CN109066750B - Photovoltaic-battery micro-grid hybrid energy scheduling management method based on demand side response - Google Patents

Photovoltaic-battery micro-grid hybrid energy scheduling management method based on demand side response Download PDF

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CN109066750B
CN109066750B CN201811056883.2A CN201811056883A CN109066750B CN 109066750 B CN109066750 B CN 109066750B CN 201811056883 A CN201811056883 A CN 201811056883A CN 109066750 B CN109066750 B CN 109066750B
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photovoltaic
battery
power
grid
energy storage
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CN109066750A (en
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王磊
王康康
蔡明�
陈柳
严晋跃
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Chongqing University
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
    • H02J3/385—
    • 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
    • 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]
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/50—Photovoltaic [PV] energy
    • Y02E10/56—Power conversion systems, e.g. maximum power point trackers
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • 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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Abstract

The invention discloses a photovoltaic-battery micro-grid hybrid energy scheduling management method based on demand side response, which comprises the following steps: 1) designing a photovoltaic current equivalent circuit model of the photovoltaic power generation system; 2) establishing a maximum power output rate model of the photovoltaic power generation system; … …, respectively; 5) establishing a total economic benefit model of the photovoltaic-battery micro-grid system; 6) establishing models of the highest economic benefit NPV and the highest self-supporting rate SSR of the photovoltaic-battery micro-grid system; 7) the energy dispatching management strategy is established to control energy storage battery units consisting of lithium batteries in the photovoltaic-battery micro-grid system to switch between the following states. The seasonal characteristics of user loads and photovoltaic power sources are fully considered, the energy dispatching management strategy of the photovoltaic-battery microgrid adopts a mode of mixing two strategies, the function of an energy storage system is fully exerted, real-time seamless switching of the two strategies is realized, the economic benefit is improved, and meanwhile, the reliability and the environmental protection performance of the system are considered.

Description

Photovoltaic-battery micro-grid hybrid energy scheduling management method based on demand side response
Technical Field
The invention relates to a micro-grid energy scheduling management method, in particular to a hybrid energy scheduling management method based on demand side response.
Background
Although the engineering popularization and application of the distributed micro-grid system can greatly relieve the environmental and energy crisis, the adverse effect on the power grid is more and more obvious along with the gradual increase of the permeability of the distributed micro-grid system in the power grid system. Since the distributed power sources (wind power generation, photovoltaic power generation and the like) are greatly influenced by the outside (wind speed, illumination, temperature and the like), the power supply power of the distributed power sources has great fluctuation, the power supply reliability of a power grid is undoubtedly influenced after grid connection, and the complexity of electric energy scheduling management is increased. In order to reduce the adverse factors of the microgrid system, the addition of an energy storage system in the microgrid system becomes a main method for solving the problem and is widely applied. However, due to the high cost of the energy storage system, the economic problem of the microgrid system is also brought, and the size of the energy storage capacity is a main parameter influencing the economic efficiency of the energy storage system, so that the energy storage capacity is optimally configured to be a problem to be faced when designing the energy scheduling management scheme of the microgrid.
When designing a micro-grid energy scheduling management method, the permeability (ensuring the maximum power output of a distributed power supply) and the power loss rate (power supply reliability) of a user of the micro-grid are taken as main optimization objects and research contents. However, the engineering popularization and application of the microgrid aim at ensuring the reliability of the microgrid power supply of the community residential microgrid system, and the economic factors of the microgrid are main factors influencing commercialization and further popularization, so that the external market environment and the natural environment influencing the economic operation of the microgrid should be fully considered.
Disclosure of Invention
In view of the above, the present invention provides a method for scheduling and managing hybrid energy of a photovoltaic-battery microgrid based on demand-side response, so as to solve the problem of optimal configuration of battery energy storage capacity in a photovoltaic-battery microgrid system, and improve the economic benefit of the microgrid on the basis of fully considering internal and external factors affecting the economic operation of the microgrid and ensuring the power supply reliability and environmental protection.
