CN109599879B - Power distribution network active power scheduling method considering energy storage device charging and discharging times optimization - Google Patents

Power distribution network active power scheduling method considering energy storage device charging and discharging times optimization Download PDF

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CN109599879B
CN109599879B CN201811503104.9A CN201811503104A CN109599879B CN 109599879 B CN109599879 B CN 109599879B CN 201811503104 A CN201811503104 A CN 201811503104A CN 109599879 B CN109599879 B CN 109599879B
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energy storage
storage equipment
distribution network
load
power distribution
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CN109599879A (en
Inventor
吕项羽
李德鑫
高长征
姚强
王佳蕊
王鹏
陈俊涛
玄京岩
张艳
常学飞
丁浩
蔡丽霞
刘畅
高松
张海锋
张俊刚
金成日
延东洙
孟涛
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Yanbian Power Supply Co Of State Grid Jilinsheng Electric Power Supply Co
Electric Power Research Institute of State Grid Jilin Electric Power Co Ltd
State Grid Jilin Electric Power Corp
Beijing King Star Hi Tech System Control Co Ltd
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Yanbian Power Supply Co Of State Grid Jilinsheng Electric Power Supply Co
Electric Power Research Institute of State Grid Jilin Electric Power Co Ltd
State Grid Jilin Electric Power Corp
Beijing King Star Hi Tech System Control 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
    • 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
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H02J3/383—
    • 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
    • H02J3/48—Controlling the sharing of the in-phase component
    • 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
    • Y02E10/50—Photovoltaic [PV] energy
    • Y02E10/56—Power conversion systems, e.g. maximum power point trackers

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  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Supply And Distribution Of Alternating Current (AREA)
  • Charge And Discharge Circuits For Batteries Or The Like (AREA)

Abstract

The invention relates to a power distribution network active power scheduling method considering energy storage equipment charging and discharging times optimization, and belongs to the technical field of power distribution network scheduling automation. Obtaining a gateway load curve of a 96 prediction point on the next day according to the day-ahead load prediction and the photovoltaic power generation prediction of the power distribution network; starting at point 1, the energy storage action demand at the predicted point of the day 96 is recorded. And when the load of the gate is higher than the upper limit, the energy storage device discharges, and when the load of the gate is lower than the lower limit, the energy storage device charges. When the charging requirement exceeds the upper limit of the energy storage capacity or the discharging requirement is lower than the lower limit of the capacity of the energy storage equipment at the ith point, optimizing the instruction at the previous i-1 point, and preferentially meeting the moment when the requirement of the energy storage action is larger; finally, the 96 predicted point storage adjustment is distributed to the storage devices in the form of power. The method effectively reduces the charging and discharging times of the energy storage equipment in the power distribution network, and prolongs the service life of the energy storage equipment; meanwhile, the peak-valley difference of gateway load is reduced, and the upgrading time of the gateway equipment capacity is effectively prolonged.

Description

Power distribution network active power scheduling method considering energy storage device charging and discharging times optimization
Technical Field
The invention relates to a power distribution network active power scheduling method considering energy storage equipment charging and discharging times optimization, and belongs to the technical field of power distribution network scheduling automation.
Background
In the automatic dispatching process of the power distribution network, a load forecasting module and a photovoltaic power generation forecasting module are indispensable links, and the two modules can provide the results of the photovoltaic power generation active forecasting and the load active forecasting in the day ahead of the next day by taking 15 minutes as a period according to information such as weather forecasting and the like. On the basis, some related modules in the technical field of distribution network automation can possibly further set the operation mode, power generation and load injection of the distribution network through methods such as load flow calculation and the like, calculate the voltage of each bus and the load flow of each branch of the distribution network, and provide technical support for distribution network automation scheduling. Therefore, the control of the energy storage device by the power distribution network usually adopts a 15-minute period, and 96 points in a day, so as to fully utilize the load prediction data and the photovoltaic prediction data.
