CN117220356B - Multi-time-scale-based annual loss reduction operation optimization method and system for power transmission network - Google Patents
Multi-time-scale-based annual loss reduction operation optimization method and system for power transmission network Download PDFInfo
- Publication number
- CN117220356B CN117220356B CN202311484412.2A CN202311484412A CN117220356B CN 117220356 B CN117220356 B CN 117220356B CN 202311484412 A CN202311484412 A CN 202311484412A CN 117220356 B CN117220356 B CN 117220356B
- Authority
- CN
- China
- Prior art keywords
- transformer
- optimization
- loss
- loss reduction
- power grid
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000005457 optimization Methods 0.000 title claims abstract description 97
- 230000009467 reduction Effects 0.000 title claims abstract description 81
- 238000000034 method Methods 0.000 title claims abstract description 38
- 230000005540 biological transmission Effects 0.000 title claims abstract description 29
- 238000013486 operation strategy Methods 0.000 claims description 48
- 230000005611 electricity Effects 0.000 claims description 8
- 238000012545 processing Methods 0.000 claims description 6
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 6
- 239000003990 capacitor Substances 0.000 claims description 5
- 230000007935 neutral effect Effects 0.000 claims description 4
- 238000004519 manufacturing process Methods 0.000 claims description 3
- 230000008569 process Effects 0.000 claims description 3
- 230000009471 action Effects 0.000 abstract description 5
- 238000006243 chemical reaction Methods 0.000 abstract 1
- 238000012216 screening Methods 0.000 abstract 1
- 238000004364 calculation method Methods 0.000 description 4
- 230000007774 longterm Effects 0.000 description 4
- 238000009825 accumulation Methods 0.000 description 3
- 238000009826 distribution Methods 0.000 description 3
- 238000004088 simulation Methods 0.000 description 3
- 238000004458 analytical method Methods 0.000 description 2
- 230000006399 behavior Effects 0.000 description 2
- 230000007547 defect Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000005259 measurement Methods 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000010891 electric arc Methods 0.000 description 1
- 238000004134 energy conservation Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000002708 enhancing effect Effects 0.000 description 1
- 230000003137 locomotive effect Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012806 monitoring device Methods 0.000 description 1
- 238000003908 quality control method Methods 0.000 description 1
- 238000009628 steelmaking Methods 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Abstract
The invention discloses a method and a system for optimizing annual loss reduction operation of a power transmission network based on multiple time scales, which relate to the technical field of power transmission networks and have the technical scheme that: based on screening and conversion of QS files of a power transmission network, annual optimal five-stage loss reduction measures and action time scales comprising active loss reduction optimization, AVC loss reduction optimization, power supply path optimization, economic operation of a transformer and additional loss optimization of large user power quality are provided.
Description
Technical Field
The invention relates to the technical field of power transmission networks, in particular to a power transmission network annual loss reduction operation optimization method and system based on multiple time scales.
Background
From the aspect of the running line loss rate of the power grid, the annual representative daily theoretical line loss rate of the power company in each province and the city is between 3% and 7%, and the calculated result is still at a higher level, and has certain loss reduction potential.
At present, all levels of power companies do not have stable, perfect and universal loss reduction tools or systems, and the main problem of loss reduction work is that most loss reduction schemes still stay in a simulation stage, so that the ground verification is difficult in consideration of operation safety and operation cost; secondly, the loss reduction measures do not consider the long-time fluctuation of the load, and the comprehensive economic operation of the season and the long-time scale is difficult to realize; thirdly, the loss reducing measures are single, and the loss reducing potential of the power grid under various loss reducing measures cannot be quantified.
Therefore, how to study and design a multi-time scale-based annual loss reduction operation optimization method and system for a power transmission network, which can overcome the defects, is a problem which needs to be solved in the present day.
Disclosure of Invention
In order to solve the defects in the prior art, the invention aims to provide the annual loss reduction operation optimization method and system for the power transmission network based on multiple time scales, different action time scales are selected by combining with the operation characteristics of the power transmission network and different loss reduction measures, and finally, the optimal operation mode with the lowest annual loss of the power transmission network is realized.
And different action time scales are selected by combining with the operation characteristics of the power grid and different loss reduction measures, so that the annual economic operation comprehensive optimization of the power transmission network is finally realized. Compared with the existing loss reduction research, the method has the characteristics of strong floor-standing property, strong universality and long-term comprehensive optimization, and is applied to floor-standing of two ground municipal power grids.
