CN116706905A - Multi-energy prediction and scheduling method, equipment and storage medium based on power system - Google Patents
Multi-energy prediction and scheduling method, equipment and storage medium based on power system Download PDFInfo
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- H02J3/24—Arrangements for preventing or reducing oscillations of power in networks
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- 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
- H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
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- H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
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Abstract
The invention provides a method, equipment and a storage medium for multi-energy prediction and scheduling based on a power system, which relate to the technical field of power systems, and the method comprises the following steps: acquiring power grid multi-source data of a park; classifying a park into a plurality of levels of electricity utilization areas according to multi-source data of a power grid, predicting electricity utilization loads of all the electricity utilization areas and predicting new energy output of the park, wherein the electricity utilization areas comprise a first level electricity utilization area, and the new energy output comprises wind power stations and photovoltaic power station output; constructing a plurality of multi-energy power supply combination schemes according to the new energy output, wherein each multi-energy power supply combination scheme at least comprises a combination of wind power and photovoltaic power generation of a preset unit; the multi-energy power supply combination schemes are respectively matched with power supply scheduling of each power utilization sheet region according to power utilization loads, and the multi-energy power supply combination schemes are distributed to the first-level power utilization sheet regions to simultaneously supply power to the first-level power utilization sheet regions. The invention has the beneficial effects that: the power supply stability of the power grid can be improved.
Description
Technical Field
The invention relates to the technical field of power systems, in particular to a method, equipment and a storage medium for multi-energy prediction and scheduling based on a power system.
Background
At present, the park power system can effectively save energy, reduce emission and reduce cost by combining new energy sources such as wind power, photovoltaic and the like and through an effective mode of multi-energy coordination control and demand side load control. However, considering the fluctuation of the renewable energy source with high permeability and the load side, for example, in the power generation side, the wind power and the photovoltaic power generation, the generated power of the photovoltaic power and the wind power equipment may have opposite conditions in the same time period, and meanwhile, different power consumption requirements, power consumption plans and the like exist in each region on the load side, so that the fluctuation of the power grid is caused, at the moment, certain difficulty is caused for coordinated power supply of multiple energy sources, and the power supply stability is insufficient.
Disclosure of Invention
The invention solves the problem of how to improve the stability of power supply of a power grid.
In order to solve the above problems, the present invention provides a method for multi-energy prediction and scheduling based on a power system, comprising the steps of: classifying the park into a plurality of levels of electricity consumption areas according to the power grid multi-source data, predicting the electricity consumption load of each electricity consumption area, and predicting the new energy output of the park, wherein the classified electricity consumption areas comprise a first level electricity consumption area, and the new energy output comprises the output of a wind power station and the output of a photovoltaic power station;
Constructing a plurality of multi-energy power supply combination schemes according to the new energy output, wherein each multi-energy power supply combination scheme at least comprises a combination of wind power and photovoltaic power generation of a preset unit;
and carrying out power supply scheduling matching on the multi-energy power supply combination schemes and the power consumption sheet areas respectively according to the power consumption load, wherein the power supply scheduling matching comprises the steps of distributing a plurality of multi-energy power supply combination schemes to the first-level power consumption sheet areas so as to supply power to the first-level power consumption sheet areas simultaneously.
According to the power system-based multi-energy prediction and scheduling method, the parks are classified through the power grid multi-source data, so that a plurality of power utilization areas with different levels are obtained, power is supplied in a targeted matching mode, the classified power utilization areas are matched through a multi-energy power supply combination scheme mixed with photoelectricity and wind power, so that power is supplied, dependence on traditional energy sources is reduced through more diversified energy sources, carbon emission is reduced, energy cost is reduced, fluctuation of each other can be offset through combined utilization of wind power and photovoltaics, stable power supply is achieved, reliability of power supply is improved, combination is formed through wind power generation equipment and photovoltaic power generation equipment, matched power supply is further achieved for the power utilization areas, power supply requirements of a power grid of the parks are met, coordinated operation and stability of the power grid are ensured, and energy utilization efficiency is maximized. For the first-level power utilization sheet area obtained in a grading manner, the combined power supply of the multiple multi-energy power supply combination schemes can further reduce the influence of environmental fluctuation on new energy power generation, and the power supply reliability and stability of the power utilization sheet area are further ensured while the power supply power is improved and the power supply redundancy is ensured.
