CN113393077A - Method for configuring an electric-gas multi-energy storage system taking into account the uncertainty of the energy used by the user - Google Patents

Method for configuring an electric-gas multi-energy storage system taking into account the uncertainty of the energy used by the user Download PDF

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CN113393077A
CN113393077A CN202110451877.2A CN202110451877A CN113393077A CN 113393077 A CN113393077 A CN 113393077A CN 202110451877 A CN202110451877 A CN 202110451877A CN 113393077 A CN113393077 A CN 113393077A
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energy storage
energy
power
storage system
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CN113393077B (en
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杨波
潘军
黄旭锐
朱以顺
张行
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Guangzhou Power Supply Bureau of Guangdong Power Grid Co Ltd
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Guangzhou Power Supply Bureau of Guangdong Power Grid Co Ltd
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    • G06Q10/06313—Resource planning in a project environment
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    • G06—COMPUTING; CALCULATING OR COUNTING
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    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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Abstract

The invention discloses an electric-gas multi-energy storage system configuration method considering user energy uncertainty. Firstly, establishing a regional comprehensive energy system model containing an electricity-gas multi-energy storage system; then, the influence of different load characteristics and uncertainty of user energy types on the configuration of the energy storage system is analyzed; on the basis of the economy as a target, an electric-gas multi-energy storage system optimization configuration model containing an energy storage battery, P2G equipment (power to gas), gas storage equipment and a gas transmission pipeline is established; finally, calling CPLEX in Matlab to solve the verification method is provided, and the complementary characteristics of the multi-energy storage system are proved to be utilized, so that the cost can be further reduced.

Description

Method for configuring an electric-gas multi-energy storage system taking into account the uncertainty of the energy used by the user
Technical Field
The invention belongs to the research field of a multi-energy storage system, and particularly relates to an electric-gas multi-energy storage system configuration method considering user energy uncertainty.
Background
With the exhaustion of fossil energy and the increasing severity of environmental pollution, the energy internet has been widely recognized as an effective way to solve the problem. The energy internet is a novel technical information energy fusion open system based on the internet concept, can greatly improve the energy use efficiency, and promotes the large-scale development of renewable energy.
The regional comprehensive energy system generally comprises energy forms such as cold, heat, electricity and gas as an important component of an energy internet, and all energy supply equipment sources in a region are integrated and scheduled in a unified manner by using an internet of things technology and an information technology so as to achieve the effects of optimizing energy supply on regional cold, heat and electricity loads and improving energy utilization efficiency.
Energy storage technology has received wide attention as a support technology for integrated energy systems. The comprehensive energy system introduces a multi-energy storage system based on the traditional energy storage battery, and comprises various forms of electricity storage, heat storage, cold storage, gas storage, composite energy storage and the like. The energy storage system with a single energy form is installed in the comprehensive energy system to have a certain peak clipping and valley filling effect, but when the multi-energy type load needs to be supplemented by energy storage output, certain energy loss can be caused by certain interconversion among multiple energy sources, for example, the heat load cannot be supplied by the energy storage system in time. And the electricity storage system is relatively high in manufacturing cost, and the loss of large-scale energy storage is large. The heat and gas storage system can store energy in a large scale, but the inertia of the system is larger than that of the electricity storage system, and the energy transfer is slow. Thus, the different types of energy storage systems complement each other in performance. In addition, the multi-energy storage system plays a key role in electric energy replacement, and the multi-energy storage system with certain configuration can ensure complete electric energy replacement. Therefore, in order to enhance the flexibility of the integrated energy network, a multi-energy storage system is introduced to achieve the purpose of complementary advantages.
The research on the multi-energy storage system is concerned by students recently, if the students establish a regional comprehensive energy system optimization operation model taking the minimum comprehensive cost as a target and considering the multi-energy storage; scholars propose a novel real-time energy management method to control an island direct-current microgrid driven by a photovoltaic array, and the microgrid is simultaneously provided with 2 different types of energy storage systems of electricity and hydrogen; researchers study the configuration of a hydrogen storage system in the process of converting electricity into natural gas; researchers have proposed an energy storage optimization configuration method for a regional comprehensive energy system considering electric/thermal flexible load;
however, the research does not research the optimal configuration of the electric-gas multi-energy system, does not research the optimal configuration model of various devices of the electric-gas multi-energy storage system, such as an energy storage battery, a P2G device, a gas storage device, a gas transmission pipeline and the like, does not consider the uncertainty of the types of the user energy in the optimal configuration of the multi-energy storage system, and has little discussion on the feasibility of electric energy substitution after the multi-energy storage system is added.
