CN111009912B - Thermal power plant energy storage configuration system and strategy based on power distribution network scene - Google Patents

Thermal power plant energy storage configuration system and strategy based on power distribution network scene Download PDF

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CN111009912B
CN111009912B CN201911298506.4A CN201911298506A CN111009912B CN 111009912 B CN111009912 B CN 111009912B CN 201911298506 A CN201911298506 A CN 201911298506A CN 111009912 B CN111009912 B CN 111009912B
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distribution network
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CN111009912A (en
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郝思鹏
唐蕾
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Nanjing Institute of Technology
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/008—Circuit arrangements for ac mains or ac distribution networks involving trading of energy or energy transmission rights
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • 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

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Abstract

The invention discloses a thermal power plant energy storage configuration system based on a power distribution network scene, which comprises a power grid, a main transformer, a high-voltage station transformer, a thermal power plant generator set, energy storage equipment, a measurement and control device, a telecontrol device, a unit DCS system, an energy storage control system and strategies, wherein the main transformer is connected with the high-voltage station transformer; a thermal power plant energy storage configuration strategy based on a power distribution network scene comprises the following steps: 1) collecting power distribution network data and establishing a load prediction power curve; 2) load flow calculation is carried out to obtain power and voltage of the thermal power plant access node; 3) establishing an energy storage configuration optimization model of the thermal power plant; 4) solving to obtain an optimal node for installing the energy storage system and energy storage capacity; 5) and evaluating the solving result. According to the invention, the position and the capacity of the energy storage system are effectively and reasonably configured in the thermal power plant, so that the frequent start and stop of the thermal power unit are reduced, the power peak-valley difference of the system is effectively stabilized, and the system is more economical to operate.

Description

Thermal power plant energy storage configuration system and strategy based on power distribution network scene
Technical Field
The invention belongs to the field of optimal configuration of a power generation side energy storage system, and particularly relates to a thermal power plant energy storage configuration system and strategy based on a power distribution network scene.
Background
In recent years, the generation of new energy such as photovoltaic, wind power and the like in China is rapidly developed, the installed capacity of new energy grid-connected equipment is rapidly increased, and due to the uncertainty of the new energy generation, the load peak-valley difference of a power grid is greatly increased during power generation and grid connection while energy conservation and emission reduction are realized, and the peak regulation difficulty of a thermal power plant is increased. Due to the characteristics of long frequency modulation response time and low climbing speed of the traditional thermal power generating unit, the new energy grid connection also deepens the frequency modulation pressure of a power grid.
The peak regulation of the power system is mainly completed by a peak regulation power supply, the installed capacity occupation ratio of thermal power generating units in China at the present stage is high, the main peak regulation task is undertaken, and when the adjustable power supply capacity of the thermal power generating units can not meet the peak regulation requirement, the phenomena of wind and light abandonment and frequent start and stop of the thermal power generating units commonly occur. In order to relieve the pressure of peak regulation and frequency modulation of a thermal power plant, various remedial measures such as energy storage and the like are developed. Because the energy storage system is expensive in manufacturing cost, how to configure energy storage for the thermal power plant to achieve the best economic benefit is a new problem to be solved urgently.
Disclosure of Invention
The purpose of the invention is as follows: aiming at the problems in the prior art, the invention discloses a thermal power plant energy storage configuration system and strategy based on a power distribution network scene, and the position and the capacity of an energy storage system are effectively and reasonably configured in a thermal power plant so as to achieve the best economic benefit.
The technical scheme is as follows: the invention adopts the following technical scheme: a thermal power plant energy storage configuration strategy based on a power distribution network scene is characterized by comprising the following steps:
step A, collecting historical and real-time data of a power distribution network, and establishing a load prediction power curve;
b, obtaining the power and the voltage of a plurality of thermal power plant access nodes in an energy storage planning period through load flow calculation;
step C, establishing an energy storage configuration optimization model of the thermal power plant by taking the minimized thermal power plant operation cost and the energy storage system cost as objective functions and the thermal power plant unit operation conditions and the energy storage system operation conditions as constraint conditions;
d, solving the optimized model in the step C to obtain an optimal node and energy storage capacity of the energy storage system;
and E, calculating the adjustment depth, the adjustment performance index and the daily compensation cost of the thermal power plant participating in the secondary frequency modulation after the energy storage system is installed, and evaluating the solving result.