Further, the classified power consumption sheet area further comprises a second-level power consumption sheet area with a level higher than that of the first-level power consumption sheet area; the power system-based multi-energy prediction and scheduling method further comprises the following steps: constructing a plurality of standby power supply schemes, wherein the standby power supply schemes comprise thermal power generation, gas power generation or a combination of thermal power generation and gas power generation;
the matching of the power supply schedule of the multi-energy power supply combination scheme with each power consumption slice region according to the power consumption load comprises the following steps:
and distributing the multiple multi-energy power supply combination schemes to the second-level power utilization sheet area so as to simultaneously supply power to the second-level power utilization sheet area, and distributing the standby power supply scheme to the second-level power utilization sheet area so as to be used for standby power supply to the second-level power utilization sheet area.
Further, the classified power consumption sheet area further comprises a third-level power consumption sheet area with the level lower than that of the first-level power consumption sheet area; the power system-based multi-energy prediction and scheduling method further comprises the following steps:
marking the multi-energy power supply combination scheme distributed to the third-level power consumption sheet area as a new energy standby power supply scheme;
When the first-level power consumption sheet area and the second-level power consumption sheet area accord with preset power consumption conditions, the new energy standby power supply scheme is distributed to the first-level power consumption sheet area and the second-level power consumption sheet area so as to be used for standby power supply of the first-level power consumption sheet area and the second-level power consumption sheet area.
Further, the power grid multisource data comprises load demand data, electricity reliability demand data and voltage class demand data; the grading the campus into a plurality of levels of electricity utilization areas according to the power grid multi-source data comprises the following steps:
and grading the campus into a plurality of levels of the electricity utilization film areas according to at least one of the load demand data, the electricity utilization reliability demand data and the voltage level demand data.
Further, the grading the campus into multiple levels of electricity utilization areas according to the grid multi-source data further includes the steps of:
determining a plurality of first campus areas in the same load demand level in the campus according to the load demand data, and determining a plurality of second campus areas in the same reliability demand level in the campus according to the electricity consumption reliability demand data;
Determining a coincidence zone of the first campus area and the second campus area;
and determining the classification of the electricity consumption area according to the load demand level and the reliability demand level of the overlapping area.
Further, the step of determining the classification of the electricity consumption area according to the load demand level and the reliability demand level of the overlapping area includes the steps of:
when the load demand level of the overlapping area is higher than a preset load level and the reliability demand level of the overlapping area is higher than a preset reliability demand level, determining the overlapping area as a second-level power consumption area; when the load demand level of the overlapping area is lower than the preset load level and the reliability demand level of the overlapping area is lower than the preset reliability demand level, determining the overlapping area as a third-level power consumption area;
otherwise, determining the overlapping area as the first-level power consumption area, wherein the level of the second-level power consumption area is higher than that of the first-level power consumption area, and the level of the first-level power consumption area is higher than that of the third-level power consumption area.
Further, the park comprises a plurality of wind power stations and a plurality of photovoltaic power stations arranged in a distributed mode; the construction of a plurality of multi-energy power supply combination schemes according to the new energy output comprises the following steps:
combining at least one of said wind power plants and at least one of said photovoltaic power plants to obtain said multi-energy power combining scheme; or (b)
And combining the partial power supply of the wind power station with the partial power supply of the photovoltaic power station to obtain the multi-energy power supply combination scheme.
Further, the power grid multisource data comprises power grid historical load data, power grid topological relation, numerical weather, power outage plans and industry characteristics;
predicting the electricity load of each electricity consumption region according to the multi-source data of the power grid comprises the following steps:
inputting power grid historical load data, power grid topological relation, numerical weather, power outage plans and industry characteristics of each power utilization zone into a preset load fusion prediction model to obtain daily system load, ultra-short-term system load, daily bus and distribution transformer load, ultra-short-term bus and distribution transformer load of each power utilization zone;
predicting new energy output of the park according to the power grid multi-source data comprises:
And inputting the power grid topological relation and the numerical weather into a preset output fusion prediction model to obtain the daily wind power station power, the ultra-short-term wind power station power, the daily photovoltaic power station power and the ultra-short-term photovoltaic power station power.
The invention also proposes a computing device comprising a computer readable storage medium storing a computer program and a processor, the computer program implementing the power system based multi-energy prediction and scheduling method as described above when read and run by the processor.
The computing device of the present invention has similar technical effects to the above-described power system-based multi-energy prediction and scheduling method, and will not be described in detail herein.
The invention also proposes a computer readable storage medium storing a computer program which, when read and run by a processor, implements a power system based multi-energy prediction and scheduling method as described above.
The computer readable storage medium of the present invention has similar technical effects to the above-mentioned power system-based multi-energy prediction and scheduling method, and will not be described in detail herein.
Drawings
FIG. 1 is a flowchart of a method for power system-based multi-energy prediction and scheduling according to an embodiment of the present invention;
FIG. 2 is a second flowchart of a power system-based multi-energy prediction and scheduling method according to an embodiment of the present invention;
fig. 3 is a flowchart of a method for power system-based multi-energy prediction and scheduling according to an embodiment of the present invention.
