CN111932400A - Wind/storage integrated power scheduling plan optimization implementation method - Google Patents
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Abstract
The invention relates to the technical field of micro-grid dispatching of an electric power system, in particular to a wind/storage integrated power dispatching plan optimization implementation method, which comprises the steps of firstly, acquiring a regional numerical weather forecast value and an actual wind speed parameter relation of a fan position in a trial operation stage in the operation of a single discrete wind generating set without a wind measuring tower, acquiring a data relation model by a multi-grid analysis algorithm based on finite element analysis, and performing weather forecast on short-term and ultra-short-term fan mounting points; then, short-term and ultra-short-term wind power prediction is carried out by means of limited local weather forecast and factory-leaving experimental parameters of the wind turbine generator, and generated power prediction is adopted to be stabilized through fluctuation to serve as reported grid-connected power planning data, so that smoothness of grid-connected power fluctuation is guaranteed; and secondly, calculating the power plan deviation in real time by using the lag inertial response of the wind generating set and the wind speed signal actually detected by the fan, dynamically setting the energy storage system, participating in the dynamic compensation of the power plan deviation, and ensuring the accuracy of the plan.
Description
Technical Field
The invention relates to the technical field of micro-grid dispatching of an electric power system, in particular to a wind/storage integrated power dispatching plan optimization implementation method.
Background
All countries in the world advocate vigorous development and utilization of new energy technology, unstable output of wind power generation brings great difficulty to grid-connected power generation, and large fluctuation of grid-connected wind power and large deviation of plan forecast always restrict smooth realization of grid-connected power generation of wind turbine generators. All countries in the world require that the installed projects with extra large power need to carry out day-ahead power prediction, 15 minutes are taken as time intervals, and if the prediction error exceeds the limit, the wind power station needs to pay penalty to a power grid company. In China, in order to standardize the construction of a power grid dispatching mechanism and a wind power plant power prediction system, the national power grid company and the energy bureau issue standard standards such as wind power prediction system function specification (QGDW10588-2015), wind power prediction system anemometer tower data measurement technical requirement (NB/T31079-2016) and the like in sequence, the functions of the wind power plant power prediction system are specified, and the prediction accuracy is strictly quantized.
The conventional wind power plant grid-connected power generation power forecast data directly come from information acquired by field prediction of a wind power plant and are directly reported to a power grid for dispatching as forecast data. However, the absolute value of the existing predicted power error is still very large along with the increase of the installed capacity, and the predicted data is directly reported to the power grid, so that the generalized operation cost of the power grid is correspondingly increased due to the fact that the power output fluctuation of the wind power plant is responded by the power grid, the power quality of the power supply of the whole power grid is influenced by the wind power generation grid-connected power which fluctuates greatly, and even the electric equipment of a user is damaged. Therefore, the power management department can only ensure the stable operation of the power grid by limiting the proportion of the wind power generation to the power generation amount of the whole power grid. Part of wind power generation equipment has to 'abandon wind', and a lot of green resources are wasted invisibly; on the contrary, the coal power which is unfavorable for environmental protection and can be used continuously has a high power generation capacity in the proportion of the power grid due to the stable output. The wind power integration forecast with high accuracy can ensure the reliable implementation of the dispatching plan.
The flexible handling characteristic of the energy storage technology can fully play the problems of grid-connected power fluctuation stabilization and plan deviation compensation in the application of the wind power generation field. The accuracy of plan (especially ultra-short-term plan) forecasting is improved, the wind power generation is ensured to effectively participate in power dispatching, the power generation priority is obtained, and the problem of new energy consumption is solved.
If the wind power prediction data is directly used for forecasting, intermittent fluctuation is not beneficial to the healthy and stable operation of the power grid. In order to reduce the negative influence of the wind power generation grid-connected electric energy quality on a power grid, a forecasting curve with low fluctuation rate is designed based on actual power forecasting data, and then the forecasting deviation is corrected by means of energy storage throughput, so that the actual grid-connected power smoothly approaches the forecasting data, and the friendly grid connection of wind power generation is realized.