The technical aim of the invention is realized by the following technical scheme:
in a first aspect, a method for optimizing annual loss reduction operation of a power transmission network based on multiple time scales is provided, which comprises the following steps:
acquiring QS files containing all electrical information during steady-state operation of a power grid in a target power grid, and performing boundary equivalence processing on the target power grid;
acquiring day-ahead prediction data and active upper and lower limits of an adjustable generator, and solving the optimal output of the adjustable generator at the next day hour level by adopting an interior point method and taking the minimum total network loss as an optimization target to obtain a first operation strategy after active loss reduction optimization;
based on the first operation strategy, solving the optimal voltage of the hour level of the central point of the target power grid in the next day by adopting an interior point method and taking the minimum loss of the whole network as an optimization target, and obtaining a second operation strategy after AVC loss reduction optimization;
based on the second operation strategy, determining an optimal power supply mode of a quarter level of the transformer substation by taking the minimum total network loss of the off-grid transformer substation under different loads as an optimization target when the target power grid operates in a typical annual operation mode, and obtaining a third operation strategy;
based on the third operation strategy, determining the optimal operation mode of the monthly level transformer of each level of transformer substation, which cannot generate six or more power grid accidents under the condition of N-1, by stopping the low-load transformer at each level of transformer substation, so as to obtain a fourth operation strategy;
and based on the fourth operation strategy, installing a corresponding compensation device for the electricity utilization user with the power factor not reaching the standard and/or the harmonic wave exceeding the standard, and obtaining a fifth operation strategy serving as a final operation strategy of the target power grid.
Further, the QS file is converted to a matpower computable mpc format using matlab programming.
Further, the QS file contains all electrical information of steady state operation of the target power grid at a corresponding moment.
Further, the second operation strategy after AVC loss reduction optimization specifically includes:
the optimal voltage is issued to the locally controlled secondary AVC;
the transformer tap and the parallel capacitor switching of the region where the secondary AVC is located are controlled, so that the neutral point is maintained at the optimal voltage determined by the tertiary optimization.
Further, the annual typical operation mode comprises a heavy load in a water-rich period, a light load in a water-rich period, a heavy load in a water-free period, a light load in a water-free period and a light load in a water-free period.
Further, the optimal power supply mode is a power supply mode of the transformer substation after being switched by the main power supply mode and the standby power supply mode in actual operation.
Further, constraint conditions of the low-load transformer of each stage of transformer substation through pulling and stopping are as follows:
the transformer substations of 500kV and above do not consider the loss reduction of the low-load transformer when the transformer is started and stopped;
the transformer substation with 3 running transformers configured at 220kV can consider that one transformer is pulled and stopped to reduce loss when in low load, and the rest one transformer is not overloaded under the condition of the transformer N-1 after the transformer substation is pulled and stopped;
the transformer stations with 2 or more running transformers configured at 110-35kV can consider that one transformer is pulled and stopped to reduce loss when in low load, the residual transformers are not overloaded after the pulling and stopping, and six or more power grid accidents can not occur in the transformer stations after the pulling and stopping under the condition of N-1.
Further, the specific process of the pull-stop low-load transformer is as follows:
after transformer stations with various levels capable of considering the pull-stop loss reduction are selected, calculating critical economic load rates of the transformer stations through no-load and short-circuit parameters of transformers in the stations;
and comparing the maximum load predicted value of each transformer substation in the beginning of each month with the critical economic load rate to judge whether the loss is reduced by stopping or not: when the current month maximum load predicted value of the transformer substation is lower than the corresponding critical economic load rate, the transformer substation can be started and stopped for reducing the loss at the beginning of the month; otherwise, no measures of stopping and reducing the loss are taken.
Further, the fifth operating strategy optimized time scale is related to the production behavior of the electricity consumer.