Detailed Description
In order that the above objects, features and advantages of the invention will be readily understood, a more particular description of the invention will be rendered by reference to specific embodiments thereof which are illustrated in the appended drawings. While certain embodiments of the invention have been illustrated in the accompanying drawings, it is to be understood that the invention may be practiced in a variety of ways and should not be interpreted as limited to the embodiments set forth herein, which are instead provided to provide a more thorough and complete understanding of the invention. It should be understood that the drawings and embodiments of the invention are for illustration purposes only and are not intended to limit the scope of the present invention.
It should be understood that the various steps recited in the method embodiments of the present invention may be performed in a different order and/or performed in parallel. Furthermore, method embodiments may include additional steps and/or omit performing the illustrated steps. The scope of the invention is not limited in this respect.
The term "including" and variations thereof as used herein are intended to be open-ended, i.e., including, but not limited to. The term "based on" is based at least in part on. The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments"; the term "optionally" means "alternative embodiments". Related definitions of other terms will be given in the description below. It should be noted that the terms "first," "second," and the like herein are merely used for distinguishing between different devices, modules, or units and not for limiting the order or interdependence of the functions performed by such devices, modules, or units.
Referring to fig. 1, an embodiment of the present invention provides a method for multi-energy prediction and scheduling based on a power system, including the steps of:
and acquiring power grid multi-source data of the park.
The power grid multisource data of the park refers to data of various sources of a power system in the park, and the data cover various aspects of power grid operation and management of the power system, such as load data of various users or facilities in the park, energy supply data (such as new energy, power generation/output of traditional energy and the like), numerical weather (weather data of the park power grid including observation data of weather elements such as temperature, humidity, wind speed, sunlight time and the like, and the data are used for analyzing influences of the weather factors on the load and the power output), power grid operation data (such as operation data of power grid equipment, topological relations, including transformer substation parameters, line loads, voltage frequencies, user industry characteristics and the like) and the like. These data together affect the operation of the campus power system to be a basis for grid operation prediction and optimization.
The park in the embodiment of the invention may not be limited to an industrial park, and in other embodiments, the method of the invention may be applicable to power system construction and control of cities, where the park may correspond to an urban area, or the like.
Classifying the park into a plurality of levels of electricity consumption areas according to the power grid multi-source data, predicting the electricity consumption load of each electricity consumption area and predicting the new energy output of the park, wherein the classified electricity consumption areas comprise a first level electricity consumption area, and the new energy output comprises the output of a wind power station and the output of a photovoltaic power station.
The power consumption characteristics, the power consumption requirements and other data can be embodied in the multi-source data of the power grid, and the parks are classified, so that a plurality of power consumption areas with different levels are obtained. Meanwhile, the historical load in the power grid multisource data of each power utilization zone can be combined, and the power utilization load of each power utilization zone can be predicted according to future power utilization arrangement and the like. In addition, the output of the equipment in the park is estimated by combining the corresponding working model of the power generation equipment, and specifically, in the embodiment of the invention, the processing of the new energy power generation equipment is estimated, including the estimation of the output of the wind power station and the output of the photovoltaic power station.
The campus is staged to be divided into multiple levels of electricity usage tiles, with the levels defining electricity usage priorities. Specifically, the divided multiple levels of power utilization zones include at least a first level of power utilization zones of moderate level, and accordingly, in other embodiments, other levels of power utilization zones of higher or relatively lower levels may be included.
And constructing a plurality of multi-energy power supply combination schemes according to the new energy output, wherein each multi-energy power supply combination scheme at least comprises a combination of wind power and photovoltaic power generation of a preset unit.
For the predicted new energy output, it represents the power generation condition of the wind power station and the photovoltaic power station in the garden in a future period of time, and typically, the power generation devices of the wind power station and the photovoltaic power station are multiple, for example, distributed photovoltaic power generation devices. In this way, the power generation facilities may be combined in units of a single power generation facility, or in units of a wind power plant or a photovoltaic power plant constituted by a plurality of power generation facilities, or the predicted power generation powers of the wind power plant and the photovoltaic power plant may be split and combined to form a plurality of multi-energy power supply combination schemes.
And carrying out power supply scheduling matching on the multi-energy power supply combination schemes and the power consumption sheet areas respectively according to the power consumption load, wherein the power supply scheduling matching comprises the steps of distributing a plurality of multi-energy power supply combination schemes to the first-level power consumption sheet areas so as to supply power to the first-level power consumption sheet areas simultaneously.