Disclosure of Invention
Aiming at the problems, the invention provides a wind/storage integrated power scheduling plan optimization implementation method, which improves the smoothness and the scheduling accuracy of wind power grid-connected power fluctuation, realizes forecast optimization, maintains the balance of supply and demand of a power grid, effectively avoids the scheduling problem caused by the access of a large proportion of wind power to the power grid, reduces the scheduling reserve capacity of the power grid to a certain extent, and enhances the wind power grid-connected operation capacity.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
the wind/storage integrated power scheduling plan optimization implementation method comprises the following steps:
step 3, calculating power plan deviation in real time by using lag inertial response of the wind generating set and a wind speed signal actually detected by a fan, dynamically setting an energy storage system, participating in dynamic compensation of the power plan deviation, and ensuring the accuracy of the plan;
and 4, the power plan deviation is realized through the control of a converter between the energy storage system and the power grid, the actual effect of deviation compensation is fed back to the input end in real time, and the ultra-short-term power plan is adjusted in real time by combining the energy condition of the energy storage system, so that the power plan tracking is realized.
Preferably, the step 3 includes the following steps:
step 3-1, the energy storage configuration is that forecast deviation data is counted according to grid-connected power forecast data and sampled actual power data in a trial operation stage;
3-2, connecting the lithium battery and the super capacitor in parallel in the energy storage system, connecting the lithium battery with the bidirectional direct current converter in series, and then connecting the lithium battery with the super capacitor in parallel, maintaining the voltage at two ends of the super capacitor to be stable by the battery energy storage system, and maintaining the voltage of a bus to be constant while the hybrid energy storage system responds to the handling of power;
and 3-3, adjusting the initial energy storage configuration in a repeated experiment, expanding the energy storage capacity configuration requirement through a series-parallel circuit structure, and determining a configuration optimal value through daily cycle operation and real-time grid-connected power deviation feedback according to the variation condition of deviation accumulated data.
Meanwhile, it should be noted that the wind/storage integrated power scheduling plan optimization implementation method is applicable to a distributed power generation system without a anemometer tower and with less sample data, the method is carried out under the condition that the energy storage capacity meets the requirement, and the problem of overcharge and overdischarge can be solved by adopting a standby energy storage configuration mode under the condition that the initial energy storage capacity is uncertain.
The invention has the following beneficial effects:
1. the wind/storage combination is adopted, the method that the original wind power forecast data is directly taken from wind speed forecast and historical information is improved, the fluctuation rate inhibition is considered, meanwhile, the accuracy and the smoothness of the existing method can be further improved by using the throughput energy compensation of an energy storage system, the wind power generation is converted from inferior resources into high-quality resources capable of replacing coal power, the wind power grid-connected dispatching is more reasonable in practical application, the grid-connected operation is more stable, and the penalty problem caused by inaccurate forecast can be solved;
2. the method can fully utilize local wind power resources in the process of establishing and executing the grid-connected forecast, avoids the occurrence of wind abandoning and electricity limiting events as much as possible, and avoids the waste problem caused by the remote transmission of electric energy;
3. the method has certain value to power generation enterprises and power systems, and accurate daily forecast can help the power systems to better determine the optimal starting delay or switching-out time and starting mode of the traditional generator set, maintain the optimal efficiency of the generator set, save fuel and reduce the operation cost of a power plant; and the forecast of 1-2 hours can better help a power grid dispatching department to determine the regulation capacity of the power grid.
Drawings
FIG. 1 is a schematic workflow diagram of the present invention;
FIG. 2 is a schematic diagram of the actual power, predicted power and planned power curves of the power generation assembly of the present invention;
FIG. 3 is a schematic diagram of a battery and supercapacitor power distribution for planned deviation correction according to the present invention;
FIG. 4 is a schematic diagram of the change in actual throughput power versus capacity of the battery for plan bias correction according to the present invention;
FIG. 5 is a schematic diagram of the ultracapacitor throughput power versus capacity change for planning bias correction in accordance with the present invention.
Detailed Description
The technical solution of the present invention is described below with reference to the accompanying drawings and examples.