Preferably, the power distribution network data in the step a includes power plant operation output, load and energy storage state of charge value.
Preferably, in the step a, a load power curve is obtained by using an exponential smoothing algorithm according to the collected data of the power distribution network.
Preferably, the power flow calculation process in step B is:
step B1, inputting data information: admittance between adjacent thermal power plant access nodes;
b2, dividing a network of n nodes into PV nodes, PQ nodes and balance nodes according to the node types, wherein the PV nodes are given with injection active power P and injection voltage U, the PQ nodes are given with injection active power P and reactive power Q, the balance nodes are 1, the voltage U is given, the phase angle is 0 degree, and the initial value of the node voltage and the initial value of the intersection difference between the node voltage and the current are obtained through a column power equation set;
step B3, the node voltage value is substituted to obtain the unbalance amount delta Pi (0)And
Figure BDA0002319976030000021
b4, calculating each element of the Jacobian matrix, and solving the correction equation to obtain the voltage difference
Figure BDA0002319976030000022
Phase angle difference Δ δi (k)Updating the node voltage value and the intersection difference between the node voltage and the current;
step B5, if the voltage difference is not enough
Figure BDA0002319976030000023
Phase angle difference Δ δi (k)If not, repeating the steps B3 and B4; if the voltage difference is
Figure BDA0002319976030000024
Phase angle difference Δ δi (k)And after convergence, the node power value can be obtained.
Preferably, the thermal power plant energy storage configuration optimization model objective function in step C is as follows:
min f＝f1+f2
operating costs f of thermal power plants1：
Figure BDA0002319976030000025
Wherein T is the running time, and N is the number of the thermal power plant units; a isi、bi、ciRespectively representing the power generation cost coefficients of the unit i; p is a radical ofi，tGenerating power of the unit i at the time t; u. ofi，tThe starting and stopping state of the unit i at the moment t is shown, wherein 0 represents the shutdown and 1 represents the starting; si，tThe starting cost of the unit i at the moment t is obtained;
cost f of energy storage system2：
Figure BDA0002319976030000026
Wherein, CsThe cost for complete cycle charging and discharging of the energy storage device once; n is a radical ofcThe equivalent complete cycle times of the energy storage device in the whole life cycle are obtained; epsiloniThe over-charge and over-discharge penalty coefficient is 1.5 when the battery is over-charged and over-discharged and 1 when the battery is normal; n is1The number of cycles, n, for the full life cycle of the energy storage device2Half cycle number; n is a radical ofcy(Di) When the depth of discharge of the energy storage battery is DiCycle life of the time.
Preferably, the constraint conditions of the thermal power plant energy storage configuration optimization model in the step C are as follows:
(1) the operation constraint conditions of the thermal power plant unit are as follows:
and (3) restraining the upper and lower limits of the unit output:
ui，tpi，min≤pi，t≤ui，tpi，max
wherein p isi，min、pi，maxRespectively the minimum and maximum active output allowed by the unit i;
unit climbing restraint:
Figure BDA0002319976030000031
wherein R isi，up、Ri，downRespectively adjusting the upward and downward speed of the maximum active output of the unit i;
and (3) restraining the start and stop of the unit:
Figure BDA0002319976030000032
wherein,
Figure BDA0002319976030000033
the number of the time periods when the unit i is started and stopped is respectively;
Figure BDA0002319976030000034
the minimum starting-up and stopping time periods of the unit i are respectively set;
and (3) rotating standby constraint of the unit:
Figure BDA0002319976030000035
wherein p isi，max，pi，minRespectively the upper limit and the lower limit of the active output of the unit i; r isi u、ri dThe maximum uplink active output change rate and the maximum downlink active output change rate of the unit i in unit time are respectively set;
Figure BDA0002319976030000036
respectively rotating upwards and downwards at the time t for standby; p is a radical oftIs the load power at time t; Δ t is the operating period;
(2) the energy storage system operation constraint conditions are as follows:
and (3) charge and discharge restraint of the energy storage system:
Figure BDA0002319976030000041
wherein,
Figure BDA0002319976030000042
respectively the maximum discharge power and the maximum charge power allowed by the energy storage system;
Figure BDA0002319976030000043
respectively indicating that the energy storage system is in discharging and charging;
and (4) energy storage restraint of an energy storage system:
Figure BDA0002319976030000044
wherein e isess，tThe energy value stored by the energy storage system is t time period; etach、ηdRespectively charging and discharging efficiencies of the energy storage system; e.g. of the typemax、eminStoring the maximum value and the minimum value allowed by energy for the energy storage system;
Figure BDA0002319976030000045
and respectively charging and discharging power plan values of the energy storage system in the time period t.