In a second aspect, a multi-time scale based grid annual loss reduction operation optimization system is provided, comprising:
the information acquisition module is used for acquiring QS files containing all electric information during steady-state operation of the power grid in the target power grid and carrying out boundary equivalence processing on the target power grid;
the first optimization module is used for acquiring day-ahead prediction data and the upper and lower active limits of the adjustable generator, and solving the optimal output of the adjustable generator at the next day hour level by adopting an interior point method and taking the minimum total network loss as an optimization target to obtain a first operation strategy after active loss reduction optimization;
the second optimization module is used for solving the optimal voltage of the hour level of the central point of the target power grid in the next day by taking the minimum total network loss as an optimization target by adopting an interior point method based on the first operation strategy to obtain a second operation strategy after AVC loss reduction optimization;
the third optimizing module is used for determining an optimal power supply mode of a quarter level of the transformer substation by taking the minimum total network loss of the off-grid transformer substation under different loads as an optimizing target to obtain a third operating strategy based on the second operating strategy when the target power grid operates in a typical annual operating mode;
the fourth optimizing module is used for determining the optimal operation mode of the monthly-level transformer of each level of transformer substation, which cannot generate six or more power grid accidents under the condition of N-1, by stopping the low-load transformer at each level of transformer substation based on the third operation strategy to obtain a fourth operation strategy;
and the fifth optimizing module is used for installing a corresponding compensating device for electricity users with power factors not reaching standards and/or harmonic wave exceeding standards based on the fourth operating strategy to obtain a fifth operating strategy serving as a final operating strategy of the target power grid.
Compared with the prior art, the invention has the following beneficial effects:
the multi-time-scale-based power transmission network annual loss reduction operation optimization method provided by the invention combines the power transmission network operation characteristics, different action time scales are selected by different loss reduction measures, and finally, the optimal operation mode with the lowest power transmission network annual loss is realized.
Drawings
The accompanying drawings, which are included to provide a further understanding of embodiments of the invention and are incorporated in and constitute a part of this application, illustrate embodiments of the invention. In the drawings:
FIG. 1 is a flow chart in an embodiment of the invention;
FIG. 2 is a schematic diagram of multi-period loss comparison before and after five-stage optimization of a power grid in an embodiment of the invention;
fig. 3 is a system block diagram in an embodiment of the invention.
Detailed Description
For the purpose of making apparent the objects, technical solutions and advantages of the present invention, the present invention will be further described in detail with reference to the following examples and the accompanying drawings, wherein the exemplary embodiments of the present invention and the descriptions thereof are for illustrating the present invention only and are not to be construed as limiting the present invention.
Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more such feature. In the description of the present invention, the meaning of "a plurality" is two or more, unless explicitly defined otherwise.
Example 1: the annual loss reduction operation optimization method for the power transmission network based on the multiple time scales is specifically realized by the following steps as shown in fig. 1.
Step one: and acquiring QS files containing all electrical information during steady-state operation of the power grid in the target power grid, and performing boundary equivalence processing on the target power grid.
The QS file is a result file generated after the actual measurement information state of the 500-35kV power system is estimated. At present, most provincial power grid D5000 systems update and generate a QS file every 15 minutes according to the latest measurement information, wherein the QS file comprises information of power grid reference values, stations, buses, alternating current circuits, generators, transformers, loads, parallel compensation devices, serial compensation devices, converters, direct current circuits, island numbers, nodes, circuit breakers and knife switches 15, so that the actual running condition of any element of the power grid can be accurately reflected, and the QS file is a data base for analysis and application of various power grids. However, due to the fact that the data structure is complex and comprises a plurality of elements, the single QS file occupies a large memory (more than 50M), the trend distribution is not visual, and the like, the problems of long time consumption, difficult convergence of trend calculation and the like exist in various power grid analysis applications according to the QS file, and no example of power grid loss reduction through large-scale QS files is found at present.
In order to facilitate simulation, power flow calculation, optimal power flow calculation and the like on a target power grid, a matlab programming is adopted to convert a QS file into a mpc format which can be calculated by a matpower.
Step two: and acquiring day-ahead prediction data and the active upper and lower limits of the adjustable generator, and solving the optimal output of the adjustable generator at the next day hour level by adopting an interior point method and taking the minimum total network loss as an optimization target to obtain a first operation strategy after active loss reduction optimization.
Specifically, the active power optimization can improve the flow distribution of the whole network, and the influence on the loss of the whole network is maximum, so that the active power loss reduction optimization is used as the first-stage optimization. The time scale for the active loss reduction implementation is on the order of hours. And carrying out active power output optimization calculation for 24 hours per hour on the next day according to the predicted data on the target power grid in the mpc format. By setting the upper and lower limits of the active power of the adjustable generator, the optimal output of the adjustable generator is solved by adopting a matpower self-contained interior point method and the minimum total network loss, and the optimal output is used as the output plan of the adjustable generator in the next day, namely the active power loss reduction optimization in the next day is completed. Daily active optimal operation accumulation realizes annual active optimal operation.
Step three: and solving the optimal voltage of the hour level of the central point of the target power grid in the next day by adopting an interior point method and taking the minimum loss of the whole network as an optimization target based on the first operation strategy, and obtaining a second operation strategy after AVC loss reduction optimization.
