CN112103955B - Electric energy storage accident reserve capacity optimal utilization method of comprehensive energy system - Google Patents

Electric energy storage accident reserve capacity optimal utilization method of comprehensive energy system Download PDF

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CN112103955B
CN112103955B CN202010974491.5A CN202010974491A CN112103955B CN 112103955 B CN112103955 B CN 112103955B CN 202010974491 A CN202010974491 A CN 202010974491A CN 112103955 B CN112103955 B CN 112103955B
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CN112103955A (en
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李欣然
刘小龙
杨徉
刘志谱
卢颖华
罗真
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Hunan 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
    • 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
    • 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
    • H02J3/008—Circuit arrangements for ac mains or ac distribution networks involving trading of energy or energy transmission rights
    • 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
    • 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
    • H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
    • 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
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Abstract

The invention discloses an optimal utilization method of electric energy storage accident reserve capacity of a comprehensive energy system, which comprises the following steps: respectively constructing an energy model for each device of the comprehensive energy system of the battery production park; constructing a grid-connected expected income model and a grid-disconnected expected loss model based on demand response of a battery production park to the comprehensive energy system and the grid-disconnected risk of the battery production park; the offline risk of the battery production park is obtained by comprehensively considering the probability of unplanned offline and important load loss for quantification; synthesizing the grid-connected expected yield and the off-grid expected loss, and establishing a comprehensive energy system optimization scheduling model considering off-grid risk and grid-connected yield; and solving the comprehensive energy system optimization scheduling model. According to the invention, under the condition of considering both the off-grid risk and the grid-connected income, the accident capacity of the energy storage equipment is fully utilized, and the grid-connected operation economy of the comprehensive energy system in the battery production park is improved.

Description

Electric energy storage accident reserve capacity optimal utilization method of comprehensive energy system
Technical Field
The invention relates to an optimal utilization method of electric energy storage accident reserve capacity of an integrated energy system.
Background
The electric energy storage has the advantages of quick response capability, short-time high-rate discharge and the like, and is an ideal standby power supply of a comprehensive energy system. However, the contradiction is that, by virtue of the extremely high safety and stability of the existing large power grid, the configured electric energy storage accident standby is basically in an idle state in the actual operation process of the comprehensive energy system, and the waste of resources is caused to a certain extent.
Therefore, under the condition of bearing certain risks, the electricity utilization energy storage standby can be optimized by considering the following factors, and the economical efficiency of system operation is further improved: 1) considering the difference of important load requirements of each time period of the system; 2) considering the probability difference of accidents in different states (particularly weather state, load state and the like) of the area where the system is located; 3) the difference in losses after different accidents is taken into account. On the other hand, the regulation of the flexible load is one of the important means for alleviating the contradiction between supply and demand. With the rapid development of mobile phones, intelligent wireless devices and electric automobiles, the market demand of batteries is more and more extensive. The capacity grading test in the battery production process gradually adopts an energy feedback mode to realize energy conservation and environmental protection. At present, manufacturers set charging and discharging parameters of a capacity grading process too simply, the capacity grading process is optimized through a demand response means, the economy of grid-connected operation can be improved, meanwhile, the power supply demand of part of important loads under the off-line condition can be met, and the spare capacity of the electric energy storage accident is further optimized. If the system contains temperature control load, the comfort level can be reduced within the allowable range by utilizing the flexibility characteristic of the system, and the effect of short-time buffering and insufficient energy supply can be achieved.
Based on the method, the off-grid risk and the grid-connected benefit are considered, the flexible characteristics of the capacity-divided battery and the temperature control load are considered, and the optimal utilization method of the electric energy storage accident reserve capacity based on risk quantification and demand side response is provided. For a comprehensive energy system of a battery production park containing large-scale electric energy storage accident standby, the invention has good economic application value.
Disclosure of Invention
The invention aims to solve the technical problem that the accident capacity utilization rate of energy storage equipment is not high in the grid-connected operation process of a comprehensive energy system of a battery production park, and provides an optimized utilization method of the electric energy storage accident reserve capacity of the comprehensive energy system.
In order to achieve the technical purpose, the invention adopts the following technical scheme:
the comprehensive energy system optimal utilization method based on risk quantification and demand side response comprises the following steps:
step 1, respectively constructing energy models for all equipment of a comprehensive energy system of a battery production park, wherein the energy models comprise an energy storage model, a cogeneration model, a refrigeration equipment model and a water pump model;
step 2, constructing a grid-connected expected income model and a grid-disconnected expected loss model based on demand response of the battery production park to the comprehensive energy system and the grid-disconnected risk of the battery production park;
the offline risk of the battery production park is obtained by comprehensively considering the probability of unplanned offline and important load loss for quantification;
step 3, integrating the grid-connected expected yield and the off-grid expected loss, and establishing an integrated energy system optimization scheduling model considering the off-grid risk and the grid-connected yield;
and 4, solving the optimized scheduling model of the comprehensive energy system to obtain the accident reserve capacity of the energy storage equipment in the comprehensive energy system, the power of each equipment in the comprehensive energy system and the switching state of each important link load of the battery generation park.
Further, the solving method of step 4 is as follows: and converting the comprehensive energy system optimization scheduling model into a mixed integer linear programming model through linearization treatment, and calling an MATLAB mixed integer linear programming intlinprog function to solve.
