CN112633669A - Energy management system and method suitable for large-scale light storage charging electric vehicle charging station - Google Patents

Energy management system and method suitable for large-scale light storage charging electric vehicle charging station Download PDF

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CN112633669A
CN112633669A CN202011511860.3A CN202011511860A CN112633669A CN 112633669 A CN112633669 A CN 112633669A CN 202011511860 A CN202011511860 A CN 202011511860A CN 112633669 A CN112633669 A CN 112633669A
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station
charging
power
time
energy
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陆彬
李德胜
马华峰
傅诚
郑隽一
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National Innovation Energy Automobile Intelligent Energy Equipment Innovation Center Jiangsu Co Ltd
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National Innovation Energy Automobile Intelligent Energy Equipment Innovation Center Jiangsu Co Ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06312—Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling
    • 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
    • B60L53/64—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
    • 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
    • B60L55/00—Arrangements for supplying energy stored within a vehicle to a power network, i.e. vehicle-to-grid [V2G] arrangements
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Energy or water supply
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
    • H02J3/322—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means the battery being on-board an electric or hybrid vehicle, e.g. vehicle to grid arrangements [V2G], power aggregation, use of the battery for network load balancing, coordinated or cooperative battery charging
    • H—ELECTRICITY
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    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/381—Dispersed generators
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • 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
    • 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
    • H02J2310/00—The network for supplying or distributing electric power characterised by its spatial reach or by the load
    • H02J2310/40—The network being an on-board power network, i.e. within a vehicle
    • H02J2310/48—The network being an on-board power network, i.e. within a vehicle for electric vehicles [EV] or hybrid vehicles [HEV]
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    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/50—Photovoltaic [PV] energy
    • Y02E10/56—Power conversion systems, e.g. maximum power point trackers
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    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
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    • Y02E40/70—Smart grids as climate change mitigation technology in the energy generation sector
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    • Y02E70/00—Other energy conversion or management systems reducing GHG emissions
    • Y02E70/30—Systems combining energy storage with energy generation of non-fossil origin
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    • Y02T10/00—Road transport of goods or passengers
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Abstract

The invention discloses an energy management system and method suitable for a light storage charging electric vehicle charging station, wherein the system comprises a primary system and a secondary system, the primary system comprises a power distribution network system, a light storage charging station system and an electric vehicle group connected to a station, and the secondary system comprises a power grid dispatching system, a station management system and a cloud platform; the station management system and the power distribution network system receive the dispatching and control of the power grid dispatching system; the station management system collects data information of the light storage and charging station system and the electric vehicle group connected to the station and uploads the data information to the cloud platform, the cloud platform calculates scheduling control sequences of real-time states and future states, and sends instructions to the station management system to perform energy distribution of the whole station and power distribution of the charging pile. According to the invention, through the omnibearing top-level design of four energy systems of photovoltaic, energy storage, power grid and electric vehicle, the optimal energy control of the large-scale optical storage charging station is realized, and the maximum income of an operator of the large-scale optical storage charging station is realized.

Description

Energy management system and method suitable for large-scale light storage charging electric vehicle charging station
Technical Field
The invention relates to an energy management system and method, and belongs to the technical field of electric automobiles.
Background
With the development of science and technology and the improvement of society, the development of electric vehicles has been promoted to the national strategic level, the quantity of electric vehicles which can be expected will show geometric increase in the next 10 years, but most of the current charging stations supply power for a single power grid power supply, and with the slope receding of the national subsidy, the disordered charging, the high electricity purchasing cost and the low profit become important factors which restrict the social capital from actively participating in the construction of large-scale charging stations, and the high cost is indirectly transferred to the electric vehicle owners, thereby generating a vicious circle for the development of the electric vehicles.