Specifically, after active optimization is realized, voltage and reactive power are the largest factors influencing the loss of the whole network, so the invention takes AVC loss reduction optimization as second-stage optimization. The time scale of AVC loss reduction implementation is in the order of hours, and the optimization variable is the central point voltage in the three-level optimization. According to the method, an interior point method is adopted in the day before, the optimal voltage of the central point of the target power grid is solved at the minimum of the total network loss for 24 hours in the next day, and the optimal voltage is issued to the secondary AVC. The secondary AVC is local control, and the neutral point is maintained under the optimal voltage determined by the tertiary optimization by controlling the tap of the transformer in the area and the switching of the parallel capacitor, so that the AVC loss reduction optimization in the next day is completed. The annual AVC optimal operation is realized through the daily AVC optimal operation accumulation.
Step four: and based on the second operation strategy, determining an optimal power supply mode of the quarter level of the transformer substation by taking the minimum total network loss of the off-grid transformer substation under different loads as an optimization target when the target power grid operates in a typical annual operation mode, and obtaining a third operation strategy.
Specifically, the power supply path optimization, namely network reconstruction, is an important tool for realizing the economic operation of the power grid, and the power loss, balance overload and the like of the whole power grid can be reduced only by changing the states of part of switches without additional equipment, so that the power supply path optimization is used as third-stage optimization after the active output of the generator and the three-stage neutral point voltage of the AVC are realized.
In order to ensure the power supply reliability, a transformer substation with the electric quantity in the off-grid mode usually comprises a main power supply mode and a standby power supply mode in actual operation, and a line switch of the main power supply mode is closed in normal operation, and the line switch of the standby power supply mode is in a hot standby state. The level optimization is to determine what power supply mode the off-grid substation adopts to minimize the total network loss when the power grid is in a typical annual operation mode and different loads of the off-grid substation.
The time scale for the optimized implementation of the power supply path is generally in the quarter level, and is related to the typical operation mode of the power grid and the load of the transformer substation. Firstly, QS files of a target power grid in the last year are acquired, and the typical operation mode of the power grid is analyzed through clustering. Taking a Sichuan power grid as an example, typical annual operation modes comprise heavy load in a water-rich period, light load in a water-rich period, heavy load in a water-withered period, light load in a water-withered period and light load in a water-withered period 6 types. After dividing a typical operation mode of a power grid year, calculating an optimal power supply mode of an off-grid transformer substation of a target power grid under different loads. For a determined power grid typical operation mode, the off-grid load of a transformer substation is gradually increased from 0 to 1.5 times of the annual maximum load in a fixed step length, and the power supply loss of the main and standby modes under different loads is compared, so that the optimal power supply mode under different loads is obtained. And repeating the process for different typical operation modes of the power grid until the optimal power supply mode of all the typical operation modes of the power grid under different loads of the transformer substation is obtained. When the power grid actually operates, the optimal power supply path is selected by identifying the power grid operation mode and the actual load of the transformer substation, and the annual whole-grid power supply path can be optimal.
Step five: based on the third operation strategy, determining the optimal operation mode of the monthly-level transformer, which does not cause six or more grid accidents under the condition of N-1, of each level of transformer substation by stopping the low-load transformer, and obtaining a fourth operation strategy.
Specifically, as one of the most important devices in the power grid, the transformer has a loss exceeding 30% in each voltage class ratio, and has a large influence on the loss of the whole power grid. Due to the natural difference of load distribution, the heavy and light load problems of all levels of power grid transformers are increasingly prominent, and economic operation is not facilitated. After the active power loss reduction, AVC loss reduction and power supply path optimization of the power grid are realized, the loss reduction of the pull-stop low-load transformer is continuously adopted as a fourth-stage loss reduction measure under the premise of considering the power supply reliability and the safe operation of the power grid.
Considering the power supply reliability and the safe operation of a power grid, the conditions of each stage of transformer stations capable of considering the loss reduction of the low-load transformer by pulling and stopping are as follows: 1) The safe operation requirement of the transformer substation of 500kV and above is high, and the loss reduction of the low-load transformer is not considered when the transformer is stopped; 2) The transformer substation with 3 running transformers in 220kV configuration can consider the loss reduction of one transformer when in low load, and the premise is that the transformer is provided with spare power automatic switching protection and can be rapidly put into operation. The transformer station is not overloaded under the condition of the transformer N-1 after the transformer station is stopped; 3) The transformer substation with 2 or more running transformers configured at 110-35kV can consider the loss reduction of one transformer when in low load, and the premise is that the transformer is provided with spare power automatic switching protection and can be rapidly put into operation. The remaining transformer is not overloaded after the pull-stop. Six-stage or more grid accidents of the transformer substation can not occur under the condition of N-1 after the transformer substation is started and stopped. Wherein N is the total number of operating transformers of the substation.