Disclosure of Invention
The present invention is directed to overcoming the disadvantages of the prior art and providing a method for configuring an electric-gas multi-energy storage system that takes into account user energy uncertainty.
The purpose of the invention is realized by the following technical scheme: an electric-gas multi-energy storage system configuration method considering user energy uncertainty, comprising the steps of:
(1) establishing a regional comprehensive energy system model containing an electricity-gas multi-energy storage system;
(2) analyzing the influence of different load characteristics and uncertainty of user energy types on the configuration of the energy storage system and adjusting the load:
and (2.1) determining different supply sources of the loads.
(2.2) determining the proportion of the selectable load.
(3) With the economy as a target, an electricity-gas multi-energy storage system optimization configuration model containing an energy storage battery, P2G equipment, gas storage equipment and a gas transmission pipeline is established:
and (3.1) planning the rated power and the capacity of the multi-energy storage system in the built integrated energy system to minimize the total cost in the whole life cycle. Meanwhile, the time value of capital is considered, and all the cost is reduced to the equal-year value.
And (3.2) adding gas turbine output constraint, gas boiler constraint, electric boiler constraint, energy storage battery constraint and gas storage constraint in the established model.
(4) And (4) optimizing and solving the model established in the step (3).
Further, the step (1) is specifically as follows:
and (1.1) establishing a physical model of the regional comprehensive energy system based on the electricity-gas multi-energy storage system. The multi-energy storage system comprises an energy storage battery, a P2G device, a gas storage device and input and output pipelines of the gas storage device. The loads are divided into electrical and thermal loads, and other devices are gas turbines, wind generators, gas boilers and electric boilers.
And (1.2) establishing a mathematical model of the regional comprehensive energy system based on the electricity-gas multi-energy storage system. The method specifically comprises the following steps:
(1.2.1) external energy injection: injection power of distribution network
Figure BDA0003039027340000021
And net injection power
Figure BDA0003039027340000022
(1.2.2) electric load
Figure BDA0003039027340000023
Power generated by fanWTEnergy storage battery output PBatPart for power purchasing of distribution network
Figure BDA0003039027340000024
And the output P of the gas turbineGTSupplying:
Figure BDA0003039027340000025
wherein, mu and (1-mu) respectively represent the shunt coefficients of the power for the P2G equipment and the direct power supply; λ and (1- λ) represent the split coefficients of natural gas input to the gas turbine and the gas boiler. EtaP2G、ηGF、ηGTThe conversion efficiencies of the P2G plant, gas boiler, gas turbine, and electric boiler, respectively.
(1.2.3) Heat load
Figure BDA0003039027340000031
Supplied by a gas boiler:
Figure BDA0003039027340000032
wherein, PGSOutputting power to the gas storage device.
(1.2.4) Power P of P2G deviceP2GReferring to the conversion of power into natural gas power, the P2G equipment, as part of the gas storage device, directly enters the gas storage system through the gas transmission pipeline, and supplies load from the gas storage system through the gas transmission pipeline when necessary:
Figure BDA0003039027340000033
(1.2.5) the gas source of the gas turbine is a part of the output of the gas storage device and the input of the gas network:
Figure BDA0003039027340000034
wherein eta isGSThe conversion efficiency of the gas storage equipment.
Further, in step (2.2), the optional load is partially powered by the gas boiler and partially powered by the electric boiler and is treated as an electric load. The load type of each time period is distributed with a proportional load uniform distribution.
Further, the step (3.1) is specifically:
(3.1) the objective function of the plan can be expressed as:
min C＝kpaIC+OC+FC
wherein C is the total cost converted to annuity; IC is the initial investment cost; OC is the annual operating cost; FC is a fixed cost and a fixed value, and mainly refers to annual maintenance cost; k is a radical ofpaWhen the annual interest rate is r and the energy storage life cycle is y years, the expression is as follows:
Figure BDA0003039027340000035
further, in step (3.1):
(3.1.1) the investment cost mainly comprises two parts of an energy storage battery and a gas storage device:
Figure BDA0003039027340000036
in the formula:
Figure BDA0003039027340000037
respectively representing the maximum power and the maximum capacity of the storage battery;
Figure BDA0003039027340000038
represents the maximum power of the P2G device;
Figure BDA0003039027340000039
indicating the maximum capacity of the gas storage device;
Figure BDA00030390273400000310
respectively representing the maximum power of the input and output gas storage devices; k is a radical of1、k2Respectively representing the unit power investment coefficient and the unit capacity investment coefficient of the storage battery; k is a radical of3Representing the specific power investment coefficient of the P2G equipment; k is a radical of4Representing the unit capacity investment coefficient of the gas storage device; k is a radical of5The unit power investment coefficient of the gas transmission pipeline is shown.