Further, the types of the energy storage devices include an electrical energy storage device, a cold energy storage device, a hot energy storage device, and a productive energy storage device, the same type of battery is used as one productive energy storage device, and the energy storage model constructed for each energy storage model can be represented as:
for the
Figure BDA0002685296090000021
Figure BDA0002685296090000022
Figure BDA0002685296090000023
0≤Pt ESc≤PESn (1c)
0≤Pt ESd≤PESn (1d)
Pt ESdPt ESc＝0 (1e)
Pt ES＝Pt ESd-Pt ESc (1f)
In the formula: t is the operation time period; n is a running time period set; ES is an energy storage type, can be bes, ces, hes, ges, respectively corresponding to electricity, cold, heat, productive energy storage;
Figure BDA0002685296090000024
the ratio of the capacity stored by the energy storage device to the rated capacity; kappaESIs the energy self-loss rate;
Figure BDA0002685296090000025
respectively charging and discharging the energy storage device; pt ESc、Pt ESdRespectively charging and discharging energy of the energy storage equipment; wESnIs the rated capacity of the energy storage device; Δ t is a scheduling period;
Figure BDA0002685296090000026
the ratio of the minimum allowed energy storage capacity, the maximum allowed energy storage capacity and the rated energy storage capacity is respectively; pESnThe rated power of the energy storage device; pt ESSetting the energy discharge as positive and the energy charging as negative for the energy storage power;
the cogeneration model constructed for a cogeneration plant is represented as:
for the
Figure BDA0002685296090000027
Figure BDA0002685296090000028
Figure BDA0002685296090000031
Figure BDA0002685296090000032
Figure BDA0002685296090000033
Figure BDA0002685296090000034
Figure BDA0002685296090000035
In the formula: t is the operation time period; n is a running time period set; pt chp、
Figure BDA0002685296090000036
Electric power and thermal power output by the cogeneration equipment are respectively;
Figure BDA0002685296090000037
respectively inputting the upper and lower power limits of heat energy for the cogeneration equipment; kappachpp、κpThe conversion coefficient and deviation between the input heat energy and the output electric energy; kappachpq、κqThe conversion coefficient and deviation between the input heat energy and the output heat energy are obtained; the delta U and the delta D are respectively the maximum climbing force and the maximum descending force of the cogeneration;
Figure BDA0002685296090000038
the heat power is recovered and utilized by waste heat recovery equipment; etachprThe heat energy utilization coefficient; ft chpPower representing input thermal energy of the cogeneration plant;
the refrigeration equipment comprises an absorption type cold and warm water machine taking heat energy as energy and an electric refrigerator taking electric energy as energy, and the constructed refrigeration equipment models are respectively expressed as follows:
Figure BDA0002685296090000039
Figure BDA00026852960900000310
in the formula:
Figure BDA00026852960900000311
respectively the cold supply power and the heat consumption power of the cold and warm water machine;
Figure BDA00026852960900000312
Pt ecrespectively the cooling power and the power consumption power of the electric refrigerator; etaac、ηecThe performance coefficients of the absorption refrigeration equipment and the electric refrigeration equipment are respectively;
Figure BDA00026852960900000313
rated capacity for refrigeration equipment;
the water pump equipment model constructed for the water pump equipment is represented as follows:
Figure BDA00026852960900000314
in the formula, Pt pumpThe power is consumed by the water pump;
Figure BDA00026852960900000315
and λc、λhRespectively for transporting cold and heat energy and corresponding power consumption coefficients.
Further, the calculation formula for quantifying the probability of unplanned offline is as follows:
Figure BDA00026852960900000316
in the formula, s, w and i respectively represent time periods, weather types and off-line types in one day, and S, W, I respectively represent the number of the time periods, the number of the weather types and the number of the off-line types in one day; rs,w,iThe probability of i-type offline for w-type weather in s time period; m iss,w,iThe number of sections of i-type off-line for w-type weather in s time period; ms,wTotal number of segments for type w weather in s period;
important load loss of unplanned offline includes important ring power saving load loss and important temperature control load loss of a battery production park;
the calculation formula for quantifying the important ring power-saving load loss of the unplanned offline is as follows:
assuming time τ is off-line, for
Figure BDA0002685296090000041
Figure BDA0002685296090000042
In the formula, Vs PThe loss is the total loss of important links after the net is disconnected; Δ toffThe offline duration is; h represents the H important link, and H represents the number of the important links;
Figure BDA0002685296090000043
loss generated by unit power shortage in unit time of an important link at a certain moment after offline;
Figure BDA0002685296090000044
power is required for an important link at a certain moment after the network is disconnected;
Figure BDA0002685296090000045
in the form of a binary variable, the variable,
Figure BDA0002685296090000046
1 and 0 are respectively taken to representSupplying and not supplying important link loads at all times;
the calculation formula for quantifying the important temperature control load loss of the unplanned offline is as follows:
assuming time τ is off-line, for
Figure BDA0002685296090000047
Figure BDA0002685296090000048
Figure BDA0002685296090000049
In the formula, Vs QThe total loss of temperature control load after off-line;
Figure BDA00026852960900000410
loss generated by unit cold/heat power shortage at a certain time after the net is disconnected;
Figure BDA00026852960900000411
power is required for an important temperature control load at a certain time; qtOutputting power for the temperature control equipment at a certain time; c. Cair、mairAir specific heat capacity and mass; t ist in、Tt outIndoor and outdoor temperatures at a certain time; k is a radical ofq、Aq、DqThe heat conduction coefficient, area and thickness of the wall.