After transformer stations with the pull-stop loss reduction considered at each stage are selected, the critical economic load rate of each transformer station is calculated through the no-load and short-circuit parameters of the transformers in the station. The implementation scale of the economic operation loss reduction measure of the transformer is of the order of months. And comparing the maximum load predicted value of each transformer substation in the month with the critical economic load rate to judge whether to stop the transformer for reducing the loss, and stopping one transformer for reducing the loss in the month when the maximum load predicted value of each transformer substation in the month is lower than the corresponding critical economic load rate, otherwise, not taking the stop loss reduction measures. And judging whether all substations which can consider the pull-stop loss reduction in the target power grid are pulled to stop and land, and completing the economic operation loss reduction measure of the transformer in the month. Monthly transformer economic operation accumulation realizes the annual economic operation of the transformer.
Step six: and based on the fourth operation strategy, installing a corresponding compensation device for the electricity utilization user with the power factor not reaching the standard and/or the harmonic wave exceeding the standard, and obtaining a fifth operation strategy serving as a final operation strategy of the target power grid.
Specifically, after the active optimization, the AVC three-level central point voltage optimization, the power supply path optimization and the transformer economic operation four-level loss reduction measures are applied to the target power grid, the current level optimization is optimized for local additional loss caused by the power quality problem generated by large users in the target power grid, such as electrified locomotives, steelmaking electric arc furnaces and the like.
The influence of large users on the power grid loss is mainly reflected in additional loss caused by low circuit power factor and harmonic waves. In order to ensure the electric energy quality of the whole power grid, an electric energy quality monitoring device is generally installed at a large user and power grid connection gateway, and the time scale of electric energy quality control is related to the production behaviors of users. The invention calculates the average power factor of the line month sent by the user through QS files, and negotiates with the user to install a compensation device such as a parallel capacitor and the like aiming at the condition of high line loss caused by the too low power factor. And for the users with the overtime harmonic wave detected for many times, negotiating with the users to install the harmonic wave compensation device, adopting the power electronic technology to restrain harmonic waves, and enhancing the power quality monitoring to reduce the additional loss. The annual power quality additional loss is minimum by improving the annual average power factor of the outgoing line of the user and reducing the annual harmonic generation times.
According to the invention, through modifying the simulation five-stage optimization of generator output, transformer tap transformation ratio, capacitor switching, line switching state, transformer switching state and the like in the target power grid mpc, the power flow and power grid loss before and after five-stage optimization at 8760 whole points in the target power grid year are calculated, the loss after optimization is subtracted from the loss before optimization to obtain five-stage optimized loss-reducing electric quantity at the moment, and the loss-reducing electric quantity at 8760 times in the year is accumulated to obtain five-stage optimized loss-reducing electric quantity.
The loss reduction, the landing and the monitoring are carried out on the transmission network in the actual region according to the invention, and the line loss, the transformer loss and the total loss of the network before and after the five-level optimization implementation are calculated by depending on the QS file at a plurality of moments are shown in figure 2.
By accumulating the loss values at multiple moments in the graph 2 as shown in the table 1, it can be seen that under the premise of considering the power supply reliability and the operation safety, the total loss of the power grid can be reduced by 6.91 percent after the five-stage loss reduction optimization of the power grid, by means of the invention, the long-term operation loss reduction potential of the power grid is excavated, the corresponding loss reduction measures are landed, and the long-term economic operation and energy conservation loss reduction of the power grid are realized.
Table 1 five-level optimization loss reduction effect
Example 2: the system for optimizing the annual loss reduction operation of the power transmission network based on the multiple time scales is used for realizing the annual loss reduction operation optimization method of the power transmission network based on the multiple time scales described in the embodiment 1, and as shown in fig. 3, the system comprises an information acquisition module, a first optimization module, a second optimization module, a third optimization module, a fourth optimization module and a fifth optimization module.