Based on the power consumption load of each power consumption region, the multiple power consumption regions divided by the multi-energy power supply combination scheme mixed with photoelectricity and wind power are matched, so that power supply is realized, and it can be understood that the power supply of the multi-energy power supply combination scheme is larger than the power consumption load of the corresponding park. Through more diversified energy sources, reduce the dependence on traditional energy, reduce carbon emission, help environmental protection and sustainable development, and reduce energy cost, in addition, the output of wind energy and solar energy receives weather condition's influence, there is volatility, for example, when solar photovoltaic output is higher, probably the lower condition of wind-force output, vice versa, through wind-powered electricity and photovoltaic combined utilization, can offset each other's fluctuation, realize comparatively steady power supply, improve the reliability of power supply, form the combination through wind power generation equipment and photovoltaic power generation equipment, and then pair the power supply to the electricity consumption district, also be convenient for pertinently supply, satisfy the power supply demand of garden electric wire netting, ensure electric wire netting coordinated operation and stability, and maximize energy utilization efficiency. For the first-level power utilization sheet area obtained in a grading manner, the combined power supply of the multiple multi-energy power supply combination schemes can further reduce the influence of environmental fluctuation on new energy power generation, and the power supply reliability and stability of the power utilization sheet area are further ensured while the power supply power is improved and the power supply redundancy is ensured.
In an alternative embodiment of the invention, the campus includes a plurality of wind power plants and a plurality of photovoltaic plants arranged in a distributed manner; the constructing a plurality of multi-energy power supply combination schemes according to the new energy output comprises the following steps: combining at least one of said wind power plants and at least one of said photovoltaic power plants to obtain said multi-energy power combining scheme; or combining the partial power supply of the wind power station with the partial power supply of the photovoltaic power station to obtain the multi-energy power supply combination scheme. When the multi-energy power supply combination schemes are formed, the complementarity of the wind power generation station and the photovoltaic power generation station can be considered more to carry out pairing combination, for example, historical power generation data are considered, and finally, each multi-energy power supply combination scheme can be ensured to stably output certain power supply.
In an optional embodiment of the present invention, the graded power consumption area further includes a second-level power consumption area having a level higher than that of the first-level power consumption area; the power system-based multi-energy prediction and scheduling method further comprises the following steps: constructing a plurality of standby power supply schemes, wherein the standby power supply schemes comprise thermal power generation, gas power generation or a combination of thermal power generation and gas power generation;
The matching of the power supply schedule of the multi-energy power supply combination scheme with each power consumption slice region according to the power consumption load comprises the following steps:
and distributing the multiple multi-energy power supply combination schemes to the second-level power utilization sheet area so as to simultaneously supply power to the second-level power utilization sheet area, and distributing the standby power supply scheme to the second-level power utilization sheet area so as to be used for standby power supply to the second-level power utilization sheet area.
Referring to fig. 2, in the embodiment of the present invention, the division of the segments into segments is specifically classified into a plurality of levels of power utilization segments by grading, and the levels are used to define the power utilization priority. Specifically, the divided power consumption areas of multiple levels at least comprise a first-level power consumption area and a second-level power consumption area, wherein the level of the second-level power consumption area is higher than that of the first-level power consumption area, namely the power consumption priority is relatively higher, so that the power supply of the second-level power consumption area is matched and supplied through multiple multi-energy power supply combination schemes, and meanwhile, the standby power supply scheme is combined to carry out standby power supply on the second-level power utilization sheet area, so that stable power supply of the second-level power utilization sheet area is ensured, wherein the standby power supply scheme comprises thermal power, gas power generation or a combination of thermal power and gas power generation, and more energy sources and new energy sources are combined to form a power supply combination, so that the power supply reliability and stability of the second-level power utilization sheet area are higher. And for the first-level power consumption area with relatively lower level, combining a plurality of multi-energy power supply combination schemes to supply power.
In an optional embodiment of the present invention, the graded power consumption region further includes a third-level power consumption region having a level lower than that of the first-level power consumption region; the power system-based multi-energy prediction and scheduling method further comprises the following steps:
marking the multi-energy power supply combination scheme distributed to the third-level power consumption sheet area as a new energy standby power supply scheme;
when the first-level power consumption sheet area and the second-level power consumption sheet area accord with preset power consumption conditions, the new energy standby power supply scheme is distributed to the first-level power consumption sheet area and the second-level power consumption sheet area so as to be used for standby power supply of the first-level power consumption sheet area and the second-level power consumption sheet area.
Referring to fig. 2, in the embodiment of the present invention, a third-level power consumption area may be divided, where the third-level power consumption area has a lower power consumption priority than the first-level and second-level power consumption areas, and for the third-level power consumption area, a combination scheme of multiple power supplies, which is less than other power consumption areas, may be allocated to supply power, for example, a combination scheme of multiple power supplies, which is slightly greater than the power of the power consumption load, may be allocated according to the power consumption load.