The invention relates to a wind/storage integrated power scheduling plan optimization implementation method, which comprises the following steps:
referring to fig. 1, step 1, a wind tower-free discrete single wind generating set is adopted to perform trial operation, generated power prediction is mainly input into wind direction, wind speed, humidity and pressure of atmosphere at a blade point, in the trial operation stage, an actual anemoscope configured on a fan body is used for obtaining an actual wind speed parameter relation between a regional numerical weather forecast value and a fan position, and a multi-grid analysis algorithm based on finite element analysis is used for obtaining a data relation model, so that weather forecast data of short-term and ultra-short-term fan mounting points are obtained.
Referring to fig. 1 and 2, in step 2, performing short-term and ultra-short-term wind power prediction on the weather forecast data and factory experimental parameters of the wind turbine generator, and using the generated power prediction as reported grid-connected power plan data through fluctuation stabilization to ensure the smoothness of grid-connected power fluctuation;
the actual operation parameters of the model operation of the wind turbine are from factory data, the predicted wind speed data of the fan installation position are used as the input of the wind turbine, the wind power data are predicted by machine learning, the predicted data are used as the planned forecast data of future wind power grid-connected power generation after fluctuation stabilization, the planned forecast data are used as the control target of hardware, and the smoothness of future actual grid-connected power fluctuation can be guaranteed at the later stage.
Referring to fig. 1 and 3, in step 3, calculating power plan deviation in real time by using lag inertial response of a wind generating set and a wind speed signal actually detected by a fan, dynamically setting an energy storage system, participating in dynamic compensation of the power plan deviation, and ensuring the accuracy of the plan;
the forecasting optimization realization technology fully utilizes the inertia response time of the wind turbine generator, firstly, the actual value monitored by wind speed is used for calculating the corresponding wind power actual output power, the energy storage participates in the deviation regulation process, the ultra-short-period wind storage system grid-connected power plan is compared with the actual power output by the fan system, the planned deviation power value is used as the given value of the converter, the pulse duty ratio controlled by the converter switch is calculated according to the current energy storage condition of an energy storage element in the converter system, the actual output power condition of wind power generation, the grid-connected generation power of the wind storage system and the voltage and current parameters of a power grid, the target value is controlled by combining the energy storage dynamic charge state and the energy storage voltage and current parameters, the energy throughput of the energy storage system is controlled, the grid-connected power plan forecasting.
Step 4, the power plan deviation is realized through the control of a converter between the energy storage system and the power grid, the actual effect of deviation compensation is fed back to the input end in real time, and the ultra-short-term power plan is adjusted in real time by combining the energy condition of the energy storage system, so that the power plan tracking is realized;
the power plan can be properly adjusted by referring to the energy storage state, the error condition of actual power deviation compensation is calculated after deviation compensation execution of each sampling period is finished, the error condition is fed back to the input end and the energy storage energy management system in real time, the plan is reasonably adjusted according to the state of the energy storage system, and the energy storage system does not work beyond the limit under the condition of realizing plan tracking as much as possible.
Referring to fig. 1, 4 and 5, the step 3 includes the following steps:
step 3-1, the energy storage configuration is that forecast deviation data is counted according to grid-connected power forecast data and sampled actual power data in a trial operation stage; the power deviation time integral is used as a data statistical reference for planning deviation compensation energy storage demand configuration, and the upper envelope curve and the lower envelope curve of an integral data change curve are used as energy storage capacity upper and lower limit reference thresholds.
And 3-2, considering the intermittent change of wind power generation, wherein large impact harmonic waves need to be quickly absorbed by an energy storage system, the energy storage system adopts a lithium battery and a super capacitor to be connected in parallel, the lithium battery is firstly connected with a bidirectional direct current converter in series and then connected with the super capacitor in parallel, the voltage at two ends of the super capacitor is kept stable by the battery energy storage system, and the voltage of a bus is kept constant while the hybrid energy storage system responds to the handling of power.
And 3-3, adjusting the initial energy storage configuration in repeated experiments, expanding the configuration requirement of energy storage capacity through a series-parallel circuit structure, adding a standby mode to prevent overcharge and overdischarge according to the change condition of deviation accumulated data, gradually changing the mode of formal configuration from a switched-in standby energy storage system along with the time lapse, correcting the capacity, and determining the optimal configuration value through daily cycle operation and real-time grid-connected power deviation feedback.
In addition, it should be noted that the hybrid energy storage system mainly serves as a direct current source, power deviation is realized through control of a converter between the energy storage system and a power grid, the actual effect of deviation compensation is fed back to an input end in real time, and the ultra-short-term power plan is adjusted in real time by combining the energy condition of the energy storage system, so that power plan tracking is realized. Meanwhile, the energy storage capacity configuration requirement is adjusted through the actual power prediction deviation integral change range of machine learning.
In conclusion, the overall design of the invention solves the problem of non-scheduling caused by inaccurate wind power plan, improves the smoothness and the planning accuracy of wind power grid-connected power fluctuation, realizes forecast optimization, maintains the balance of supply and demand of a power grid, effectively avoids the scheduling problem caused by the access of a large proportion of wind power to the power grid, reduces the scheduling reserve capacity of the power grid to a certain extent and enhances the wind power grid-connected operation capacity.
While one embodiment of the present invention has been described in detail, the description is only a preferred embodiment of the present invention and should not be taken as limiting the scope of the invention. All equivalent changes and modifications made within the scope of the present invention shall fall within the scope of the present invention.
Claims (2)
1. The wind/storage integrated power scheduling plan optimization implementation method is characterized by comprising the following steps: the method comprises the following steps:
step 1, adopting a single discrete wind generating set without a wind measuring tower to perform trial operation, acquiring a regional numerical weather forecast value and an actual wind speed parameter relation of a fan position through an actual anemometer configured on a fan body in the trial operation stage, and acquiring a data relation model through a multi-grid analysis algorithm based on finite element analysis so as to acquire weather forecast data of short-term and ultra-short-term fan mounting points;
step 2, carrying out short-term and ultra-short-term wind power prediction on the weather forecast data and the factory-leaving experimental parameters of the wind turbine generator, and using the generated power prediction as reported grid-connected power plan data after fluctuation stabilization to ensure the smoothness of grid-connected power fluctuation;
step 3, calculating power plan deviation in real time by using lag inertial response of the wind generating set and a wind speed signal actually detected by a fan, dynamically setting an energy storage system, participating in dynamic compensation of the power plan deviation, and ensuring the accuracy of the plan;
and 4, the power plan deviation is realized through the control of a converter between the energy storage system and the power grid, the actual effect of deviation compensation is fed back to the input end in real time, and the ultra-short-term power plan is adjusted in real time by combining the energy condition of the energy storage system, so that the power plan tracking is realized.
2. The wind/storage integrated power scheduling plan optimization implementation method according to claim 1, wherein: the step 3 comprises the following steps:
step 3-1, the energy storage configuration is that forecast deviation data is counted according to grid-connected power forecast data and sampled actual power data in a trial operation stage;
3-2, connecting the lithium battery and the super capacitor in parallel in the energy storage system, connecting the lithium battery with the bidirectional direct current converter in series, and then connecting the lithium battery with the super capacitor in parallel, maintaining the voltage at two ends of the super capacitor to be stable by the battery energy storage system, and maintaining the voltage of a bus to be constant while the hybrid energy storage system responds to the handling of power;
and 3-3, adjusting the initial energy storage configuration in a repeated experiment, expanding the energy storage capacity configuration requirement through a series-parallel circuit structure, and determining a configuration optimal value through daily cycle operation and real-time grid-connected power deviation feedback according to the variation condition of deviation accumulated data.
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| CN113610374A (en) * | 2021-07-29 | 2021-11-05 | 南通大学 | Wind-solar complementary power plan deviation dynamic compensation energy storage energy management method |
| CN113610374B (en) * | 2021-07-29 | 2024-01-16 | 南通大学 | Wind-solar complementary power plan deviation dynamic compensation energy storage energy management method |
| CN114336703A (en) * | 2021-12-17 | 2022-04-12 | 中国长江三峡集团有限公司 | Automatic cooperative control method for large-scale wind-solar power storage station |
| CN114336703B (en) * | 2021-12-17 | 2023-10-13 | 中国长江三峡集团有限公司 | Automatic cooperative control method for large-scale wind-solar energy storage station |
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