The information acquisition module is used for acquiring QS files containing all electric information during steady-state operation of the power grid in the target power grid and carrying out boundary equivalence processing on the target power grid; the first optimization module is used for acquiring day-ahead prediction data and the upper and lower active limits of the adjustable generator, and solving the optimal output of the adjustable generator at the next day hour level by adopting an interior point method and taking the minimum total network loss as an optimization target to obtain a first operation strategy after active loss reduction optimization; the second optimization module is used for solving the optimal voltage of the hour level of the central point of the target power grid in the next day by taking the minimum total network loss as an optimization target by adopting an interior point method based on the first operation strategy to obtain a second operation strategy after AVC loss reduction optimization; the third optimizing module is used for determining an optimal power supply mode of a quarter level of the transformer substation by taking the minimum total network loss of the off-grid transformer substation under different loads as an optimizing target to obtain a third operating strategy based on the second operating strategy when the target power grid operates in a typical annual operating mode; the fourth optimizing module is used for determining the optimal operation mode of the monthly-level transformer of each level of transformer substation, which cannot generate six or more power grid accidents under the condition of N-1, by stopping the low-load transformer at each level of transformer substation based on the third operation strategy to obtain a fourth operation strategy; and the fifth optimizing module is used for installing a corresponding compensating device for electricity users with power factors not reaching standards and/or harmonic wave exceeding standards based on the fourth operating strategy to obtain a fifth operating strategy serving as a final operating strategy of the target power grid.
Working principle: the invention combines the power grid operation characteristics, selects different action time scales by different loss reduction measures, finally realizes the optimal operation mode with the lowest annual loss of the power grid, has the characteristics of strong landability, strong universality and long-term comprehensive optimization compared with the existing loss reduction research, and is applied to the landing of two ground utility power grids.
The foregoing description of the embodiments has been provided for the purpose of illustrating the general principles of the invention, and is not meant to limit the scope of the invention, but to limit the invention to the particular embodiments, and any modifications, equivalents, improvements, etc. that fall within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (10)
1. The annual loss reduction operation optimization method for the power transmission network based on the multiple time scales is characterized by comprising the following steps of:
acquiring QS files containing all electrical information during steady-state operation of a power grid in a target power grid, and performing boundary equivalence processing on the target power grid;
acquiring day-ahead prediction data and active upper and lower limits of an adjustable generator, and solving the optimal output of the adjustable generator at the next day hour level by adopting an interior point method and taking the minimum total network loss as an optimization target to obtain a first operation strategy after active loss reduction optimization;
based on the first operation strategy, solving the optimal voltage of the hour level of the central point of the target power grid in the next day by adopting an interior point method and taking the minimum loss of the whole network as an optimization target, and obtaining a second operation strategy after AVC loss reduction optimization;
based on the second operation strategy, determining an optimal power supply mode of a quarter level of the transformer substation by taking the minimum total network loss of the off-grid transformer substation under different loads as an optimization target when the target power grid operates in a typical annual operation mode, and obtaining a third operation strategy;
based on the third operation strategy, determining the optimal operation mode of the monthly level transformer of each level of transformer substation, which cannot generate six or more power grid accidents under the condition of N-1, by stopping the low-load transformer at each level of transformer substation, so as to obtain a fourth operation strategy;
and based on the fourth operation strategy, installing a corresponding compensation device for the electricity utilization user with the power factor not reaching the standard and/or the harmonic wave exceeding the standard, and obtaining a fifth operation strategy serving as a final operation strategy of the target power grid.
2. The multi-time scale based grid annual loss reduction operation optimization method of claim 1, wherein the QS file is converted to a matpower computable mpc format using matlab programming.
3. The multi-time scale based annual loss reduction operation optimization method of a power transmission network according to claim 1, wherein the QS file contains all electrical information of steady state operation of a target power transmission network at corresponding moments.
4. The multi-time scale-based transmission grid annual loss reduction operation optimization method according to claim 1, wherein the second operation strategy after AVC loss reduction optimization is specifically:
the optimal voltage is issued to the locally controlled secondary AVC;
the transformer tap and the parallel capacitor switching of the region where the secondary AVC is located are controlled, so that the neutral point is maintained at the optimal voltage determined by the tertiary optimization.
5. The multi-time scale based annual loss reduction operation optimization method for a power transmission network according to claim 1, wherein the annual typical operation mode comprises a heavy load in a water-rich period, a light load in a water-rich period, a heavy load in a water-free period, a light load in a water-free period and a light load in a water-free period.
6. The multi-time scale-based annual loss reduction operation optimization method for the power transmission network according to claim 1, wherein the optimal power supply mode is a power supply mode obtained by switching a main power supply mode and a standby power supply mode when a transformer substation is actually operated.