The invention relates to a photovoltaic-battery micro-grid hybrid energy scheduling management method based on demand side response, which comprises the following steps of:
1) designing a photovoltaic current equivalent circuit model of a photovoltaic system as follows:
Figure GDA0002405816740000021
in the formula: i isPHIs photovoltaic current, with unit a; i is0Is the reverse saturation current of the diode model, and the unit is A; a is an ideal parameter factor; rshIs a shunt resistor with the unit of omega; rsIs a series resistance with the unit of omega; i isPVFor simulating the supply current, V, of a photovoltaic systemPVSupplying power voltage for the analog photovoltaic system;
2) the maximum power output model of the photovoltaic system is established as follows:
PPV,mpp＝max(VPV,IPV) (2)
3) the energy storage battery unit of the photovoltaic system adopts a lithium ion battery, and under the condition of considering the charge state of the lithium ion battery, the equation relation between the voltage and the current of the battery is established as follows:
Figure GDA0002405816740000022
Figure GDA0002405816740000023
in the formula: v is the voltage of the lithium ion battery and the unit is V; e0Is the open circuit voltage of the lithium ion battery, with the unit of V; k is a polarization constant and has the unit of V/Ah; q is the capacity of the lithium ion battery; the integral number of charge electric quantity is IT; a is the amplitude of the exponential region in V; i is the current of the lithium ion battery; i.e. i*To filter the current; r is an internal resistance; b is the reciprocal of the time constant of the exponential zone;
4) the standard charge and discharge frequency is used for measuring and calculating the service life of the lithium ion battery, and the relationship between the charge and discharge frequency and the charge and discharge depth of the lithium ion battery is as follows:
Figure GDA0002405816740000024
in the formula: n is the charging and discharging times of the lithium ion battery, DOD represents the charging and discharging depth of the lithium ion battery, and c, m and d are parameters determined by fitting;
according to the standard of the charging and discharging depth, an equation of the relation between the charging and discharging times and the cycle service life of the lithium ion battery is established:
Figure GDA0002405816740000031
in the formula, NstThe number of detection cycles under standard conditions; n is a radical ofredThe number of charge and discharge times of the lithium ion battery in a unit year; DODiThe charging and discharging depth of the lithium ion battery in the ith cycle charging and discharging is determined; DODSTIs the charge-discharge depth under the standard detection condition; riTaking the value as the periodicity, generally taking the values of 0.5 and 1;
calculating the circulation times to obtain LcycleAnd product standard life LcalAnd comparing, wherein in order to ensure the power supply reliability of the photovoltaic-battery micro-grid system, the service life of the lithium ion battery takes a small value:
L＝min(Lcycle,Lcal) (7)
5) establishing a total economic profit model R of a photovoltaic-battery micro-grid systemyComprises the following steps:
Ry＝REX,y+RER,y+RPS,y(8)
wherein: rER,yThe photovoltaic and energy storage battery units are connected, so that the electricity purchasing from a power grid is reduced, and the economic benefit is brought;
Figure GDA0002405816740000032
m is the hours in a unit year, and the value of M in one year is set to 8760 hours; el (electro luminescence)r,tIs a dynamic market price; pL,tFor the user load at time t, PGim,tThe electric quantity output by the power grid at the moment t;
REX,yis economic benefit obtained by the output power of the photovoltaic-battery micro-grid system,
Figure GDA0002405816740000033
PGex,tpurchasing electric quantity for the power grid at the time t; el (electro luminescence)w,tThe unit electric quantity real-time wholesale dynamic electricity price is the electricity price for selling extra electric energy to the power grid by the photovoltaic-battery micro-grid system;
RPS,ythe method is characterized in that the energy storage battery units in the photovoltaic-battery micro-grid system carry out peak value adjustment according to market electricity price and user load demand to obtain economic benefit RPS,y＝(max(PL,t)-max(PGim,t))·GFPS，GFPSThe economic benefit obtained by the peak value adjustment every year for the unit electric quantity;
PGim,tand PGex,tThe constraints of (2) are as follows:
Figure GDA0002405816740000034
Figure GDA0002405816740000041
PG,tthe power is exchanged from the power grid to the photovoltaic-battery micro-grid system, when the power grid transmits power to the micro-grid, the power is a positive value, and when the micro-grid sells power to the power grid, the power is a negative value;
6) establishing models of the highest economic benefit NPV and the highest self-supporting rate SSR of the photovoltaic-battery micro-grid system:
Figure GDA0002405816740000042
in the formula: cinvInvestment cost for system construction; cmai,yFor operating maintenance costs, Crep,yTo replacement costs; ryThe total income of the system; drThe discount rate is obtained; t is the standard service life of the photovoltaic system, and the set value of T is 25 years; wherein:
Cinv＝UICbattery·CAPbattery+UICPV·CAPPV(12)
in the formula: UICbatteryCost per unit battery capacity; CAP (common Place Capacity)batteryStoring energy capacity for the battery; UICPVCost per photovoltaic capacity; CAP (common Place Capacity)PVPhotovoltaic power source capacity;
in the whole life cycle of the system, the service life of the energy storage battery unit is shorter than that of the photovoltaic system, so that the energy storage battery unit has replacement cost which is consistent with the investment cost of the energy storage battery unit; in addition, the photovoltaic-battery micro-grid system also has operation and maintenance costs, and the operation and maintenance costs are set to be unchanged every year, namely:
Crep,y＝UICbattery·CAPbattery·rrep,battery+UICPV·CAPPV·rrep,PV(13)
in the formula: r isrep,batteryOperating and maintaining parameter factors of the energy storage battery unit in a full life cycle; r isrep,PVOperating and maintaining parameter factors of the photovoltaic system in a full life cycle;
the model for the highest self-sufficiency SSR is as follows:
Figure GDA0002405816740000043
m is the hours in a unit year, and the value of M in one year is set to 8760 hours;
solving the model of the highest economic profit NPV and the highest self-supporting rate SSR to find out a Pareto optimal solution;
7) the following energy dispatching management strategy is established, and an energy storage battery unit consisting of lithium batteries in the photovoltaic-battery micro-grid system is controlled to be switched between the following states:
① in cold season, when T<Ts∩T>TeWhen the energy storage battery unit is in the following three states:
case 1: pNet,t≥PHIn time, the energy storage battery is only PHDischarging according to the size, wherein the constraint conditions are as follows:
PB,t≥PH,
0≤PB,t≤PMdisc,t；
case 2: pNet,t≤PLIn time, the energy storage battery unit in the micro-grid is in a state of charge PMchart≤PB,tLess than or equal to 0, and simultaneously, in order to ensure the economical efficiency of the power consumption of the user load, P is required to be satisfiedG,t≤PH(ii) a In addition, according to the power exchange between the dc bus and the ac bus, the following A, B cases are classified:
A、PB,t+PPV,t≥0：
besides charging the battery, the photovoltaic system also bears load power, namely power is transferred from the direct current bus to the alternating current bus, namely the photovoltaic-battery microgrid system meets the power condition: (P)B,t+PPV,t)·ηinv＝PL,t-PG,t；
B、PB,t+PPV,t＜0：
Except thatThe photovoltaic system charges the batteries completely, and the power grid charges the batteries through the direct current bus, namely, power is transferred from the alternating current bus to the direct current bus, namely, the photovoltaic-battery micro-grid system meets the power condition: pB,t+PPV,t＝(PL,t-PG,t)·ηinv；
Case 3: pL＜PNet,t＜PHWhen the photovoltaic system and the power grid meet the load, power flows from the direct current bus to the alternating current bus, and the storage battery system in the microgrid is in a state of not charging or discharging, namely the photovoltaic-battery microgrid system meets the power condition: pB,t＝0，PPV,t·ηnv＝PL,t-PG,t；
TsAnd TeRespectively referring to a starting point and an end point, or T, of a traditional microgrid energy scheduling operation strategysAnd TeRespectively indicating an end point and a starting point of a photovoltaic-battery micro-grid hybrid energy scheduling management method based on demand side response;
t represents the time axis of the operation of the photovoltaic-battery microgrid system at any time;
PNet,trepresenting net grid supply power, PNet,t＝PL,t-PPV,t·ηinvRemoving the residual load directly supplied by the photovoltaic power source in the photovoltaic-battery micro-grid system;
PHthe reference upper limit value is used for determining the charging and discharging state of the energy storage battery unit in the micro-grid;
PLthe reference lower limit value is used for determining the charging and discharging state of the energy storage battery unit in the microgrid;
PL,tload power required for power utilization of a user;
PPV,tis the output power of the photovoltaic system;
PG,tthe power is the exchange power from the power grid to the micro-grid system, when the power grid transmits power to the micro-grid, the power is a positive value, and when the micro-grid sells power to the power grid, the power is a negative value;
PB,tis the charged power of the energy storage cell unitA positive value when in a discharge state and a negative value when the battery cell is in a charge state;
ηinvthe inverter conversion efficiency between the direct current bus and the alternating current bus is represented, and the value is 0.95;
PMdisc,tthe minimum value, namely the lower limit value, of the energy storage battery unit in a discharging state is represented;
PMchar,tthe maximum value, namely the upper limit value, of the energy storage battery unit in the charging state is represented;
② in warm season, when Ts≤T≤TeIn time, a traditional microgrid energy scheduling operation strategy is adopted, and the following two conditions exist:
I. power supply power of photovoltaic system meets load
When the photovoltaic system supply power meets the user load demand, that is
Figure GDA0002405816740000061
When the energy storage battery unit is fully charged, the extra power wholesale dynamic electricity price EL is given in unit electric quantity in real timew,tTransmitting the power to a power grid, and receiving energy dispatching of the power grid;
II, the power supply power of the photovoltaic system can not meet the load, namely
Figure GDA0002405816740000062
Then, the following two cases are divided:
1) the photovoltaic-battery energy storage micro-grid system is in an off-grid operation state: at the moment, the part of the photovoltaic system, which does not meet the load requirement of the user, is compensated and supplied by the energy storage battery unit, namely, is in a discharging state, and the photovoltaic system and the battery system meet the load requirement of the user.
2) The photovoltaic-battery energy storage micro-grid system is in a grid-connected operation state: at the moment, the part of the photovoltaic system which does not meet the load requirement of the user is compensated and supplied by the energy storage battery unit, and the power supply with the maximum power still can not meet the load requirement of the user, at the moment, the photovoltaic-battery micro-grid system uses the dynamic market electrovalence EL from the power gridr,tGo on to purchaseAnd (4) electricity.
The invention has the beneficial effects that:
the photovoltaic-battery microgrid hybrid energy scheduling management method based on demand side response fully considers seasonal characteristics of user loads and photovoltaic power sources, adopts a mode of mixing two strategies for energy scheduling management strategies of the photovoltaic-battery microgrid, fully exerts the function of an energy storage system, realizes real-time seamless switching of the two strategies, achieves the purpose of improving economic benefits, and simultaneously gives consideration to the reliability and environmental protection of the system.
Drawings
Fig. 1 is a diagram of an overall system architecture of a photovoltaic-battery energy storage microgrid;
FIG. 2 is a diagram of a single diode model of a photovoltaic system;
FIG. 3 is an equivalent circuit diagram of a lithium ion battery model;
FIG. 4 is a relationship between the number of times of charging and discharging the storage battery and the depth of charging and discharging;
FIG. 5 is a block diagram of a process for multi-objective dynamic optimization scheduling of the microgrid;
FIG. 6 is a SSR-NPV relationship diagram of a hybrid energy scheduling operation strategy based on demand side response;
FIG. 7 is a simplified flow diagram of a hybrid energy scheduling operating strategy based on demand side responses;
FIG. 8 is a net power P under hybrid energy scheduling operation based on demand side responseNet,tAnd Ts、TeA parameter relation graph;
FIG. 9 is a SSR-NPV relationship diagram of the system when the price cost of the battery is reduced by 50%;
FIG. 10 is a hybrid energy scheduling management strategy CAP based on demand side responsesbattery-an NPV map;
FIG. 11 is a graph comparing a hybrid energy management strategy based on demand side responses to a conventional energy management scheduling strategy;
fig. 12 is a flow chart of a conventional energy scheduling operation strategy.
Detailed Description
The invention is further described below with reference to the figures and examples.
As shown in the figure, the photovoltaic-battery microgrid hybrid energy scheduling management method based on demand side response in the embodiment includes the following steps:
1) and designing a photovoltaic current equivalent circuit model of the photovoltaic system. The output power of the photovoltaic system mainly depends on the illumination intensity and the temperature, as shown in fig. 2, the photovoltaic current equivalent model adopted in this embodiment is a single diode model, which is specifically as follows:
Figure GDA0002405816740000081
in the formula: i isPHIs photovoltaic current, with unit a; i is0Is the reverse saturation current of the diode model, and the unit is A; a is an ideal parameter factor; rshIs a shunt resistor with the unit of omega; rsIs the series resistance in omega. I isPVFor simulating the supply current, V, of a photovoltaic systemPVThe power supply voltage of the photovoltaic system is simulated.
2) The maximum power output model of the photovoltaic system is established as follows:
PPV,mpp＝max(VPV,IPV) (2)
maximum power point tracking control (MPPT) is adopted to ensure maximum power output of the photovoltaic system, in this embodiment, a photovoltaic module model no.is STP255-20/Wd is selected, the maximum output power is 255KW, and the photovoltaic module parameters are as shown in table 1.
TABLE 1 characterization parameters in photovoltaic Single diode model
Figure GDA0002405816740000082
3) An energy storage battery unit of the photovoltaic system adopts a lithium ion battery, the lithium ion energy storage battery unit adopts an improved Shepherd model, and under the condition of considering the charge state of the lithium ion battery, an equation relation between the voltage and the current of the battery is established as follows, and an equivalent circuit of the equation relation is shown in the following figure 3.
Figure GDA0002405816740000091
Figure GDA0002405816740000092
In the formula: v is the voltage of the lithium ion battery and the unit is V; e0Is the open circuit voltage of the lithium ion battery, with the unit of V; k is a polarization constant and has the unit of V/Ah; q is the capacity of the lithium ion battery; the integral number of charge electric quantity is IT; a is the amplitude of the exponential region in V; i is the current of the lithium ion battery; i.e. i*To filter the current; r is an internal resistance; b is the inverse of the exponential-region time constant.
In addition, the summary of relevant parameters of the lithium ion battery is shown in table 2 below.
TABLE 2 lithium ion battery model parameter table
Figure GDA0002405816740000093
4) The standard charge and discharge frequency is used for measuring and calculating the service life of the lithium ion battery, the relationship between the service life of the battery and the charge and discharge depth is shown as the following figure 4, and the relationship between the charge and discharge frequency and the charge and discharge depth of the lithium ion battery is as follows:
Figure GDA0002405816740000094
in the formula: n is the charging and discharging times of the lithium ion battery, DOD represents the charging and discharging depth of the lithium ion battery, and c, m and d are parameters determined by fitting;
according to the standard of the charging and discharging depth, an equation of the relation between the charging and discharging times and the cycle service life of the lithium ion battery is established:
Figure GDA0002405816740000101
in the formula, NstThe number of detection cycles under standard conditions; n is a radical ofredThe number of charge and discharge times of the lithium ion battery in a unit year; DODiLithium ions in the i-th cycleThe battery charge-discharge depth; DODSTIs the charge-discharge depth under the standard detection condition; riTaking the value as the periodicity, generally taking the values of 0.5 and 1;
calculating the circulation times to obtain LcycleAnd product standard life LcalAnd comparing, wherein in order to ensure the power supply reliability of the photovoltaic-battery micro-grid system, the service life of the lithium ion battery takes a small value:
L＝min(Lcycle,Lcal) (7)
5) establishing a total economic profit model R of a photovoltaic-battery micro-grid systemyComprises the following steps:
Ry＝REX,y+RER,y+RPS,y(8)
wherein: rER,yThe access of photovoltaic and energy storage battery units reduces the electricity purchasing from the power grid, brings economic benefits,
Figure GDA0002405816740000102
m is the number of hours in a year, in this example, M is 8760 (365 days a year times 24 hours a day equals 8760 hours); el (electro luminescence)r,tIs a dynamic market price; pL,tFor the user load power at time t, PGim,tThe electric quantity output by the power grid at the moment t;
REX,yis economic benefit obtained by the output power of the photovoltaic-battery micro-grid system,
Figure GDA0002405816740000103
PGex,tpurchasing electric quantity for the power grid at the time t;
RPS,ythe method is characterized in that the energy storage battery units in the photovoltaic-battery micro-grid system carry out peak value adjustment according to market electricity price and user load demand to obtain economic benefit RPS,y＝(max(PL,t)-max(PGim,t))·GFPS，GFPSThe economic benefit obtained by the peak value adjustment every year for the unit electric quantity;
PGim,tand PGex,tThe constraints of (2) are as follows:
Figure GDA0002405816740000104
Figure GDA0002405816740000105
6) establishing models of the highest economic benefit NPV and the highest self-supporting rate SSR of the photovoltaic-battery micro-grid system:
Figure GDA0002405816740000111
in the formula: cinvInvestment cost for system construction; cmai,yFor operating maintenance costs, Crep,yTo replacement costs; ryThe total income of the system; drThe discount rate is obtained; t is the service life of the photovoltaic module, and the service life of the photovoltaic module specified by the existing national standard is T25 years, and of course, the standard service life of the photovoltaic module may also be other values according to the change of the national standard.