In addition, the power utilization priority of the first-level power utilization zone is relatively low, the assigned multi-energy power supply combination scheme is marked clearly to be used as a new energy standby power supply scheme, such as a wind power generation device and a photovoltaic power generation device in the multi-energy power supply combination scheme, so that subsequent scheduling is facilitated, and in particular, the power generation devices can be used as standby power supply devices of other power utilization zones with higher priority, such as power utilization conditions meeting preset power utilization conditions in the first-level power utilization zone and the second-level power utilization zone, for example, when power utilization requirements of partial devices in the zones are required to be continuously powered off, sudden increase in a specific time period is caused, and the like, the third-level power utilization zone corresponding to the devices is adjusted to be the other first-level or second-level power utilization zone, so that standby power supply is realized, the power supply coordination degree of a power grid is improved, and the power utilization requirements of the high-level power utilization zone are met.
In an alternative embodiment of the invention, the grid multisource data includes load demand data, electricity reliability demand data and voltage class demand data; the grading the campus into a plurality of levels of electricity utilization zones according to the power grid multi-source data comprises the following steps:
And grading the campus into a plurality of levels of the electricity utilization film areas according to at least one of the load demand data, the electricity utilization reliability demand data and the voltage level demand data.
In this embodiment, the campus area may be screened uniformly, and the power load, the power voltage, the stability requirement, the reliability requirement and the like in different areas are classified, for example, the residential areas of personnel are identified, the power load, the voltage and the stability requirement in these areas are relatively low, and the areas with higher power load, higher stability and other specific power supply requirements such as heavy industry and machine room can be classified into the power supply areas with higher level by identification, and the comprehensive areas such as office buildings and light industry can be classified into the power supply areas with moderate level by identification.
In an alternative embodiment of the present invention, the grading the campus into a plurality of levels of electricity usage areas according to the grid multisource data further includes the steps of:
determining a plurality of first campus areas in the same load demand level in the campus according to the load demand data, and determining a plurality of second campus areas in the same reliability demand level in the campus according to the electricity consumption reliability demand data;
Determining a coincidence zone of the first campus area and the second campus area;
and determining the classification of the electricity consumption area according to the load demand level and the reliability demand level of the overlapping area.
In the embodiment of the invention, the parks are divided by specifically combining the load demand data and the electricity reliability demand data. Specifically, in a campus, a building and a factory building can be used as units, and the areas are firstly divided, wherein historical electricity data in each area is researched to serve as load demand data, electricity and industry characteristics, electric equipment sensitivity, building attributes and other data are researched to serve as reliability demand data, the data are combined to divide the load demand level and the reliability demand level, the grading and dividing rules can be set according to actual demands, and then each first campus area and each second campus area which are in the same load demand level and the same reliability demand level can be further clarified.
For example, for residential buildings and offices at different locations distributed in a park, by identifying that the area of these buildings is in a first park area which is also of low load demand level, and a second park area which is also of low reliability demand level only comprises residential building areas, determining that the overlapping area is a residential building area, and determining that the overlapping area is a specific-level electricity consumption area in a specific-level electricity consumption area.
Therefore, the power consumption areas are divided in the park by combining the load demand data and the reliability demand data, and then the power consumption areas with different grades are obtained, so that power supply distribution is conducted adaptively.
In an optional embodiment of the present invention, the determining the classification of the electricity consumption area according to the load demand level and the reliability demand level of the overlapping area includes:
when the load demand level of the overlapping area is higher than a preset load level and the reliability demand level of the overlapping area is higher than a preset reliability demand level, determining the overlapping area as a second-level power consumption area; when the load demand level of the overlapping area is lower than the preset load level and the reliability demand level of the overlapping area is lower than the preset reliability demand level, determining the overlapping area as a third-level power consumption area;
otherwise, determining the overlapping area as the first-level power consumption area, wherein the level of the second-level power consumption area is higher than that of the first-level power consumption area, and the level of the first-level power consumption area is higher than that of the third-level power consumption area.
Referring to fig. 3, in this embodiment, based on the above determination of the overlapping area of the first campus area and the second campus area, there may be a case where the difference in power supply demand is large or small for the overlapping area, for example, when the reliability demand level and the load demand level of the residential building after the overlapping at different positions are both low, specifically, the load demand level of the overlapping area is lower than the preset load level, and the reliability demand level of the overlapping area is lower than the preset reliability demand level, at this time, the overlapping area may be directly divided into third-level power consumption areas with lower power consumption priority, and meanwhile, for a plant area with high power consumption and high reliability demand, for example, when the load demand level of the overlapping area is higher than the preset load level, and the reliability demand level of the overlapping area is higher than the preset reliability demand level, at this time, the overlapping area may also be directly divided into second-level power consumption areas with higher power consumption priority. For certain office buildings and factories with specific industry characteristics, the situations of low power consumption and low reliability requirements or low power consumption and high reliability requirements may exist, and for these areas, the areas may be divided into first-level power consumption areas with moderate power consumption priority.