7. The multi-time scale-based annual loss reduction operation optimization method for power transmission networks according to claim 1, wherein the constraint conditions of the low-load transformer passing through the pull-stop transformer of each stage of transformer substation are as follows:
the transformer substations of 500kV and above do not consider the loss reduction of the low-load transformer when the transformer is started and stopped;
220kV configures 3 transformer substations of running transformers to stop one transformer to reduce loss when in low load, and the rest one transformer is not overloaded under the condition of the transformer N-1 after stopping;
and 2 or more transformer substations with 110-35kV configuration are used for pulling and stopping one transformer to reduce loss when in low load, the residual transformers are not overloaded after pulling and stopping, and six or more power grid accidents can not occur in the transformer substations after pulling and stopping under the condition of N-1.
8. The multi-time scale-based annual loss reduction operation optimization method for a power transmission network according to claim 1, wherein the specific process of stopping the low-load transformer is as follows:
after each level of transformer stations with pull-stop loss reduction is selected, calculating critical economic load rates of all the transformer stations through no-load and short-circuit parameters of transformers in the stations;
and comparing the maximum load predicted value of each transformer substation in the beginning of each month with the critical economic load rate to judge whether the loss is reduced by stopping or not: when the current month maximum load predicted value of the transformer substation is lower than the corresponding critical economic load rate, the transformer substation is started and stopped at the beginning of the month to reduce the loss; otherwise, no measures of stopping and reducing the loss are taken.
9. The multi-time scale based grid annual loss reduction operation optimization method in accordance with claim 1, wherein the time scale of the fifth operation strategy optimization is related to the production behavior of the electricity consumer.
10. The utility model provides a transmission network annual loss reduction operation optimizing system based on many timescales which characterized in that includes:
the information acquisition module is used for acquiring QS files containing all electric information during steady-state operation of the power grid in the target power grid and carrying out boundary equivalence processing on the target power grid;
the first optimization module is used for acquiring day-ahead prediction data and the upper and lower active limits of the adjustable generator, and solving the optimal output of the adjustable generator at the next day hour level by adopting an interior point method and taking the minimum total network loss as an optimization target to obtain a first operation strategy after active loss reduction optimization;
the second optimization module is used for solving the optimal voltage of the hour level of the central point of the target power grid in the next day by taking the minimum total network loss as an optimization target by adopting an interior point method based on the first operation strategy to obtain a second operation strategy after AVC loss reduction optimization;
the third optimizing module is used for determining an optimal power supply mode of a quarter level of the transformer substation by taking the minimum total network loss of the off-grid transformer substation under different loads as an optimizing target to obtain a third operating strategy based on the second operating strategy when the target power grid operates in a typical annual operating mode;
the fourth optimizing module is used for determining the optimal operation mode of the monthly-level transformer of each level of transformer substation, which cannot generate six or more power grid accidents under the condition of N-1, by stopping the low-load transformer at each level of transformer substation based on the third operation strategy to obtain a fourth operation strategy;
and the fifth optimizing module is used for installing a corresponding compensating device for electricity users with power factors not reaching standards and/or harmonic wave exceeding standards based on the fourth operating strategy to obtain a fifth operating strategy serving as a final operating strategy of the target power grid.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311484412.2A CN117220356B (en) | 2023-11-09 | 2023-11-09 | Multi-time-scale-based annual loss reduction operation optimization method and system for power transmission network |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311484412.2A CN117220356B (en) | 2023-11-09 | 2023-11-09 | Multi-time-scale-based annual loss reduction operation optimization method and system for power transmission network |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117220356A CN117220356A (en) | 2023-12-12 |
| CN117220356B true CN117220356B (en) | 2024-01-16 |
Family
ID=89044837