Along with the continuous rising of urban power load, the day and night peak-valley difference of the power distribution network load is continuously increased. Rely on traditional electricity generation side power regulation to be difficult to satisfy the economic operation requirement of distribution network, rely on increasing to drop into to increase installed capacity and carry out the dilatation to transmission and distribution lines alone, not only the cost is higher, and equipment utilization is lower. The gradual maturity of energy storage battery technology has changed this situation, and load management on the demand side has become possible by discharging during peak load and charging during valley load. The power grid company can delay the updating of the power equipment caused by insufficient capacity by controlling the energy storage equipment, and the utilization rate of the equipment is improved. However, the energy storage device has limited charge and discharge times, and the service life of the energy storage device is reduced due to excessive charge and discharge times. Therefore, when the energy storage device is used for optimizing the operation of the power grid, how to consider the charging and discharging life of the energy storage device is an important aspect of the energy storage device regulation strategy.
Disclosure of Invention
The invention aims to provide a power distribution network active power scheduling method considering optimization of charging and discharging times of energy storage equipment.
The invention provides a power distribution network active power scheduling method considering energy storage equipment charging and discharging times optimization, which comprises the following steps:
(1) the dispatching planning center of the power distribution network sets the total load predicted value of 96 predicted points of the power distribution network in the future day
Figure BDA0001898710350000011
And the photovoltaic power generation value of a 96 predicted point in the future day in the power distribution network
Figure BDA0001898710350000012
Wherein i is a prediction point, i belongs to (1-96), i is a prediction point in a period of 15 minutes, and a prediction value is obtained according to the total load
Figure BDA0001898710350000021
And photovoltaic power generation value
Figure BDA0001898710350000022
Obtaining an action area of energy storage equipment in the power distribution network, and specifically comprising the following steps:
(1-1) calculation of the Point load predicted by the gateway 96 according to the following equation
Figure BDA0001898710350000023
Figure BDA0001898710350000024
(1-2) predicting Point loads based on the gateway 96
Figure BDA0001898710350000025
Calculating an action area of energy storage equipment in the power distribution network:
Figure BDA0001898710350000026
Pt＝avr*1.2
Pb＝avr*0.8
wherein, PavrIs the average value of the gateway load, and is the average value P of the gateway loadavrFor the center, an upper limit and a lower limit are respectively set at the upper and lower 20% of the average value of the gateway load, and are marked as PtAnd Pb；
When the load of the gateway is at the upper limit PtAnd a lower limit PbIn between, the load of the gateway is recorded as a dead zone value, and when the load of the gateway is higher than or equal to the upper limit PtOr less than or equal to the lower limit PbRecording the gateway load as a zone value to be regulated;
(2) determining the energy storage equipment adjustment amount of the energy storage equipment in the power distribution network at 96 prediction points according to the action area of the energy storage equipment in the power distribution network in the step (1), and specifically comprising the following steps:
(2-1) judging the gateway load of the ith prediction point, if the gateway load is equal to the dead zone value, the energy storage equipment does not act,
Figure BDA0001898710350000027
if the gateway load is equal to the value of the area to be regulated, the gateway load is further judged, and if the gateway load is smallIs equal to or higher than the lower limit PbIf the energy storage equipment is in the state of the power failure, the energy storage equipment records the change of the electric quantity according to the power difference between the gateway load and the lower limit in 15 minutes
Figure BDA0001898710350000028
Namely, it is
Figure BDA0001898710350000029
Step (2-2) is carried out, if the gateway load is greater than or equal to the upper limit PtThe energy storage device follows the upper limit PtRecording the change of electric quantity by the power difference of the gateway load of 15 minutes
Figure BDA00018987103500000210
Namely, it is
Figure BDA00018987103500000211
Figure BDA00018987103500000212
Carrying out the step (2-3);
(2-2) recording the charging adjustment quantity of the energy storage equipment at the ith prediction point, and recording the electric quantity adjustment quantity of the energy storage equipment according to the power difference between the gateway load and the lower limit in 15 minutes
Figure BDA00018987103500000213
Namely, it is
Figure BDA00018987103500000214
Adjust the electric quantity by the quantity
Figure BDA00018987103500000215
And the current electric quantity E of the energy storage devicecurrSum and upper limit E of energy storage capacity of energy storage equipmentmaxIn comparison, if
Figure BDA00018987103500000216
Then adjust the amount of power
Figure BDA00018987103500000217
Storing a charging sequence Qin-seqAnd carrying out the step (2-4)) If, if
Figure BDA00018987103500000218
Performing the step (2-5);
(2-3) recording the discharge adjustment quantity of the energy storage equipment at the predicted point i, and recording the electric quantity adjustment quantity of the energy storage equipment according to the power difference between the upper limit and the 15-minute gateway load
Figure BDA00018987103500000219
Adjust the electric quantity by the quantity
Figure BDA00018987103500000220
And the current electric quantity E of the energy storage devicecurrSum and lower energy storage capacity limit E of energy storage deviceminIn comparison, if
Figure BDA00018987103500000221
Then adjust the amount of power
Figure BDA00018987103500000222
Storing a discharge sequence Qout-seqAnd carrying out the step (2-6) if
Figure BDA00018987103500000223
Performing the step (2-7);
(2-4) charging sequence Qin-seqThe electric quantity adjustment quantity from the 1 st prediction point to the i-1 th prediction point stored in the step (b) is sorted from large to small, and the minimum electric quantity adjustment quantity is recorded as
Figure BDA0001898710350000031
To the same
Figure BDA0001898710350000032
Make a judgment if
Figure BDA0001898710350000033
Figure BDA0001898710350000034
Then the charging sequence Q will bein-seqLast charge regulation from Qin-seqIs deleted and made
Figure BDA0001898710350000035
Repeating the steps until the conditions are met
Figure BDA0001898710350000036
And make the charging sequence Qin-seqThe medium and minimum charge adjustment amounts are:
Figure BDA0001898710350000037
(2-5) regulating the quantity of electricity
Figure BDA0001898710350000038
Charging sequence Qin-seqPerforming the following steps;
(2-6) discharging sequence Qout-seqThe electric quantity regulating quantity from the 1 st forecasting point to the i-1 st forecasting point stored in the step (b) is sorted from small to large, and the minimum electric quantity regulating quantity is recorded as
Figure BDA0001898710350000039
To the same
Figure BDA00018987103500000322
Make a judgment if
Figure BDA00018987103500000311
Figure BDA00018987103500000312
Then discharge sequence Q will be initiatedout-seqFrom Qout-seqIs deleted and made
Figure BDA00018987103500000313
Repeating the steps until the conditions are met
Figure BDA00018987103500000314
And make the discharging sequence Qout-seqThe minimum discharge adjustment amount in (1) is:
Figure BDA00018987103500000315
(2-7) adjusting the quantity of electricity
Figure BDA00018987103500000316
Put into a discharge sequence Qout-seq；
(2-8) judging the predicted point i, if i is smaller than 96, increasing i by 1, returning to the step (2-1) until i is equal to 96, and performing the step (3);
(3) distributing the energy storage equipment adjustment quantity of the energy storage equipment in the power distribution network at 96 prediction points to each energy storage equipment of the power distribution network in a power mode according to the energy storage equipment adjustment quantity of the energy storage equipment in the power distribution network in the step (2), and specifically comprising the following steps:
(3-1) converting the electric quantity regulating quantity of the energy storage equipment at the 96 prediction points into power, wherein the negative power represents charging of the energy storage equipment, the positive power represents discharging of the energy storage equipment, and according to the electric quantity regulating quantity of the energy storage equipment at the ith prediction point, the total regulating power of the energy storage equipment at the ith prediction point is obtained through calculation according to the following formula
Figure BDA00018987103500000317
Figure BDA00018987103500000318
(3-2) regulating the total power of the energy storage equipment at the ith prediction point according to the step (3-1)
Figure BDA00018987103500000319
Calculating and obtaining a charging and discharging regulation instruction of each energy storage device in the power distribution network by using the following formula
Figure BDA00018987103500000320
The method realizes the power distribution network active power scheduling considering the optimization of the charging and discharging times of the energy storage equipment:
Figure BDA00018987103500000321
wherein n is the number of energy storage devices in the power distribution network, EnFor the current capacity of each energy storage device, EnmaxThe maximum capacity of each energy storage device.
The power distribution network active power scheduling method considering the optimization of the charging and discharging times of the energy storage equipment has the advantages that:
the active power dispatching method of the power distribution network considering the optimization of the charging and discharging times of the energy storage equipment fully considers the capacity of the energy storage equipment, optimizes the regulation of the energy storage equipment, and preferentially meets the regulation requirements of load peaks and load valleys, and meanwhile, the phenomenon of excessive charging and discharging of the energy storage equipment caused by load fluctuation is avoided by setting a regulation dead zone. Therefore, the scheduling method effectively reduces the charging and discharging times of the energy storage equipment in the power distribution network, and prolongs the service life of the equipment; meanwhile, because the energy storage equipment in the power distribution network discharges at the peak of the load and charges at the valley of the load, the peak-valley difference of the gateway load is reduced, the upgrading time of the capacity of the gateway equipment is effectively prolonged, and the running economy of the power distribution network is improved.
Drawings
Fig. 1 is a schematic diagram of a typical structure of a power distribution network according to the method of the present invention.
Detailed Description
According to the active power scheduling method of the power distribution network considering the optimization of the charging and discharging times of the energy storage equipment, a typical structure of the power distribution network is shown in figure 1, and a 10kV gateway is a boundary of the power distribution network and a transmission network. The nodes on the right side of the 10kV gateway represent a power distribution network, and equipment such as load, energy storage and photovoltaic power generation can be arranged below each node. The load prediction in the day-ahead gives the predicted values of all the loads, the photovoltaic prediction is the predicted value of the photovoltaic power generation of the distribution network, and the predicted value of the final gateway is equal to the load prediction minus the photovoltaic prediction.
The method comprises the following steps:
(1) dispatching plan center of power distribution network is establishedDetermining total load prediction value of 96 prediction points of power distribution network in future day
Figure BDA0001898710350000041
And the photovoltaic power generation value of a 96 predicted point in the future day in the power distribution network
Figure BDA0001898710350000042
Wherein i is a prediction point, i belongs to (1-96), i is a prediction point in a period of 15 minutes, and a prediction value is obtained according to the total load
Figure BDA0001898710350000043
And photovoltaic power generation value
Figure BDA0001898710350000044
Obtaining an action area of energy storage equipment in the power distribution network, and specifically comprising the following steps:
(1-1) calculation of the Point load predicted by the gateway 96 according to the following equation
Figure BDA0001898710350000045
Figure BDA0001898710350000046
(1-2) predicting Point loads based on the gateway 96
Figure BDA0001898710350000047
Calculating an action area of energy storage equipment in the power distribution network:
Figure BDA0001898710350000048
Pt＝avr*1.2
Pb＝avr*0.8
wherein, PavrIs the average value of the gateway load, and is the average value P of the gateway loadavrFor the center, an upper limit and a lower limit are respectively set at the upper and lower 20% of the average value of the gateway load, and are marked as PtAnd Pb；
When the load of the gateway is at the upper limit PtAnd a lower limit PbIn the meantime, the gateway load is recorded as a dead zone value, the energy storage equipment does not participate in regulation at the moment, and when the gateway load is higher than or equal to the upper limit PtOr less than or equal to the lower limit PbRecording the gateway load as a zone value to be regulated, and at the moment, the energy storage equipment participates in regulation;
(2) determining the energy storage equipment adjustment amount of the energy storage equipment in the power distribution network at 96 prediction points according to the action area of the energy storage equipment in the power distribution network in the step (1), and specifically comprising the following steps:
defining the energy storage regulating quantity of the energy storage equipment at the ith point as
Figure BDA0001898710350000051
The method is characterized by comprising the steps of charging to be positive and discharging to be negative in an electric quantity form, and setting the upper limit of the energy storage capacity of the energy storage equipment to be EmaxLower limit of EminWhen the current energy storage capacity is equal to 0, the current energy storage capacity is EcurrStarting from the point i-1, recording the energy storage adjustment quantity of 96 predicted points successively, and storing the charging adjustment quantity in the energy storage adjustment quantity into a charging sequence Qin-seqThe discharge regulation being stored in a discharge sequence Qout-seqTo Q, pairin-seqAnd Qout-seqThe adjustment quantities in the process are sorted from large to small according to absolute values, and each time corresponding to the charging adjustment quantity and the discharging adjustment quantity is respectively recorded;
(2-1) judging the gateway load of the ith prediction point, if the gateway load is equal to the dead zone value, the energy storage equipment does not act,
Figure BDA0001898710350000052
if the gateway load is equal to the value of the area to be regulated, further judging the gateway load, and if the gateway load is less than or equal to the lower limit PbIf the energy storage equipment is in the state of the power failure, the energy storage equipment records the change of the electric quantity according to the power difference between the gateway load and the lower limit in 15 minutes
Figure BDA0001898710350000053
Namely, it is
Figure BDA0001898710350000054
Step (2-2) is carried out, if the gateway load is greater than or equal to the upper limit PtThe energy storage device follows the upper limit PtRecording the change of electric quantity by the power difference of the gateway load of 15 minutes
Figure BDA0001898710350000055
Namely, it is
Figure BDA0001898710350000056
Figure BDA0001898710350000057
Carrying out the step (2-3);
(2-2) recording the charging adjustment quantity of the energy storage equipment at the ith prediction point, and recording the electric quantity adjustment quantity of the energy storage equipment according to the power difference between the gateway load and the lower limit in 15 minutes
Figure BDA0001898710350000058
Namely, it is
Figure BDA0001898710350000059
Adjust the electric quantity by the quantity
Figure BDA00018987103500000510
And the current electric quantity E of the energy storage devicecurrSum and upper limit E of energy storage capacity of energy storage equipmentmaxIn comparison, if
Figure BDA00018987103500000511
Then adjust the amount of power
Figure BDA00018987103500000512
Storing a charging sequence Qin-seqAnd carrying out the step (2-4) if
Figure BDA00018987103500000513
Performing the step (2-5);
(2-3) recording the discharge adjustment quantity of the energy storage equipment at the predicted point i, and recording the electric quantity adjustment quantity of the energy storage equipment according to the power difference between the upper limit and the 15-minute gateway load
Figure BDA00018987103500000514
Adjust the electric quantity by the quantity
Figure BDA00018987103500000515
And the current electric quantity E of the energy storage devicecurrSum and lower energy storage capacity limit E of energy storage deviceminIn comparison, if
Figure BDA00018987103500000516
Then adjust the amount of power
Figure BDA00018987103500000517
Storing a discharge sequence Qout-seqAnd carrying out the step (2-6) if
Figure BDA00018987103500000518
Performing the step (2-7);
(2-4) charging sequence Qin-seqThe electric quantity adjustment quantity from the 1 st prediction point to the i-1 th prediction point stored in the step (b) is sorted from large to small, and the minimum electric quantity adjustment quantity is recorded as
Figure BDA00018987103500000519
To the same
Figure BDA00018987103500000520
Make a judgment if
Figure BDA00018987103500000521
Figure BDA00018987103500000522
Then the charging sequence Q will bein-seqLast charge regulation from Qin-seqIs deleted and made
Figure BDA00018987103500000523
Repeating the steps until the conditions are met
Figure BDA00018987103500000524
And make the charging sequence Qin-seqThe medium and minimum charge adjustment amounts are:
Figure BDA00018987103500000525
(2-5) regulating the quantity of electricity
Figure BDA00018987103500000526
Charging sequence Qin-seqPerforming the following steps;
(2-6) discharging sequence Qout-seqThe electric quantity regulating quantity from the 1 st forecasting point to the i-1 st forecasting point stored in the step (b) is sorted from small to large, and the minimum electric quantity regulating quantity is recorded as
Figure BDA0001898710350000061
To the same
Figure BDA0001898710350000062
Make a judgment if
Figure BDA0001898710350000063
Figure BDA0001898710350000064
Then discharge sequence Q will be initiatedout-seqFrom Qout-seqIs deleted and made
Figure BDA0001898710350000065
Repeating the steps until the conditions are met
Figure BDA0001898710350000066
And make the discharging sequence Qout-seqThe minimum discharge adjustment amount in (1) is:
Figure BDA0001898710350000067
(2-7) adjusting the quantity of electricity
Figure BDA0001898710350000068
Put into a discharge sequence Qout-seq；
(2-8) judging the predicted point i, if i is smaller than 96, increasing i by 1, returning to the step (2-1) until i is equal to 96, and performing the step (3);
(3) distributing the energy storage equipment adjustment quantity of the energy storage equipment in the power distribution network at 96 prediction points to each energy storage equipment of the power distribution network in a power mode according to the energy storage equipment adjustment quantity of the energy storage equipment in the power distribution network in the step (2), and specifically comprising the following steps:
(3-1) converting the electric quantity regulating quantity of the energy storage equipment at the 96 prediction points into power, wherein the negative power represents charging of the energy storage equipment, the positive power represents discharging of the energy storage equipment, and according to the electric quantity regulating quantity of the energy storage equipment at the ith prediction point, the total regulating power of the energy storage equipment at the ith prediction point is obtained through calculation according to the following formula
Figure BDA0001898710350000069
Figure BDA00018987103500000610
(3-2) regulating the total power of the energy storage equipment at the ith prediction point according to the step (3-1)
Figure BDA00018987103500000611
Calculating and obtaining a charging and discharging regulation instruction of each energy storage device in the power distribution network by using the following formula
Figure BDA00018987103500000612
The method realizes the power distribution network active power scheduling considering the optimization of the charging and discharging times of the energy storage equipment:
Figure BDA00018987103500000613
wherein n is the number of energy storage devices in the power distribution network, EnFor the current capacity of each energy storage device, EnmaxThe maximum capacity of each energy storage device.

Claims (1)

1. A power distribution network active power scheduling method considering energy storage equipment charging and discharging times optimization is characterized by comprising the following steps:
(1) the dispatching planning center of the power distribution network sets the total load predicted value of 96 predicted points of the power distribution network in the future day
Figure FDA0003398850050000011
And the photovoltaic power generation value of a 96 predicted point in the future day in the power distribution network
Figure FDA0003398850050000012
Wherein i is a prediction point, i belongs to (1-96), i is a prediction point in a period of 15 minutes, and a prediction value is obtained according to the total load
Figure FDA0003398850050000013
And photovoltaic power generation value
Figure FDA0003398850050000014
Obtaining an action area of energy storage equipment in the power distribution network, and specifically comprising the following steps:
(1-1) calculation of the Point load predicted by the gateway 96 according to the following equation
Figure FDA0003398850050000015
Figure FDA0003398850050000016
(1-2) predicting Point loads based on the gateway 96
Figure FDA0003398850050000017
Calculating an action area of energy storage equipment in the power distribution network:
Figure FDA0003398850050000018
Pt＝Pavr*1.2
Pb＝Pavr*0.8
wherein, PavrIs the average value of the gateway load, and is the average value P of the gateway loadavrFor the center, an upper limit and a lower limit are respectively set at the upper and lower 20% of the average value of the gateway load, and are marked as PtAnd Pb；
When the load of the gateway is at the upper limit PtAnd a lower limit PbIn between, the load of the gateway is recorded as a dead zone value, and when the load of the gateway is higher than or equal to the upper limit PtOr less than or equal to the lower limit PbRecording the gateway load as a zone value to be regulated;
(2) determining the energy storage equipment adjustment amount of the energy storage equipment in the power distribution network at 96 prediction points according to the action area of the energy storage equipment in the power distribution network in the step (1), and specifically comprising the following steps:
(2-1) judging the gateway load of the ith prediction point, if the gateway load is equal to the dead zone value, the energy storage equipment does not act,
Figure FDA0003398850050000019
if the gateway load is equal to the value of the area to be regulated, further judging the gateway load, and if the gateway load is less than or equal to the lower limit PbIf the energy storage equipment is in the state of the power failure, the energy storage equipment records the change of the electric quantity according to the power difference between the gateway load and the lower limit in 15 minutes
Figure FDA00033988500500000110
Namely, it is
Figure FDA00033988500500000111
Step (2-2) is carried out, if the gateway load is greater than or equal to the upper limit PtThe energy storage device follows the upper limit PtRecording the change of electric quantity by the power difference of the gateway load of 15 minutes
Figure FDA00033988500500000112
Namely, it is
Figure FDA00033988500500000113
Figure FDA00033988500500000114
Carrying out the step (2-3);
(2-2) recording the charging adjustment quantity of the energy storage equipment at the ith prediction point, and recording the electric quantity change of the energy storage equipment according to the power difference between the gateway load and the lower limit in 15 minutes
Figure FDA00033988500500000115
Namely, it is
Figure FDA00033988500500000116
Change the electric quantity
Figure FDA00033988500500000117
And the current electric quantity E of the energy storage devicecurrSum and upper limit E of energy storage capacity of energy storage equipmentmaxIn comparison, if
Figure FDA00033988500500000118
Figure FDA00033988500500000119
Then the electric quantity is changed
Figure FDA00033988500500000120
Storing a charging sequence Qin-seqAnd carrying out the step (2-4) if
Figure FDA0003398850050000021
Performing the step (2-5);
(2-3) recording the discharge adjustment quantity of the energy storage equipment at the predicted point i, and recording the electric quantity change of the energy storage equipment according to the power difference between the upper limit and the 15-minute gateway load
