CN109149571B - Energy storage optimal configuration method considering characteristics of system gas and thermal power generating unit - Google Patents

Energy storage optimal configuration method considering characteristics of system gas and thermal power generating unit Download PDF

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CN109149571B
CN109149571B CN201811106000.4A CN201811106000A CN109149571B CN 109149571 B CN109149571 B CN 109149571B CN 201811106000 A CN201811106000 A CN 201811106000A CN 109149571 B CN109149571 B CN 109149571B
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energy storage
power
thermal power
load
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CN109149571A (en
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张成炜
林瑞宗
彭传相
陈卓琳
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State Grid Fujian Electric Power Co Ltd
Economic and Technological Research Institute of State Grid Fujian Electric Power Co Ltd
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State Grid Fujian Electric Power Co Ltd
Economic and Technological Research Institute of State Grid Fujian Electric Power Co Ltd
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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
    • 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
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/003—Load forecast, e.g. methods or systems for forecasting future load demand
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/70—Wind energy
    • Y02E10/76—Power conversion electric or electronic aspects

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Abstract

The invention relates to an energy storage optimal configuration method considering system gas and thermal power generating units. The method comprises the following steps: firstly, according to historical data, the output of a new energy generator set is predicted, a typical scene set of the output of the new energy generator set is constructed, and a load scene set of a power system is constructed in combination with load fluctuation characteristics; analyzing the operating characteristics of the start-stop stages of the gas generating unit and the thermal power generating unit, establishing a state transfer equation set, determining state transfer conditions, establishing a state transfer model for the start-stop stage operation of the gas generating unit and the thermal power generating unit, and realizing the transfer and switching between different states in the start-stop stage operation process of the gas generating unit and the thermal power generating unit; according to the system and the operation parameters, on the basis of considering a wind power consumption target, constructing an energy storage optimization configuration model considering the climbing capacity and multi-stage state transfer of a gas turbine unit and a thermal power unit by taking the minimum related investment and total operation cost as a target; and solving the energy storage optimization configuration problem of the power system to obtain an energy storage optimization configuration scheme of the power system.

Description

Energy storage optimal configuration method considering characteristics of system gas and thermal power generating unit
Technical Field
The invention belongs to the technical field of power system planning, and particularly relates to an energy storage optimal configuration method considering characteristics of system gas and thermal power generating units.
Background
Environmental issues arising from extensive economic development models have caused renewable energy sources to be of great interest for their green environmental friendliness (e.g., wind energy). The access of large-scale clean energy tends to improve the environment and simultaneously brings new challenges to the operation of an electric power system, for example, the peak regulation pressure of the electric power system is increased day by day, the system peak regulation becomes one of new problems of the dispatching operation of the electric power system, and the insufficient peak regulation capability becomes a main factor for restricting the consumption capability of the clean energy. On one hand, the power grid needs to have a more flexible operation mode, and the regulation capacity of the power system is improved; on the other hand, the volatility and intermittency of the renewable energy sources need to be fully considered in the planning process of the power system (especially flexible resources including energy storage), so that the power grid has the capability of actively accessing the clean energy sources.
Compared with the traditional operation mode, the power system needs more standby resources to deal with the uncertainty caused by the new energy access. At present, whether each resource in the system has the capability of receiving a system standby scheduling instruction in the running process is not considered when the power system solves the standby optimization problem. In order to solve the above problems, the operation characteristics of each resource of the system (for example, the start-stop characteristic and the climbing characteristic of the unit need to be considered, the limitation on the SOC range needs to be considered for energy storage, etc.) need to be fully considered, and a more refined operation model is further proposed.
Based on the method, the operation characteristics and the climbing capacity of the gas and thermal power generating units in the starting and stopping stages are comprehensively considered, and the energy storage optimization configuration method considering the climbing capacity and the multi-stage state transfer of the system gas and thermal power generating units is provided.
Disclosure of Invention
The invention aims to provide an energy storage optimal configuration method considering characteristics of system gas and a thermal power unit, which can represent mutual switching and transferring relations between states of the gas power unit and the thermal power unit during operation, and can represent power tracks and operation characteristics of the thermal power unit under different starting types in a differentiated mode. The standby problem of power system operation is considered simultaneously, and the condition of comprehensively considering energy storage and unit to provide rotation standby for the system together more accords with the actual operation condition, more accords with the actual condition, and the practicality is stronger simultaneously.
In order to achieve the purpose, the technical scheme of the invention is as follows: an energy storage optimal configuration method considering characteristics of system gas and thermal power generating units comprises the following steps,
s1, firstly, predicting the output of the new energy generator set according to historical data, constructing a typical scene set of the output of the new energy generator set, and constructing a load scene set of the power system by combining with the load fluctuation characteristic;
s2, analyzing the operation characteristics of the gas generating unit and the thermal power generating unit in the start-stop stage, establishing a state transfer equation set, determining state transfer conditions, establishing a state transfer model for the operation of the gas generating unit and the thermal power generating unit in the start-stop stage, and realizing the transfer and switching between different states in the operation process of the gas generating unit and the thermal power generating unit in the start-stop stage;
s3: according to the system and the operation parameters, on the basis of considering a wind power consumption target, constructing an energy storage optimization configuration model considering the climbing capacity and multi-stage state transfer of a gas turbine unit and a thermal power unit by taking the minimum related investment and total operation cost as a target;
s4: and solving the energy storage optimal configuration problem of the power system to obtain an energy storage optimal configuration scheme of the power system.
In an embodiment of the present invention, the step S1 is specifically implemented as follows:
uncertainty of wind power output and load mainly considers deviation of wind speed and load prediction, and respective deviation is considered to be normal load distribution; the actual values of the wind speed and the load can be represented after the predicted expected value and the predicted error; the form is as follows:
Figure GDA0001831202190000021
Figure GDA0001831202190000022
in the formula: v (t), PL(t) true values for wind speed and load, respectively;
Figure GDA0001831202190000023
respectively predicting expected values for wind speed and load; e.g. of the typev(t)、eL(t) wind speed and load prediction errors, respectively, both obeying probability distribution;
the wind power output can be calculated according to the following formula:
Figure GDA0001831202190000024
in the formula: p (v) is the output of the wind turbine generator at the wind speed v; v is the wind speed; v. ofinCutting wind speed for the wind driven generator; v. ofrThe rated power wind speed of the wind driven generator; v. ofoutCutting wind speed for the wind driven generator; (v) wind speed vinTo vrIn time, the function of the relation between the output power of the wind driven generator and the wind speed; pmaxThe rated power of the wind turbine generator is set;
and combining the wind power output and the load generated by the simulation to generate a power system operation scene set.