The electric vehicle is different from common electric equipment, has the prominent problems of large capacity, large power, random access and the like, and particularly, the concentrated charging of a large-scale electric vehicle can cause larger power load impact on the current power grid system to influence the operation safety of the power grid. Meanwhile, the photovoltaic power generation is clean, pollution-free and convenient to arrange, the storage battery makes up for the defect of an intermittent power source of the photovoltaic power generation, the load power utilization requirement is met at any time and all the time, and the transient balance of electric energy is achieved in space and time. At present, the cost of a photovoltaic and energy storage system is greatly reduced, and the requirement of a large-scale charging station from a traditional 'single power grid access' mode to a 'photovoltaic + energy storage + power grid' comprehensive mode is more and more strong. On the one hand, under the mode that the large-scale light stores the charging station and is based on "spontaneous self-service, surplus electricity is on the net", thereby on the one hand make full use of photovoltaic power generation can reduce the energy demand of electric automobile charging to the electric wire netting, reduce the impact of charging load to the electric wire netting, on the other hand utilizes the peak valley electricity price difference to carry out reverse electricity selling thereby obtaining profit. Meanwhile, as the research and application of the V2G technology are deepened, the V2G technology is connected to a power grid and provides power injection and reactive compensation services, so that the section power is increased under the unbalanced state of the power grid, and a charging station and a user can obtain high fund compensation.
The light stores up the charging station and has included multiple different energy systems, namely photovoltaic, energy storage, electric wire netting, electric motor car, and each energy system can realize the energy flow each other, and this set of complicated system architecture also makes the energy coordination control of light storage charging station become complicated and difficult. The current research has the following drawbacks: (1) most of applications stay in a charging station with 'single power grid access', and the dynamic adjustment of charging load and power supply of a power grid side is realized under an electric vehicle energy demand side management framework; (2) most applications are from light storage charging station principle advantage, and photovoltaic + energy storage cooperation green power consumption promptly, and reverse electricity of selling based on peak valley price realizes clipping and fills in the millet etc. nevertheless mostly general means of controlling, lack accurate data quantization and carry out energy distribution. Therefore, an energy distribution mode of quantitative management is urgently needed for a large-scale optical storage type charging station, four energy systems of photovoltaic, energy storage, power grid and electric vehicle are coordinately controlled, power grid operation scheduling needs to be met, energy flow coordination control can be achieved, and income maximization of a charging station operator is achieved.
Disclosure of Invention
The invention mainly aims to provide an energy management system and method for a large-scale light storage charging electric vehicle charging station, which can be used for coordinating the mutual flowing distribution of energy among photovoltaic power generation, an energy storage battery, a power grid and an electric vehicle, reducing the load of the power grid, meeting the operation scheduling of the power grid, realizing the coordination control of energy flow and realizing the maximum income of a charging station operator.
The technical scheme adopted by the invention is as follows:
an energy management system suitable for a light storage charging electric vehicle charging station is characterized by comprising a primary system and a secondary system, wherein the primary system is an equipment side, and the secondary system is a management side; the primary system comprises a power distribution network system, a light storage charging station system and an electric vehicle group accessed to a station, and the secondary system comprises a power grid dispatching system, a station management system and a cloud platform; the station management system and the power distribution network system receive the dispatching and control of the power grid dispatching system; the station management system collects data information of the light storage and charging station system and the electric vehicle group connected to the station and uploads the data information to the cloud platform, target function modeling is carried out from three aspects of station income, power grid load scheduling and charging user satisfaction, scheduling control sequences of a real-time state and a future state are calculated, and then an instruction is issued to the station management system to carry out energy distribution of the whole station and power distribution of charging piles.
An energy management method suitable for a light storage charging electric vehicle charging station is characterized by comprising the following steps:
(1) performing objective function modeling from three aspects of station income, power grid load scheduling and charging user satisfaction, and designing an objective function by taking the maximum comprehensive income of the light storage charging station as a main objective;
G(t)＝max(S1(t)+β2S2(t)+β3S3(t))
in the formula, S1(t) is a comprehensive income objective function of the optical storage and charging station at the moment t; s2(t) is a penalty function of the deviation value of the power consumption of the power grid of the station at the moment t, beta2Is a penalty factor row vector; s3(t) is a function of the user satisfaction at time t, charging3Is a use factor row vector;
(2) establishing a simplified energy management model of the station under the constraint condition:
Figure BDA0002846616070000021
wherein G (t) is the top level objective function at time t, g1(t) is the equality constraint function, g2(t) is an inequality constraint function;
(3) and solving the objective function to obtain scheduling control sequences of real-time states and future states, and performing energy distribution of the whole station and power distribution of the charging pile according to the scheduling control sequences.