Further, the constructed grid-connected expected profit model is as follows:
Figure BDA00026852960900000412
in the formula, EcFor expected revenue of grid connection, C0C is the grid-connected operation cost of the standby energy storage and the standby energy storage; n is the number of sections in grid-connected operation; ft chp、ft chpThe cost of the thermal power and the unit power of the fuel gas at a certain time; kQFor the number of cooling/heating units, KPFor the number of power supply devices in the integrated energy system,
Figure BDA00026852960900000413
in order to provide a force to the cold/hot equipment,
Figure BDA00026852960900000414
the operation and maintenance cost of the unit output of the cooling/heating equipment in the comprehensive energy system; pt kAnd
Figure BDA00026852960900000415
the operation and maintenance cost of the output of the power supply equipment and the unit output in the comprehensive energy system is saved; pt grid、ft gridRespectively the interaction power and the interaction cost of the comprehensive energy system and the power grid;
the off-line expected loss model is constructed as follows:
Figure BDA0002685296090000051
in the formula, ElThe expected loss of the offline is obtained, and V is the sum of the offline operation cost and the load shedding loss; tau and i are offline time and type;
Figure BDA0002685296090000052
the thermal power of the gas at a certain moment under the condition of tau moment offline;
Figure BDA0002685296090000053
the output of cold/hot supply equipment and the output of power supply equipment at a certain moment under the condition of tau moment offline;
Figure BDA0002685296090000054
in the form of a binary variable, the variable,
Figure BDA0002685296090000055
get 1And 0 respectively represents the load of the h important link supplied and not supplied at a certain moment under the condition of tau moment offline;
the objective function of the comprehensive energy system optimization scheduling model is as follows:
maxE＝Ec-El (10)
wherein E is the target expected yield;
the energy system optimization scheduling model comprises grid connection constraint, off-grid constraint, grid connection and off-grid association constraint and productive energy storage production constraint, which are respectively expressed as follows:
for the
Figure BDA0002685296090000056
Figure BDA0002685296090000057
Figure BDA0002685296090000058
Formula (11a) is cold energy or heat energy balance constraint, and formula (11b) is electric energy balance constraint; lambda is the power consumption coefficient of the water pump; pt lIs a grid-connected electrical load;
Figure BDA0002685296090000059
electrical cooling/heating power;
Figure BDA00026852960900000510
is a grid-connected cold/heat load;
Figure BDA00026852960900000511
outputting force for the d productive energy storage; d is the number of productive stored energy;
for the
Figure BDA00026852960900000512
Figure BDA00026852960900000513
In the formula (12), the first term is the continuous energy supply constraint of the important link; the second term is the electric energy balance constraint under the condition of tau moment off-line, Pt conIs used for controlling the center and the fire-fighting load; the third and fourth terms are temperature control load flexible constraint under the condition of T moment offline, TsIs the standard temperature;
Figure BDA0002685296090000061
the lower limit and the upper limit of the temperature control load comfort range;
for the
Figure BDA0002685296090000062
Figure BDA0002685296090000063
In the formula (13), the reaction mixture is,
Figure BDA0002685296090000064
for the electric power of the gas engine at the time tau in the grid-connected operation process,
Figure BDA0002685296090000065
the initial electric power of the gas engine is off-line for the time tau;
Figure BDA0002685296090000066
for the energy storage capacity state at the time tau in the grid-connected operation process,
Figure BDA0002685296090000067
the energy storage initial capacity state is operated for the tau moment offline;
for the
Figure BDA0002685296090000068
Figure BDA0002685296090000069
Figure BDA00026852960900000610
Figure BDA00026852960900000611
In the formula, KrIn order to reserve the number of time segments,
Figure BDA00026852960900000612
and
Figure BDA00026852960900000613
the upper limit of the charge/discharge rate is shown.
Further, the solution variables of the integrated energy system optimization scheduling model include: the comprehensive energy system is in interactive power with a power grid during grid-connected operation, the reserve capacity of the energy storage equipment, the charging and discharging power of the energy storage equipment, the power of heat energy input by the cogeneration equipment, the power of the absorption type cold and warm water machine, the power of the electric refrigerator, and the switching state of loads of important links in a battery production park during off-grid operation of the comprehensive energy system.
Advantageous effects
According to the method, the unplanned offline probability and important load loss in different states are considered, offline risks are quantized, offline risks and grid-connected benefits are considered, capacity-divided batteries and temperature-controlled load flexible characteristics are considered, and a comprehensive energy system optimization scheduling model based on risk quantization and demand side response is constructed. According to the existing prediction technology, the weather state is judged in advance, and the optimal utilization of the electric energy storage accident reserve capacity and the optimal arrangement of the battery capacity grading process under different states are realized.
The invention has the beneficial effects that:
(1) the unplanned offline probability calculation method takes multiple factors of weather conditions, load rate level and offline types into consideration, and can accurately pre-judge the offline risk.
(2) According to the comprehensive energy system economic optimization scheduling method, offline risk and grid-connected income are considered, and a comprehensive energy system economic optimization scheduling model based on risk quantification and demand side response is constructed by utilizing the flexible characteristics of the capacity-divided battery and the temperature control load. The method can realize the optimal utilization of the reserve capacity of the electric energy storage accident and the optimal arrangement of the battery capacity grading process under different states, can improve the economical efficiency of system operation under the condition of bearing less risks, and has better practicability and economical efficiency.
Drawings
FIG. 1 is a block flow diagram of a method according to an embodiment of the invention;
FIG. 2 is an energy flow diagram of a battery production park according to an embodiment of the present invention;
fig. 3 is a schematic diagram of a battery production link in the battery production park according to an embodiment of the present invention.
Detailed Description
The embodiment is developed based on the technical scheme of the present invention, and a detailed implementation manner and a specific operation process are given, so as to further explain the technical scheme of the present invention.
The embodiment of the invention discloses an optimal utilization method of electric energy storage accident reserve capacity of a comprehensive energy system, which comprises the following steps as shown in figure 1:
step 1, respectively constructing energy models for all equipment of a comprehensive energy system of a battery production park, wherein the energy models comprise an energy storage model, a cogeneration model, a refrigeration equipment model and a water pump model. The power flow chart of the battery production park in this example is shown with reference to fig. 2.
The energy storage device types in the comprehensive energy system comprise electric energy storage, cold energy storage, hot energy storage and productive energy storage, the production park is provided with four types of batteries of A/B/C/D, the same type of battery is used as a productive energy storage device, and all the energy storage devices can establish a unified model expressed as:
for the
Figure BDA0002685296090000071
Figure BDA0002685296090000072
Figure BDA0002685296090000073
0≤Pt ESc≤PESn (1c)
0≤Pt ESd≤PESn (1d)
Pt ESdPt ESc＝0 (1e)
Pt ES＝Pt ESd-Pt ESc (1f)
Wherein, the formula (1a) represents the energy balance relation of adjacent time intervals of the energy storage operation; the formula (1b) represents the upper and lower limit constraints of the energy storage capacity state; formulas (1c) - (1e) represent energy storage output limit and complementary charging/discharging constraint; formula (1f) represents the stored energy output power;
in formula (1): t is the operation time period; n is a running time period set; ES is an energy storage type, can be bes, ces, hes, ges, respectively corresponding to electricity, cold, heat, productive energy storage;
Figure BDA0002685296090000081
the ratio of the capacity stored by the energy storage device to the rated capacity; kappaESIs the energy self-loss rate;
Figure BDA0002685296090000082
respectively charging and discharging the energy storage device; pt ESc、Pt ESdRespectively charging and discharging energy of the energy storage equipment; wESnIs the rated capacity of the energy storage device; Δ t is a scheduling period;
Figure BDA0002685296090000083
respectively minimum allowable energy storageThe ratio of the capacity, the maximum allowed energy storage capacity and the rated energy storage capacity; pESnThe rated power of the energy storage device; pt ESFor energy storage power, the energy discharge is specified to be positive and the energy charging is specified to be negative.
The cogeneration equipment is mainly a gas engine. When the input heat energy reaches a certain degree, the gas engine outputs electric energy and heat energy at the same time, and the model is described as an equation (2). Formulas (2a) - (2e) are for cogeneration output and climbing constraint; the expression (2f) indicates that a part of the heat generated by the gas engine is recovered by the waste heat recovery device, and the other part of the heat is not utilized to become waste heat.
For the
Figure BDA0002685296090000084
Figure BDA0002685296090000085
Figure BDA0002685296090000086
Figure BDA0002685296090000087
Figure BDA0002685296090000088
Figure BDA0002685296090000089
Figure BDA00026852960900000810
In formula (2): t is the operation time period; n is a running time period set; pt chp、
Figure BDA00026852960900000811
Electric power and thermal power output by the cogeneration equipment are respectively;
Figure BDA00026852960900000812
respectively inputting the upper and lower power limits of heat energy for the cogeneration equipment; kappachpp、κpThe conversion coefficient and deviation between the input heat energy and the output electric energy; kappachpq、κqThe conversion coefficient and deviation between the input heat energy and the output heat energy are obtained; the delta U and the delta D are respectively the maximum climbing force and the maximum descending force of the cogeneration;
Figure BDA00026852960900000813
the heat power is recovered and utilized by waste heat recovery equipment; etachprAs a coefficient of thermal energy utilization, Ft chpRepresenting the power of the input thermal energy of the cogeneration plant.
The refrigeration equipment comprises an absorption type cold and warm water machine taking heat energy as energy and an electric refrigerator taking electric energy as energy, and the constructed refrigeration equipment models are respectively expressed as follows:
Figure BDA0002685296090000091
Figure BDA0002685296090000092
in the formula:
Figure BDA0002685296090000093
respectively the cold supply power and the heat consumption power of the cold and warm water machine;
Figure BDA0002685296090000094
Pt ecrespectively the cooling power and the power consumption power of the electric refrigerator; etaac、ηecThe performance coefficients of the absorption refrigeration equipment and the electric refrigeration equipment are respectively;
Figure BDA0002685296090000095
rated capacity for refrigeration equipment;
the water pump is equipment for conveying cold and heat energy in a combined cooling and heating system, and a water pump equipment model formed by the relation between power consumption and the conveyed cold and heat energy is expressed as follows:
Figure BDA0002685296090000096
in the formula, Pt pumpThe power is consumed by the water pump;
Figure BDA0002685296090000097
and λc、λhRespectively for transporting cold and heat energy and corresponding power consumption coefficients.
Step 2, constructing a grid-connected expected income model and a grid-disconnected expected loss model based on demand response of the battery production park to the comprehensive energy system and the grid-disconnected risk of the battery production park;
the key point of the offline risk of the battery production park is to calculate the probability of occurrence of an event and the consequences caused by the event, so that the offline risk can be obtained by comprehensively considering the probability of unplanned offline and important load loss for quantification.
The formula for quantifying the probability of unplanned outages is:
Figure BDA0002685296090000098
in the formula, s, w and i respectively represent time periods, weather types and off-line types in one day, and S, W, I respectively represent the number of the time periods, the number of the weather types and the number of the off-line types in one day; rs,w,iThe probability of i-type offline for w-type weather in s time period; m iss,w,iThe number of sections of i-type off-line for w-type weather in s time period; ms,wTotal number of segments for type w weather in s period; in the present embodiment, S ═ 3, W ═ 3, and I ═ 3.
Important load loss of unplanned offline includes important ring power saving load loss and important temperature control load loss of a battery production park;
as shown in fig. 3, in the battery production link, the internal frames of stage 1 and stage 2 are important ring power loads, 4 in total, in the formation link of stage 3, the battery is activated by charging the battery, and in the capacity grading link, the battery capacity is tested by charging and discharging. After unplanned offline, the critical links need to be maintained to work normally for a period of time to process the remaining material of the current batch. The quantity of the processing materials is basically proportional to the consumed electric energy, the product of the economic loss generated by unit power shortage in unit time of an important link and the shortage electric energy represents the important ring power-saving load loss, namely, the calculation formula for quantifying the important ring power-saving load loss of the unplanned offline is as follows:
assuming time τ is off-line, for
Figure BDA0002685296090000101
Figure BDA0002685296090000102
In the formula, Vs PThe loss is the total loss of important links after the net is disconnected; Δ toffThe offline duration is; h represents the H-th important link, H represents the number of important links, and H is 4 in the embodiment;
Figure BDA0002685296090000103
loss generated by unit power shortage in unit time of an important link at a certain moment after offline;
Figure BDA0002685296090000104
power is required for an important link at a certain moment after the network is disconnected;
Figure BDA0002685296090000105
in the form of a binary variable, the variable,
Figure BDA0002685296090000106
1 and 0 are taken to represent important links of supply and non-supply at a certain moment respectivelyAnd (4) loading.
After unplanned offline, the battery production park needs to be maintained within a comfortable temperature range to prevent material damage of each production link, and deviation from a standard temperature within the comfortable range can reduce the comfort level. Therefore, the product of the economic loss generated by the shortage of cold/hot power per unit time of the temperature-controlled load and the shortage of cold/heat energy represents the loss caused by the reduction of comfort level, i.e., the calculation formula for quantifying the important temperature-controlled load loss of the unplanned offline is as follows:
assuming time τ is off-line, for
Figure BDA0002685296090000107
Figure BDA0002685296090000108
Figure BDA0002685296090000109
In the formula, Vs QThe total loss of temperature control load after off-line;
Figure BDA00026852960900001010
loss generated by unit cold/heat power shortage at a certain time after the net is disconnected;
Figure BDA00026852960900001011
power is required for an important temperature control load at a certain time; qtOutputting power for the temperature control equipment at a certain time; c. Cair、mairAir specific heat capacity and mass; t ist in、Tt outIndoor and outdoor temperatures at a certain time; k is a radical ofq、Aq、DqThe heat conduction coefficient, area and thickness of the wall.
When the comprehensive energy system of the battery production park operates in a grid-connected mode, based on the demand response of the battery production park to the comprehensive energy system and the off-grid risk of the battery production park, a grid-connected expected profit model is constructed and obtained as follows:
Figure BDA00026852960900001012
in the formula, EcFor expected revenue of grid connection, C0C is the grid-connected operation cost of the standby energy storage and the standby energy storage; n is the number of sections in grid-connected operation; ft chp、ft chpThe cost of the thermal power and the unit power of the fuel gas at a certain time; kQFor the number of cooling/heating units, KPIn order to supply the number of devices,
Figure BDA00026852960900001013
in order to provide a force to the cold/hot equipment,
Figure BDA00026852960900001014
the operating and maintaining cost of the unit output of the cooling/heating equipment; pt kAnd
Figure BDA0002685296090000111
the operation and maintenance cost of the power supply equipment output and the unit output is saved; pt grid、ft gridRespectively, the interaction power and the interaction cost of the comprehensive energy system and the power grid. If the net release occurs at T1And in the time period, after grid connection is recovered, energy storage can still complete peak-valley difference arbitrage in the rest time period, and the income is the same as the income without off-line. Thus, calculate EcS does not take 1.
When the comprehensive energy system of the battery production park is in unplanned disconnection, based on the demand response of the battery production park to the comprehensive energy system and the disconnection risk of the battery production park, constructing an obtained disconnection expected loss model as follows:
Figure BDA0002685296090000112
in the formula, ElExpected loss for off-line, V is off-line operating cost and off-load lossAnd; tau and i are offline time and type;
Figure BDA0002685296090000113
the thermal power of the gas at a certain moment under the condition of tau moment offline;
Figure BDA0002685296090000114
the output of cold/hot supply equipment and the output of power supply equipment at a certain moment under the condition of tau moment offline;
Figure BDA0002685296090000115
in the form of a binary variable, the variable,
Figure BDA0002685296090000116
taking 1 and 0 respectively represents the load of the h important link supplied and not supplied at a certain moment under the condition of tau moment offline.
Step 3, integrating the grid-connected expected yield and the off-grid expected loss, and establishing an integrated energy system optimization scheduling model considering the off-grid risk and the grid-connected yield, namely an objective function established by the grid-connected expected yield and the off-grid expected loss:
maxE＝Ec-El (10)
wherein E is the target expected yield; and the objective function also comprises grid connection constraint, off-grid constraint, grid connection and off-grid association constraint and productive energy storage production constraint.
The grid tie constraint is expressed as:
for the
Figure BDA0002685296090000117
Figure BDA0002685296090000118
Figure BDA0002685296090000119
The formula (11a) is cold energy or heat energy balance constraint, and the formula (11b) is electric energy balance constraintWeighing constraint; lambda is the power consumption coefficient of the water pump; pt lIs a grid-connected electrical load;
Figure BDA00026852960900001110
electrical cooling/heating power;
Figure BDA00026852960900001111
is a grid-connected cold/heat load;
Figure BDA00026852960900001112
outputting force for the d productive energy storage; d is the number of productive stored energy.
The off-net constraint is expressed as:
for the
Figure BDA00026852960900001113
Figure BDA0002685296090000121
In the formula (12), the first term is the continuous energy supply constraint of the important link; the second term is the electric energy balance constraint under the condition of tau moment off-line, Pt conIs used for controlling the center and the fire-fighting load; the third and fourth terms are temperature control load flexible constraint under the condition of T moment offline, TsIs the standard temperature;
Figure BDA0002685296090000122
the lower limit and the upper limit of the temperature control load comfort range.
The grid-connected and off-grid association constraints are expressed as:
for the
Figure BDA0002685296090000123
Figure BDA0002685296090000124
In the formula (13), the reaction mixture is,
Figure BDA0002685296090000125
for the electric power of the gas engine at the time tau in the grid-connected operation process,
Figure BDA0002685296090000126
the initial electric power of the gas engine is off-line for the time tau;
Figure BDA0002685296090000127
for the energy storage capacity state at the time tau in the grid-connected operation process,
Figure BDA0002685296090000128
and (4) carrying out the energy storage initial capacity state for the offline operation at the moment tau.
The productive energy storage production constraints of a battery production park include: a. a certain time is reserved for automatically loading all the batteries into the capacity grading cabinet; b. the charging and discharging multiplying power range in the capacity grading process needs to be set according to the requirements of customers; c. the grading step needs to be carried out according to the sequence of filling, discharging and filling to an initial state, all the steps need to be completed within one day, and the grading process can be kept still. The above constraint is expressed as formula (14):
for the
Figure BDA0002685296090000129
Figure BDA00026852960900001210
Figure BDA00026852960900001211
Figure BDA00026852960900001212
Equation (14a) satisfies the constraints of items a and b, KrIn order to reserve the number of time segments,
Figure BDA0002685296090000131
and
Figure BDA0002685296090000132
is the upper limit value of the charge-discharge multiplying power; the equations (14b) and (14c) satisfy the constraint condition of the c-th term, wherein the equation (14b) is the constraint of the sequence of the battery being fully charged and then fully discharged, and the equation (14c) is the constraint of the full charge and discharge in one cycle.
And 4, converting the comprehensive energy system optimization scheduling model into a mixed integer linear programming model through linearization treatment, and calling an MATLAB mixed integer linear programming inlingprog function to solve the comprehensive energy system optimization scheduling model.
The solving variables of the comprehensive energy system optimization scheduling model comprise: the comprehensive energy system is in interactive power with a power grid during grid-connected operation, the reserve capacity of the energy storage equipment, the charging and discharging power of the energy storage equipment, the power of heat energy input by the cogeneration equipment, the power of the absorption type cold and warm water machine, the power of the electric refrigerator, and the switching state of loads of important links in a battery production park during off-grid operation of the comprehensive energy system.
In the step 4, the comprehensive energy system optimization scheduling model is converted into a mixed integer linear programming model through linearization treatment, and specifically, the mixed integer linear programming model is shown in a formula (15) to a formula (17).
Since the energy storage device model shown in equation (1) is a complementary constraint, a binary variable can be introduced to linearize the complementary constraint, resulting in a complementary constraint linear process shown in equation (15):
for the
Figure BDA0002685296090000133
Figure BDA0002685296090000134
In formula (15):
Figure BDA0002685296090000135
the energy storage state and the energy release state are binary variables and respectively represent the energy storage state and the energy release state at a certain moment. When the stored energy is charged, the energy storage device,
Figure BDA0002685296090000136
the number of the carbon atoms is 1,
Figure BDA0002685296090000137
is 0; when the energy is stored and released, the energy storage device,
Figure BDA0002685296090000138
is a non-volatile organic compound (I) with a value of 0,
Figure BDA0002685296090000139
is 1.
The production energy storage constraint formula (14c) contains max and min term constraints, the two constraint processing methods are similar, and taking the constraint min term as an example, binary variables are introduced for linearization processing, and the linearization processing is expressed as max term linearization processing shown in formula (16):
for the
Figure BDA00026852960900001310
Figure BDA00026852960900001311
Figure BDA00026852960900001312
Figure BDA00026852960900001313
Figure BDA00026852960900001314
In the formula (16), the compound represented by the formula,
Figure BDA00026852960900001315
is a binary variable;
Figure BDA00026852960900001316
there is a unique 1, which when taken as 1, is a productive energy storage
Figure BDA00026852960900001317
To fully place the constraint.
In the cogeneration equipment model shown in formula (2), the cogeneration equipment output has a segmentation point, and a segmentation function constraint process of processing a binary variable and a continuous variable is introduced, and is expressed as:
for the
Figure BDA0002685296090000141
Figure BDA0002685296090000142
Figure BDA0002685296090000143
Figure BDA0002685296090000144
Figure BDA0002685296090000145
Figure BDA0002685296090000146
Figure BDA0002685296090000147
Figure BDA0002685296090000148
In the formula (17), the compound represented by the formula (I),
Figure BDA0002685296090000149
the lower limit and the upper limit of the adjustable power of the gas engine are set;
Figure BDA00026852960900001410
are all binary variables;
Figure BDA00026852960900001411
is a continuous variable.
Figure BDA00026852960900001412
When the average molecular weight is 0, the average molecular weight,
Figure BDA00026852960900001413
one is 0, namely when the input heat energy does not meet the requirement, the output power of the gas engine is always 0;
Figure BDA00026852960900001414
when the number of the carbon atoms is 1,
Figure BDA00026852960900001415
may be replaced by [0,1 ]]The inner continuous value, namely the power of the gas engine, is continuously adjustable within the upper limit and the lower limit.
The above embodiments are preferred embodiments of the present application, and those skilled in the art can make various changes or modifications without departing from the general concept of the present application, and such changes or modifications should fall within the scope of the claims of the present application.

Claims (5)

1. A method for optimally utilizing the electric energy storage accident reserve capacity of an integrated energy system is characterized by comprising the following steps:
step 1, respectively constructing energy models for all equipment of a comprehensive energy system of a battery production park, wherein the energy models comprise an energy storage model, a cogeneration model, a refrigeration equipment model and a water pump model;
the types of the energy storage devices comprise an electric energy storage device, a cold energy storage device, a hot energy storage device and a productive energy storage device, the same type of battery is used as the productive energy storage device, and an energy storage model constructed for each energy storage device can be represented as follows:
for the
Figure FDA0003386227240000011
Figure FDA0003386227240000012
Figure FDA0003386227240000013
0≤Pt ESc≤PESn (1c)
0≤Pt ESd≤PESn (1d)
Pt ESdPt ESc＝0 (1e)
Pt ES＝Pt ESd-Pt ESc (1f)
In the formula: t is the operation time period; n is a running time period set; ES is an energy storage type, can be bes, ces, hes, ges, respectively corresponding to electricity, cold, heat, productive energy storage;
Figure FDA0003386227240000014
the ratio of the capacity stored by the energy storage device to the rated capacity; kappaESIs the energy self-loss rate;
Figure FDA0003386227240000015
respectively charging and discharging the energy storage device; pt ESc、Pt ESdRespectively charging and discharging energy of the energy storage equipment; wESnIs the rated capacity of the energy storage device; Δ t is a scheduling period;
Figure FDA0003386227240000016
the ratio of the minimum allowed energy storage capacity, the maximum allowed energy storage capacity and the rated energy storage capacity is respectively; pESnThe rated power of the energy storage device; pt ESSetting the energy discharge as positive and the energy charging as negative for the energy storage power;
the cogeneration model constructed for a cogeneration plant is represented as:
for the
Figure FDA0003386227240000017
Figure FDA0003386227240000018
Figure FDA0003386227240000019
Figure FDA00033862272400000110
Figure FDA00033862272400000111
Figure FDA00033862272400000112
Figure FDA0003386227240000021
In the formula: t is the operation time period; n is a running time period set; pt chp、
Figure FDA0003386227240000022
Electric power and thermal power output by the cogeneration equipment are respectively;
Figure FDA0003386227240000023
respectively inputting the upper and lower power limits of heat energy for the cogeneration equipment; kappachpp、κpThe conversion coefficient and deviation between the input heat energy and the output electric energy; kappachpq、κqThe conversion coefficient and deviation between the input heat energy and the output heat energy are obtained; delta U and delta D are respectively the maximum climbing force and the maximum descending force of the cogeneration;
Figure FDA0003386227240000024
the heat power is recovered and utilized by waste heat recovery equipment; etachprThe heat energy utilization coefficient; ft chpPower representing input thermal energy of the cogeneration plant;
the refrigeration equipment comprises an absorption type cold and warm water machine taking heat energy as energy and an electric refrigerator taking electric energy as energy, and the constructed refrigeration equipment models are respectively expressed as follows:
Figure FDA0003386227240000025
Figure FDA0003386227240000026
in the formula:
Figure FDA0003386227240000027
respectively the cold supply power and the heat consumption power of the cold and warm water machine;
Figure FDA0003386227240000028
respectively the cooling power and the power consumption power of the electric refrigerator; etaac、ηecRespectively absorption refrigeration equipment andcoefficient of performance of the electric refrigeration equipment;
Figure FDA0003386227240000029
rated capacity for refrigeration equipment;
the water pump equipment model constructed for the water pump equipment is represented as follows:
Figure FDA00033862272400000210
in the formula (I), the compound is shown in the specification,
Figure FDA00033862272400000211
the power is consumed by the water pump;
Figure FDA00033862272400000212
and λc、λhRespectively conveying cold and heat energy and corresponding power consumption coefficients;
step 2, constructing a grid-connected expected income model and a grid-disconnected expected loss model based on demand response of the battery production park to the comprehensive energy system and the grid-disconnected risk of the battery production park;
the offline risk of the battery production park is obtained by comprehensively considering the probability of unplanned offline and important load loss for quantification;
step 3, integrating the grid-connected expected yield and the off-grid expected loss, and establishing an integrated energy system optimization scheduling model considering the off-grid risk and the grid-connected yield;
and 4, solving the optimized dispatching model of the comprehensive energy system to obtain the accident reserve capacity of the energy storage equipment in the comprehensive energy system, the power of each equipment in the comprehensive energy system and the switching state of each important link load in the battery production park.
2. The method of claim 1, wherein the solution method of step 4 is: and converting the comprehensive energy system optimization scheduling model into a mixed integer linear programming model through linearization treatment, and calling an MATLAB mixed integer linear programming intlinprog function to solve.