In an embodiment of the present invention, the step S2 is specifically implemented as follows:
1) analyzing the operating characteristics of the thermal power generating unit in the starting and stopping stage: the starting and stopping processes of the thermal power generating unit need to go through the load increasing and load reducing processes;
2) modeling the state of the thermal power generating unit, determining the number of running states, and configuring a 0-1 variable representing the state: according to the operating state characteristics of the thermal power generating unit in the starting and stopping stage, 4 variables 0-1 are introduced to represent the operating state of the unit: u. ofi(t)、
Figure GDA0001831202190000025
Wherein: u. ofi(t) indicates whether the unit i is in an operating and shutdown state at the moment t;
Figure GDA0001831202190000026
indicating whether the unit i is in a load-up state at the moment t;
Figure GDA0001831202190000027
indicating whether the unit n is in a scheduling receiving state at the moment t;
Figure GDA0001831202190000028
indicating whether the unit n is in a load reduction state at the moment t;
3) defining the state establishing and transferring condition of the thermal power generating unit, and establishing a state transferring equation set: according to the operating state characteristics of the thermal power generating unit in the starting and stopping stage, the following state transfer equation set is introduced to represent the switching of the thermal power generating unit among the operating states;
Figure GDA0001831202190000031
yi(t)-zi(t)＝ui(t) (5)
Figure GDA0001831202190000032
Figure GDA0001831202190000033
Figure GDA0001831202190000034
yi(t)+zi(t)≤1 (9)
Figure GDA0001831202190000035
Figure GDA0001831202190000036
Figure GDA0001831202190000037
Figure GDA0001831202190000038
Figure GDA0001831202190000039
Figure GDA00018312021900000310
Figure GDA00018312021900000311
the formula (4) ensures that the unit can only be in a unique state each time; the formula (5) to the formula (12) represent a state transition model and logic constraints of the unit operation state; equation (13) -equation (16) represent a constraint relationship from one state to another state at the time of state transition; the variables in the above formulae are all variables from 0 to 1, wherein: y isi(t)、zi(t) is a variable for controlling the starting and stopping states of the unit;
Figure GDA00018312021900000312
the variable is a variable for controlling the unit to enter and jump out of the load-lifting state;
Figure GDA00018312021900000313
the variable is a variable for controlling the unit to enter and jump out of a schedulable state;
Figure GDA00018312021900000314
the variable is used for controlling the unit to enter and jump out of the load reduction state;
Figure GDA00018312021900000315
Figure GDA00018312021900000316
wherein M represents a large positive number, pi(t) is the output of the unit i at the moment t;the formula (17) -formula (18) shows that the power output of the thermal power generating unit just after entering the schedulable state and the load reduction state must be PiThe connection among the states of the thermal power generating unit is ensured, and meanwhile, the two formulas are only suitable for the thermal power generating unit and are not suitable for a quick start-stop unit comprising a gas unit;
Δpi(t)＝pi(t)-pi(t-1) (19)
Figure GDA0001831202190000041
Figure GDA0001831202190000042
the output variation delta p of the unit under the normal operation state of the systems of the formula (19) and the formula (21) respectivelyi(t) the amount of change in output when the upper spinning reserve is called
Figure GDA0001831202190000043
And the amount of change in output when the lower spinning reserve is called
Figure GDA0001831202190000044
Wherein the content of the first and second substances,
Figure GDA0001831202190000045
and
Figure GDA0001831202190000046
is the value of upper rotation standby and lower rotation standby provided by the unit;
4) writing a thermal power unit operation characteristic constraint equation in a column mode, and perfecting a thermal power unit start-stop stage model:
Figure GDA0001831202190000047
wherein, Rui(t) and Rdi(t) is the climbing and descending capacity of the unit at the moment t and can be communicatedCalculating by the following formula;
Figure GDA0001831202190000048
Figure GDA0001831202190000049
wherein, IthermalIs a thermal power generating unit set; i isgasIs a gas turbine set; RU (RU)iAnd RDiThe up-climbing and down-climbing capacities of the unit under the adjustable state are achieved;
Figure GDA00018312021900000410
the climbing capacity and the climbing capacity of the unit in the load ascending state and the load descending state are calculated according to the following formula;
Figure GDA00018312021900000411
wherein the content of the first and second substances,
Figure GDA00018312021900000412
and
Figure GDA00018312021900000413
is the duration of the load up and load down;
Figure GDA00018312021900000414
Figure GDA00018312021900000415
Figure GDA00018312021900000416
Figure GDA00018312021900000417
equation (26) to equation (28) are respectively the maximum and minimum output of the time group when the upper spinning standby is called and the lower spinning standby is called in the normal running state of the system; equation (29) is the constraint of the maximum minimum up-down rotation reserve capacity of the unit;
the minimum start-stop time constraint of the unit is shown as follows:
Figure GDA0001831202190000051
wherein the content of the first and second substances,
Figure GDA0001831202190000052
and
Figure GDA0001831202190000053
respectively starting and stopping time;
Figure GDA0001831202190000054
and
Figure GDA0001831202190000055
respectively minimum startup and minimum shutdown time;
under the condition of the output curve of the piecewise linearization unit, the generated electricity quantity e of the uniti(t) can be calculated from formula (31);
Figure GDA0001831202190000056
in an embodiment of the present invention, the step S3 is specifically implemented as follows:
1) an energy storage optimization configuration model objective function considering the climbing capacity and the multi-stage state transition of the gas power unit and the thermal power unit is constructed as follows:
Figure GDA0001831202190000057
in the formula: n is a power system network topology node set; t is a scheduling time interval set; i is a gas and thermal power generating unit set, I belongs to I; j is a wind generating set; s is an electric energy storage equipment set, and S belongs to S; e, wind power output scene set;
Figure GDA0001831202190000058
Figure GDA0001831202190000059
generating cost, starting cost, stopping cost and standby service cost of the gas and thermal power generating unit i at the moment t are respectively set;
Figure GDA00018312021900000510
investment costs for electrical energy storage devices;
Figure GDA00018312021900000511
investment cost for the transmission line; pr (total reflection)εThe probability of occurrence of the wind power output scene epsilon is determined; VOLL and λwLoad loss cost and unit wind abandon punishment cost for power system scheduling; the last two parts of the above equation are expectations for conditional risk values for upper and lower spares;
the power generation cost, the starting cost, the shutdown cost and the standby service cost of the gas and thermal power generating unit i at the moment t can be calculated by the following formulas (33) -35; the investment reserve of the electric energy storage equipment and the transmission line can be calculated according to an equation (36) and an equation (37);
Figure GDA00018312021900000512
Figure GDA0001831202190000061
Figure GDA0001831202190000062
Figure GDA0001831202190000063
Figure GDA0001831202190000064
in the above formulas:
Figure GDA0001831202190000065
respectively the no-load cost and the linear power generation cost of the unit i;
Figure GDA0001831202190000066
respectively starting, stopping, up-standby and down-standby service fees of the unit at a single time or unit capacity; c. CmAnd cpThe investment cost required for allocating unit capacity and unit power electric energy storage equipment respectively; l is a set of transmission lines; c. ClineInvestment costs required to build a unit capacity line; plIs the capacity expansion requirement of line l;
2) the method comprises the following steps of constructing energy storage optimization configuration model constraint conditions considering the climbing capacity and multi-stage state transition of a gas power unit and a thermal power unit as follows:
2.1) Power System operating characteristic constraints
The power system operation characteristic constraints comprise power balance, direct current power flow constraint, transmission line capacity constraint and power system standby requirement constraint;
the power balance constraint can be expressed in the form:
Figure GDA0001831202190000067
in the formula: n is a power system network topology node set;
Figure GDA0001831202190000068
the node n is a set of the units;
Figure GDA0001831202190000069
the wind generating set is a set of wind generating sets at the node n;
Figure GDA00018312021900000612
is a set of electrical energy storage devices at node n; p is a radical ofi(t) is the output of the unit i at the moment t;
Figure GDA00018312021900000610
the scheduling value of the wind power plant j at the time t;
Figure GDA00018312021900000611
respectively charging and discharging power of the electric energy storage device s at the moment t; dn(t) is the load demand of the load node n at the time t;
secondly, direct current power flow constraint, a direct current power flow equation with network loss neglected is adopted, and a common expression of a direct current power flow model is as follows:
Figure GDA0001831202190000071
in the formula: b isn,kAn imaginary part of an admittance matrix of the grid node; delta thetaε,n,k(t) is the voltage phase angle difference of the system node n and the node k at the time t; thetaε,n(t)、θε,k(t) the voltage phase angles of the system node n and the node k at the moment t respectively; x is the number ofn,kIs the line impedance of node n and node k;
third, the transmission line capacity constraint can be expressed as follows:
Figure GDA0001831202190000072
in the formula:
Figure GDA0001831202190000073
maximum transmission capacity of a line connecting a system node n and a node k;
fourthly, the standby demand of the power system is restricted: the expressions of equations (41) and (42) apply to different types of backup requirements of the power system:
Figure GDA0001831202190000074
Figure GDA0001831202190000075
in the formula: pr (-) is a probability function;
Figure GDA0001831202190000076
and
Figure GDA0001831202190000077
respectively providing upper standby values and lower standby values for the system according to the electric energy storage obtained by the wind power prediction and the load prediction errors;
Figure GDA0001831202190000078
and
Figure GDA0001831202190000079
the requirements of upper backup and lower backup of the power system can be estimated through wind power and load prediction errors; α and β are confidence levels that satisfy the upper and lower spares of the system, respectively;
2.2) Electrical energy storage device operating characteristic constraints
The electrical energy storage device operating characteristic constraints are as shown in equations (43) - (48):
Figure GDA00018312021900000710
Figure GDA00018312021900000711
Figure GDA00018312021900000712
Figure GDA00018312021900000713
Figure GDA00018312021900000714
Figure GDA0001831202190000081
equations (43) - (48) are energy constraints of the electrical energy storage device; es(t) is the electric energy stored by the electric energy storage device s at the moment t; deltasThe loss coefficient under self-discharge condition of the electrical energy storage device s;
Figure GDA0001831202190000082
the charge-discharge efficiency of the electrical energy storage device s, respectively;
Figure GDA0001831202190000083
γ srespectively representing the SOC upper limit coefficient and the SOC lower limit coefficient of the electric energy storage equipment s;
Figure GDA0001831202190000084
is the rated capacity of the electrical energy storage device s; equations (45) - (46) are the charge and discharge power constraints of the electrical energy storage device;
Figure GDA0001831202190000085
the maximum charging and discharging power of the electrical energy storage device s is respectively;
Figure GDA0001831202190000086
Figure GDA0001831202190000087
the charging and discharging working states of the electric energy storage equipment s are respectively 0-1 variable; equation (47) is the electrical energy storage device operating state constraint; formula (48) is that the electrical energy storage device is considered to be self-dischargingCharge-discharge balance constraint under electrical conditions;
2.3) energy storage Standby service Capacity
The energy storage backup service capacity needs to satisfy the following constraints:
Figure GDA0001831202190000088
Figure GDA0001831202190000089
Figure GDA00018312021900000810
Figure GDA00018312021900000811
Figure GDA00018312021900000812
in the formula:
Figure GDA00018312021900000813
and
Figure GDA00018312021900000814
respectively calling SOC values of upper standby time electric energy storage equipment and lower standby time electric energy storage equipment for the system;
2.4) wind generating set output restraint
The output of the wind generating set is restricted as follows:
Figure GDA00018312021900000815
in the formula:
Figure GDA00018312021900000816
is windThe output value of the electric field j at the moment t;
in an embodiment of the present invention, in step S4, the established energy storage optimization configuration method considering the climbing capability and the multi-stage state transition of the gas and thermal power generating units is linearized into a standard mixed integer linear programming model, and then the CPLEX is called by using the business software GAMS to facilitate the solution, so as to obtain the power system scheduling decision scheme.
Compared with the prior art, the invention has the following beneficial effects: the method provides a unified form, represents the mutual switching and transferring relation between the states of the gas power unit and the thermal power unit during operation, and simultaneously and differentially represents the power track and the operation characteristics of the thermal power unit under different starting types. Meanwhile, the problem of operation standby of the power system is considered, the situation that the stored energy and the unit provide rotation standby for the system together is comprehensively considered, the situation is more consistent with the actual operation situation and the actual situation, and meanwhile, the practicability is higher; the invention provides a multi-resource scheduling model of the power system, realizes multi-resource optimized scheduling of the power system, and effectively reduces waste of clean energy. Compared with the existing power system scheduling model or unit combination model, the method provided by the invention is more practical and more practical, improves the precision of the operation characteristic model of the thermal power unit in the power system scheduling analysis, provides an analysis tool for the power system to develop peak regulation resource optimization configuration decision, and has certain economic benefit and environmental benefit.
Drawings
FIG. 1 is a schematic diagram of a process flow framework of the method of the present invention.
Fig. 2 is a schematic diagram of the output trajectory of the gas turbine set in the start-stop stage.
Fig. 3 is a schematic diagram of the power output trajectory of the thermal power generating unit in the start-stop stage.
Fig. 4 is a modified PJM5 node system of the present invention.
FIG. 5 shows predicted values of wind power of each scene according to the present invention.
FIG. 6 illustrates system backup requirements for various scenarios of the present invention.
FIG. 7 is a predicted value of the load of the power system according to the present invention.
Detailed Description
The technical scheme of the invention is specifically explained below with reference to the accompanying drawings.
The invention provides an energy storage optimal configuration method considering the climbing capacity and multi-stage state transfer of a system gas and thermal power generating unit. The proposed method comprises several key steps, S1: firstly, according to historical data, the output of a new energy generator set is predicted, a typical scene set of the output of the new energy generator set (such as wind power generation) is constructed, and a load scene set of a power system is constructed by combining the load fluctuation characteristic; s2: analyzing the operating characteristics of the start-stop stages of the gas generating unit and the thermal power generating unit, establishing a state transfer equation set, determining state transfer conditions, establishing a state transfer model for the start-stop stage operation of the gas generating unit and the thermal power generating unit, and realizing the transfer and switching between different states in the start-stop stage operation process of the gas generating unit and the thermal power generating unit; s3: according to the system and the operation parameters, on the basis of considering a wind power consumption target, constructing an energy storage optimization configuration model considering the climbing capacity and multi-stage state transfer of a gas turbine unit and a thermal power unit by taking the minimum related investment and total operation cost as a target; s4: and solving the energy storage optimal configuration problem of the power system to obtain an energy storage optimal configuration scheme of the power system. The method is concretely realized as follows:
s1: constructing power system operation scene set
According to the wind power output and load related statistical data, fitting a distribution function, randomly simulating by adopting a Monte-Carlo simulation method to generate a corresponding wind power output sample and a power load time sequence sample of each node, and combining the two samples to generate a power system operation scene set. And if necessary, the scene reduction technology can be used for reducing the number of scenes, keeping typical scenes, reducing the operation complexity without lacking precision and improving the operation speed of solving the problem.
The uncertainty of the wind power output and the load mainly considers the deviation of wind speed and load prediction, and the deviation of the wind power output and the load is considered to be normal load distribution. The actual values of wind speed and load can be represented after the predicted expected value and the predicted error. The form is as follows:
Figure GDA0001831202190000101
Figure GDA0001831202190000102
in the formula: v (t), PL(t) true values for wind speed and load, respectively;
Figure GDA0001831202190000103
respectively predicting expected values for wind speed and load; e.g. of the typev(t)、eL(t) wind speed and load prediction errors, respectively, both obeying probability distribution;
the wind power output can be calculated according to the following formula:
Figure GDA0001831202190000104
in the formula: p (v) is the output of the wind turbine generator at the wind speed v; v is the wind speed; v. ofinCutting wind speed for the wind driven generator; v. ofrThe rated power wind speed of the wind driven generator; v. ofoutCutting wind speed for the wind driven generator; (v) wind speed vinTo vrIn time, the function of the relation between the output power of the wind driven generator and the wind speed; pmaxThe rated power of the wind turbine generator is set;
and combining the wind power output and the load generated by the simulation to generate a power system operation scene set.
S2: multi-stage state transition modeling for gas generating unit and thermal power generating unit
The step S2 can be specifically divided into the following sub-steps: 1) analyzing the operating characteristics of the thermal power generating unit in a starting and stopping stage; 2) modeling the state of the thermal power generating unit, determining the number of running states, and configuring 0-1 variable representing the state; 3) determining a state establishing and transferring condition of the thermal power generating unit, and establishing a state transferring equation set; 4) and writing an operating characteristic constraint equation of the thermal power unit in a row, and perfecting a start-stop stage model of the thermal power unit.
1) Thermal power generating unit start-stop stage operation characteristic analysis
In actual power system scheduling, the starting and stopping actions of the thermal power generating unit are not finished instantaneously, the thermal power generating unit meets a specific starting and stopping curve when being started and stopped, and the thermal power generating unit can still provide electric energy in the period. The start-stop process of a common thermal power generating unit needs to go through the load increasing and load reducing processes, as shown in fig. 2 and 3.
2) Thermal power generating unit state modeling
According to the operating state characteristics of the unit in the start-stop stage shown in fig. 2 and 3, 4 variables 0-1 are introduced to represent the operating state of the unit: u. ofi(t)、
Figure GDA0001831202190000111
Wherein: u. ofi(t) indicates whether the unit i is in an operating and shutdown state at the moment t;
Figure GDA0001831202190000112
indicating whether the unit i is in a load-up state at the moment t;
Figure GDA0001831202190000113
indicating whether the unit n is in a scheduling receiving state at the moment t;
Figure GDA0001831202190000114
indicating whether the unit n is in a load reduction state at the moment t;
3) set state transfer equation
According to the operating state characteristics of the unit in the start-stop stage shown in fig. 2 and 3, the following state transfer equations are introduced to represent the switching of the unit between the operating states.
Figure GDA0001831202190000115
yi(t)-zi(t)＝ui(t) (5)
Figure GDA0001831202190000116
Figure GDA0001831202190000117
Figure GDA0001831202190000118
yi(t)+zi(t)≤1 (9)
Figure GDA0001831202190000119
Figure GDA00018312021900001110
Figure GDA00018312021900001111
Figure GDA00018312021900001112
Figure GDA00018312021900001113
Figure GDA00018312021900001114
Figure GDA00018312021900001115
The formula (4) ensures that the unit can only be in a unique state each time; the formula (5) to the formula (12) represent a state transition model and logic constraints of the unit operation state; equation (13) -equation (16) represent a constraint relationship from one state to another state at the time of state transition; as described aboveThe variables in the formulae are all 0-1 variables, wherein: y isi(t)、zi(t) is a variable for controlling the starting and stopping states of the unit;
Figure GDA0001831202190000121
the variable is a variable for controlling the unit to enter and jump out of the load-lifting state;
Figure GDA0001831202190000122
the variable is a variable for controlling the unit to enter and jump out of a schedulable state;
Figure GDA0001831202190000123
the variable is used for controlling the unit to enter and jump out of the load reduction state;
Figure GDA0001831202190000124
Figure GDA0001831202190000125
wherein M represents a large positive number, pi(t) is the output of the unit i at the moment t; the formula (17) -formula (18) shows that the power output of the thermal power generating unit just after entering the schedulable state and the load reduction state must be PiThe connection among the states of the thermal power generating unit is ensured, and meanwhile, the two formulas are only suitable for the thermal power generating unit and are not suitable for a quick start-stop unit comprising a gas unit;
Δpi(t)＝pi(t)-pi(t-1) (19)
Figure GDA0001831202190000126
Figure GDA0001831202190000127
in the normal operation state of the systems of formula (19) and formula (21)Output variation delta p of uniti(t) the amount of change in output when the upper spinning reserve is called
Figure GDA0001831202190000128
And the amount of change in output when the lower spinning reserve is called
Figure GDA0001831202190000129
Wherein the content of the first and second substances,
Figure GDA00018312021900001210
and
Figure GDA00018312021900001211
is the value of upper rotation standby and lower rotation standby provided by the unit;
4) and (3) restraining the climbing rate of the unit:
Figure GDA00018312021900001212
wherein, Rui(t) and Rdi(t) the climbing and descending capacities of the unit at the time t and can be calculated by the following formula;
Figure GDA00018312021900001213
Figure GDA00018312021900001214
wherein, IthermalIs a thermal power generating unit set; i isgasIs a gas turbine set; RU (RU)iAnd RDiThe up-climbing and down-climbing capacities of the unit under the adjustable state are achieved;
Figure GDA00018312021900001215
the climbing capacity and the climbing capacity of the unit in the load ascending state and the load descending state are calculated according to the following formula;
Figure GDA00018312021900001216
wherein the content of the first and second substances,
Figure GDA0001831202190000131
and
Figure GDA0001831202190000132
is the duration of the load up and load down;
Figure GDA0001831202190000133
Figure GDA0001831202190000134
Figure GDA0001831202190000135
Figure GDA0001831202190000136
equation (26) to equation (28) are respectively the maximum and minimum output of the time group when the upper spinning standby is called and the lower spinning standby is called in the normal running state of the system; equation (29) is the constraint of the maximum minimum up-down rotation reserve capacity of the unit;
the minimum start-stop time constraint of the unit is shown as follows:
Figure GDA0001831202190000137
wherein the content of the first and second substances,
Figure GDA0001831202190000138
and
Figure GDA0001831202190000139
respectively starting and stopping time;
Figure GDA00018312021900001310
and
Figure GDA00018312021900001311
respectively minimum startup and minimum shutdown time;
under the condition of the output curve of the piecewise linearization unit, the generated electricity quantity e of the uniti(t) can be calculated from formula (31);
Figure GDA00018312021900001312
s3: establishing an energy storage optimization configuration model considering the climbing capacity and multi-stage state transition of a gas power unit and a thermal power unit
The objective function of the model created by the present invention is to minimize the associated investment and total operating costs.
In summary, the objective function of the model proposed by the present invention is shown in the following formula (32). The expenses in the formula are as follows: the method comprises the following steps of generating cost of the thermal power generating unit, starting cost of the thermal power generating unit, shutdown cost of the thermal power generating unit, wind abandoning penalty cost of power system scheduling, scheduling cost of DR resources and charging and discharging cost of the electric energy storage equipment.
Figure GDA00018312021900001313
In the formula: n is a power system network topology node set; t is a scheduling time interval set; i is a gas and thermal power generating unit set, I belongs to I; j is a wind generating set; s is an electric energy storage equipment set, and S belongs to S; e, wind power output scene set;
Figure GDA0001831202190000141
Figure GDA0001831202190000142
respectively as fuel gas andgenerating cost, starting cost, stopping cost and standby service cost of the thermal power generating unit i at the moment t;
Figure GDA0001831202190000143
investment costs for electrical energy storage devices;
Figure GDA0001831202190000144
investment cost for the transmission line; pr (total reflection)εThe probability of occurrence of the wind power output scene epsilon is determined; VOLL and λwLoad loss cost and unit wind abandon punishment cost for power system scheduling; the last two parts of the above equation are expectations for conditional risk values for upper and lower spares;
the power generation cost, the starting cost, the shutdown cost and the standby service cost of the gas and thermal power generating unit i at the moment t can be calculated by the following formulas (33) -35; the investment reserve of the electric energy storage equipment and the transmission line can be calculated according to an equation (36) and an equation (37);
Figure GDA0001831202190000145
Figure GDA0001831202190000146
Figure GDA0001831202190000147
Figure GDA0001831202190000148
Figure GDA0001831202190000149
in the above formulas:
Figure GDA00018312021900001410
are respectively machinesNo-load cost, linear generation cost for group i;
Figure GDA00018312021900001411
respectively starting, stopping, up-standby and down-standby service fees of the unit at a single time or unit capacity; c. CmAnd cpThe investment cost required for allocating unit capacity and unit power electric energy storage equipment respectively; l is a set of transmission lines; c. ClineInvestment costs required to build a unit capacity line; plIs the capacity expansion requirement of line l;
the invention provides an energy storage optimization configuration method considering the climbing capacity and multi-stage state transition of a system gas and thermal power generating unit, wherein the constraint conditions of an optimization model used by the method are expressed as follows:
1) power system operating characteristic constraints
Such types of constraints include, for example, power balance, dc power flow constraints, transmission line capacity constraints, and power system backup demand constraints. Wherein the power balance constraint may be expressed in the form:
Figure GDA00018312021900001412
in the formula: n is a power system network topology node set;
Figure GDA0001831202190000151
the node n is a set of the units;
Figure GDA0001831202190000152
the wind generating set is a set of wind generating sets at the node n;
Figure GDA0001831202190000153
is a set of electrical energy storage devices at node n; p is a radical ofi(t) is the output of the unit i at the moment t;
Figure GDA0001831202190000154
the scheduling value of the wind power plant j at the time t;
Figure GDA0001831202190000155
respectively charging and discharging power of the electric energy storage device s at the moment t; dn(t) is the load demand of the load node n at the time t;
for power grid power flow constraint, a direct current power flow equation with neglected network loss is adopted, and a common expression of a direct current power flow model is as follows:
Figure GDA0001831202190000156
in the formula: b isn,kAn imaginary part of an admittance matrix of the grid node; delta thetaε,n,k(t) is the voltage phase angle difference of the system node n and the node k at the time t; thetaε,n(t)、θε,k(t) the voltage phase angles of the system node n and the node k at the moment t respectively; x is the number ofn,kIs the line impedance of node n and node k;
the transmission line capacity constraint may be expressed in the form:
Figure GDA0001831202190000157
in the formula:
Figure GDA0001831202190000158
maximum transmission capacity of a line connecting a system node n and a node k;
power system backup demand constraints:
the expressions of equations (41) and (42) apply to different types of backup requirements of the power system (e.g., 1 hour spinning backup, 15 minute spinning backup, non-spinning backup, etc.). The present invention contemplates only the 15 minute spinning standby version.
Figure GDA0001831202190000159
Figure GDA00018312021900001510
In the formula: pr (-) is a probability function;
Figure GDA00018312021900001511
and
Figure GDA00018312021900001512
respectively providing upper standby values and lower standby values for the system according to the electric energy storage obtained by the wind power prediction and the load prediction errors;
Figure GDA00018312021900001513
and
Figure GDA00018312021900001514
the requirements of upper backup and lower backup of the power system can be estimated through wind power and load prediction errors; α and β are confidence levels that satisfy the upper and lower spares of the system, respectively;
2) electrical energy storage device operating characteristic constraints
The electrical energy storage device operating characteristic constraints are as shown in equations (43) - (48).
Figure GDA0001831202190000161
Figure GDA0001831202190000162
Figure GDA0001831202190000163
Figure GDA0001831202190000164
Figure GDA0001831202190000165
Figure GDA0001831202190000166
Equations (43) - (48) are energy constraints of the electrical energy storage device; es(t) is the electric energy (SOC) stored by the electric energy storage device s at the time t; deltasThe loss coefficient under self-discharge condition of the electrical energy storage device s;
Figure GDA0001831202190000167
the charge-discharge efficiency of the electrical energy storage device s, respectively;
Figure GDA0001831202190000168
γ srespectively representing the SOC upper limit coefficient and the SOC lower limit coefficient of the electric energy storage equipment s;
Figure GDA0001831202190000169
is the rated capacity of the electrical energy storage device s; equations (45) - (46) are the charge and discharge power constraints of the electrical energy storage device;
Figure GDA00018312021900001610
the maximum charging and discharging power of the electrical energy storage device s is respectively;
Figure GDA00018312021900001611
Figure GDA00018312021900001617
the charging and discharging working states of the electric energy storage equipment s are respectively 0-1 variable; equation (47) is the electrical energy storage device operating state constraint; equation (48) is the charge-discharge balance constraint of the electrical energy storage device under consideration of self-discharge;
3) the energy storage backup service capacity needs to satisfy the following constraints:
Figure GDA00018312021900001612
Figure GDA00018312021900001613
Figure GDA00018312021900001614
Figure GDA00018312021900001615
Figure GDA00018312021900001616
in the formula:
Figure GDA0001831202190000171
and
Figure GDA0001831202190000172
respectively calling SOC values of upper standby time electric energy storage equipment and lower standby time electric energy storage equipment for the system;
4) unit characteristic constraints
Wind generating set output restraint
Figure GDA0001831202190000173
Relevant constraints such as output constraint, climbing rate constraint, minimum start-stop time constraint and the like of the gas generating unit and the thermal power generating unit are shown in the relevant expressions.
S4: solving multi-resource optimization scheduling problem of power system
The energy storage optimization configuration method which is established in the method and takes the climbing capacity and the multi-stage state transition of the gas and thermal power generating units into consideration can be linearly processed into a standard Mixed Integer Linear Programming (MILP) model, so that CPLEX can be called by a business software GAMS to be conveniently solved, and a power system scheduling decision scheme is obtained.
The energy storage optimization configuration model considering the climbing capacity and the multi-stage state transition of the gas and thermal power generating unit is further explained by combining with an example as follows:
example simulation analysis was performed using a modified PJM5 node system as an example, as shown in fig. 4. The system has 5 generators (a gas power unit and a thermal power unit), and relevant parameters of the generators are shown in a table 1. Table 2 is the operating parameters of the electrical energy storage device and table 3 is the transmission line capacity. VOLL and λwThe values are 3000 yuan/MWh and 500 yuan/MWh respectively. The confidence levels α and β both take values of 0.95. Consider the 24 hour day case, with 1 hour each time interval. 1 wind power plant is accessed at a node 1 of the system, the installed capacity is 600MW, the output and standby requirements under each scene (S1-S5) of the wind power plant are respectively shown in FIG. 5 and FIG. 6, and the probability of each scene is respectively 23.22%, 18.78%, 16.08%, 21.36% and 20.56%. The total load of the system is shown in fig. 7, and the load of the system at nodes 2, 3, 4, and 3 respectively accounts for about 41.5%, 30.3%, and 28.2% of the total load.
TABLE 1 thermal power generating unit parameters
Figure GDA0001831202190000174
Figure GDA0001831202190000181
TABLE 2 electric energy storage device scheduling parameters
Figure GDA0001831202190000182
Table 3 shows system indexes in different scenarios. The analysis result shows that the method provided by the invention is superior to other schemes on most system indexes because the capability of the electric energy storage equipment for providing system standby is considered. When the electric energy storage equipment is not considered to provide the standby capacity for the system, the conventional capacity can provide the standby capacity, so that the adjustment space of the unit in operation is compressed, and certain flexibility is sacrificed.
Meanwhile, the optimized configuration result also shows that the energy storage equipment configured in the power system can reduce the capacity expansion requirement of the line, and can absorb more clean energy, especially can provide a standby for the power system, provide a larger operation space for the traditional unit and enable the unit to operate in a better operation state.
TABLE 3 System indices under different scenarios
Figure GDA0001831202190000183
Note: "-" indicates that the indicator is not applicable in this scenario
The invention provides an energy storage optimal configuration method considering the climbing capacity and multi-stage state transition of a system gas and a thermal power unit, which represents the mutual switching and transferring relation between various states of the gas power unit and the thermal power unit during operation in a unified mode. Meanwhile, the problem of the operation and standby of the power system is considered, a power system multi-resource scheduling model is provided,
the comprehensive consideration energy storage and the unit provide the condition of rotating reserve for the system together and better accord with the actual operation condition, the actual condition is better accorded with, and the practicality is stronger simultaneously.
A multi-resource scheduling model of the power system is provided, multi-resource optimized scheduling of the power system is achieved, and waste of clean energy is effectively reduced. Compared with the existing power system scheduling model or unit combination model, the method provided by the invention is more practical and more practical, improves the precision of the operation characteristic model of the thermal power unit in the power system scheduling analysis, provides an analysis tool for the power system to develop peak regulation resource optimization configuration decision, and has certain economic benefit and environmental benefit.
The above are preferred embodiments of the present invention, and all changes made according to the technical scheme of the present invention that produce functional effects do not exceed the scope of the technical scheme of the present invention belong to the protection scope of the present invention.

Claims (3)

1. An energy storage optimal configuration method considering characteristics of system gas and thermal power generating units is characterized by comprising the following steps,
s1, firstly, predicting the output of the new energy generator set according to historical data, constructing a typical scene set of the output of the new energy generator set, and constructing a load scene set of the power system by combining with the load fluctuation characteristic;
s2, analyzing the operation characteristics of the start-stop stages of the gas generating unit and the thermal power generating unit, establishing a state transfer equation set, determining the transfer conditions among the states, establishing a state transfer model of the start-stop stage operation of the gas generating unit and the thermal power generating unit, and realizing the transfer and switching among different states in the start-stop stage operation process of the gas generating unit and the thermal power generating unit;
s3: according to the system and the operation parameters, on the basis of considering a wind power consumption target, constructing an energy storage optimization configuration model considering the climbing capacity and multi-stage state transfer of a gas turbine unit and a thermal power unit by taking the minimum related investment and total operation cost as a target;
s4: solving the energy storage optimization configuration problem of the power system to obtain an energy storage optimization configuration scheme of the power system;
the step S1 is specifically implemented as follows:
uncertainty of wind power output and load mainly considers deviation of wind speed and load prediction, and respective deviation is considered to accord with normal distribution; the actual values of the wind speed and the load are both represented by the sum of the predicted expected value and the predicted error; the form is as follows:
Figure FDA0003497260030000011
Figure FDA0003497260030000012
in the formula: v (t), PL(t) true values for wind speed and load, respectively;
Figure FDA0003497260030000013
respectively predicting expected values for wind speed and load; e.g. of the typev(t)、eL(t) is divided intoWind speed and load prediction errors are distinguished, and both obey probability distribution;
the wind power output is calculated according to the following formula:
Figure FDA0003497260030000014
in the formula: p (v) is the output of the wind turbine generator at the wind speed v; v is the wind speed; v. ofinCutting wind speed for the wind driven generator; v. ofrThe rated power wind speed of the wind driven generator; v. ofoutCutting wind speed for the wind driven generator; (v) wind speed vinTo vrIn time, the function of the relation between the output power of the wind driven generator and the wind speed; pmaxThe rated power of the wind turbine generator is set;
combining wind power output and load to generate a power system operation scene set;
the step S2 is specifically implemented as follows:
1) analyzing the operating characteristics of the thermal power generating unit in the starting and stopping stage: the starting and stopping processes of the thermal power generating unit need to go through the load increasing and load reducing processes;
2) modeling the state of the thermal power generating unit, determining the number of running states, and configuring a 0-1 variable representing the state: according to the operating state characteristics of the thermal power generating unit in the starting and stopping stage, 4 variables 0-1 are introduced to represent the operating state of the unit: u. ofi(t)、
Figure FDA0003497260030000021
Wherein: u. ofi(t) indicates whether the unit i is in an operating and shutdown state at the moment t;
Figure FDA0003497260030000022
indicating whether the unit i is in a load-up state at the moment t;
Figure FDA0003497260030000023
indicating whether the unit i is in a scheduling receiving state at the moment t;
Figure FDA0003497260030000024
indicating whether the unit i is in a load reduction state at the moment t;
3) defining the state transition condition between the states of the thermal power generating unit, and establishing a state transition equation set: according to the operating state characteristics of the thermal power generating unit in the starting and stopping stage, the following state transfer equation set is introduced to represent the switching of the thermal power generating unit among the operating states;
Figure FDA0003497260030000025
yi(t)-zi(t)＝ui(t) (5)
Figure FDA0003497260030000026
Figure FDA0003497260030000027
Figure FDA0003497260030000028
yi(t)+zi(t)≤1 (9)
Figure FDA0003497260030000029
Figure FDA00034972600300000210
Figure FDA00034972600300000211
Figure FDA00034972600300000212
Figure FDA00034972600300000213
Figure FDA00034972600300000214
Figure FDA00034972600300000215
the formula (4) ensures that the unit can only be in a unique state each time; the formula (5) to the formula (12) represent a state transition model and logic constraints of the unit operation state; equation (13) -equation (16) represent a constraint relationship from one state to another state at the time of state transition; the variables in the above formulae are all variables from 0 to 1, wherein: y isi(t)、zi(t) is a variable for controlling the starting and stopping states of the unit;
Figure FDA0003497260030000031
the variable is a variable for controlling the unit to enter and jump out of the load-lifting state;
Figure FDA0003497260030000032
the variable is a variable for controlling the unit to enter and jump out of a schedulable state;
Figure FDA0003497260030000033
the variable is used for controlling the unit to enter and jump out of the load reduction state;
Figure FDA0003497260030000034
Figure FDA0003497260030000035
wherein M represents a large positive number, pi(t) is the output of the unit i at the moment t; the formula (17) to the formula (18) show that the output of the thermal power generating unit just entering the schedulable state and the load reduction state must be equal toP iThe connection among the states of the thermal power generating unit is ensured, and meanwhile, the formulas (17) and (18) are only suitable for the thermal power generating unit and are not suitable for a quick start-stop unit comprising a gas unit;
Δpi(t)＝pi(t)-pi(t-1) (19)
Figure FDA0003497260030000036
Figure FDA0003497260030000037
the expressions (19) and (21) are respectively the output variation Δ p of the unit in the normal operation state of the systemi(t) the amount of change in output when the upper spinning reserve is called
Figure FDA0003497260030000038
And the amount of change in output when the lower spinning reserve is called
Figure FDA0003497260030000039
Wherein the content of the first and second substances,
Figure FDA00034972600300000310
and
Figure FDA00034972600300000311
is the value of upper rotation standby and lower rotation standby provided by the unit;
4) writing a thermal power unit operation characteristic constraint equation in a column mode, and perfecting a thermal power unit start-stop stage model:
Figure FDA00034972600300000312
wherein, Rui(t) and Rdi(t) the climbing and descending capacities of the unit at the time t and can be calculated by the following formula;
Figure FDA00034972600300000313
Figure FDA00034972600300000314
wherein, IthermalIs a thermal power generating unit set; i isgasIs a gas turbine set; RU (RU)iAnd RDiThe up-climbing and down-climbing capacities of the unit under the adjustable state are achieved;
Figure FDA00034972600300000315
the climbing capacity and the climbing capacity of the unit in the load ascending state and the load descending state are calculated according to the following formula;
Figure FDA00034972600300000316
wherein the content of the first and second substances,
Figure FDA0003497260030000041
and
Figure FDA0003497260030000042
is the duration of the load up and load down;
Figure FDA0003497260030000043
Figure FDA0003497260030000044
Figure FDA0003497260030000045
Figure FDA0003497260030000046
equation (26) is the maximum minimum output of the system in the normal operation state, equation (27) is the maximum minimum output of the upper spinning standby invoked time group, and equation (28) is the maximum minimum output of the lower spinning standby invoked time group; equation (29) is the constraint of the maximum minimum up-down rotation reserve capacity of the unit;
the minimum start-stop time constraint of the unit is shown as follows:
Figure FDA0003497260030000047
wherein, Ti on(T) and Ti off(t) start-up and shut-down times, respectively;
Figure FDA0003497260030000048
and
Figure FDA0003497260030000049
respectively minimum startup and minimum shutdown time;
under the condition of the output curve of the piecewise linearization unit, the generated electricity quantity e of the uniti(t) is calculated from formula (31);
Figure FDA00034972600300000410
2. the energy storage optimal configuration method considering characteristics of system gas and thermal power generating units according to claim 1, wherein the step S3 is implemented as follows:
1) an energy storage optimization configuration model objective function considering the climbing capacity and the multi-stage state transition of the gas power unit and the thermal power unit is constructed as follows:
Figure FDA00034972600300000411
in the formula: n is a power system network topology node set; t is a scheduling time interval set; i is a gas and thermal power generating unit set, I belongs to I; j is a wind generating set; s is an electric energy storage equipment set, and S belongs to S; e, wind power output scene set;
Figure FDA0003497260030000051
Figure FDA0003497260030000052
generating cost, starting cost, stopping cost and standby service cost of the gas and thermal power generating unit i at the moment t are respectively set;
Figure FDA0003497260030000053
investment costs for electrical energy storage devices;
Figure FDA0003497260030000054
investment cost for the transmission line; pr (total reflection)εThe probability of occurrence of the wind power output scene epsilon is determined; VOLL and λwLoad loss cost and unit wind abandon punishment cost for power system scheduling; the last two parts of the above equation are expectations for conditional risk values for upper and lower spares;
the power generation cost, the starting cost, the shutdown cost and the standby service cost of the gas and thermal power generating unit i at the moment t are calculated by the following formulas (33) -35; calculating the investment standby of the electric energy storage equipment and the transmission line according to an equation (36) and an equation (37);
Figure FDA0003497260030000055
Figure FDA0003497260030000056
Figure FDA0003497260030000057
Figure FDA0003497260030000058
Figure FDA0003497260030000059
in the above formulas:
Figure FDA00034972600300000510
respectively the no-load cost and the linear power generation cost of the unit i;
Figure FDA00034972600300000511
respectively starting, stopping, up-standby and down-standby service fees of the unit at a single time or unit capacity; c. CmAnd cpThe investment cost required for allocating unit capacity and unit power electric energy storage equipment respectively; l is a set of transmission lines; c. ClineInvestment costs required to build a unit capacity line; plIs the capacity expansion requirement of line l;
2) the method comprises the following steps of constructing energy storage optimization configuration model constraint conditions considering the climbing capacity and multi-stage state transition of a gas power unit and a thermal power unit as follows:
2.1) Power System operating characteristic constraints
The power system operation characteristic constraints comprise power balance, direct current power flow constraint, transmission line capacity constraint and power system standby requirement constraint;
the power balance constraint is expressed in the form:
Figure FDA0003497260030000061
in the formula: n is a power system network topology node set;
Figure FDA0003497260030000062
the node n is a set of the units;
Figure FDA0003497260030000063
the wind generating set is a set of wind generating sets at the node n;
Figure FDA0003497260030000064
is a set of electrical energy storage devices at node n; p is a radical ofi(t) is the output of the unit i at the moment t;
Figure FDA0003497260030000065
the scheduling value of the wind power plant j at the time t;
Figure FDA0003497260030000066
respectively charging and discharging power of the electric energy storage device s at the moment t; dn(t) is the load demand of the load node n at the time t;
secondly, direct current power flow constraint, a direct current power flow equation with network loss neglected is adopted, and a common expression of a direct current power flow model is as follows:
Figure FDA0003497260030000067
in the formula: b isn,kAn imaginary part of an admittance matrix of the grid node; delta thetaε,n,k(t) is the system section at time tVoltage phase angle difference of point n and node k; thetaε,n(t)、θε,k(t) the voltage phase angles of the system node n and the node k at the moment t respectively; x is the number ofn,kIs the line impedance of node n and node k;
thirdly, the capacity constraint of the transmission line is expressed as follows:
Figure FDA0003497260030000068
in the formula:
Figure FDA0003497260030000069
maximum transmission capacity of a line connecting a system node n and a node k;
fourthly, the standby demand of the power system is restricted: the expressions of equations (41) and (42) apply to different types of backup requirements of the power system:
Figure FDA00034972600300000610
Figure FDA00034972600300000611
in the formula: pr (-) is a probability function;
Figure FDA00034972600300000612
and
Figure FDA00034972600300000613
respectively providing upper standby values and lower standby values for the system according to the electric energy storage obtained by the wind power prediction and the load prediction errors;
Figure FDA00034972600300000614
and
Figure FDA00034972600300000615
respectively estimating the upper standby requirement and the lower standby requirement of the power system through wind power and load prediction errors; α and β are confidence levels that satisfy the upper and lower spares of the system, respectively;
2.2) Electrical energy storage device operating characteristic constraints
The electrical energy storage device operating characteristic constraints are as shown in equations (43) - (48):
Figure FDA0003497260030000071
Figure FDA0003497260030000072
Figure FDA0003497260030000073
Figure FDA0003497260030000074
Figure FDA0003497260030000075
Figure FDA0003497260030000076
equations (43) - (48) are energy constraints of the electrical energy storage device; es(t) is the electric energy stored by the electric energy storage device s at the moment t; deltasThe loss coefficient under self-discharge condition of the electrical energy storage device s;
Figure FDA0003497260030000077
the charge-discharge efficiency of the electrical energy storage device s, respectively;
Figure FDA0003497260030000078
γ srespectively representing the SOC upper limit coefficient and the SOC lower limit coefficient of the electric energy storage equipment s;
Figure FDA0003497260030000079
is the rated capacity of the electrical energy storage device s; equations (45) - (46) are the charge and discharge power constraints of the electrical energy storage device;
Figure FDA00034972600300000710
the maximum charging and discharging power of the electrical energy storage device s is respectively;
Figure FDA00034972600300000711
Figure FDA00034972600300000712
the charging and discharging working states of the electric energy storage equipment s are respectively 0-1 variable; equation (47) is the electrical energy storage device operating state constraint; equation (48) is the charge-discharge balance constraint of the electrical energy storage device under consideration of self-discharge;
2.3) energy storage Standby service Capacity
The energy storage backup service capacity needs to satisfy the following constraints:
Figure FDA00034972600300000713
Figure FDA00034972600300000714
Figure FDA00034972600300000715
Figure FDA0003497260030000081
Figure FDA0003497260030000082
in the formula:
Figure FDA0003497260030000083
and
Figure FDA0003497260030000084
respectively calling SOC values of upper standby time electric energy storage equipment and lower standby time electric energy storage equipment for the system;
2.4) wind generating set output restraint
The output of the wind generating set is restricted as follows:
Figure FDA0003497260030000085
in the formula:
Figure FDA0003497260030000086
the output value of the wind power plant j at the moment t is obtained;
3. the energy storage optimization configuration method considering the characteristics of the system gas and the thermal power generating unit as claimed in claim 1 or 2, wherein in the step S4, the established energy storage optimization configuration method considering the climbing capability and the multi-stage state transition of the gas and thermal power generating unit is linearized into a standard mixed integer linear programming model, and then the business software GAMS is adopted to call CPLEX for convenient solution, so as to obtain the power system scheduling decision scheme.
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