According to the invention, through the omnibearing top-level design of four energy systems of photovoltaic, energy storage, power grid and electric vehicle, the optimal energy control of the large-scale optical storage charging station is realized, and the income maximization of an operator of the large-scale optical storage charging station is realized while the power grid operation scheduling is satisfied and the user satisfaction is improved.
Drawings
FIG. 1 is a schematic diagram of an energy management system according to the present invention;
fig. 2 is a schematic diagram of energy interchange between the distribution network system and the light storage and charging station system;
FIG. 3 is a flow chart of the energy management method of the present invention.
Detailed Description
An energy management system of a large-scale light storage charging electric vehicle charging station is shown in fig. 1 and comprises a primary system and a secondary system, wherein the primary system is an equipment side, and the secondary system is a management side. The primary system comprises a power distribution network system, a light storage and charging station system and an electric vehicle group connected to the station, wherein the light storage and charging station system comprises a photovoltaic power generation system, an energy storage system, a station power utilization system and a charging pile system. The secondary system comprises a power grid dispatching system, a station management system and a cloud platform. The charging station control system and the power distribution network system receive scheduling and control of the power grid scheduling system, the scheduling comprises issued daily power utilization plans and sudden scheduling instructions, and the control comprises energy exchange between the power distribution network and the stations. The photovoltaic power generation system, the energy storage battery system, the station power utilization system, the charging pile and the electric vehicle group connected to the station receive a control command issued by the charging station management system. The control priority of the power grid dispatching system is higher than that of the station management system, and dispatching commands of the power grid dispatching system can be used as marginal control to carry out strong constraint.
The station management system integrates a power grid dispatching receiving module, a station data acquisition module, a station energy management module and an orderly charging control module. And the power grid dispatching receiving module is used for receiving dispatching and control information of the power grid dispatching system. The station data acquisition module acquires data information (including current photovoltaic power generation capacity, energy storage system SOC electric quantity, current station power load, current charging power and number of charging piles, SOC electric quantity and charging power of electric vehicle batteries, predicted off-site time of user input and the like) of a photovoltaic power generation system, an energy storage battery system, a station power utilization system, a charging pile system, an electric vehicle group connected to a station and the like according to different time step lengths, and uploads the data information to the cloud. The data are processed and analyzed through the cloud platform advanced application module, a scheduling control sequence of a real-time state and a future state is calculated by combining external information such as time-of-use electricity price information and weather, then an instruction is issued to the station energy management module and the orderly charging control module, and the station energy management module carries out energy distribution response according to the instruction issued by the cloud platform to carry out energy distribution of the whole station. And the ordered charging control module performs power distribution on the charging pile according to the instruction issued by the cloud platform.
Photovoltaic power generation system installs solar cell panel at the parking shed top, and photovoltaic power generation system utilizes solar energy to convert direct current electric energy into, inserts charging station power supply, battery accumulate, surplus electric quantity through direct current converter and sells. The life cycle of the photovoltaic power generation system is long, usually 25-30 years, so that the cost of the electric energy can be considered to be close to zero, and the photovoltaic power generation energy should be utilized to the maximum. Photovoltaic power generation systems typically operate in a Maximum Power Point Tracking (MPPT) mode.
An energy storage battery system arranged in the form of a container in the area around the charging station. The energy storage battery and the charging station are connected through the bidirectional direct current converter, so that charging and discharging can be realized. The stored electric energy mainly comes from charging of photovoltaic surplus electric energy, and when the photovoltaic power generation power is smaller than the station requirement, the energy storage battery system discharges to meet the charging requirement of the electric automobile. Under the special condition of the power grid, the emergency power supply is connected into the power grid for supporting, and the power grid is prevented from being disconnected and rushing.