Figure FDA0003398850050000022
Change the electric quantity
Figure FDA0003398850050000023
And the current electric quantity E of the energy storage devicecurrSum and lower energy storage capacity limit E of energy storage deviceminIn comparison, if
Figure FDA0003398850050000024
Then the electric quantity is changed
Figure FDA0003398850050000025
Storing a discharge sequence Qout-seqAnd carrying out the step (2-6) if
Figure FDA0003398850050000026
Performing the step (2-7);
(2-4) charging sequence Qin-seqThe electric quantity adjustment quantity from the 1 st prediction point to the i-1 th prediction point stored in the step (b) is sorted from large to small, and the minimum electric quantity adjustment quantity is recorded as
Figure FDA0003398850050000027
To the same
Figure FDA0003398850050000028
Make a judgment if
Figure FDA0003398850050000029
Figure FDA00033988500500000210
Then the charging sequence Q will bein-seqLast charge regulation from Qin-seqIs deleted and made
Figure FDA00033988500500000211
Repeating the steps until the conditions are met
Figure FDA00033988500500000212
And make the charging sequence Qin-seqThe medium and minimum charge adjustment amounts are:
Figure FDA00033988500500000213
(2-5) regulating the quantity of electricity
Figure FDA00033988500500000214
Charging sequence Qin-seqPerforming the following steps;
(2-6) discharging sequence Qout-seqThe electric quantity regulating quantity from the 1 st forecasting point to the i-1 st forecasting point stored in the step (b) is sorted from small to large, and the minimum electric quantity regulating quantity is recorded as
Figure FDA00033988500500000215
To the same
Figure FDA00033988500500000216
Make a judgment if
Figure FDA00033988500500000217
Figure FDA00033988500500000218
Then discharge sequence Q will be initiatedout-seqFrom Qout-seqIs deleted and made
Figure FDA00033988500500000219
Repeating the steps until the conditions are met
Figure FDA00033988500500000220
And make the discharging sequence Qout-seqThe minimum discharge adjustment amount in (1) is:
Figure FDA00033988500500000221
(2-7) changing the electric quantity
Figure FDA00033988500500000222
Put into a discharge sequence Qout-seq；
(2-8) judging the predicted point i, if i is smaller than 96, increasing i by 1, returning to the step (2-1) until i is equal to 96, and performing the step (3);
(3) distributing the energy storage equipment adjustment quantity of the energy storage equipment in the power distribution network at 96 prediction points to each energy storage equipment of the power distribution network in a power mode according to the energy storage equipment adjustment quantity of the energy storage equipment in the power distribution network in the step (2), and specifically comprising the following steps:
(3-1) converting the electric quantity regulating quantity of the energy storage equipment at the 96 prediction points into power, wherein the negative power represents charging of the energy storage equipment, the positive power represents discharging of the energy storage equipment, and according to the electric quantity regulating quantity of the energy storage equipment at the ith prediction point, the total regulating power of the energy storage equipment at the ith prediction point is obtained through calculation according to the following formula
Figure FDA00033988500500000223
Figure FDA00033988500500000224
(3-2) regulating the total power of the energy storage equipment at the ith prediction point according to the step (3-1)
Figure FDA00033988500500000225
Calculating and obtaining a charging and discharging regulation instruction of each energy storage device in the power distribution network by using the following formula
Figure FDA00033988500500000226
The method realizes the power distribution network active power scheduling considering the optimization of the charging and discharging times of the energy storage equipment:
Figure FDA0003398850050000031
wherein n is the number of energy storage devices in the power distribution network, EnFor the current capacity of each energy storage device, EnmaxThe maximum capacity of each energy storage device.
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Publication number Priority date Publication date Assignee Title
CN111709574B (en) * 2020-06-16 2022-02-22 广东电网有限责任公司 Distributed cluster configuration scheduling method, computer equipment and storage medium
CN112736902B (en) * 2020-12-24 2023-04-04 国网山西省电力公司 STL decomposition-based time series short-term power load prediction method

Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103311942A (en) * 2013-03-18 2013-09-18 国家电网公司 Control method of battery energy storage system for peak clipping and valley filling in distribution network
CN103606967A (en) * 2013-11-26 2014-02-26 华中科技大学 Dispatching method for achieving robust operation of electrical power system
CN103887816A (en) * 2014-02-25 2014-06-25 国家电网公司 Multi-component composite energy storage system grid combination control method based on power prediction
CN104682380A (en) * 2013-12-03 2015-06-03 北京睿能世纪科技有限公司 Power grid load dispatching instruction response method and power grid load dispatching instruction response system
CN106410831A (en) * 2016-11-15 2017-02-15 广东电网有限责任公司茂名供电局 Method and system for active distribution network energy storage configuration
CN107181272A (en) * 2017-05-23 2017-09-19 国网吉林省电力有限公司电力科学研究院 A kind of wind electricity digestion method in utilization energy-storage system lifting peak regulation space
CN107294122A (en) * 2017-04-17 2017-10-24 国网浙江省电力公司电力科学研究院 A kind of mixed energy storage system is layered dynamic control method
CN107482679A (en) * 2017-08-25 2017-12-15 河海大学 Consider the active distribution network Optimization Scheduling a few days ago of energy-storage system discharge and recharge number
CN107623323A (en) * 2017-10-17 2018-01-23 酒泉职业技术学院 Micro-capacitance sensor operation reserve under a kind of Demand Side Response
CN108471130A (en) * 2018-04-25 2018-08-31 合肥工业大学 Meter and the battery energy storage system power allocation scheme of optimization loss

Family Cites Families (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101630840B (en) * 2009-08-12 2011-06-08 电子科技大学 Intelligent control system for microgrid energy
CN102780236B (en) * 2012-08-11 2014-05-21 山东大学 Active optimal control system of wind and light storage combined power generation system and method
CN103475020B (en) * 2013-08-22 2015-05-06 国电联合动力技术有限公司 Method for controlling load following operation of micro-grid
CN104242329B (en) * 2014-09-12 2017-01-11 上海电力学院 Micro-grid hybrid energy storage system power distribution method based on fuzzy control rules
CN104967149B (en) * 2015-06-29 2017-08-25 山东电力研究院 A kind of micro-capacitance sensor wind-light storage model predictive control method
CN105515209B (en) * 2016-01-28 2017-09-22 山东鲁能智能技术有限公司 A kind of micro-capacitance sensor mixed energy storage system and its control method

Patent Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103311942A (en) * 2013-03-18 2013-09-18 国家电网公司 Control method of battery energy storage system for peak clipping and valley filling in distribution network
CN103606967A (en) * 2013-11-26 2014-02-26 华中科技大学 Dispatching method for achieving robust operation of electrical power system
CN104682380A (en) * 2013-12-03 2015-06-03 北京睿能世纪科技有限公司 Power grid load dispatching instruction response method and power grid load dispatching instruction response system
CN103887816A (en) * 2014-02-25 2014-06-25 国家电网公司 Multi-component composite energy storage system grid combination control method based on power prediction
CN106410831A (en) * 2016-11-15 2017-02-15 广东电网有限责任公司茂名供电局 Method and system for active distribution network energy storage configuration
CN107294122A (en) * 2017-04-17 2017-10-24 国网浙江省电力公司电力科学研究院 A kind of mixed energy storage system is layered dynamic control method
CN107181272A (en) * 2017-05-23 2017-09-19 国网吉林省电力有限公司电力科学研究院 A kind of wind electricity digestion method in utilization energy-storage system lifting peak regulation space
CN107482679A (en) * 2017-08-25 2017-12-15 河海大学 Consider the active distribution network Optimization Scheduling a few days ago of energy-storage system discharge and recharge number
CN107623323A (en) * 2017-10-17 2018-01-23 酒泉职业技术学院 Micro-capacitance sensor operation reserve under a kind of Demand Side Response
CN108471130A (en) * 2018-04-25 2018-08-31 合肥工业大学 Meter and the battery energy storage system power allocation scheme of optimization loss

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
Software Design for Short-Term Prediction of Wind Power Generation and Electrical Load in Jilin;Ding Wang，等;《2018 2nd IEEE Advanced Information Management,Communicates,Electronic and Automation Control Conference(IMCEC 2018)》;20180924;274-278页 *
主动配电网储能优化规划;刘波，等;《仪器仪表学报》;20160531;第37卷(第5期);1180-1184页 *
储能***容量优化配置及全寿命周期经济性评估研究综述;李建林，等;《电源学报》;20180731;第16卷(第4期);1-7页 *
微网下风光储预测滚动协调优化策略;王文宾，等;《电力***及其自动化学报》;20151231;第27卷;27-31页 *

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