(3.1.2) operating costs refer to electricity purchase from the main grid and gas purchase from the gas grid, and are expressed as follows:
Figure BDA0003039027340000041
wherein S, T represents typical days and scheduled hours of the day, respectively; dsRepresents the total number of days for a typical day s;
Figure BDA0003039027340000042
the electricity purchase price for the t-th scheduled hour;
Figure BDA0003039027340000043
representing the purchased electric power of the t scheduled hour on the s typical day; lambda [ alpha ]gRepresenting a uniform price of the natural gas network; r represents the calorific value coefficient of natural gas combustion;
Figure BDA0003039027340000044
and scheduling the purchased gas power of the hour for the tth typical day.
Further, since the natural gas produced by the P2G plant is directly transferred to the gas storage facility, it is approximately considered that
Figure BDA0003039027340000045
Further, in step (3.2):
(3.2.1) device constraints
(3.2.1.1) gas turbine output constraint
0≤PGT≤PGT，max
Figure BDA0003039027340000046
In the formula: pGT，maxIs the maximum output of the gas turbine; etaGTThe gas-electricity conversion efficiency of the gas turbine is obtained;
Figure BDA0003039027340000047
for inputting gas turbine gas power.
(3.2.1.2) gas boiler constraint
0≤PGF≤PGF，max
Figure BDA0003039027340000048
In the formula: pGF，maxThe maximum thermal output of the gas boiler; etaGFThe gas heat conversion efficiency of the gas boiler is obtained;
Figure BDA0003039027340000049
for inputting the gas power of the gas boiler.
(3.2.1.3) electric boiler restraint
0≤PEB≤PEB，max
Figure BDA0003039027340000051
In the formula: pEB，maxThe maximum thermal output of the electric boiler; etaEBThe electric heat conversion efficiency of the electric boiler is obtained;
Figure BDA0003039027340000052
for inputting electric power to the electric boiler.
(3.2.2) energy storage System restraint
(3.2.2.1) energy storage cell restraint:
Figure BDA0003039027340000053
Figure BDA0003039027340000054
Figure BDA0003039027340000055
Figure BDA0003039027340000056
in the formula (I), the compound is shown in the specification,
Figure BDA0003039027340000057
representing the state of charge of the energy storage battery at the tth scheduling hour of the sth typical day; etae,C、ηe,FRespectively representing the charge and discharge efficiency of the energy storage battery; deltaeRepresenting the self-discharge efficiency of the energy storage battery;
Figure BDA0003039027340000058
the charge state upper and lower limits of the energy storage battery are set;
Figure BDA0003039027340000059
the charging and discharging power in the period of the tth scheduling hour of the sth typical day cannot be charged and discharged simultaneously in the same period, and the product of the charging and discharging power and the discharging power is 0; Δ t represents a time interval.
(3.2.2.2) gas storage system constraint:
Figure BDA00030390273400000510
Figure BDA00030390273400000511
Figure BDA00030390273400000512
Figure BDA0003039027340000061
Figure BDA0003039027340000062
Figure BDA0003039027340000063
Figure BDA0003039027340000064
in the formula (I), the compound is shown in the specification,
Figure BDA0003039027340000065
representing the charge energy state of the gas storage system at the tth scheduling hour of the sth typical day; etag,C、ηg,FRespectively representing the charge and discharge efficiency of the energy storage battery; deltagThe gas consumption efficiency of the gas storage system is shown;
Figure BDA0003039027340000066
the upper and lower limits of the charge energy state of the gas storage system;
Figure BDA0003039027340000067
representing the charge energy state of the gas storage system at the end of the t-1 time period of the s-th typical day;
Figure BDA0003039027340000068
the gas storage and gas consumption power of the time interval representing the t scheduled hour of the s typical day; etaP2GThe electrical gas transfer efficiency of the P2G equipment is improved;
Figure BDA0003039027340000069
the electrical power input for the P2G device.
Further, the SOC of the last period of the multi-energy storage system is equal to the SOC of the first period for each typical day:
Figure BDA00030390273400000610
Figure BDA00030390273400000611
further, in the step (4), the optimal configuration model established in the step (3) is solved by using CPLEX. Wherein, for the condition that the product of [0, 1] continuous variable and [0, M ] continuous variable appears in the model, the product is linearized by adopting a relaxation method to obtain a linear programming model with the following form:
obj.min f(x)
s.t.Aeqx＝beq Ax≤b
where x is the control and state variables and f (x) is the planned total cost objective function. A. theeqFor equality-constrained independent variable coefficients, beqIs a constant in the equality constraint; a is an independent variable coefficient in an inequality constraint, and b is a constant in the inequality constraint.
Further, the control variable and the state variable x comprise rated power and capacity of the energy storage device, output of the device in each scheduling period, system electricity and gas purchasing amount, a shunting coefficient and the like.
The invention has the beneficial effects that:
(1) the planning and construction of the multi-energy storage system in the comprehensive energy system can influence the total cost of the whole system, and the method can increase the system income and reduce the total cost of the system by selecting more reasonable energy storage system configuration;
(2) the planning construction of the multi-energy storage system is beneficial to electric energy substitution, and the multi-energy storage system with certain configuration can realize complete electric energy substitution.
Detailed Description
The invention relates to a configuration method of an electricity-gas multi-energy storage system considering user energy uncertainty, which researches the configuration of the electricity-gas multi-energy storage system in a regional comprehensive energy system and aims to further establish the relation between the electricity-gas systems through the electricity-gas multi-energy storage system. Firstly, establishing a comprehensive energy network model containing an electricity-gas multi-energy storage system; then, the influence of different load characteristics and uncertainty of user energy types on the configuration of the energy storage system is analyzed; on the basis, with the economy as a target, an electricity-gas multi-energy storage system optimization configuration model containing an energy storage battery, P2G equipment, gas storage equipment, a gas transmission pipeline and other equipment is established; finally, it is solved by CPLEX. The method comprises the following specific steps:
(1) establishing a regional comprehensive energy system model containing an electricity-gas multi-energy storage system; the method specifically comprises the following steps:
and (1.1) establishing a physical model of the regional comprehensive energy system based on the electricity-gas-containing multi-energy storage system. The multifunctional storage system comprises an energy storage battery (Bat), a P2G device (power to gas, electricity to gas), a gas storage device (GS), and input and output pipelines of the gas storage device. The loads are divided into electrical and thermal loads, and other devices include Gas Turbines (GT), Wind Turbines (WT), gas boilers (GF), and Electric Boilers (EB). The energy conversion devices include P2G, GF, GT, EB.
(1.2) establishing a mathematical model of a regional comprehensive energy system based on the electricity-gas containing multi-energy storage system; the method specifically comprises the following steps:
(1.2.1) external energy injection: injection power of distribution network
Figure BDA0003039027340000071
And net injection power
Figure BDA0003039027340000072
(1.2.2) electric load
Figure BDA0003039027340000073
Power generated by fanWTEnergy storage battery output PBatPart for power purchasing of distribution network
Figure BDA0003039027340000074
And the output P of the gas turbineGTSupplying:
Figure BDA0003039027340000075
wherein, mu and (1-mu) respectively represent the shunt coefficients of the power for the P2G equipment and the direct power supply, and the sum of the shunt coefficients and the direct power supply is 1; λ and (1- λ) represent the split coefficients of natural gas input to the gas turbine and the gas boiler, the sum of which is 1; etaP2G、ηGF、ηGTThe conversion efficiencies of the P2G plant, gas boiler, gas turbine, and electric boiler, respectively.
(1.2.3) Heat load
Figure BDA0003039027340000076
Supplied by a gas boiler:
Figure BDA0003039027340000077
wherein, PGSOutputting power to the gas storage device. In particular, the electric boiler can also be supplied with a thermal load, which the model of the invention deals with as an electrical load.
(1.2.4) Power P of P2G deviceP2GThe power of the natural gas is converted from the electric power, the output of the P2G equipment directly enters a gas storage system through a gas transmission pipeline, and the load is supplied from the gas storage system through the gas transmission pipeline when needed:
Figure BDA0003039027340000081
(1.2.5) gas turbine gas source is gas storage device output PGSPart of the inputs to the air grid:
Figure BDA0003039027340000082
wherein eta isGSThe conversion efficiency of the gas storage equipment.
(2) Analyzing the influence of different load characteristics and uncertainty of user energy types on the configuration of the energy storage system and adjusting the load; the method specifically comprises the following steps:
(2.1) determining the supply sources of different loads, for example, the supply of heat load can be selected from an electric boiler or a gas boiler.
(2.2) determining the proportion of the selectable load.
The invention mainly aims at the uncertainty of selecting different heating equipment according to different preferences of users, and a certain proportion of heat loads are used as selectable supply loads. In the invention, part of the selective load is powered by a gas boiler, and part of the selective load is powered by an electric boiler and is treated as an electric load. The load type of each time period is distributed with a proportional load uniform distribution as follows:
Figure BDA0003039027340000083
Figure BDA0003039027340000084
in the formula, Pran.eFor selectable electrical load portions of the load, P[0,1]Is at [0, 1]]Probability of medium uniform distribution, ηhTo select the ratio of load to thermal load, Pran.hThe portion of the load that remains as a thermal load is selected.