Accordingly, the first-level power consumption area, the second-level power consumption area, and the third-level power consumption area obtained by dividing may be based on the multiple multi-energy power supply combination schemes in the above embodiments and the combination standby power supply scheme, etc. to perform specific power supply scheduling, which is not described herein.
In addition, it can be understood that the electricity consumption area of the campus can be divided and classified according to actual requirements, in this embodiment, the electricity consumption area is specifically divided into 3 levels, and in other embodiments, the electricity consumption area can be divided into more or less levels, or divided into other types, so as to realize fine management.
In an optional embodiment of the present invention, the matching of the power supply schedule of the multi-energy power supply combination scheme with each power consumption slice area according to the power consumption load further includes the steps of:
determining a preset load demand coefficient and a preset reliability demand coefficient corresponding to each power utilization area;
determining the power supply power of the power utilization sheet areas according to the preset load demand coefficient, the preset reliability demand coefficient and the power utilization load of each power utilization sheet area;
and determining the multi-energy power supply combination scheme matched with the power utilization sheet area according to the power supply power.
In general, for each level of electricity consumption area, the total output power of the corresponding multi-energy power supply combination scheme is larger than the electricity consumption load thereof, so as to prevent uncertainty caused by factors such as environment or faults in a future time period.
In the above embodiment, the unified screening may be performed on the campus area, the load demand level and the electricity reliability level may be divided on the campus area by combining the load demand data and the electricity reliability demand data of each electricity consumption area, and for each level, a corresponding preset load demand coefficient and a preset reliability demand coefficient may be set in advance for adjusting the estimated electricity consumption load, where the power supply may be obtained by multiplying the preset load demand coefficient and the preset reliability demand coefficient by the electricity consumption load, so as to implement the adjustment, or the product value of the preset load demand coefficient and the preset reliability demand coefficient and the preset power may be calculated respectively, and the product value may be added as a weighted value to the estimated electricity consumption load, so as to obtain the adjusted power supply, so as to improve the actual power supply of each electricity consumption area.
And combining the power supply power, and determining one or more adaptive multi-energy power supply schemes in the constructed multi-energy power supply combination scheme so as to carry out matched power supply on the power utilization areas.
For the three power consumption areas with different power consumption priorities in the embodiment of the invention, the load demand level and the power consumption reliability level are different, the corresponding preset load demand coefficient and preset reliability demand coefficient are different, specifically, each coefficient corresponding to the higher level is set to be larger, and the power supply redundancy value provided by the power consumption area with the higher power consumption priority after the adjustment and the estimated power consumption load difference value are larger after the power consumption area is matched with the multi-energy power supply combination scheme.
In the embodiment of the invention, the power consumption sheet area is divided into three power consumption sheet areas with different priorities.
For the third-level power utilization area with the lowest priority, a multi-energy power supply combination scheme with estimated generated power matched with the power supply power of the power utilization area can be determined for power supply.
For the first-level power consumption area with moderate priority level, the power consumption area is powered through a plurality of multi-energy power supply combination schemes, the power generation power estimated by the whole multi-energy power supply combination schemes is larger than the power consumption load of the power consumption area, and meanwhile, the power supply power adjusted through the preset load demand coefficient and the preset reliability demand coefficient is larger, so that larger power supply redundancy is provided for the power consumption area, so that the power supply stability is improved, and meanwhile, the power supply is convenient for reducing the power generation fluctuation caused by natural environment change when the multi-energy power supply combination schemes are powered simultaneously, and the adjustment is convenient when a problem exists in a certain multi-energy power supply combination scheme.
For the second-level power utilization area with the highest priority level, the standby power supply scheme is provided for standby power supply, and the power of the power utilization area is also supplied through the multiple multi-energy power supply combination schemes, so that the power consumption load difference value of the power utilization area is larger compared with the power generation power estimated by the multiple multi-energy power supply combination schemes as a whole, and the power supply stability and the reliability of the area are further improved.
In an optional embodiment, determining the multi-energy power supply combination scheme matched with the power consumption sheet area according to the power supply power further includes determining a plurality of multi-energy power supply combination schemes to supply power to the power consumption sheet area when the power consumption reliability level of the second-level power consumption sheet area is greater than or equal to a preset level, wherein the generated power of one of the plurality of multi-energy power supply combination schemes is greater than the power supply power and the total generated power of the remaining multi-energy power supply combination schemes is greater than the power supply power.
For the second-level electricity consumption area with extremely high power supply stability requirement, for example, the second-level electricity consumption area is a data machine room, the electricity consumption reliability is extremely high, when the damage caused by outage is relatively high, the electricity supply of the second-level electricity consumption area is met by one generated power in the second-level electricity consumption area, meanwhile, the power supply of the second-level electricity consumption area can be also met by the total generated power of other combination schemes in the multiple multi-energy power supply combination schemes, the electricity consumption area is supplied by multiple combinations capable of meeting the power supply redundancy, the power supply instability of new energy multi-energy power supply is further reduced, and the production work of the electricity consumption area can be ensured stably.
In an alternative embodiment of the invention, the grid multisource data includes grid historical load data, grid topology, numerical weather, outage plans, and industry characteristics;
predicting the electricity load of each electricity consumption region according to the multi-source data of the power grid comprises the following steps:
inputting power grid historical load data, power grid topological relation, numerical weather, power outage plans and industry characteristics of each power utilization zone into a preset load fusion prediction model to obtain daily system load, ultra-short-term system load, daily bus and distribution transformer load, ultra-short-term bus and distribution transformer load of each power utilization zone;
predicting new energy output of the park according to the power grid multi-source data comprises:
and inputting the power grid topological relation and the numerical weather into a preset output fusion prediction model to obtain the daily wind power station power, the ultra-short-term wind power station power, the daily photovoltaic power station power and the ultra-short-term photovoltaic power station power.
In the embodiment of the invention, the power load prediction of the power utilization area and the new energy output prediction of the park can be predicted by combining with a fusion prediction model, wherein the fusion prediction model of the power grid is a model combining with various data sources and prediction technologies and used for predicting and optimizing various aspects of power grid operation, and can integrate various key parameters and information such as power grid topological relation, energy supply and demand conditions, meteorological data, load characteristics and the like so as to provide accurate prediction results and relevant decision support.
For electricity load prediction, the load demand in a future period can be predicted by using data such as historical load data of a power grid, topological relation of the power grid, numerical weather, power failure plans, industry characteristics and the like and a preset load fusion prediction model formed by methods such as statistical analysis, a time sequence model, machine learning and the like, so that the power grid planning, scheduling and resource allocation can be facilitated. For new energy output prediction, the renewable energy power generation system such as distributed photovoltaic, wind power and the like can be used for predicting the power generation amount of renewable energy by combining the power grid topological relation and numerical weather, and further combining the power generation device parameters, historical power generation data and the like, so that a basis is provided for power grid dispatching and energy management.
The preset load fusion prediction model and the preset output fusion prediction model can be constructed according to actual conditions of a park power system, for example, the preset load fusion prediction model can be an autoregressive moving average model, a neural network model and the like, the autoregressive moving average model can be modeled according to power grid multisource data, the model considers the influences of time sequence trends, seasonality, environmental factors and the like, so that the load prediction is realized, and the model can also be modeled and learned by taking historical load data and other power grid multisource data as input or influence factors of the model based on a machine learning method, for example, a multi-layer perceptron (MLP), a cyclic neural network (RNN), a long-short-term memory network (LSTM) and the like neural network model, so that the load prediction is realized. For the preset output fusion prediction model, a physical model and a neural network model can be adopted, for example, the physical model can be a twin model of wind power generation equipment and photovoltaic power generation equipment, and wind speed, wind direction, mechanical rotation speed, solar illumination and other parameters are considered in combination with environmental influence, power grid loss and the like to predict wind energy and photovoltaic output. The neural network model can use historical data and real-time data to build a model, and predict the output of new energy through a machine learning and statistical analysis method, and the model can consider a plurality of influencing factors, such as weather, time, seasons, load demands and the like, and correlate the factors with the historical data, so that the accuracy of model prediction is improved.