The station power system and the necessary power unit for station operation can be divided into a first-level load, a second-level load and a third-level load according to importance, wherein the first-level load is not allowed to be powered off, the second-level load is allowed to be powered off for a short time (within 2 hours), and the third-level load is powered off for a long time (within 3 days). The station power system is a pure power load, backup power supply of a multi-circuit is carried out according to different important levels, photovoltaic power generation is preferentially used in principle, and non-inductive switching of different power supplies is supported.
Electric vehicle access is a main profit source of a station, but the number of electric vehicles, the vehicle state, the charging power and the charging mode are random in space and time. The orderly charging of the electric automobile is scheduled in a rolling manner in time, so that the real-time power utilization balance is realized, and the impact on a power grid is reduced; and energy distribution pretreatment is carried out in the space in the future day, so that the profit maximization of an operator is realized, and the satisfaction degree of a user is met. Under the special condition of the power grid, the V2G technology is used as an emergency power supply to be connected into the power grid for supporting, and the power grid is prevented from being disconnected and rushed.
The charging station control system integrates a power grid dispatching receiving module, a station data acquisition module, a station energy management module and an ordered charging control module. All data and models collected by the station are uploaded to the cloud end, are processed and analyzed by the cloud platform advanced application module, and are combined with time-of-use electricity price information to calculate scheduling control sequences (namely vector control of energy flow of the whole station including size and direction) of real-time states and future states, and then instructions are issued to the station energy management module to perform energy distribution of the whole station and perform power distribution on charging piles by the ordered charging control module.
The large-scale optical storage charging station performs energy optimal automatic distribution management in the whole time period based on the principle of 'self-generation and surplus power internet access', the energy management design concept performs modeling from three aspects of field station income, power grid dispatching and charging user satisfaction, but the three layers of functions are highly strongly coupled, and if single function optimization is pursued, the results of other two functions are certainly extremely poor. The comprehensive variables and the constraint conditions are huge, and the solved matrix scale is increased by geometric times. Therefore, the three-layer model function is decoupled by using a proper mathematical method, and the global optimization solution is quickly searched. The specific scheme is as follows:
(1) a three-layer intelligent charging strategy for station energy management aims to maximize profits of an optical storage charging station, ensure safe and stable operation of an existing accessed power distribution network and improve satisfaction of users as much as possible. Therefore, the top design function with the maximum comprehensive income of the optical storage charging station as the main objective function is as follows:
G(t)＝max(S1(t)+β2S2(t)+β3S3(t))
in the formula, S1(t) is a comprehensive income objective function of the optical storage charging station at the moment t; s2(t) is a penalty function of the deviation value of the power consumption of the power grid of the station at the moment t, beta2Is a penalty factor row vector; s3(t) is a function of the user satisfaction at time t, charging3A factor row vector is used.
(2) The first tier targets the maximum of the charging station's integrated revenue. Starting from an actual scenario, the assumption is given that: the service life of the photovoltaic can reach 25-30 years, and no other resource is lost, so that the electric energy generated by the photovoltaic is used as zero-cost electric energy; the storage battery is only used as an intermediate host of energy (discharging more or less electricity, charging more or less electricity), and the cycle number of the storage battery is limited, so the charge and discharge need to calculate the loss price of the battery; stations and distribution networks can be considered "cassettes", i.e. there is no need to consider energy flow subdivision within a single cassette, but only concern about energy interaction between two cassettes, thus simplifying the complex problem, as shown in fig. 2.