3. The method of claim 1, wherein the formula for quantifying the probability of unplanned outages is:
Figure FDA0003386227240000031
in the formula, s, w and i respectively represent time periods, weather types and off-line types in one day, and S, W, I respectively represent the number of the time periods, the number of the weather types and the number of the off-line types in one day; rs,w,iThe probability of i-type offline for w-type weather in s time period; m iss,w,iThe number of sections of i-type off-line for w-type weather in s time period; ms,wTotal number of segments for type w weather in s period;
important load loss of unplanned offline includes important ring power saving load loss and important temperature control load loss of a battery production park;
the calculation formula for quantifying the important ring power-saving load loss of the unplanned offline is as follows:
assuming time τ is off-line, for
Figure FDA0003386227240000032
Figure FDA0003386227240000033
In the formula, Vs PThe loss is the total loss of important links after the net is disconnected; Δ toffThe offline duration is; h represents the H important link, and H represents the number of the important links;
Figure FDA0003386227240000034
loss generated by unit power shortage in unit time of an important link at a certain moment after offline;
Figure FDA0003386227240000035
power is required for an important link at a certain moment after the network is disconnected;
Figure FDA0003386227240000036
in the form of a binary variable, the variable,
Figure FDA0003386227240000037
taking 1 and 0 to respectively represent the load of supplying and not supplying important links at a certain time;
the calculation formula for quantifying the important temperature control load loss of the unplanned offline is as follows:
assuming time τ is off-line, for
Figure FDA0003386227240000038
Figure FDA0003386227240000039
Figure FDA00033862272400000310
In the formula, Vs QThe total loss of temperature control load after off-line;
Figure FDA00033862272400000311
loss generated by unit cold/heat power shortage at a certain time after the net is disconnected;
Figure FDA00033862272400000312
power is required for an important temperature control load at a certain time; qtOutputting power for the temperature control equipment at a certain time; c. Cair、mairAir specific heat capacity and mass; t ist in、Tt outIndoor and outdoor temperatures at a certain time; k is a radical ofq、Aq、DqThe heat conduction coefficient, area and thickness of the wall.
4. The method according to claim 3, wherein the grid-connected expected benefit model is constructed by:
Figure FDA0003386227240000041
in the formula, EcFor expected revenue of grid connection, C0C is the grid-connected operation cost of the standby energy storage and the standby energy storage; n is the number of sections in grid-connected operation; ft chp、ft chpThe cost of the thermal power and the unit power of the fuel gas at a certain time; kQFor the number of cooling/heating units, KPFor the number of power supply devices in the integrated energy system,
Figure FDA0003386227240000042
in order to provide a force to the cold/hot equipment,
Figure FDA0003386227240000043
the operation and maintenance cost of the unit output of the cooling/heating equipment in the comprehensive energy system; pt kAnd
Figure FDA0003386227240000044
the operation and maintenance cost of the output of the power supply equipment and the unit output in the comprehensive energy system is saved; pt grid、ft gridRespectively the interaction power and the interaction cost of the comprehensive energy system and the power grid;
the off-line expected loss model is constructed as follows:
Figure FDA0003386227240000045
in the formula, ElThe expected loss of the offline is obtained, and V is the sum of the offline operation cost and the load shedding loss; tau and i are offline time and type;
Figure FDA0003386227240000046
the thermal power of the gas at a certain moment under the condition of tau moment offline;
Figure FDA0003386227240000047
the output of cold/hot supply equipment and the output of power supply equipment at a certain moment under the condition of tau moment offline;
Figure FDA0003386227240000048
in the form of a binary variable, the variable,
Figure FDA0003386227240000049
taking 1 and 0 to respectively represent the load of the h-th important link supplied and not supplied at a certain moment under the condition of tau moment offline;
the objective function of the comprehensive energy system optimization scheduling model is as follows:
max E＝Ec-El (10)
wherein E is the target expected yield;
the energy system optimization scheduling model comprises grid connection constraint, off-grid constraint, grid connection and off-grid association constraint and productive energy storage production constraint, which are respectively expressed as follows:
for the
Figure FDA00033862272400000410
Figure FDA00033862272400000411
Figure FDA00033862272400000412
Formula (11a) is cold energy or heat energy balance constraint, and formula (11b) is electric energy balance constraint; lambda is the power consumption coefficient of the water pump; pt lIs a grid-connected electrical load;
Figure FDA00033862272400000413
electrical cooling/heating power;
Figure FDA00033862272400000414
is a grid-connected cold/heat load;
Figure FDA00033862272400000415
outputting force for the d productive energy storage; d is the number of productive stored energy;
for the
Figure FDA0003386227240000051
Figure FDA0003386227240000052
In the formula (12), the first term is the continuous energy supply constraint of the important link; the second term is the power balance constraint in the off-line situation at time tau,
Figure FDA0003386227240000053
is used for controlling the center and the fire-fighting load; the third and fourth terms are temperature control load flexible constraint under the condition of T moment offline, TsIs the standard temperature;
Figure FDA0003386227240000054
the lower limit and the upper limit of the temperature control load comfort range;
for the
Figure FDA0003386227240000055
Figure FDA0003386227240000056
In the formula (13), the reaction mixture is,
Figure FDA0003386227240000057
for the electric power of the gas engine at the time tau in the grid-connected operation process,
Figure FDA0003386227240000058
the initial electric power of the gas engine is off-line for the time tau;
Figure FDA0003386227240000059
for the energy storage capacity state at the time tau in the grid-connected operation process,
Figure FDA00033862272400000510
the energy storage initial capacity state is operated for the tau moment offline;
for the
Figure FDA00033862272400000511
Figure FDA00033862272400000512
Figure FDA00033862272400000513
Figure FDA00033862272400000514
In the formula, KrIn order to reserve the number of time segments,
Figure FDA00033862272400000515
and
Figure FDA00033862272400000516
the upper limit of the charge/discharge rate is shown.
5. The method of claim 4, wherein the solution variables of the integrated energy system optimization scheduling model comprise: the comprehensive energy system is in interactive power with a power grid during grid-connected operation, the reserve capacity of the energy storage equipment, the charging and discharging power of the energy storage equipment, the power of heat energy input by the cogeneration equipment, the power of the absorption type cold and warm water machine, the power of the electric refrigerator, and the switching state of loads of important links in a battery production park during off-grid operation of the comprehensive energy system.
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