The cost parameters for photovoltaic systems and battery systems in photovoltaic-cell microgrid systems are shown in table 3 below.
TABLE 3 cost of each module of photovoltaic-cell microgrid system
Figure GDA0002405816740000112
The cost parameters shown in table 3 include installation and operation and maintenance costs of the inverter, the controller, and other components. That is, all component costs in the pv-cell microgrid system are contained in the battery system or the pv system, so the total pv-cell microgrid system cost is equal to the battery system cost plus the pv system cost, which is calculated as shown in equation (12):
Cinv＝UICbattery·CAPbattery+UICPV·CAPPV(12)
in the formula: UICbatteryCost per unit battery capacity; CAP (common Place Capacity)batteryStoring energy capacity for the battery; UICPVCost per photovoltaic capacity; CAP (common Place Capacity)PVPhotovoltaic power source capacity.
In the whole life cycle of the system, the service life of the battery system is shorter than the photovoltaic life cycle, and the replacement cost is consistent with the investment cost of the battery system. In addition, for the calculation of the operation and maintenance cost, for the convenience of calculation, the annual operation and maintenance cost is set to be unchanged, namely:
Crep,y＝UICbattery·CAPbattery·rrep,battery+UICPV·CAPPV·rrep,PV(13)
in the formula: r isrep,batteryOperating and maintaining parameter factors of the energy storage battery unit in a full life cycle; r isrep,PVThe parameter factors of the photovoltaic system operation and maintenance in the whole life cycle.
The self-sufficiency SSR represents the proportion of the micro-grid power supply in the power demand of a user, and the highest self-sufficiency SSR is as follows:
Figure GDA0002405816740000121
and solving the model of the highest economic profit NPV and the highest self-supporting rate SSR to find out a Pareto optimal solution. In this embodiment, a non-dominated sorting multi-objective genetic algorithm (NSGA-II) is specifically used to solve the model of the highest economic profit NPV and the highest self-sufficiency SSR, the genetic algorithm is from a global optimization toolbox of MATLAB, and the parameter configuration of the algorithm according to the solving efficiency and the solving precision is shown in table 4 below.
TABLE 4 parameter configuration table for multi-target genetic algorithm
Figure GDA0002405816740000122
7) Two energy scheduling management strategies which are respectively suitable for cold seasons and warm seasons are established, a battery energy storage system is applied to compensate and supply power to a user load, the user load is reduced, high-price electricity purchasing from a power grid is achieved, the peak power demand is met, the compensation system obtains extra economic benefits due to the increased cost of the energy storage system, and an energy storage battery unit consisting of lithium batteries in a photovoltaic-battery micro-grid system is controlled to be switched between the following states:
① in cold seasons (T)<Ts∩T>Te) The energy storage battery unit is switched among the following three states:
case 1: pNet,t≥PHWhen the accumulator is as P as possibleHDischarging according to the size, wherein the constraint conditions are as follows:
PB,t≥PH，0≤PB,t≤PMdisc,t；
case 2: pNet,t≤PLIn time, the energy storage battery unit in the micro-grid is in a state of charge PMchart≤PB,tLess than or equal to 0, and simultaneously, in order to ensure the economical efficiency of the power consumption of the user load, P is required to be satisfiedG,t≤PH(ii) a In addition, according to the power exchange between the dc bus and the ac bus, the following A, B cases are classified:
A、PB,t+PPV,t≥0：
besides charging the battery, the photovoltaic system also bears load power, namely power is transferred from the direct current bus to the alternating current bus, namely the photovoltaic-battery microgrid system meets the power condition: (P)B,t+PPV,t)·ηinv＝PL,t-PG,t；
B、PB,t+PPV,t＜0：
Except that the photovoltaic system fully charges the battery, the power grid also charges the battery through the direct current bus, namely, power is transferred from the alternating current bus to the direct current bus, namely, the photovoltaic-battery microgrid system meets the power condition: pB,t+PPV,t＝(PL,t-PG,t)·ηinv；
Case 3: pL＜PNet,t＜PHWhen the photovoltaic system and the power grid meet the load, power flows from the direct current bus to the alternating current bus, and the storage battery system in the microgrid is in a state of not charging or discharging, namely the photovoltaic-battery microgrid system meets the power condition: pB,t＝0，PPV,t·ηnv＝PL,t-PG,t；
TsAnd TeRespectively referring to a starting point and an end point, or T, of a traditional microgrid energy scheduling operation strategysAnd TeRespectively indicating an end point and a starting point of a photovoltaic-battery micro-grid hybrid energy scheduling management method based on demand side response;
t represents the time axis of the operation of the photovoltaic-battery microgrid system at any time;
PNet,trepresenting net grid supply power, PNet,t＝PL,t-PPV,t·ηinvRemoving the residual load directly supplied by the photovoltaic power source in the photovoltaic-battery micro-grid system;
for at TsAnd TeOutside the time range, when the photovoltaic-battery microgrid system adopts a photovoltaic-battery microgrid hybrid energy scheduling management method based on demand side response, two parameters are also required to be introduced for determining the charging and discharging states of a battery energy storage system in the microgrid: pHAnd PL(ii) a Two upper and lower limit parameter reference values;
PL,tload power required for power utilization of a user;
PPV,tis the output power of the photovoltaic system;
PG,tthe power is the exchange power from the power grid to the micro-grid system, when the power grid transmits power to the micro-grid, the power is a positive value, and when the micro-grid sells power to the power grid, the power is a negative value;
PB,tthe charge power of the energy storage battery unit is a positive value when the energy storage battery unit is in a discharge state, and a negative value when the storage battery unit is in a charge state;
ηinvthe inverter conversion efficiency between the direct current bus and the alternating current bus is represented, and the value is 0.95;
PMdisc,tthe minimum value, namely the lower limit value, of the energy storage battery unit in a discharging state is represented;
PMchar,tthe maximum value, namely the upper limit value, of the energy storage battery unit in the charging state is represented;
② in warm season, when Ts≤T≤TeIn time, a traditional microgrid energy scheduling operation strategy is adopted, and the following two conditions exist:
I. power supply power of photovoltaic system meets load
When the photovoltaic system supply power meets the user load demand, that is
Figure GDA0002405816740000141
When the energy storage battery unit is fully charged, the extra power wholesale dynamic electricity price EL is given in unit electric quantity in real timew,tTransmitting the power to a power grid, and receiving energy dispatching of the power grid;
II, the power supply power of the photovoltaic system can not meet the load, namely
Figure GDA0002405816740000142
Then, the following two cases are divided:
1) the photovoltaic-battery energy storage micro-grid system is in an off-grid operation state: at the moment, the part of the photovoltaic system, which does not meet the load requirement of the user, is compensated and supplied by the energy storage battery unit, namely, is in a discharging state, and the photovoltaic system and the battery system meet the load requirement of the user.
2) The photovoltaic-battery energy storage micro-grid system is in a grid-connected operation state: at the moment, the part of the photovoltaic system which does not meet the load requirement of the user is compensated and supplied by the energy storage battery unit, and the power supply with the maximum power still can not meet the load requirement of the user, at the moment, the photovoltaic-battery micro-grid system uses the dynamic market electrovalence EL from the power gridr,tAnd (5) purchasing electricity.
TABLE 5 Combined application runtime of two energy scheduling management policies
Figure GDA0002405816740000143
Figure GDA0002405816740000151
Table 6 battery operating conditions and constraints under the energy scheduling management policy based on demand side response
Figure GDA0002405816740000152
In this embodiment, the photovoltaic current equivalent circuit model in step 1) and the photovoltaic system maximum power output model in step 2) relate to P in an energy scheduling management strategyPV,t(PPV,tThe output power of the photovoltaic system) to ensure that the photovoltaic system is in a maximum power tracking control state no matter what state the system is in, and ensure the maximum power output; the equation relationship between the voltage and the current of the storage battery of the photovoltaic system established in step 3 relates to Pchar,t(ii) a P in FIG. 7char,tIndicating the state of charge, P, of the battery celldisc,tIndicating a discharge state of the battery cell; and 4, measuring and calculating the service life of the lithium ion battery by using the standard charging and discharging times, wherein the value of the measured service life of the lithium ion battery is 15 years which is less than the service life of the photovoltaic system by 25 years as shown in Table 3, and the system takes 25 years as a service life cycle, so that the replacement cost (C) needs to be calculated for the lithium ion battery (C)rep,yCost for replacement), revenue (NPV) for computing the system; and 6) establishing models of the highest economic benefit NPV and the highest self-supporting rate SSR of the photovoltaic-battery micro-grid system, wherein the models are two objective function models for expressing a photovoltaic-battery micro-grid hybrid energy scheduling management method based on demand side response.
Fig. 7 is a schematic flow diagram of an energy dispatching operation strategy based on dynamic wholesale market prices, which shows a flow relationship for controlling the switching of energy storage cells in a photovoltaic-battery microgrid system between several operating states. System SOC in t-1 battery statet-1Load power PL,tAnd photovoltaic power PPV,tAs the input of the system, the charge and discharge power of the energy storage system of the lithium ion battery is calculated through the power supply and demand relationship, and the decision variable T is combinedS、TeAnd PH、PLThe system carries out seamless switching on a plurality of working states of the system so as to lead the working state P of the lithium ion battery energy storage system and the power gridB,tAnd PG,tAnd determining the overall system operation scheme. Wherein, no matter in any working state, the number of users from the power grid is reduced as much as possiblePurchase electricity, i.e. min (| P)G,t|) to maximize the economic benefit (NPV is maximized) of the microgrid system; also, in any working state, the electricity purchasing of the user from the power grid needs to be reduced as much as possible, namely min (| P)G,tAnd | the power supply proportion of the micro-grid system meeting the load requirements of users is increased, namely the system obtains the highest self-supporting rate (SSR is the highest).
Finally, the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all of them should be covered in the claims of the present invention.

Claims (1)

1. A photovoltaic-battery microgrid hybrid energy scheduling management method based on demand side response is characterized by comprising the following steps: the method comprises the following steps:
1) designing a photovoltaic current equivalent circuit model of a photovoltaic system as follows:
Figure FDA0002458496240000011
in the formula: i isPHIs photovoltaic current, with unit a; i is0Is the reverse saturation current of the diode model, and the unit is A; a is an ideal parameter factor; rshIs a shunt resistor with the unit of omega; rsIs a series resistance with the unit of omega; i isPVFor simulating the supply current, V, of a photovoltaic systemPVSupplying power voltage for the analog photovoltaic system;
2) the maximum power output model of the photovoltaic system is established as follows:
PPV,mpp＝max(VPV,IPV) (2)
3) the energy storage battery unit of the photovoltaic system adopts a lithium ion battery, and under the condition of considering the charge state of the lithium ion battery, the equation relation between the voltage and the current of the lithium ion battery is established as follows:
Figure FDA0002458496240000012
Figure FDA0002458496240000013
in the formula: v is the voltage of the lithium ion battery and the unit is V; e0Is the open circuit voltage of the lithium ion battery, with the unit of V; k is a polarization constant and has the unit of V/Ah; q is the capacity of the lithium ion battery; the integral number of charge electric quantity is IT; a is the amplitude of the exponential region in V; i is the current of the lithium ion battery; i.e. i*To filter the current; r is an internal resistance; b is the reciprocal of the time constant of the exponential zone;
4) the service life of the lithium ion battery is measured and calculated by using the charging and discharging times of the lithium ion battery, and the relationship between the charging and discharging times and the charging and discharging depth of the lithium ion battery is as follows:
Figure FDA0002458496240000014
in the formula: n is the charging and discharging times of the lithium ion battery, DOD represents the charging and discharging depth of the lithium ion battery, and c, m and d are parameters determined by fitting;
according to the standard of the charging and discharging depth, an equation of the relation between the charging and discharging times of the lithium ion battery in a unit year and the detection cycle times under the standard condition is established:
Figure FDA0002458496240000021
in the formula, NstThe number of detection cycles under standard conditions; n is a radical ofredThe number of charge and discharge times of the lithium ion battery in a unit year; DODiThe charging and discharging depth of the lithium ion battery in the ith cycle charging and discharging is determined; DODSTIs the charge-discharge depth under the standard detection condition; riTaking the value as the periodicity, generally taking the values of 0.5 and 1;
calculating the detection cycle times under the standard condition to obtain LcycleWith product labelQuasi life LcalAnd comparing, wherein in order to ensure the power supply reliability of the photovoltaic-battery micro-grid system, the service life of the lithium ion battery takes a small value:
L＝min(Lcycle,Lcal) (7)
5) establishing a total economic profit model R of a photovoltaic-battery micro-grid systemyComprises the following steps:
Figure FDA0002458496240000022
wherein: rER,yThe photovoltaic system and the energy storage battery unit are connected, so that the electricity purchasing from a power grid is reduced, and the economic benefit is brought;
Figure FDA0002458496240000023
m is the hours in a unit year, and the value of M in one year is set to 8760 hours; el (electro luminescence)r,tIs a dynamic market price; pL,tFor the user load at time t, PGim,tThe electric quantity output by the power grid at the moment t;
REX,yis economic benefit obtained by the output power of the photovoltaic-battery micro-grid system,
Figure FDA0002458496240000024
PGex,tpurchasing electric quantity for the power grid at the time t; el (electro luminescence)w,tThe unit electric quantity real-time wholesale dynamic electricity price is the electricity price for selling extra electric energy to the power grid by the photovoltaic-battery micro-grid system;
RPS,ythe method is characterized in that the energy storage battery unit in the photovoltaic-battery micro-grid system carries out peak value adjustment according to the dynamic market price and the user load demand to obtain economic benefit RPS,y＝(max(PL,t)-max(PGim,t))·GFPS，GFPSThe economic benefit obtained by the peak value adjustment every year for the unit electric quantity;
PGim,tand PGex,tThe constraints of (2) are as follows:
Figure FDA0002458496240000025
Figure FDA0002458496240000031
PG,tthe power is exchanged from the power grid to the photovoltaic-battery micro-grid system, when the power grid transmits power to the photovoltaic-battery micro-grid, the power is a positive value, and when the photovoltaic-battery micro-grid sells power to the power grid, the power is a negative value;
6) establishing models of the highest economic benefit NPV and the highest self-supporting rate SSR of the photovoltaic-battery micro-grid system:
Figure FDA0002458496240000032
in the formula: cinvInvestment cost for system construction; cmai,yFor operating maintenance costs, Crep,yTo replacement costs; ryThe total economic benefit of the photovoltaic-battery micro-grid system is obtained; drThe discount rate is obtained; t is the standard service life of the photovoltaic system, and the set value of T is 25 years; wherein:
Cinv＝UICbattery·CAPbattery+UICPV·CAPPV(12)
in the formula: UICbatteryCost per unit battery capacity; CAP (common Place Capacity)batteryStoring energy capacity for the battery; UICPVCost per photovoltaic capacity; CAP (common Place Capacity)PVIs the photovoltaic system capacity;
in the whole life cycle, the service life of the energy storage battery unit is shorter than that of the photovoltaic system, so that the energy storage battery unit has replacement cost which is consistent with the investment cost of the energy storage battery unit; in addition, the photovoltaic-battery micro-grid system also has operation and maintenance costs, and the operation and maintenance costs are set to be unchanged every year, namely:
Crep,y＝UICbattery·CAPbattery·rrep,battery+UICPV·CAPPV·rrep,PV(13)
in the formula: r isrep,batteryOperating and maintaining parameter factors of the energy storage battery unit in a full life cycle; r isrep,PVOperating and maintaining parameter factors of the photovoltaic system in a full life cycle;
the model for the highest self-sufficiency SSR is as follows:
Figure FDA0002458496240000033
m is the hours in a unit year, and the value of M in one year is set to 8760 hours;
solving the model of the highest economic profit NPV and the highest self-supporting rate SSR to find out a Pareto optimal solution;
7) the following energy dispatching management strategy is established, and an energy storage battery unit consisting of lithium ion batteries in the photovoltaic-battery microgrid system is controlled to be switched between the following states:
① in cold season, when T<Ts∩T>TeWhen the energy storage battery unit is in the following three states:
case 1: pNet,t≥PHWhile, the energy storage cell is operated at PHDischarging according to the size, wherein the constraint conditions are as follows:
PG,t≥PH,
0≤PB,t≤PMdisc,t；
case 2: pNet,t≤PLIn time, the energy storage cell unit in the photovoltaic-battery microgrid is in a state of charge PMchar,t≤PB,tLess than or equal to 0, and simultaneously, in order to ensure the economical efficiency of the power consumption of the user load, P is required to be satisfiedG,t≤PH(ii) a In addition, according to the power exchange between the dc bus and the ac bus, the following A, B cases are classified:
A、PB,t+PPV,t≥0：
the photovoltaic system charges the energy storage battery unit and bears load power, namely power is transferred from the direct current bus to the alternating current bus, namely the photovoltaic-battery microgrid system meets the power condition: (P)B,t+PPV,t)·ηinv＝PL,t-PG,t；
B、PB,t+PPV,t＜0：
Except that the photovoltaic system charges the energy storage battery units, the power grid charges the energy storage battery units through the direct current bus, namely, power is transferred from the alternating current bus to the direct current bus, namely, the photovoltaic-battery microgrid system meets the power condition: pB,t+PPV,t＝(PL,t-PG,t)·ηinv；
Case 3: pL＜PNet,t＜PHWhen the photovoltaic system and the photovoltaic-battery microgrid meet the load, power flows from the direct current bus to the alternating current bus, and the energy storage battery unit in the microgrid is in a state of not being charged or discharged, namely the photovoltaic-battery microgrid system meets the power condition: pB,t＝0，PPV,t·ηinv＝PL,t-PG,t；
TsAnd TeRespectively referring to a starting point and an end point, or T, of a traditional microgrid energy scheduling operation strategySAnd TeRespectively indicating an end point and a starting point of a photovoltaic-battery micro-grid hybrid energy scheduling management method based on demand side response;
t represents any time of a time axis of operation of the photovoltaic-battery microgrid system;
PNet,trepresenting net grid supply power, PNet,t＝PL,t-PPV,t·ηinvRemoving the residual load of the direct power supply of the photovoltaic system in the photovoltaic-battery micro-grid system;
PHthe method comprises the following steps of determining a reference upper limit value of a charge-discharge state of an energy storage battery unit in a photovoltaic-battery microgrid;
PLthe reference lower limit value is used for determining the charging and discharging state of an energy storage battery unit in the photovoltaic-battery microgrid;
PL,tthe load of the user at the moment t;
PPV,tis the output power of the photovoltaic system;
PG,tthe power is exchanged from the power grid to the photovoltaic-battery micro-grid system, and when the power grid is switched to the photovoltaic-battery micro-grid systemWhen power is transmitted, the power is a positive value, and when the photovoltaic-battery micro-grid sells power to the power grid, the power is a negative value;
PB,tthe charge power of the energy storage battery unit is a positive value when the energy storage battery unit is in a discharge state, and a negative value when the energy storage battery unit is in a charge state;
ηinvthe inverter conversion efficiency between the direct current bus and the alternating current bus is represented, and the value is 0.95;
PMdisc,tthe minimum value, namely the lower limit value, of the energy storage battery unit in a discharging state is represented;
PMchar,tthe maximum value, namely the upper limit value, of the energy storage battery unit in the charging state is represented;
② in warm season, when Ts≤T≤TeIn time, a traditional micro-grid energy scheduling operation strategy is adopted, and the method specifically comprises the following steps:
i, the power supply power of the photovoltaic system meets the load
When the photovoltaic system supply power meets the user load demand, that is
Figure FDA0002458496240000051
When the energy storage battery unit is fully charged, the extra power wholesale dynamic electricity price EL is given in unit electric quantity in real timew,tTransmitting the power to a power grid, and receiving energy dispatching of the power grid;
II, the power supply power of the photovoltaic system can not meet the load, namely
Figure FDA0002458496240000052
Then, the following two cases are divided:
1) the photovoltaic-battery energy storage micro-grid system is in an off-grid operation state: at the moment, the part of the photovoltaic system, which does not meet the load requirement of the user, is compensated and powered by the energy storage battery unit, namely, is in a discharging state, and the photovoltaic system and the energy storage battery unit meet the load requirement of the user;
2) the photovoltaic-battery energy storage micro-grid system is in a grid-connected operation state: the part of the photovoltaic system which does not meet the load requirement of the user at the moment is composed ofThe energy storage battery unit performs compensation power supply, and the maximum power supply still cannot meet the load demand of a user, and then the photovoltaic-battery micro-grid system performs EL (electric quantity) supply from the power grid at a dynamic market pricer,tAnd (5) purchasing electricity.
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