Preferably, in the step D, the energy storage configuration optimization model of the thermal power plant is solved through an Fmincon function in Matlab.
Preferably, in the step E, the depth D:
Figure BDA0002319976030000046
wherein D is the adjusting depth of the unit for the automatic power generation control on the same day; n is the daily regulation frequency; djAdjusting the depth of the unit for the jth time;
adjustment of the Performance index Kp：
Figure BDA0002319976030000047
Figure BDA0002319976030000048
Figure BDA0002319976030000049
Wherein,
Figure BDA00023199760300000410
the performance value of the ith set in the jth adjusting process is obtained;
Figure BDA00023199760300000411
to adjust the rate;
Figure BDA00023199760300000412
to adjust the precision;
Figure BDA0002319976030000051
to adjust the time;
Figure BDA0002319976030000052
adjusting the performance index of the process for the ith unit for n times in one day; kpThe method comprises the following steps of (1) obtaining adjustment performance indexes of all units in a thermal power plant within one day;
daily compensation charge f3：
f3＝D×ln(Kp)×YAGC
In the formula, YAGCFor the automatic generation control compensation standard, 7.5 yuan/MW was taken.
A thermal power plant energy storage configuration system based on a power distribution network scene is characterized by comprising a power grid, a main transformer, a high-voltage station transformer, a thermal power plant generator set, energy storage equipment, a measurement and control device, a telecontrol device, a unit DCS system and an energy storage control system; wherein, thermal power plant's generating set passes through the main transformer and is connected with the electric wire netting, energy storage equipment passes through high-pressure mill and is connected with the electric wire netting, and energy storage equipment sets up the low pressure side at high-pressure mill with the transformer, measurement and control device detects the unit of thermal power plant's generating set output signal and energy storage equipment's energy storage output signal, and measurement and control device gives telemechanical device with the signal transfer who detects, telemechanical device sends automatic generation control instruction and gives unit DCS system and energy storage control system, and unit DCS system and energy storage control system regulate and control thermal power plant's generating set and energy storage equipment respectively.
Has the advantages that: the invention discloses a thermal power plant energy storage configuration system and a thermal power plant energy storage configuration strategy based on a power distribution network scene, wherein the position and the capacity of an energy storage system are effectively and reasonably configured in a thermal power plant, the frequent start and stop of a thermal power unit are reduced, the peak-valley difference of the system power is more effectively stabilized, and the system operation is more economical.
Drawings
Fig. 1 is a diagram of a regional power grid network structure provided in an embodiment of the present invention;
fig. 2 is a schematic diagram of an overall network topology for energy storage-assisted frequency modulation according to an embodiment of the present invention;
fig. 3 is a flow chart of the method of the present invention.
Detailed Description
The present invention will be further described with reference to the accompanying drawings.
The invention discloses a thermal power plant energy storage configuration system based on a power distribution network scene, as shown in figure 1, energy storage scheduling is controlled by a power plant side to be directly controlled by a power grid side; as shown in fig. 2, the system comprises a power grid, a main transformer, a high-voltage station transformer, a thermal power plant generator set, energy storage equipment, a measurement and control device, a telecontrol device, a unit DCS system and an energy storage control system; the monitoring device detects a unit output signal of the thermal power plant generator set and an energy storage output signal of the energy storage device, the monitoring device transmits the detected signals to the telecontrol device, the telecontrol device sends an automatic power generation control (AGC) instruction to the unit DCS system and the energy storage control system, and the unit DCS system and the energy storage control system respectively regulate and control the thermal power plant generator set and the energy storage device.
A thermal power plant energy storage configuration strategy based on a power distribution network scene is shown in FIG. 3 and comprises the following steps:
step A, collecting historical and real-time data of the power distribution network, and establishing a load prediction power curve.
The collected power distribution network data comprises the running output, load and energy storage state of charge values of the power plant.
And obtaining a load power curve by using an exponential smoothing algorithm according to the collected power distribution network data.
And B, obtaining the power and the voltage of the plurality of thermal power plant access nodes in the energy storage planning period through load flow calculation. The load flow calculation process comprises the following steps:
step B1, inputting data information: admittance y between adjacent thermal power plant access nodesijForming a node admittance matrix Y;
step B2, dividing the network of n nodes into PV nodes, PQ nodes and balance nodes according to the node types; wherein, the PV nodes n-m, given the injected active power P and the voltage U, the intersection difference delta between the voltage and the current needs to be solvediThe number of PQ nodes m-1 is given, and given the injected active power P and reactive power Q, the voltage U must be solvediAnd the intersection difference δ between the voltage and the currentiAnd 1 balancing node is provided, the voltage U is given, and the intersection difference between the voltage and the current is 0 degree, so that iterative solution is not needed.
The specific calculation steps are as follows:
1) for the node i to be connected to the node i,
Figure BDA0002319976030000061
wherein let Yij＝Gij+jBij，
Figure BDA0002319976030000062
Then
Figure BDA0002319976030000063
Wherein P, Q corresponds to a real part, an imaginary part;
2) the column power equation set is used for solving the initial value of the node voltage
Figure BDA0002319976030000064
Initial value delta of intersection difference between voltage and current of sum nodei (0)；
Wherein, the number of PQ nodes m-1,
Figure BDA0002319976030000065
the number of the PV nodes is n-m,
Figure BDA0002319976030000066
step B3, the node voltage value is substituted to obtain the unbalance amount delta Pi (0)And
Figure BDA0002319976030000071
Figure BDA0002319976030000072
wherein G isij、BijRepresents conductance, susceptance between nodes;
step B4, calculating each element of the Jacobian matrix, wherein
Figure BDA0002319976030000073
Figure BDA0002319976030000074
Solving the correction equation of
Figure BDA0002319976030000075
To obtain a voltage difference
Figure BDA0002319976030000076
Phase angle difference Δ δi (k)Then the new value of the node voltage
Figure BDA0002319976030000077
And new value of phase angle
Figure BDA0002319976030000078
Step B5, if the voltage difference is not enough
Figure BDA0002319976030000079
Phase angle difference Δ δi (k)Do not converge, i.e.
Figure BDA00023199760300000710
Repeating the steps B3 and B4; if the voltage difference is
Figure BDA00023199760300000711
Phase angle difference Δ δi (k)Converge, i.e.
Figure BDA00023199760300000712
Then the node power can be found as:
Figure BDA00023199760300000713
and step C, establishing an energy storage configuration optimization model of the thermal power plant by taking the minimized thermal power plant operation cost and the energy storage system cost as objective functions and taking the thermal power plant unit operation conditions and the energy storage system operation conditions as constraint conditions.
An objective function:
min f＝f1+f2 (4)
operating costs f of thermal power plants1：
Figure BDA00023199760300000714
Wherein T is the running time, and N is the number a of the thermal power plant unitsi、bi、ciRespectively representing the power generation cost coefficients of the unit i; p is a radical ofi，tGenerating power of the unit i at the time t; u. ofi，tThe starting and stopping state of the unit i at the moment t is shown, wherein 0 represents the shutdown and 1 represents the starting; si，tThe starting cost of the unit i at the moment t is obtained;
cost f of energy storage system2：
Figure BDA0002319976030000081
Wherein, CsThe cost for complete cycle charging and discharging of the energy storage device once; n is a radical ofcThe equivalent complete cycle times of the energy storage device in the whole life cycle are obtained; epsiloniThe over-charge and over-discharge penalty coefficient is 1.5 when the battery is over-charged and over-discharged and 1 when the battery is normal; n is1The number of cycles, n, for the full life cycle of the energy storage device2Half cycle number; n is a radical ofcy(Di) When the depth of discharge of the energy storage battery is DiCycle life of the time.
Constraint conditions are as follows:
(1) the operation constraint conditions of the thermal power plant unit are as follows:
and (3) restraining the upper and lower limits of the unit output:
ui，tpi，min≤pi，t≤ui，tpi，max (7)
wherein p isi，min、pi，maxRespectively the minimum and maximum active output allowed by the unit i;
unit climbing restraint:
Figure BDA0002319976030000082
wherein R isi，up、Ri，downRespectively adjusting the upward and downward speed of the maximum active output of the unit i;
and (3) restraining the start and stop of the unit:
Figure BDA0002319976030000083
wherein,
Figure BDA0002319976030000084
the number of the time periods when the unit i is started and stopped is respectively;
Figure BDA0002319976030000085
are respectively provided withThe minimum number of starting and stopping time periods of the unit i is set;
and (3) rotating standby constraint of the unit:
Figure BDA0002319976030000086
wherein p isi，max，pi，minRespectively the upper limit and the lower limit of the active output of the unit i; r isi u、ri dThe maximum uplink active output change rate and the maximum downlink active output change rate of the unit i in unit time are respectively set;
Figure BDA0002319976030000087
respectively rotating upwards and downwards at the time t for standby; p is a radical oftIs the load power at time t; Δ t is the operating period;
(2) and (3) operation constraint conditions of the energy storage system:
and (3) charge and discharge restraint of the energy storage system:
Figure BDA0002319976030000091
wherein,
Figure BDA0002319976030000092
respectively the maximum discharge power and the maximum charge power allowed by the energy storage system;
Figure BDA0002319976030000093
respectively indicating that the energy storage system is in discharging and charging;
and (4) energy storage restraint of an energy storage system:
Figure BDA0002319976030000094
wherein e isess，tThe energy value stored by the energy storage system is t time period; etach、ηdRespectively charging and discharging efficiencies of the energy storage system; e.g. of the typemax、eminFor energy storage systemsMaximum and minimum values allowed by stored energy;
Figure BDA0002319976030000095
and respectively charging and discharging power plan values of the energy storage system in the time period t.
And D, solving the thermal power plant energy storage configuration optimization model in the step C through an Fmincon function in Matlab to obtain the optimal node and energy storage capacity of the energy storage system.
And E, calculating the adjustment depth, the adjustment performance index and the daily compensation cost of the thermal power plant participating in the secondary frequency modulation after the energy storage system is installed, and evaluating the solving result.
Adjusting the depth D:
Figure BDA0002319976030000096
wherein D is the AGC adjusting depth of the unit on the same day; n is the daily regulation frequency; djAdjusting the depth of the unit for the jth time;
adjustment of the Performance index Kp：
Figure BDA0002319976030000097
Figure BDA0002319976030000098
Figure BDA0002319976030000101
Wherein,
Figure BDA0002319976030000102
the performance value of the ith set in the jth adjusting process is obtained;
Figure BDA0002319976030000103
to adjust the rate;
Figure BDA0002319976030000104
to adjust the precision;
Figure BDA0002319976030000105
to adjust the time;
Figure BDA0002319976030000106
adjusting the performance index of the process for the ith unit for n times in one day; kpThe method comprises the following steps of (1) obtaining adjustment performance indexes of all units in a thermal power plant within one day; wherein the performance index is ln (K)p) And (4) counting.
Daily compensation charge f3：
f3＝D×ln(Kp)×YAGC (17)
In the formula, YAGCFor the AGC compensation criteria, take 7.5 bins/MW.
The above description is only of the preferred embodiments of the present invention, and it should be noted that: it will be apparent to those skilled in the art that various modifications and adaptations can be made without departing from the principles of the invention and these are intended to be within the scope of the invention.

Claims (8)

1. A thermal power plant energy storage configuration strategy based on a power distribution network scene is characterized by comprising the following steps:
step A, collecting historical and real-time data of a power distribution network, and establishing a load prediction power curve;
b, obtaining the power and the voltage of the access nodes of the multiple thermal power plants in the energy storage planning period through load flow calculation;
step C, establishing an energy storage configuration optimization model of the thermal power plant by taking the minimized operating cost and energy storage system cost of the multiple thermal power plants as objective functions and the operating conditions of the thermal power plant units and the operating conditions of the energy storage system as constraint conditions;
d, solving the optimized model in the step C to obtain an optimal node and energy storage capacity of the energy storage system;
and E, calculating the adjustment depth, the adjustment performance index and the daily compensation cost of the thermal power plant participating in secondary frequency modulation after the energy storage system is installed, and evaluating the solving result, wherein:
adjusting the depth D:
Figure FDA0003244701210000011
wherein D is the adjusting depth of the unit for the automatic power generation control on the same day; n is the daily regulation frequency; djAdjusting the depth of the unit for the jth time;
adjustment of the Performance index Kp：
Figure FDA0003244701210000012
Figure FDA0003244701210000013
Figure FDA0003244701210000014
Wherein,
Figure FDA0003244701210000015
the performance value of the ith set in the jth adjusting process is obtained;
Figure FDA0003244701210000016
to adjust the rate;
Figure FDA0003244701210000017
to adjust the precision;
Figure FDA0003244701210000018
to adjust the time;
Figure FDA0003244701210000019
adjusting the performance index of the process for the ith unit for n times in one day; kpThe method comprises the following steps of (1) obtaining adjustment performance indexes of all units in a thermal power plant within one day;
daily compensation charge f3：
f3＝D×ln(Kp)×YAGC
Wherein, YAGCThe compensation standard is used for automatic power generation control.
2. The thermal power plant energy storage configuration strategy based on the power distribution network scene as claimed in claim 1, wherein the power distribution network data in step a includes thermal power plant operating output, load and energy storage state of charge values.
3. The thermal power plant energy storage configuration strategy based on the power distribution network scene as claimed in claim 1, wherein in the step a, a load prediction power curve is obtained by using an exponential smoothing algorithm according to the collected power distribution network data.
4. The thermal power plant energy storage configuration strategy based on the power distribution network scene as claimed in claim 1, wherein the power flow calculation process in the step B is as follows:
step B1, inputting data information: admittance between adjacent thermal power plant access nodes;
b2, dividing a network of n nodes into PV nodes, PQ nodes and balance nodes according to the node types, wherein the PV nodes are given with injection active power P and injection voltage U, the PQ nodes are given with injection active power P and reactive power Q, the balance nodes are 1, the voltage U is given, the phase angle is 0 degree, and the initial value of the node voltage and the initial value of the phase angle difference between the node voltage and the current are obtained through a column power equation set;
step B3, the initial value of the node voltage is substituted to obtain the unbalance amount delta Pi (0)And
Figure FDA0003244701210000021
b4, calculating each element of the Jacobian matrix, and solving the correction equation to obtain the voltage difference
Figure FDA0003244701210000022
Phase angle difference
Figure FDA0003244701210000023
Updating the node voltage value and the phase angle difference value between the node voltage and the current;
step B5, if the voltage difference is not enough
Figure FDA0003244701210000024
Phase angle difference
Figure FDA0003244701210000025
If not, repeating the steps B3 and B4; if the voltage difference is
Figure FDA0003244701210000026
Phase angle difference
Figure FDA0003244701210000027
And after convergence, the node power value can be obtained.
5. The thermal power plant energy storage configuration strategy based on the power distribution network scene as claimed in claim 1, wherein the thermal power plant energy storage configuration optimization model objective function in step C is as follows:
minf＝f1+f2
operating costs f of thermal power plants1：
Figure FDA0003244701210000028
Wherein T is the running time, and N is the number of the thermal power plant units; a isi、bi、ciAre respectively asGenerating cost coefficient of the unit i; p is a radical ofi,tGenerating power of the unit i at the time t; u. ofi,tThe starting and stopping state of the unit i at the moment t is shown, wherein 0 represents the shutdown and 1 represents the starting; si,tThe starting cost of the unit i at the moment t is obtained;
cost f of energy storage system2：
Figure FDA0003244701210000029
Wherein, CsThe cost for complete cycle charging and discharging of the energy storage device once; n is a radical ofcThe equivalent complete cycle times of the energy storage device in the whole life cycle are obtained; epsiloniThe over-charge and over-discharge penalty coefficient is 1.5 when the battery is over-charged and over-discharged and 1 when the battery is normal; n is1The number of cycles, n, for the full life cycle of the energy storage device2Half cycle number; n is a radical ofcy(Di) When the depth of discharge of the energy storage battery is DiCycle life of the time.
6. The thermal power plant energy storage configuration strategy based on the power distribution network scene as claimed in claim 5, wherein the thermal power plant energy storage configuration optimization model constraint conditions in step C are as follows:
(1) the operation constraint conditions of the thermal power plant unit are as follows:
and (3) restraining the upper and lower limits of the unit output:
ui,tpi,min≤pi,t≤ui,tpi,max
wherein p isi,min、pi,maxRespectively the minimum and maximum active output allowed by the unit i;
unit climbing restraint:
Figure FDA0003244701210000031
wherein R isi,up、Ri,downRespectively adjusting the upward and downward speed of the maximum active output of the unit i;
and (3) restraining the start and stop of the unit:
Figure FDA0003244701210000032
wherein,
Figure FDA0003244701210000033
the number of the time periods when the unit i is started and stopped is respectively;
Figure FDA0003244701210000034
the minimum starting-up and stopping time periods of the unit i are respectively set;
and (3) rotating standby constraint of the unit:
Figure FDA0003244701210000035
wherein p isi,max，pi,minRespectively the upper limit and the lower limit of the active output of the unit i; r isi u、ri dThe maximum uplink active output change rate and the maximum downlink active output change rate of the unit i in unit time are respectively set;
Figure FDA0003244701210000036
respectively rotating upwards and downwards at the time t for standby; p is a radical oftIs the load power at time t; Δ t is the operating period;
(2) the energy storage system operation constraint conditions are as follows:
and (3) charge and discharge restraint of the energy storage system:
Figure FDA0003244701210000041
wherein,
Figure FDA0003244701210000042
respectively the maximum discharge allowed by the energy storage systemCharging power;
Figure FDA0003244701210000043
respectively indicating that the energy storage system is in discharging and charging;
and (4) energy storage restraint of an energy storage system:
Figure FDA0003244701210000044
wherein e isess,tThe energy value stored by the energy storage system is t time period; etach、ηdRespectively charging and discharging efficiencies of the energy storage system; e.g. of the typemax、eminStoring the maximum value and the minimum value allowed by energy for the energy storage system;
Figure FDA0003244701210000045
and respectively charging and discharging power plan values of the energy storage system in the time period t.
7. The thermal power plant energy storage configuration strategy based on the power distribution network scene as claimed in claim 1, wherein in the step D, the thermal power plant energy storage configuration optimization model is solved through Fmincon function in Matlab.
8. The thermal power plant energy storage configuration strategy based on power distribution network scene as claimed in claim 1, wherein in step E, YAGCThe standard for automatic generation control compensation was taken at 7.5 yuan/MW.
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