum total cost of a complementary system as a target, establishes a constraint condition, generates the configuration capacity of various power supplies of the complementary system, guides the planning and the production of various complementary power supplies in actual production according to a determined capacity configuration result, can effectively solve the problem that the new energy field station and the new energy collection station are difficult to plan and put into production due to too high cost, optimizes resource configuration and improves the utilization rate of new energy of the system.
The embodiment of the energy storage optimization configuration apparatus provided in the embodiment of the present invention may be specifically configured to execute the processing flows of the above method embodiments, and the functions of the embodiment are not described herein again, and refer to the detailed description of the above method embodiments.
Fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present invention, and as shown in fig. 3, the electronic device includes: a processor (processor)301, a memory (memory)302, and a bus 303;
the processor 301 and the memory 302 complete communication with each other through a bus 303;
the processor 301 is configured to call program instructions in the memory 302 to perform the methods provided by the above-mentioned method embodiments, including:
acquiring energy storage data, regional resource data, system basic technical data and complementary system planning data of a new energy station and a new energy collection station;
analyzing the capacity characteristic and the electric quantity characteristic of the energy storage facing to the planning based on the energy flow relation and the technical index of the energy storage power station;
establishing an optimization target by taking the minimum normalized energy storage cost calculation model of the energy storage as an objective function, constructing a constraint condition, and calculating the scale configuration of each subsystem of the energy storage power station according to the energy storage capacity and the energy storage hours obtained by simulation calculation; the leveling energy storage cost calculation model comprises a cycle degradation parameter and a calendar degradation parameter;
and constructing an energy storage-containing complementary optimization configuration model by taking the lowest total cost of the complementary system as a target, constructing constraint conditions, generating configuration capacity of various power supplies of the complementary system, and guiding planning and production of various complementary power supplies in actual production according to a determined capacity configuration result.
The present embodiment discloses a computer program product comprising a computer program stored on a non-transitory computer readable storage medium, the computer program comprising program instructions which, when executed by a computer, enable the computer to perform the method provided by the above-mentioned method embodiments, for example, comprising:
acquiring energy storage data, regional resource data, system basic technical data and complementary system planning data of a new energy station and a new energy collection station;
analyzing the capacity characteristic and the electric quantity characteristic of the energy storage facing to the planning based on the energy flow relation and the technical index of the energy storage power station;
establishing an optimization target by taking the minimum normalized energy storage cost calculation model of the energy storage as an objective function, constructing a constraint condition, and calculating the scale configuration of each subsystem of the energy storage power station according to the energy storage capacity and the energy storage hours obtained by simulation calculation; the leveling energy storage cost calculation model comprises a cycle degradation parameter and a calendar degradation parameter;
and constructing an energy storage-containing complementary optimization configuration model by taking the lowest total cost of the complementary system as a target, constructing constraint conditions, generating configuration capacity of various power supplies of the complementary system, and guiding planning and production of various complementary power supplies in actual production according to a determined capacity configuration result.
The present embodiment provides a computer-readable storage medium, which stores a computer program, where the computer program causes the computer to execute the method provided by the above method embodiments, for example, the method includes:
acquiring energy storage data, regional resource data, system basic technical data and complementary system planning data of the new energy station and the new energy collection station;
analyzing the capacity characteristic and the electric quantity characteristic of the energy storage facing to the planning based on the energy flow relation and the technical index of the energy storage power station;
establishing an optimization target by taking the minimum of a normalized energy storage cost calculation model of energy storage as a target function, constructing constraint conditions, and calculating the scale configuration of each subsystem of the energy storage power station according to the energy storage capacity and the energy storage hours obtained by simulation calculation; the leveling energy storage cost calculation model comprises a cycle degradation parameter and a calendar degradation parameter;
and constructing an energy storage-containing complementary optimization configuration model by taking the lowest total cost of the complementary system as a target, constructing constraint conditions, generating configuration capacity of various power supplies of the complementary system, and guiding planning and production of various complementary power supplies in actual production according to a determined capacity configuration result.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In the description herein, reference to the description of the terms "one embodiment," "a particular embodiment," "some embodiments," "for example," "an example," "a particular example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (13)
1. An energy storage optimal configuration method is characterized by comprising the following steps:
acquiring energy storage data, regional resource data, system basic technical data and complementary system planning data of a new energy station and a new energy collection station;
analyzing the capacity characteristic and the electric quantity characteristic of the energy storage facing to the planning based on the energy flow relation and the technical index of the energy storage power station;
establishing an optimization target by taking the minimum normalized energy storage cost calculation model of the energy storage as an objective function, constructing a constraint condition, and calculating the scale configuration of each subsystem of the energy storage power station according to the energy storage capacity and the energy storage hours obtained by simulation calculation; the leveling energy storage cost calculation model comprises a cycle degradation parameter and a calendar degradation parameter;
and constructing an energy storage-containing complementary optimization configuration model by taking the lowest total cost of the complementary system as a target, constructing constraint conditions, generating configuration capacity of various power supplies of the complementary system, and guiding planning and production of various complementary power supplies in actual production according to a determined capacity configuration result.
2. The energy storage optimization configuration method according to claim 1, wherein obtaining the cyclic degradation parameter comprises:
and calculating the cycle degradation parameter according to the cycle life and the preset percentage.
3. The energy storage optimization configuration method according to claim 1, wherein obtaining the calendar degradation parameter comprises:
and calculating the calendar degradation parameter according to the degradation time parameter and a preset percentage.
4. The energy storage optimal configuration method according to any one of claims 1 to 3, wherein the establishing of the normalized energy storage cost calculation model comprises:
and establishing the leveling energy storage cost calculation model according to the discharge capacity index parameter, each cost item required for leveling energy storage cost calculation, the discount rate, the time point of the specific operating year and the service life of the energy storage technology.
5. The energy storage optimal configuration method according to claim 4, wherein the normalized energy storage cost calculation model comprises a discharge capacity index parameter discount corresponding to the discharge capacity index parameter.
6. The energy storage optimization configuration method according to claim 5, wherein the calculation of the discharge capacity index parameter discount comprises:
and calculating the discharge amount index parameter according to annual cycle, nominal energy storage capacity, discharge depth, conversion efficiency, cycle degradation parameter, calendar degradation parameter, external discharge rate and technical construction time, time point of specific operating year and service life of the energy storage technology.
7. The energy storage optimal configuration method according to claim 4, wherein the cost items required for smoothing energy storage cost calculation comprise:
initial investment cost, operation and maintenance cost, charging cost and scrapping cost of energy storage.
8. An energy storage optimal configuration device, comprising:
the system comprises an acquisition unit, a storage unit and a management unit, wherein the acquisition unit is used for acquiring energy storage data, regional resource data, system basic technical data and complementary system planning data of a new energy station and a new energy collection station;
the analysis unit is used for analyzing the capacity characteristic and the electric quantity characteristic of the energy storage surface for planning based on the energy flow relation and the technical index of the energy storage power station;
the building unit is used for building an optimization target by taking the minimum normalized energy storage cost calculation model of the energy storage as an objective function, building a constraint condition and calculating the scale configuration of each subsystem of the energy storage power station according to the energy storage capacity and the energy storage hours obtained by simulation calculation; the leveling energy storage cost calculation model comprises a cycle degradation parameter and a calendar degradation parameter;
and the configuration unit is used for constructing an energy storage-containing complementary optimization configuration model by taking the lowest total cost of the complementary system as a target, constructing constraint conditions, generating the configuration capacity of various power supplies of the complementary system, and guiding the planning and the production of various complementary power supplies in actual production according to the determined capacity configuration result.
9. The energy storage optimal configuration device according to claim 8, wherein the building unit is specifically configured to:
and calculating the cycle degradation parameter according to the cycle life and the preset percentage.
10. The energy storage optimal configuration device according to claim 8, wherein the building unit is specifically configured to:
and calculating the calendar degradation parameter according to the degradation time parameter and a preset percentage.
11. The energy storage optimal configuration device according to any one of claims 8 to 10, wherein the building unit is further specifically configured to:
and establishing the leveling energy storage cost calculation model according to the discharge capacity index parameter, each cost item required for leveling energy storage cost calculation, the discount rate, the time point of the specific operating year and the service life of the energy storage technology.
12. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the method of any of claims 1 to 7 are implemented when the computer program is executed by the processor.
13. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 7.
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