Setting delta t as a time step, wherein a calculation formula of a station profit model at the time t is as follows:
Figure BDA0002846616070000051
in the formula, P1(t) charging power of charging pile at time t, c1(t) charging price of the charging pile at the moment t; p2(t) selling power of photovoltaic power transmitted to the grid at time t, c2(t) selling electricity price of the photovoltaic power transmission to the power grid at the time t; p3(t) is time tThe electric vehicle battery transmits the selling power to the power grid by utilizing the V2G technology, c31(t) selling price of electric vehicle battery to power grid at time t, c32(t) the price subsidized to the owner using V2G at time t; p4(t) selling power of station energy storage and transmission to power grid at time t, c2(t) storing energy at the station at the moment t, and transmitting the stored energy to the power grid for selling the electricity price; p5(t) is the station energy storage discharge power at the moment t, and z (t) is the station energy storage discharge depreciation price at the moment t; p6(t) the power consumption of the grid to the station at time t, c6And (t) is the time-of-use electricity price of the power supplied to the station by the power grid at the moment t.
(3) And the second layer tracks the power grid dispatching plan value as a target. Power consumption P of power distribution network access station6And (t) trough depth is aggravated due to too low power consumption, and a new load peak is caused if the power consumption is too high, so that the power grid power consumption of the station is guided by tracking the power grid dispatching plan value, and certain punishment measures are given to the power deviation value. the calculation formula of the station penalty model at the time t is as follows:
Figure BDA0002846616070000052
in the formula, alpha is station punishment coefficient (alpha is more than or equal to 0), P6(t) electric power consumption of grid transmission station at time t, PLAnd (t) scheduling the power value of the power grid to the station at the time t.
(4) The third layer of user satisfaction is targeted. Close interaction relation is kept between the station energy management system and the user side, so that the power utilization requirements of users are met, and the sequential distribution of the charging pile power is finally realized based on the user satisfaction. The charging of the user is concerned with the charging quantity, the charging time, the charging price, and in addition, the V2G technology realizes the electricity selling subsidy and other factors. the user satisfaction model at the moment t is as follows:
Figure BDA0002846616070000053
in the formula (f)1i(t) is a satisfaction function of the ith vehicle user at time t, whichMiddle P1i(t) charging power at time t of ith vehicle user, c1i(T) is the charging price of the ith vehicle user at time T, Ti(t) integrating the time and then calculating the charging time according to the user requirement; f. of2i(t) use the V2G power selling subsidy function for the ith vehicle user at time t, where P3i(t) selling power of V2G at time t of ith vehicle user, c32iAnd (t) is the station subsidy price of the ith vehicle user at the time t, and N is the total number of the charging vehicle users at the time t.
(5) Establishing a simplified energy management model of the station under the constraint condition:
Figure BDA0002846616070000054
wherein G (t) is the top level objective function at time t, g1(t) is the equality constraint function, g2(t) is an inequality constraint function.
The constraint conditions include and are not limited to system power flow balance in each time period; the power generation and utilization and capacity of the equipment are restricted at each end; node voltage constraints; line current constraint; boundary conditions, etc. Those skilled in the art can design the constraint function according to actual requirements, and the design method does not belong to the scope discussed in the present invention.
The scale, the variables and the constraint conditions of the large-scale light storage and charging system are quite large, the matrix scale of corresponding solution is greatly increased, the station energy management focuses more on the higher standards of timeliness, response intelligence, safety, reliability, efficiency, accuracy and the like, and the embodiment selects an interior point method to realize second-level model calculation so as to meet the requirement of scheduling on-line calculation of the station energy management system. For the condition of low timeliness requirement, an analytic hierarchy process and an intelligent algorithm including a particle swarm algorithm, a genetic algorithm, an expert system and the like can be selected for calculation.
As shown in fig. 3, the energy management implementation process for solving the objective function by using the interior point method is as follows:
starting at time t, carrying out total-station data acquisition by a station energy management system, and initializing a sampling time interval delta t and variable step length;
uploading all data acquired by the station to a cloud platform, and performing target function modeling from three aspects of station income, power grid load scheduling and charging user satisfaction;
initializing an equation, converting equivalent of inequality constraint into equality constraint, introducing a Lagrange multiplier, and converting a mathematical model into a Lagrange function;
fourthly, calculating the compensation Gap according to the optimal condition of the KKT, and if the compensation Gap is less than alpha (alpha is convergence precision, and is usually equal to 10)-6) And outputting the optimal energy management scheme of the light storage and charging station, entering the sampling and calculating period of the next time t +1, and continuing the next step (v).