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311484412.2A Active CN117220356B (en) | 2023-11-09 | 2023-11-09 | Multi-time-scale-based annual loss reduction operation optimization method and system for power transmission network |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117220356B (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104158199A (en) * | 2014-08-05 | 2014-11-19 | 广西电网有限责任公司钦州供电局 | System and method for reactive voltage optimal control of real-time status of power system |
| CN107093893A (en) * | 2017-02-16 | 2017-08-25 | 中国电力科学研究院 | The power voltage control method for coordinating and device of a kind of DC distribution net |
| US9811061B1 (en) * | 2001-05-18 | 2017-11-07 | The Energy Authority, Inc. | Method for management and optimization of hydropower generation and consumption |
| CN114069646A (en) * | 2021-10-29 | 2022-02-18 | 国网安徽省电力有限公司电力科学研究院 | Reactive compensation optimization method based on transformer substation operation data |
| CN116054179A (en) * | 2023-01-04 | 2023-05-02 | 武汉大学 | Event-triggering-based reactive power preference control system and method for power system |
-
2023
- 2023-11-09 CN CN202311484412.2A patent/CN117220356B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9811061B1 (en) * | 2001-05-18 | 2017-11-07 | The Energy Authority, Inc. | Method for management and optimization of hydropower generation and consumption |
| CN104158199A (en) * | 2014-08-05 | 2014-11-19 | 广西电网有限责任公司钦州供电局 | System and method for reactive voltage optimal control of real-time status of power system |
| CN107093893A (en) * | 2017-02-16 | 2017-08-25 | 中国电力科学研究院 | The power voltage control method for coordinating and device of a kind of DC distribution net |
| CN114069646A (en) * | 2021-10-29 | 2022-02-18 | 国网安徽省电力有限公司电力科学研究院 | Reactive compensation optimization method based on transformer substation operation data |
| CN116054179A (en) * | 2023-01-04 | 2023-05-02 | 武汉大学 | Event-triggering-based reactive power preference control system and method for power system |
Non-Patent Citations (5)
| Title |
|---|
| Multi-time Scale Optimal Power Flow Strategy for Medium-voltage DC Power Grid Considering Different Operation Modes;Jianqiang Liu 等;《JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY》;第8卷(第1期);46-54 * |
| 含风电场的交直流互联电力系统网省协调有功调度优化方法;陆文甜;林舜江;刘明波;黄庶;杨柳青;;电力系统自动化(07);89-96 * |
| 基于模糊决策法的10kV变压器组经济运行;王建元;韩鑫泽;;水电能源科学(03);188-192 * |
| 大规模风电接入电网的无功协调降损方法;郭鹏 等;《系统仿真学报》;第29卷(第1期);190-199 * |
| 山东电网无功配置规划及优化方案的研究;沙志成;徐大鹏;赵兰明;;电气应用(18);28-30 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN117220356A (en) | 2023-12-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US8531173B2 (en) | System and method for operating a tap changer | |
| Agüero et al. | Integration challenges of photovoltaic distributed generation on power distribution systems | |
| CN107492908B (en) | Feeder line optimization planning method based on distributed power supply access | |
| CN103606932B (en) | The low voltage dynamic reactive-power compensation capacitor autocontrol method that load is relevant | |
| Anzalchi et al. | High-penetration grid-tied photovoltaics: Analysis of power quality and feeder voltage profile | |
| CN103518169A (en) | Distributed control of dynamic reactive power | |
| CN107516903B (en) | Accurate load control method considering economy and safety and stability of multiple time scales | |
| Hernando-Gil et al. | Impact of DG and energy storage on distribution network reliability: A comparative analysis | |
| Anzalchi et al. | Power quality and voltage profile analyses of high penetration grid-tied photovoltaics: A case study | |
| Bollen et al. | Is there a place for power quality in the smart grid? | |
| Radosavljević | Voltage regulation in LV distribution networks with PV generation and battery storage | |
| Leisse et al. | Coordinated voltage control in medium and low voltage distribution networks with wind power and photovoltaics | |
| CN117220356B (en) | Multi-time-scale-based annual loss reduction operation optimization method and system for power transmission network | |
| Akhtar et al. | Voltage control in LV networks using electric springs with coordination | |
| Chintakindi et al. | PMU-based real-time load balancing strategy for lights-out case in India–a case study | |
| CN112633605A (en) | Urban distribution network planning method | |
| Cai et al. | Multi-objective Dynamic Reactive Power Optimization Based on OLTC and Reactive Power Compensation | |
| Jin et al. | Research on optimal power flow of active distribution network based on soft open point | |
| Distribution | Distribution System Operability Framework | |
| Peng et al. | Evaluation and analysis of distributed photovoltaic carrying capacity of power grid based on big data technology | |
| Jiang et al. | Compensation Algorithm for Voltage Dip at Transmission End of Distribution Network Considering Uncertainty of Wind Power | |
| Zhou et al. | Research on Energy Storage-Supported Distributed PV Absorption Method Based on Net Load Characteristics | |
| Ziyat et al. | Real-time Reactive Power Compensation by Distributed Generation Simulated using GridLAB-D and PSIM | |
| CN113890009B (en) | Optimized matching method for outgoing line of 220kV transformer substation | |
| Chen et al. | A comprehensive energy saving potential evaluation method for the distribution networks |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |