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CN119189749A - Energy scheduling method and terminal for optical storage charging and testing system - Google Patents

Energy scheduling method and terminal for optical storage charging and testing system Download PDF

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Publication number
CN119189749A
CN119189749A CN202411196602.9A CN202411196602A CN119189749A CN 119189749 A CN119189749 A CN 119189749A CN 202411196602 A CN202411196602 A CN 202411196602A CN 119189749 A CN119189749 A CN 119189749A
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period
pcs
ess
limit
battery
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杜旭鹏
郑其荣
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Fujian Times Nebula Technology Co Ltd
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Fujian Times Nebula Technology Co Ltd
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
    • B60L53/60—Monitoring or controlling charging stations
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
    • B60L53/50—Charging stations characterised by energy-storage or power-generation means
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
    • B60L53/50—Charging stations characterised by energy-storage or power-generation means
    • B60L53/51—Photovoltaic means
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
    • B60L53/50—Charging stations characterised by energy-storage or power-generation means
    • B60L53/53—Batteries
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
    • B60L53/60—Monitoring or controlling charging stations
    • B60L53/63—Monitoring or controlling charging stations in response to network capacity
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
    • B60L53/60—Monitoring or controlling charging stations
    • B60L53/64—Optimising energy costs, e.g. responding to electricity rates
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
    • B60L53/60—Monitoring or controlling charging stations
    • B60L53/67—Controlling two or more charging stations
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
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    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Energy or water supply
    • 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
    • H02J1/00—Circuit arrangements for DC mains or DC distribution networks
    • H02J1/10—Parallel operation of DC sources
    • 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
    • H02J1/00—Circuit arrangements for DC mains or DC distribution networks
    • H02J1/10—Parallel operation of DC sources
    • H02J1/106—Parallel operation of DC sources for load balancing, symmetrisation, or sharing
    • 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
    • H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
    • H02J7/0013—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries acting upon several batteries simultaneously or sequentially
    • 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
    • H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
    • H02J7/007—Regulation of charging or discharging current or voltage
    • 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
    • H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
    • H02J7/34—Parallel operation in networks using both storage and other DC sources, e.g. providing buffering
    • H02J7/35—Parallel operation in networks using both storage and other DC sources, e.g. providing buffering with light sensitive cells
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2113/00—Details relating to the application field
    • G06F2113/04—Power grid distribution networks
    • 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
    • H02J2300/22—The renewable source being solar energy
    • H02J2300/24—The renewable source being solar energy of photovoltaic origin
    • 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
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    • Y02E10/50—Photovoltaic [PV] energy
    • Y02E10/56—Power conversion systems, e.g. maximum power point trackers

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Abstract

本发明公开了一种光储充检系统的能量调度方法与终端，以最小化PCS用电成本为目标，基于功率守恒条件、直流侧线路损耗以及PCS输入与输出功率的关系，建立数学模型；为所述数学模型添加约束条件，得到目标模型；所述约束条件包括SOC上下限约束和电压约束；求解所述目标模型，并基于求解结果进行能量调度；在进行以最小化PCS用电成本为目标的建模时，考虑现实运行过程中的损耗、电压约束以及储能装置的约束，能够更全面准确地考虑能量调度，降低运营成本。

The present invention discloses an energy scheduling method and terminal for a photovoltaic storage charging and testing system. With the goal of minimizing the PCS electricity cost, a mathematical model is established based on power conservation conditions, DC side line losses, and the relationship between PCS input and output power; constraints are added to the mathematical model to obtain a target model; the constraints include SOC upper and lower limit constraints and voltage constraints; the target model is solved, and energy scheduling is performed based on the solution results; when modeling with the goal of minimizing the PCS electricity cost, the losses, voltage constraints, and constraints of energy storage devices in the actual operation process are considered, so that energy scheduling can be considered more comprehensively and accurately, and operating costs can be reduced.

Description

Energy scheduling method and terminal of optical storage charging and detecting system
The scheme is a divisional application taking an invention patent of a method, a terminal and a system for minimizing cost energy scheduling of optical storage filling inspection, with an application date of 2023, 07, 03 and 202310802156.0 as a parent.
Technical Field
The invention relates to the technical field of energy scheduling control, in particular to an energy scheduling method and a terminal of an optical storage and charge detection system.
Background
Along with the increasing popularity of electric vehicles, as matched charging stations, one type of charging stations is called as an optical storage charging station, has the functions of photovoltaic, energy storage, charging and detection, and the profit mode of the optical storage charging station at present approximately comprises two aspects, namely, the charge amount of the charging station is improved, the operation cost of the reinspection station is reduced, and the method for minimizing the operation cost of the charging station in an energy scheduling mode is an effective method and has important significance for improving the profit level of the optical storage charging station.
At present, no mature method is available for solving the energy scheduling problem of the optical storage charging and detecting station, and most schemes only make simple energy scheduling according to a peak-valley electricity machine, so that the method is not comprehensive and accurate.
Disclosure of Invention
The invention aims to solve the technical problem of providing an energy scheduling method and a terminal of an optical storage and charge detection system, which can more comprehensively and accurately consider energy scheduling and reduce operation cost.
In order to solve the technical problems, the invention adopts the following technical scheme:
a method of minimizing cost energy scheduling for optical storage filling inspection, comprising the steps of:
S1, establishing a mathematical model based on a power conservation condition, direct-current side line loss and a relation between PCS input and output power by taking minimized PCS electricity cost as a target;
S2, adding constraint conditions for the mathematical model to obtain a target model;
The constraint conditions comprise SOC upper and lower limit constraints and voltage constraints;
and S3, solving the target model, and carrying out energy scheduling based on a solving result.
An energy scheduling method of an optical storage and filling detection system is characterized by comprising the following steps:
S1, establishing a mathematical model based on a power conservation condition, direct-current side line loss and a relation between PCS input and output power by taking minimized PCS electricity cost as a target;
S2, adding constraint conditions for the mathematical model to obtain a target model, wherein the constraint conditions comprise SOC upper and lower limit constraints and voltage constraints;
The upper and lower limit constraint of the SOC is specifically as follows:
wherein Cap represents energy, P represents power, Δt represents a time difference, and f () represents a function composed of parameters in parentheses;
t_ess_nominal represents the t-period battery nominal, lower_limit represents the lower limit, up_limit represents the upper limit, ess_init represents the battery initial, t_ess_out represents the t-period battery output, and t_ess_in represents the t-period battery input;
The voltage constraint is specifically:
wherein Cap represents energy, η represents efficiency, P represents power, Δt represents a time difference;
t_ess_actual represents the actual battery of the t period, lower_limit represents the lower limit, up_limit represents the upper limit, ess_init represents the initial battery, t_ess_out represents the output of the battery of the t period, and t_ess_in represents the input of the battery of the t period;
The constraint conditions are outside the upper limit constraint and the lower limit constraint of the SOC and the voltage constraint, and further comprise the following constraints:
Wherein P represents power;
t_pv_control_out represents a t-period photovoltaic controller output, t_pv_control_out_limit represents a preset t-period photovoltaic controller output limit, t_dc/dc_in represents a preset t-period DC/DC device input, t_dc/in_limit represents a preset t-period DC/DC device input limit, t_ess_in represents a t-period battery input, t_ess_in_limit represents a t-period battery input limit, t_ess_out represents a t-period battery output, t_ess_out_limit represents a t-period battery output limit, t_pcs_out represents a t-period PCS output limit, and t_pcs_out_limit represents a t-period PCS output limit;
From the power loss, it is possible to:
and S3, solving the target model, and carrying out energy scheduling based on a solving result.
In order to solve the technical problems, the invention adopts another technical scheme that:
a terminal for minimizing cost energy scheduling for optical storage battery charging and inspection, comprising a processor, a memory and a computer program stored in the memory and executable on the processor, wherein the steps in the method for minimizing cost energy scheduling for optical storage battery charging and inspection are realized when the processor executes the computer program.
An energy scheduling terminal of an optical storage filling inspection system, comprising a processor, a memory and a computer program stored in the memory and executable on the processor, the processor implementing the following steps when executing the computer program:
S1, establishing a mathematical model based on a power conservation condition, direct-current side line loss and a relation between PCS input and output power by taking minimized PCS electricity cost as a target;
S2, adding constraint conditions for the mathematical model to obtain a target model, wherein the constraint conditions comprise SOC upper and lower limit constraints and voltage constraints;
The upper and lower limit constraint of the SOC is specifically as follows:
wherein Cap represents energy, P represents power, Δt represents a time difference, and f () represents a function composed of parameters in parentheses;
t_ess_nominal represents the t-period battery nominal, lower_limit represents the lower limit, up_limit represents the upper limit, ess_init represents the battery initial, t_ess_out represents the t-period battery output, and t_ess_in represents the t-period battery input;
The voltage constraint is specifically:
wherein Cap represents energy, η represents efficiency, P represents power, Δt represents a time difference;
t_ess_actual represents the actual battery of the t period, lower_limit represents the lower limit, up_limit represents the upper limit, ess_init represents the initial battery, t_ess_out represents the output of the battery of the t period, and t_ess_in represents the input of the battery of the t period;
The constraint conditions are outside the upper limit constraint and the lower limit constraint of the SOC and the voltage constraint, and further comprise the following constraints:
Wherein P represents power;
t_pv_control_out represents a t-period photovoltaic controller output, t_pv_control_out_limit represents a preset t-period photovoltaic controller output limit, t_dc/dc_in represents a preset t-period DC/DC device input, t_dc/in_limit represents a preset t-period DC/DC device input limit, t_ess_in represents a t-period battery input, t_ess_in_limit represents a t-period battery input limit, t_ess_out represents a t-period battery output, t_ess_out_limit represents a t-period battery output limit, t_pcs_out represents a t-period PCS output limit, and t_pcs_out_limit represents a t-period PCS output limit;
From the power loss, it is possible to:
and S3, solving the target model, and carrying out energy scheduling based on a solving result.
In order to solve the technical problems, the invention adopts another technical scheme that:
The system for minimizing cost energy scheduling of optical storage and filling inspection comprises a storage and filling inspection station and a control device, wherein the storage and filling inspection station comprises a direct-current bus, a photovoltaic electric plate connected with the direct-current bus, PCS (power distribution system), ESS (ESS) and a plurality of charging piles, and the control device controls the energy scheduling of the storage and filling inspection station to realize the steps in the method for minimizing cost energy scheduling of the optical storage and filling inspection.
The energy scheduling method and the terminal of the optical storage charging and detecting system have the beneficial effects that when modeling aiming at minimizing PCS electricity cost is performed, loss and voltage constraint in the actual operation process and constraint of an energy storage device are considered, energy scheduling can be considered more comprehensively and accurately, and the operation cost is reduced.
Drawings
FIG. 1 is a flow chart of a method of minimizing cost energy scheduling for optical storage charging inspection in accordance with an embodiment of the present invention;
FIG. 2 is a block diagram of a terminal for minimizing cost energy scheduling for optical storage charging according to an embodiment of the present invention;
FIG. 3 is a diagram illustrating an exemplary configuration of a storage and fill station in a system for minimizing cost energy scheduling for optical storage and fill in accordance with an embodiment of the present invention;
Description of the reference numerals:
1. a terminal for minimizing cost energy scheduling of optical storage filling inspection, 2, a processor, 3, a memory.
Detailed Description
In order to describe the technical contents, the achieved objects and effects of the present invention in detail, the following description will be made with reference to the embodiments in conjunction with the accompanying drawings.
Referring to fig. 1, a method for minimizing cost energy scheduling for optical storage and filling inspection includes the steps of:
S1, establishing a mathematical model based on a power conservation condition, direct-current side line loss and a relation between PCS input and output power by taking minimized PCS electricity cost as a target;
S2, adding constraint conditions for the mathematical model to obtain a target model;
The constraint conditions comprise SOC upper and lower limit constraints and voltage constraints;
and S3, solving the target model, and carrying out energy scheduling based on a solving result.
From the description, the method, the terminal and the system for energy scheduling of the minimized cost of the optical storage charging inspection have the beneficial effects that when modeling aiming at minimizing the PCS electricity cost is performed, the loss and the voltage constraint in the actual operation process and the constraint of the energy storage device are considered, the energy scheduling can be more comprehensively and accurately considered, and the operation cost is reduced.
Further, the establishing of the mathematical model in the step S1 specifically includes:
the goal of minimizing PCS power costs can be expressed by the following relationship:
since PCS input and output power have the following relationship:
ηt_pcs_inPt_pcs_in＝Pt_pcs_out;
thus, minimizing PCS power costs may be equivalent to:
According to the power conservation condition, the photovoltaic device is assumed to be on the direct current side, and the power balance relationship is as follows:
Pt_ Line loss ＝f(Pt_pcs_out,Pt_pv_control_out,Pt_ess_out,Pt_ess_in,Pt_DC/DC_in);
the PCS output power can be expressed as:
Pt_pcs_out＝f(Pt_pv_control_out,Pt_ess_out,Pt_ess_in,Pt_DC/DC_in);
Wherein Cost represents Cost, P represents power, deltat represents time difference, price represents price, and eta represents efficiency;
cs_in represents a PCS input, t_pcs_in represents a PCS input of a t period, t_pcs_out represents a PCS output of the t period, t represents a certain period of 24 periods in a day, t_grid represents a t period power grid, t_pv_control_out represents a t period photovoltaic controller output, t_ess_out represents a t period battery output, t_ess_in represents a t period battery input, t_line loss represents a t period line loss, t_DC/DC_in represents a t period DC/DC device input, and t_charge_in represents a t period charging pile input.
From the above description, it will be appreciated that the specific steps and contents of the mathematical model are set forth above.
Further, the SOC upper and lower limit constraints are specifically:
wherein Cap represents energy, P represents power, Δt represents a time difference, and f () represents a function composed of parameters in parentheses;
t_ess_nominal represents the t-period battery nominal, lower_limit represents the lower limit, up_limit represents the upper limit, ess_init represents the battery initial, t_ess_out represents the t-period battery output, and t_ess_in represents the t-period battery input.
From the above description, the SOC upper and lower limit constraints are specifically as shown above.
Further, the voltage constraint is specifically:
wherein Cap represents energy, η represents efficiency, P represents power, Δt represents a time difference;
t_ess_actual represents the actual battery of the t period, lower_limit represents the lower limit, up_limit represents the upper limit, ess_init represents the battery initial, t_ess_out represents the battery output of the t period, and t_ess_in represents the battery input of the t period.
From the above description, it is clear that the voltage constraint is specifically as shown above.
Further, the constraint conditions include the following constraints besides the upper and lower limits of the SOC and the voltage constraint:
Wherein P represents power;
t_pv_control_out represents a t-period photovoltaic controller output, t_pv_control_out_limit represents a t-period photovoltaic controller output limit, t_dc/dc_in represents a t-period DC/DC device input, t_dc/dc_in_limit represents a t-period DC/DC device input limit, t_ess_in represents a t-period battery input, t_ess_in_limit represents a t-period battery input limit, t_ess_out represents a t-period battery output, t_ess_out_limit represents a t-period battery output limit, t_pcs_out represents a t-period PCS output, and t_pcs_out_limit represents a t-period PCS output limit.
From the above description, the present invention also considers photovoltaic controller output limit, DC/DC device input limit, battery output limit, and PCS output limit as constraints on the data model, in addition to SOC upper and lower limit constraints and voltage constraints.
Further, the solving of the target model in step S3 specifically includes searching for a relatively better solution in a solution space formed by the target and the constraint condition based on a preset algorithm.
From the above description, it is clear that the object model can form a solution space based on the object and constraints, and that one or more optima can be found in the solution space by means of a specific algorithm for the control of the energy scheduling.
Further, the preset algorithm is a genetic algorithm or a particle swarm algorithm.
From the above description, it is known that the objective of searching for an optimal solution can be achieved by a genetic algorithm or a particle swarm algorithm.
Referring to fig. 2, a terminal for minimizing cost energy scheduling of optical storage and filling inspection includes a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the steps in the method for minimizing cost energy scheduling of optical storage and filling inspection are implemented when the processor executes the computer program.
Referring to fig. 3, a system for minimizing cost energy scheduling of optical storage and charging inspection includes a storage and charging inspection station and a control device, wherein the storage and charging inspection station includes a dc bus, a photovoltaic panel connected with the dc bus, a PCS, an ESS, and a plurality of charging piles, and the control device controls the energy scheduling of the storage and charging inspection station to implement the steps in the method for minimizing cost energy scheduling of optical storage and charging inspection.
The method, the terminal and the system for energy scheduling of the light storage filling and checking with the minimized cost are suitable for energy scheduling control of the light storage filling and checking station with the minimized cost as a target.
Referring to fig. 1, a first embodiment of the present invention is as follows:
a method of minimizing cost energy scheduling for optical storage filling inspection, comprising the steps of:
S1, establishing a mathematical model based on a power conservation condition, direct-current side line loss and a relation between PCS input and output power by taking minimized PCS electricity cost as a target;
the establishing of the mathematical model in the step S1 specifically includes:
The optical storage charging and detecting station minimizes cost energy scheduling, and the energy scheduling mainly utilizes an energy storage device (ESS) to transfer energy in time and space, so that the operation cost of the charging and detecting station is reduced. Essentially, minimizing the cost is equivalent to minimizing the grid purchase cost, equivalent to minimizing the PCS utility running cost.
The goal of minimizing PCS power costs can be expressed by the following relationship:
since PCS input and output power have the following relationship:
ηt_pcs_inPt_pcs_in＝Pt_pcs_out;
thus, minimizing PCS power costs may be equivalent to:
According to the power conservation condition, the photovoltaic device is assumed to be on the direct current side, and the power balance relationship is as follows:
based on the research result of the line loss at the direct current side, the line loss should have the following relation:
Pt_ Line loss ＝f(Pt_pcs_out,Pt_pv_control_out,Pt_ess_out,Pt_ess_in,Pt_DC/DC_in);
the PCS output power can be expressed as:
Pt_pcs_out＝f(Pt_pv_control_out,Pt_ess_out,Pt_ess_in,Pt_DC/DC_in);
Wherein Cost represents Cost, P represents power, deltat represents time difference, price represents price, and eta represents efficiency;
cs_in represents a PCS input, t_pcs_in represents a PCS input of a t period, t_pcs_out represents a PCS output of the t period, t represents a certain period of 24 periods in a day, t_grid represents a t period power grid, t_pv_control_out represents a t period photovoltaic controller output, t_ess_out represents a t period battery output, t_ess_in represents a t period battery input, t_line loss represents a t period line loss, t_DC/DC_in represents a t period DC/DC device input, and t_charge_in represents a t period charging pile input.
S2, adding constraint conditions for the mathematical model to obtain a target model;
The constraint conditions comprise SOC upper and lower limit constraints and voltage constraints;
The ESS has upper and lower limits of SOC and upper and lower limits of voltage constraints, and since there is a loss in the ESS charging and discharging process, the SOC is calculated based on the battery as an external measurement value, and this loss is not considered, the upper and lower limits of SOC constraint is referred to herein as a nominal capacity constraint, and this constraint is expressed as:
wherein Cap represents energy, P represents power, Δt represents a time difference, and f () represents a function composed of parameters in parentheses;
t_ess_nominal represents the t-period battery nominal, lower_limit represents the lower limit, up_limit represents the upper limit, ess_init represents the battery initial, t_ess_out represents the t-period battery output, and t_ess_in represents the t-period battery input.
The voltage constraint is a direct physical constraint, and loss during charge and discharge is directly reflected on the voltage, so the voltage constraint is referred to herein as an actual capacity constraint, and the constraint is expressed as:
wherein Cap represents energy, η represents efficiency, P represents power, Δt represents a time difference;
t_ess_actual represents the actual battery of the t period, lower_limit represents the lower limit, up_limit represents the upper limit, ess_init represents the battery initial, t_ess_out represents the battery output of the t period, and t_ess_in represents the battery input of the t period.
Other constraints, also include the following:
Wherein P represents power;
t_pv_control_out represents a t-period photovoltaic controller output, t_pv_control_out_limit represents a t-period photovoltaic controller output limit, t_dc/dc_in represents a t-period DC/DC device input, t_dc/dc_in_limit represents a t-period DC/DC device input limit, t_ess_in represents a t-period battery input, t_ess_in_limit represents a t-period battery input limit, t_ess_out represents a t-period battery output, t_ess_out_limit represents a t-period battery output limit, t_pcs_out represents a t-period PCS output, and t_pcs_out_limit represents a t-period PCS output limit.
Wherein the data related to PV and DC/DC is given predicted value, if the predicted value exceeds the limit range, the correction should be performed, and the correction step should be performed when the predicted value is given. The PCS is the power of photovoltaic inversion to the AC side in the case where inversion is allowed if the value is negative, and the power of photovoltaic light rejection in the case where inversion is not allowed.
Further, based on the power loss study of the above-described portions, it is known that:
in summary, a set of suitable charging and discharging strategies for ESS are found to minimize PCS costs.
And S3, solving the target model, and carrying out energy scheduling based on a solving result.
In step S3, the solution of the target model is specifically to find a relatively better solution in a solution space formed by the target and the constraint condition based on a preset algorithm;
the preset algorithm is a genetic algorithm or a particle swarm algorithm.
In this embodiment, the current common solution algorithms of the planning model include genetic algorithm, particle swarm algorithm, and the like, and the algorithms can find a relatively better solution in the target and constrained solution space.
Taking genetic algorithm as an example:
Under normal conditions, a proper fitness function is determined according to a genetic algorithm idea and a proper solving program is written through the steps of selection, intersection, variation and the like to obtain a better solution.
Referring to fig. 2, a second embodiment of the present invention is as follows:
A terminal 1 for minimizing cost energy scheduling for optical storage filling inspection, comprising a processor 2, a memory 3 and a computer program stored in the memory 3 and executable on the processor 2, the steps of the above method for minimizing cost energy scheduling for optical storage filling inspection being implemented when the processor 2 executes the computer program.
Referring to fig. 3, a third embodiment of the present invention is:
The system for minimizing cost energy scheduling of optical storage and filling inspection comprises a storage and filling inspection station and a control device, wherein the storage and filling inspection station can be shown by referring to fig. 3 and comprises a direct current bus, a photovoltaic electric plate connected with the direct current bus, PCS (power control system), ESS (ESS) and a plurality of charging piles, and the control device controls the energy scheduling of the storage and filling inspection station so as to realize the steps in the method for minimizing cost energy scheduling of the optical storage and filling inspection.
In other equivalent embodiments, the control device may be comprised in the storage and retrieval station.
In summary, according to the method, the terminal and the system for energy scheduling of the minimized cost of the optical storage charging inspection, when modeling is performed with the aim of minimizing the PCS electricity cost, loss and voltage constraint in the actual operation process and constraint of the energy storage device are considered, energy scheduling can be considered more comprehensively and accurately, and the operation cost is reduced.
The foregoing description is only illustrative of the present invention and is not intended to limit the scope of the invention, and all equivalent changes made by the specification and drawings of the present invention, or direct or indirect application in the relevant art, are included in the scope of the present invention.

Claims (10)

1. An energy scheduling method of an optical storage and filling detection system is characterized by comprising the following steps:
S1, establishing a mathematical model based on a power conservation condition, direct-current side line loss and a relation between PCS input and output power by taking minimized PCS electricity cost as a target;
S2, adding constraint conditions for the mathematical model to obtain a target model, wherein the constraint conditions comprise SOC upper and lower limit constraints and voltage constraints;
The upper and lower limit constraint of the SOC is specifically as follows:
wherein Cap represents energy, P represents power, Δt represents a time difference, and f () represents a function composed of parameters in parentheses;
t_ess_nominal represents the t-period battery nominal, lower_limit represents the lower limit, up_limit represents the upper limit, ess_init represents the battery initial, t_ess_out represents the t-period battery output, and t_ess_in represents the t-period battery input;
The voltage constraint is specifically:
wherein Cap represents energy, η represents efficiency, P represents power, Δt represents a time difference;
t_ess_actual represents the actual battery of the t period, lower_limit represents the lower limit, up_limit represents the upper limit, ess_init represents the initial battery, t_ess_out represents the output of the battery of the t period, and t_ess_in represents the input of the battery of the t period;
The constraint conditions are outside the upper limit constraint and the lower limit constraint of the SOC and the voltage constraint, and further comprise the following constraints:
Wherein P represents power;
t_pv_control_out represents a t-period photovoltaic controller output, t_pv_control_out_limit represents a preset t-period photovoltaic controller output limit, t_dc/dc_in represents a preset t-period DC/DC device input, t_dc/in_limit represents a preset t-period DC/DC device input limit, t_ess_in represents a t-period battery input, t_ess_in_limit represents a t-period battery input limit, t_ess_out represents a t-period battery output, t_ess_out_limit represents a t-period battery output limit, t_pcs_out represents a t-period PCS output limit, and t_pcs_out_limit represents a t-period PCS output limit;
From the power loss, it is possible to:
and S3, solving the target model, and carrying out energy scheduling based on a solving result.
2. The method for energy scheduling of an optical storage and retrieval system according to claim 1, wherein the establishing of the mathematical model in the step S1 is specifically:
the goal of minimizing PCS power costs can be expressed by the following relationship:
since PCS input and output power have the following relationship:
ηt_pcs_inPt_pcs_in＝Pt_pcs_out;
thus, minimizing PCS power costs may be equivalent to:
According to the power conservation condition, the photovoltaic device is assumed to be on the direct current side, and the power balance relationship is as follows:
combining line loss:
Pt_ Line loss ＝f(Pt_pcs_out,Pt_pv_control_out,Pt_ess_out,Pt_ess_in,Pt_DC/DC_in);
the PCS output power can be expressed as:
Pt_pcs_out＝f(Pt_pv_control_out,Pt_ess_out,Pt_ess_in,Pt_DC/DC_in);
Wherein Cost represents Cost, P represents power, deltat represents time difference, price represents price, and eta represents efficiency;
cs_in represents a PCS input, t_pcs_in represents a PCS input of a t period, t_pcs_out represents a PCS output of the t period, t represents a certain period of 24 periods in a day, t_grid represents a t period power grid, t_pv_control_out represents a t period photovoltaic controller output, t_ess_out represents a t period battery output, t_ess_in represents a t period battery input, t_line loss represents a t period line loss, t_DC/DC_in represents a t period DC/DC device input, and t_charge_in represents a t period charging pile input.
3. The method according to claim 1, wherein the solving of the target model in step S3 is specifically based on a preset algorithm to find a relatively better solution in a solution space formed by the target and the constraint condition.
4. The method for energy scheduling of an optical storage and retrieval system according to claim 3, wherein the preset algorithm is a genetic algorithm;
The step S3 comprises the following steps:
And determining an fitness function based on a genetic algorithm according to the established relation and constraint conditions, and solving a target model through steps including selection, crossover and mutation.
5. The method for energy scheduling of an optical storage and retrieval system according to claim 3, wherein the predetermined algorithm is a particle swarm algorithm.
6. An energy scheduling terminal of an optical storage filling and inspection system, comprising a processor, a memory and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the following steps when executing the computer program:
S1, establishing a mathematical model based on a power conservation condition, direct-current side line loss and a relation between PCS input and output power by taking minimized PCS electricity cost as a target;
S2, adding constraint conditions for the mathematical model to obtain a target model, wherein the constraint conditions comprise SOC upper and lower limit constraints and voltage constraints;
The upper and lower limit constraint of the SOC is specifically as follows:
wherein Cap represents energy, P represents power, Δt represents a time difference, and f () represents a function composed of parameters in parentheses;
t_ess_nominal represents the t-period battery nominal, lower_limit represents the lower limit, up_limit represents the upper limit, ess_init represents the battery initial, t_ess_out represents the t-period battery output, and t_ess_in represents the t-period battery input;
The voltage constraint is specifically:
wherein Cap represents energy, η represents efficiency, P represents power, Δt represents a time difference;
t_ess_actual represents the actual battery of the t period, lower_limit represents the lower limit, up_limit represents the upper limit, ess_init represents the initial battery, t_ess_out represents the output of the battery of the t period, and t_ess_in represents the input of the battery of the t period;
The constraint conditions are outside the upper limit constraint and the lower limit constraint of the SOC and the voltage constraint, and further comprise the following constraints:
Wherein P represents power;
t_pv_control_out represents a t-period photovoltaic controller output, t_pv_control_out_limit represents a preset t-period photovoltaic controller output limit, t_dc/dc_in represents a preset t-period DC/DC device input, t_dc/in_limit represents a preset t-period DC/DC device input limit, t_ess_in represents a t-period battery input, t_ess_in_limit represents a t-period battery input limit, t_ess_out represents a t-period battery output, t_ess_out_limit represents a t-period battery output limit, t_pcs_out represents a t-period PCS output limit, and t_pcs_out_limit represents a t-period PCS output limit;
From the power loss, it is possible to:
and S3, solving the target model, and carrying out energy scheduling based on a solving result.
7. The energy scheduling terminal of the optical storage and charging system according to claim 6, wherein the mathematical model is specifically built in step S1:
the goal of minimizing PCS power costs can be expressed by the following relationship:
since PCS input and output power have the following relationship:
ηt_pcs_inPt_pcs_in＝Pt_pcs_out;
thus, minimizing PCS power costs may be equivalent to:
According to the power conservation condition, the photovoltaic device is assumed to be on the direct current side, and the power balance relationship is as follows:
combining line loss:
Pt_ Line loss ＝f(Pt_pcs_out,Pt_pv_control_out,Pt_ess_out,Pt_ess_in,Pt_DC/DC_in);
the PCS output power can be expressed as:
Pt_pcs_out＝f(Pt_pv_control_out,Pt_ess_out,Pt_ess_in,Pt_DC/DC_in);
Wherein Cost represents Cost, P represents power, deltat represents time difference, price represents price, and eta represents efficiency;
cs_in represents a PCS input, t_pcs_in represents a PCS input of a t period, t_pcs_out represents a PCS output of the t period, t represents a certain period of 24 periods in a day, t_grid represents a t period power grid, t_pv_control_out represents a t period photovoltaic controller output, t_ess_out represents a t period battery output, t_ess_in represents a t period battery input, t_line loss represents a t period line loss, t_DC/DC_in represents a t period DC/DC device input, and t_charge_in represents a t period charging pile input.
8. The energy scheduling terminal of an optical storage and filling system according to claim 6, wherein the solving of the target model in step S3 is specifically based on a preset algorithm to find a relatively better solution in a solution space formed by the target and the constraint condition.
9. The energy scheduling terminal of an optical storage and retrieval system according to claim 8, wherein the preset algorithm is a genetic algorithm;
The step S3 comprises the following steps:
And determining an fitness function based on a genetic algorithm according to the established relation and constraint conditions, and solving a target model through steps including selection, crossover and mutation.
10. The energy scheduling terminal of claim 8, wherein the predetermined algorithm is a particle swarm algorithm.
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