(3) Establishing an electricity-gas multi-energy storage system optimization configuration model containing an energy storage battery, P2G equipment, gas storage equipment and a gas transmission pipeline by taking economy as a target; the method comprises the following steps:
(3.1) establishing an objective function
In the integrated energy system that has been built, the power rating and capacity of the multi-energy storage system are planned to minimize its total cost over the life cycle. Meanwhile, the time value of capital is considered, and all the cost is reduced to the equal-year value. The planned objective function can be expressed as:
min C＝kpaIC+OC+FC
wherein C is the total cost converted to annuity; IC is the initial investment cost; OC is the annual operating cost; FC is a fixed cost and a fixed value, and mainly refers to annual maintenance cost; k is a radical ofpaWhen the annual interest rate is r and the energy storage life cycle is y years, the expression is as follows:
Figure BDA0003039027340000091
(3.1.1) investment cost
As other equipment is built, the investment plan of multi-energy storage in the comprehensive energy network mainly comprises two parts of an energy storage battery and a gas storage device:
Figure BDA0003039027340000092
in the formula:
Figure BDA0003039027340000093
respectively representing the maximum power and the maximum capacity of the storage battery;
Figure BDA0003039027340000094
represents the maximum power of the P2G device;
Figure BDA0003039027340000095
indicating the maximum capacity of the gas storage device;
Figure BDA0003039027340000096
respectively representing the maximum power of the input and output gas storage devices; among them, the natural gas produced by P2G equipment is directly transferred into gas storage device, so it is approximately considered
Figure BDA0003039027340000097
k1、k2Respectively representing the unit power investment coefficient and the unit capacity investment coefficient of the storage battery; k is a radical of3Representing the specific power investment coefficient of the P2G equipment; k is a radical of4Representing the unit capacity investment coefficient of the gas storage device; k is a radical of5The unit power investment coefficient of the gas transmission pipeline is shown.
(3.1.2) running cost
In the comprehensive energy network, the operation cost refers to the electricity purchasing cost from the main network and the gas purchasing cost from the gas network, and the expression of the operation cost is as follows:
Figure BDA0003039027340000098
wherein S, T represents typical days and scheduled hours of the day, respectively; dsRepresents the total number of days for a typical day s;
Figure BDA0003039027340000099
for the t-th toneThe electricity purchase price in the hours;
Figure BDA00030390273400000910
representing the purchased electric power of the t scheduled hour on the s typical day; lambda [ alpha ]gThe unit of the unit is Yuan/m and represents the unified price of the natural gas network3(ii) a r represents the calorific value coefficient of combustion of natural gas in kW/m3；
Figure BDA00030390273400000911
And scheduling the purchased gas power of the hour for the tth typical day.
(3.2) constraint conditions: the built model is additionally provided with gas turbine output constraint, gas boiler constraint, electric boiler constraint, energy storage battery constraint, gas storage constraint and the like; the method specifically comprises the following steps:
(3.2.1) device constraints:
(3.2.1.1) gas turbine output constraint
0≤PGT≤PGT，max
Figure BDA0003039027340000101
In the formula: pGT，maxIs the maximum output of the gas turbine; etaGTThe gas-electricity conversion efficiency of the gas turbine is obtained;
Figure BDA0003039027340000102
for inputting gas turbine gas power.
(3.2.1.2) gas boiler constraint
0≤PGF≤PGF，max
Figure BDA0003039027340000103
In the formula: pGF，maxThe maximum thermal output of the gas boiler; etaGFThe gas heat conversion efficiency of the gas boiler is obtained;
Figure BDA0003039027340000104
for inputting the gas power of the gas boiler.
(3.2.1.3) electric boiler restraint
0≤PEB≤PEB，max
Figure BDA0003039027340000105
In the formula: pEB，maxThe maximum thermal output of the electric boiler; etaEBThe electric heat conversion efficiency of the electric boiler is obtained;
Figure BDA0003039027340000106
for inputting electric power to the electric boiler.
(3.2.2) energy storage System restraint
(3.2.2.1) energy storage cell restraint:
Figure BDA0003039027340000107
Figure BDA0003039027340000108
Figure BDA0003039027340000109
Figure BDA0003039027340000111
in the formula (I), the compound is shown in the specification,
Figure BDA0003039027340000112
representing the state of charge of the energy storage battery at the tth scheduling hour of the sth typical day; etae,C、ηe,FRespectively representing the charge and discharge efficiency of the energy storage battery; deltaeRepresenting the self-discharge efficiency of the energy storage battery;
Figure BDA0003039027340000113
the charge state upper and lower limits of the energy storage battery are set;
Figure BDA0003039027340000114
the charging and discharging power in the period of the tth scheduling hour of the sth typical day cannot be charged and discharged simultaneously in the same period, and the product of the charging and discharging power and the discharging power is 0; at represents the time interval, and the time-of-use electricity price is adopted in the invention, namely, the at is taken as 1 hour.
(3.2.2.2) gas storage system constraint:
Figure BDA0003039027340000115
Figure BDA0003039027340000116
Figure BDA0003039027340000117
Figure BDA0003039027340000118
Figure BDA0003039027340000119
Figure BDA00030390273400001110
Figure BDA00030390273400001111
in the formula (I), the compound is shown in the specification,
Figure BDA00030390273400001112
storage representing the t-th scheduled hour of the s-th typical dayThe charge energy state of the gas system; etag,C、ηg,FRespectively representing the charge and discharge efficiency of the energy storage battery; deltagThe gas consumption efficiency of the gas storage system is shown;
Figure BDA00030390273400001113
the upper and lower limits of the charge energy state of the gas storage system;
Figure BDA00030390273400001114
representing the charge energy state of the gas storage system at the end of the t-1 time period of the s-th typical day;
Figure BDA00030390273400001115
the gas storage and gas consumption power of the time interval representing the t scheduled hour of the s typical day are worth explaining that the gas storage and the gas consumption are respectively performed through different gas transmission pipelines, so that the gas storage and the gas consumption can be performed simultaneously, and the gas storage power is approximately equal to the output power of the P2G device; etaP2GThe electrical gas transfer efficiency of the P2G equipment is improved;
Figure BDA0003039027340000121
electrical power input for the P2G device; and in order not to generate errors, the SOC of the last period of the multi-energy storage system is specified to be equal to the SOC of the first period for each typical day:
Figure BDA0003039027340000122
Figure BDA0003039027340000123
(4) calling CPLEX in Matlab to solve.
For the occurrence of [0, 1 in the model]Continuous variable x1And [0, M]Continuous variable y1In the case of the product, it is linearized by a relaxation method (second-order cone relaxation method); wherein, [0, 1]]Continuous variable x1Refer to the shunt coefficients μ and λ, [0, M]Continuous variable y1Refer to in the partial equality and inequality constraints (equations (6) and (7))The power of a device multiplied by μ and λ, both variables, contribute to model non-linearity; m is a positive real number. After a T variable is introduced, a CPLEX solver can be called in Matlab to solve the optimized configuration model established in the step (3) after the nonlinear part is subjected to linearization processing through linearization processing. The method specifically comprises the following steps:
introducing a new variable T, let
T＝x1y1 x1∈[0，1]y1∈[0，M]
The linearizable process is:
T-0·x1≥0
T-M·x1＜0
T-y+0·(1-x1)≤0
T-y+M·(1-x1)≥0
in order to clearly describe the flow of the algorithm, the model is unified and compact to obtain a linear programming model in the following form:
obj.min f(x) (5)
s.t.Aeqx＝beq (6)
Ax≤b (7)
wherein, the formula (5) is a planning total cost objective function; x is a control variable and a state variable, and comprises the rated power and capacity of the energy storage equipment, the output of the equipment in each scheduling period, the electricity and gas purchasing quantity of the system, the shunt coefficient and the like; the equations (6) and (7) are respectively linear equality constraint and inequality constraint, and comprise balance of electricity and gas output, equipment output constraint, energy conservation of energy storage equipment and the like; a. theeqFor equality-constrained independent variable coefficients, beqIs a constant in the equality constraint; a is an independent variable coefficient in an inequality constraint, and b is a constant in the inequality constraint.

Claims (10)

1. A method of configuring an electric-gas multi-energy storage system in consideration of user energy uncertainty, comprising the steps of:
(1) establishing a regional comprehensive energy system model containing an electricity-gas multi-energy storage system;
(2) analyzing the influence of different load characteristics and uncertainty of user energy types on the configuration of the energy storage system and adjusting the load:
and (2.1) determining different supply sources of the loads.
(2.2) determining the proportion of the selectable load.
(3) With the economy as a target, an electricity-gas multi-energy storage system optimization configuration model containing an energy storage battery, P2G equipment, gas storage equipment and a gas transmission pipeline is established:
and (3.1) planning the rated power and the capacity of the multi-energy storage system in the built integrated energy system to minimize the total cost in the whole life cycle. Meanwhile, the time value of capital is considered, and all the cost is reduced to the equal-year value.
And (3.2) adding gas turbine output constraint, gas boiler constraint, electric boiler constraint, energy storage battery constraint and gas storage constraint in the established model.
(4) And (4) optimizing and solving the model established in the step (3).
2. The method for configuring an electro-pneumatic multi-energy storage system in consideration of user energy uncertainty as claimed in claim 1, wherein the step (1) is embodied as:
and (1.1) establishing a physical model of the regional comprehensive energy system based on the electricity-gas multi-energy storage system. The multi-energy storage system comprises an energy storage battery, a P2G device, a gas storage device and input and output pipelines of the gas storage device. The loads are divided into electrical and thermal loads, and other devices are gas turbines, wind generators, gas boilers and electric boilers.
And (1.2) establishing a mathematical model of the regional comprehensive energy system based on the electricity-gas multi-energy storage system. The method specifically comprises the following steps:
(1.2.1) external energy injection: injection power of distribution network
Figure FDA0003039027330000011
And net injection power
Figure FDA0003039027330000012
(1.2.2) electric load
Figure FDA0003039027330000013
Power generated by fanWTEnergy storage battery output PBatPart for power purchasing of distribution network
Figure FDA0003039027330000014
And the output P of the gas turbineGTSupplying:
Figure FDA0003039027330000015
wherein, mu and (1-mu) respectively represent the shunt coefficients of the power for the P2G equipment and the direct power supply; λ and (1- λ) represent the split coefficients of natural gas input to the gas turbine and the gas boiler. EtaP2G、ηGF、ηGTThe conversion efficiencies of the P2G plant, gas boiler, gas turbine, and electric boiler, respectively.
(1.2.3) Heat load
Figure FDA0003039027330000021
Supplied by a gas boiler:
Figure FDA0003039027330000022
wherein, PGSOutputting power to the gas storage device.
(1.2.4) Power P of P2G deviceP2GReferring to the conversion of power into natural gas power, the P2G equipment, as part of the gas storage device, directly enters the gas storage system through the gas transmission pipeline, and supplies load from the gas storage system through the gas transmission pipeline when necessary:
Figure FDA0003039027330000023
(1.2.5) the gas source of the gas turbine is a part of the output of the gas storage device and the input of the gas network:
Figure FDA0003039027330000024
wherein eta isGSThe conversion efficiency of the gas storage equipment.
3. The method for configuring an electric-gas multi energy storage system in consideration of uncertainty of user energy according to claim 1, wherein in the step (2.2), the alternative load is partially powered by the gas boiler and partially powered by the electric boiler to be treated as the electric load. The load type of each time period is distributed with a proportional load uniform distribution.
4. The method for configuring an electric-gas multi-energy storage system taking account of the uncertainty of the user's energy according to claim 1, characterized in that the step (3.1) is embodied as:
(3.1) the objective function of the plan can be expressed as:
minC＝kpaIC+OC+FC
wherein C is the total cost converted to annuity; IC is the initial investment cost; OC is the annual operating cost; FC is a fixed cost and a fixed value, and mainly refers to annual maintenance cost; k is a radical ofpaWhen the annual interest rate is r and the energy storage life cycle is y years, the expression is as follows:
Figure FDA0003039027330000025
5. the method for configuring an electro-pneumatic multi energy storage system considering uncertainty of user energy according to claim 4, wherein in the step (3.1):
(3.1.1) the investment cost mainly comprises two parts of an energy storage battery and a gas storage device:
Figure FDA0003039027330000026
in the formula:
Figure FDA0003039027330000031
respectively representing the maximum power and the maximum capacity of the storage battery;
Figure FDA0003039027330000032
represents the maximum power of the P2G device;
Figure FDA0003039027330000033
indicating the maximum capacity of the gas storage device;
Figure FDA0003039027330000034
respectively representing the maximum power of the input and output gas storage devices; k is a radical of1、k2Respectively representing the unit power investment coefficient and the unit capacity investment coefficient of the storage battery; k is a radical of3Representing the specific power investment coefficient of the P2G equipment; k is a radical of4Representing the unit capacity investment coefficient of the gas storage device; k is a radical of5The unit power investment coefficient of the gas transmission pipeline is shown.
(3.1.2) operating costs refer to electricity purchase from the main grid and gas purchase from the gas grid, and are expressed as follows:
Figure FDA0003039027330000035
wherein S, T represents typical days and scheduled hours of the day, respectively; dsRepresents the total number of days for a typical day s;
Figure FDA0003039027330000036
the electricity purchase price for the t-th scheduled hour;
Figure FDA0003039027330000037
representing the purchased electric power of the t scheduled hour on the s typical day; lambda [ alpha ]gRepresenting a uniform price of the natural gas network; r represents the calorific value coefficient of natural gas combustion;
Figure FDA0003039027330000038
and scheduling the purchased gas power of the hour for the tth typical day.
6. The method of claim 5, wherein the natural gas produced by the P2G facility is directly introduced into the gas storage facility, so that the natural gas is approximately considered as being delivered to the gas storage facility
Figure FDA0003039027330000039
7. The method for configuring an electro-pneumatic multi energy storage system considering uncertainty of user energy according to claim 4, wherein in the step (3.2):
(3.2.1) device constraints
(3.2.1.1) gas turbine output constraint
0≤PGT≤PGT，max
Figure FDA00030390273300000310
In the formula: pGT，maxIs the maximum output of the gas turbine; etaGTThe gas-electricity conversion efficiency of the gas turbine is obtained;
Figure FDA00030390273300000311
for inputting gas turbine gas power.
(3.2.1.2) gas boiler constraint
0≤PGF≤PGF，max
Figure FDA0003039027330000041
In the formula: pGF，maxThe maximum thermal output of the gas boiler; etaGFThe gas heat conversion efficiency of the gas boiler is obtained;
Figure FDA0003039027330000042
for inputting the gas power of the gas boiler.
(3.2.1.3) electric boiler restraint
0≤PEB≤PEB，max
Figure FDA0003039027330000043
In the formula: pEB，maxThe maximum thermal output of the electric boiler; etaEBThe electric heat conversion efficiency of the electric boiler is obtained;
Figure FDA0003039027330000044
for inputting electric power to the electric boiler.
(3.2.2) energy storage System restraint
(3.2.2.1) energy storage cell restraint:
Figure FDA0003039027330000045
Figure FDA0003039027330000046
Figure FDA0003039027330000047
Figure FDA0003039027330000048
in the formula (I), the compound is shown in the specification,
Figure FDA0003039027330000049
representing the state of charge of the energy storage battery at the tth scheduling hour of the sth typical day; etae,C、ηe,FRespectively representing the charge and discharge efficiency of the energy storage battery; deltaeRepresenting the self-discharge efficiency of the energy storage battery;
Figure FDA00030390273300000410
the charge state upper and lower limits of the energy storage battery are set;
Figure FDA00030390273300000411
the charging and discharging power in the period of the tth scheduling hour of the sth typical day cannot be charged and discharged simultaneously in the same period, and the product of the charging and discharging power and the discharging power is 0; Δ t represents a time interval.
(3.2.2.2) gas storage system constraint:
Figure FDA00030390273300000412
Figure FDA0003039027330000051
Figure FDA0003039027330000052
Figure FDA0003039027330000053
Figure FDA0003039027330000054
Figure FDA0003039027330000055
Figure FDA0003039027330000056
in the formula (I), the compound is shown in the specification,
Figure FDA0003039027330000057
representing the charge energy state of the gas storage system at the tth scheduling hour of the sth typical day; etag,C、ηg,FRespectively representing the charge and discharge efficiency of the energy storage battery; deltagThe gas consumption efficiency of the gas storage system is shown;
Figure FDA0003039027330000058
the upper and lower limits of the charge energy state of the gas storage system;
Figure FDA0003039027330000059
representing the charge energy state of the gas storage system at the end of the t-1 time period of the s-th typical day;
Figure FDA00030390273300000510
the gas storage and gas consumption power of the time interval representing the t scheduled hour of the s typical day; etaP2GThe electrical gas transfer efficiency of the P2G equipment is improved;
Figure FDA00030390273300000511
the electrical power input for the P2G device.
8. The method of configuring an electric-to-gas multi-energy storage system taking into account user energy uncertainty as claimed in claim 6, wherein the SOC of the last period of the multi-energy storage system is equal to the SOC of the first period every typical day:
Figure FDA00030390273300000512
Figure FDA00030390273300000513
9. the method for configuring an electro-pneumatic multi-energy storage system in consideration of user energy uncertainty as claimed in claim 1, wherein in the step (4), the optimized configuration model established in the step (3) is solved using CPLEX. Wherein, for the condition that the product of [0, 1] continuous variable and [0, M ] continuous variable appears in the model, the product is linearized by adopting a relaxation method to obtain a linear programming model with the following form:
obj.min f(x)
s.t.Aeqx＝beq Ax≤b
where x is the control and state variables and f (x) is the planned total cost objective function. A. theeqFor equality-constrained independent variable coefficients, beqIs a constant in the equality constraint; a is an independent variable coefficient in an inequality constraint, and b is a constant in the inequality constraint.
10. The method as claimed in claim 9, wherein the control variables and the state variables x include rated power and capacity of the energy storage device, capacity of the device at each scheduling period, power and gas purchasing amount of the system, and split coefficient.
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