The optimal energy management scheme generated by the cloud platform is a set of scheduling control sequences of all devices, and vector control of station energy flow requires that all stations perform switch or software command operation one by one according to steps and have action sequencing. And issuing the control sequence command to a station energy management module to realize the control of the total station light storage and charging equipment, thus realizing the energy management of the total station.
Correcting the disturbance factor and adjusting the step length of each variable;
sixthly, correcting original variables (including dual variables);
seventhly, setting traversal k to be k +1, if k is not more than kmax (the set maximum traversal number), continuing to the next step, otherwise, calculating to be not converged, outputting an energy management scheme at the last moment t-1, and entering a sampling and calculating period at the next moment t + 1;
judging whether the accumulated calculation time ts of the interior point method is less than the sampling time interval, if ts is less than or equal to delta t, turning to the step IV, if not, outputting the energy management scheme of the last moment t-1, and entering the sampling and calculating period of the next moment t + 1.
When the optical storage charging station operates for a period of time, the number of samples accessed by the electric vehicle is enough, and a prediction curve which is more in line with the actual situation exists for the probability prediction and the charging power prediction of the access of the electric vehicle. The calculated delta t of the previous real-time state can be in the second level, the minute level and the hour level, and if the 24h scheduling before the day is calculated, the delta t is 1 hourCalculating the total day prediction curve according to each basic data
Figure BDA0002846616070000071
The overall target is optimal, and then a future energy management scheme of the light storage and charging station every hour is given. The whole day overall target optimal calculation does not need to enter the next adopting period of t +1, but the steps of the inner point method are the same as those of the previous steps, so that the optimal total energy distribution of the light storage charging station in the future is finally realized, and meanwhile, the non-convergence energy distribution scheme of the real-time calculation at the time in the future can be corrected.

Claims (10)

1. An energy management system suitable for a light storage charging electric vehicle charging station is characterized by comprising a primary system and a secondary system, wherein the primary system is an equipment side, and the secondary system is a management side; the primary system comprises a power distribution network system, a light storage charging station system and an electric vehicle group accessed to a station, and the secondary system comprises a power grid dispatching system, a station management system and a cloud platform; the station management system and the power distribution network system receive the dispatching and control of the power grid dispatching system; the station management system collects data information of the light storage and charging station system and the electric vehicle group connected to the station and uploads the data information to the cloud platform, target function modeling is carried out from three aspects of station income, power grid load scheduling and charging user satisfaction, scheduling control sequences of a real-time state and a future state are calculated, and then an instruction is issued to the station management system to carry out energy distribution of the whole station and power distribution of charging piles.
2. The energy management system according to claim 1, wherein said optical storage charging station system comprises a photovoltaic power generation system, an energy storage system, a station power system and a charging pile system.
3. The energy management system for light-storage charging electric vehicle charging stations according to claim 1, wherein said station management system integrates a power grid dispatching receiving module, a station data acquisition module, a station energy management module, and an orderly charging control module; the power grid dispatching receiving module is used for receiving dispatching and control information of a power grid dispatching system; the station data acquisition module is used for acquiring data information of the light storage and charging station system and the electric vehicle group accessed to the station and uploading the data information to the cloud platform; the station energy management module performs energy distribution of the whole station according to an instruction issued by the cloud platform; and the ordered charging control module performs power distribution on the charging pile according to the instruction issued by the cloud platform.
4. The energy management system according to claim 1, wherein said grid dispatching system comprises a daily power plan and a sudden dispatching command, and said control comprises energy exchange between said distribution grid system and said light storage charging station.
5. The energy management system for the optical storage charging electric vehicle charging station according to claim 1, wherein the cloud platform uses an interior point method to solve the objective function, so as to obtain a scheduling control sequence of a real-time state and a future state.
6. The energy management system according to claim 1, wherein the grid dispatching system has a higher control priority than the station management system.
7. The energy management system according to claim 1, wherein the grid dispatching system commands are strongly constrained as a marginal control.
8. An energy management method suitable for a light storage charging electric vehicle charging station is characterized by comprising the following steps:
(1) performing objective function modeling from three aspects of station income, power grid load scheduling and charging user satisfaction, and designing an objective function by taking the maximum comprehensive income of the light storage charging station as a main objective;
G(t)＝max(S1(t)+β2S2(t)+β3S3(t))
in the formula, S1(t) is a comprehensive income objective function of the optical storage and charging station at the moment t; s2(t) is a penalty function of the deviation value of the power consumption of the power grid of the station at the moment t, beta2Is a penalty factor row vector; s3(t) is a function of the user satisfaction at time t, charging3Is a use factor row vector;
(2) establishing a simplified energy management model of the station under the constraint condition:
Figure FDA0002846616060000021
wherein G (t) is the top level objective function at time t, g1(t) is the equality constraint function, g2(t) is an inequality constraint function;
(3) and solving the objective function to obtain scheduling control sequences of real-time states and future states, and performing energy distribution of the whole station and power distribution of the charging pile according to the scheduling control sequences.
9. The method according to claim 8, wherein the objective function is solved by using an interior point method to obtain a scheduling control sequence in real-time and future states.
10. The method of claim 8, wherein the energy management system comprises:
Figure FDA0002846616060000022
Figure FDA0002846616060000023
Figure FDA0002846616060000024
wherein, P1(t) charging power of charging pile at time t, c1(t) charging price of the charging pile at the moment t; p2(t) selling power of photovoltaic power transmitted to the grid at time t, c2(t) selling electricity price of the photovoltaic power transmission to the power grid at the time t; p3(t) the selling power of the battery of the electric vehicle to the power grid by utilizing the V2G technology at the moment t, c31(t) selling price of electric vehicle battery to power grid at time t, c32(t) the price subsidized to the owner using V2G at time t; p4(t) selling power of station energy storage and transmission to power grid at time t, c2(t) storing energy at the station at the moment t, and transmitting the stored energy to the power grid for selling the electricity price; p5(t) is the station energy storage discharge power at the moment t, and z (t) is the station energy storage discharge depreciation price at the moment t; p6(t) the power consumption of the grid to the station at time t, c6(t) is the time-of-use electricity price of the power grid for the station at the moment t; α is station penalty factor, P6(t) electric power consumption of grid transmission station at time t, PL(t) scheduling planned power values of the power grid to the station at the moment t; f. of1i(t) is a satisfaction function of the ith vehicle user at time t, where P1i(t) charging power at time t of ith vehicle user, c1i(T) is the charging price of the ith vehicle user at time T, Ti(t) integrating the time and then calculating the charging time according to the user requirement; f. of2i(t) use the V2G power selling subsidy function for the ith vehicle user at time t, where P3i(t) selling power of V2G at time t of ith vehicle user, c32i(t) subsidizing the price for the station at the moment t of the ith vehicle user; and N is the total number of the charged vehicle users at the time t of the station.
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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113283807A (en) * 2021-06-23 2021-08-20 阳光电源股份有限公司 Operation scheduling method and device for optical storage charging station
CN116646965A (en) * 2023-07-21 2023-08-25 深圳橙电新能源科技有限公司 Photovoltaic energy storage charging and discharging integrated management system

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113283807A (en) * 2021-06-23 2021-08-20 阳光电源股份有限公司 Operation scheduling method and device for optical storage charging station
CN113283807B (en) * 2021-06-23 2024-04-05 阳光慧碳科技有限公司 Operation scheduling method and device of optical storage charging station
CN116646965A (en) * 2023-07-21 2023-08-25 深圳橙电新能源科技有限公司 Photovoltaic energy storage charging and discharging integrated management system
CN116646965B (en) * 2023-07-21 2024-01-23 深圳橙电新能源科技有限公司 Photovoltaic energy storage charging and discharging integrated management system

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