In a specific embodiment of the invention, the power consumption area division, the power consumption load prediction and the new energy output prediction comprising the wind power output and the photovoltaic output are performed on the park by acquiring power grid multi-source data such as power grid historical load data, power grid topological relation, numerical weather, power outage plans, industry characteristics and the like of the park, wherein the park is divided into a plurality of levels of power consumption areas respectively comprising a second level power consumption area, a first level power consumption area and a third level power consumption area with sequentially reduced power consumption priority. And then a plurality of multi-energy power supply combination schemes are constructed by combining new energy output, wherein the multi-energy power supply combination schemes comprise a scheme obtained by combining at least one wind power generation station and at least one photovoltaic power station or a combination scheme obtained by combining partial power supply of the wind power generation station and partial power supply of the photovoltaic power station, so that the power supply stability is improved and the fluctuation of new energy power generation is reduced through the combination of wind power and photovoltaic power, and the schemes of different power supply powers can be conveniently obtained to carry out power supply scheduling on power consumption areas of different grades. For the first-level power consumption area with moderate power consumption requirements, only a plurality of multi-energy power supply combination schemes can be combined for matched power supply so as to improve the power supply and ensure the power supply redundancy. For the second-level power consumption area with higher power consumption requirement, matching power supply can be performed through a plurality of multi-energy power supply combination schemes, and meanwhile, a standby power supply scheme is constructed for standby power supply so as to further improve reliability. For a third-level electricity consumption region with moderate electricity demand, a single multi-energy power supply combination scheme can be combined for supplying electricity, and the multi-energy power supply combination schemes can be marked as standby equipment so as to supply power for standby in other areas with higher priority levels under special conditions, thereby improving the coordination capacity of the power grid.
A computing device according to another embodiment of the present invention includes a computer-readable storage medium storing a computer program that, when read and executed by a processor, implements a power system-based multi-energy prediction and scheduling method as described above.
The computing device of the present invention has similar technical effects to the above-described power system-based multi-energy prediction and scheduling method, and will not be described in detail herein.
A computer readable storage medium of another embodiment of the present invention stores a computer program which, when read and executed by a processor, implements the power system-based multi-energy prediction and scheduling method as described above.
The computer readable storage medium of the present invention has similar technical effects to the above-mentioned power system-based multi-energy prediction and scheduling method, and will not be described in detail herein.
In general, the computer instructions for carrying out the methods of the present invention may be carried in any combination of one or more computer-readable storage media. The non-transitory computer-readable storage medium may include any computer-readable medium, except the signal itself in temporary propagation.
The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code for carrying out operations of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++, c#, and conventional procedural programming languages, such as the "C" language or similar programming languages, particularly the Python language suitable for neural network computing and TensorFlow, pyTorch-based platform frameworks may be used. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).
Although the invention is disclosed above, the scope of the invention is not limited thereto. Various changes and modifications may be made by one skilled in the art without departing from the spirit and scope of the invention, and such changes and modifications would be within the scope of the invention.
Claims (10)
1. A power system-based multi-energy prediction and scheduling method, comprising:
acquiring power grid multi-source data of a park;
classifying the park into a plurality of levels of electricity consumption areas according to the power grid multi-source data, predicting the electricity consumption load of each electricity consumption area, and predicting the new energy output of the park, wherein the classified electricity consumption areas comprise a first level electricity consumption area, and the new energy output comprises the output of a wind power station and the output of a photovoltaic power station;
constructing a plurality of multi-energy power supply combination schemes according to the new energy output, wherein each multi-energy power supply combination scheme at least comprises a combination of wind power and photovoltaic power generation of a preset unit;
and carrying out power supply scheduling matching on the multi-energy power supply combination schemes and the power consumption sheet areas respectively according to the power consumption load, wherein the power supply scheduling matching comprises the steps of distributing a plurality of multi-energy power supply combination schemes to the first-level power consumption sheet areas so as to supply power to the first-level power consumption sheet areas simultaneously.
2. The power system-based multi-energy prediction and scheduling method of claim 1, wherein the classified power utilization zones further comprise a second-level power utilization zone having a higher level than the first-level power utilization zone; the power system-based multi-energy prediction and scheduling method further comprises the following steps: constructing a plurality of standby power supply schemes, wherein the standby power supply schemes comprise thermal power generation, gas power generation or a combination of thermal power generation and gas power generation;
the matching of the power supply schedule of the multi-energy power supply combination scheme with each power consumption slice region according to the power consumption load comprises the following steps:
and distributing the multiple multi-energy power supply combination schemes to the second-level power utilization sheet area so as to simultaneously supply power to the second-level power utilization sheet area, and distributing the standby power supply scheme to the second-level power utilization sheet area so as to be used for standby power supply to the second-level power utilization sheet area.
3. The power system-based multi-energy prediction and scheduling method according to claim 2, wherein the classified power utilization zones further include a third-level power utilization zone having a lower level than the first-level power utilization zone; the power system-based multi-energy prediction and scheduling method further comprises the following steps:
Marking the multi-energy power supply combination scheme distributed to the third-level power consumption sheet area as a new energy standby power supply scheme;
when the first-level power consumption sheet area and the second-level power consumption sheet area accord with preset power consumption conditions, the new energy standby power supply scheme is distributed to the first-level power consumption sheet area and the second-level power consumption sheet area so as to be used for standby power supply of the first-level power consumption sheet area and the second-level power consumption sheet area.
4. The power system-based multi-energy prediction and dispatch method of claim 1, wherein the grid multi-source data includes load demand data, power reliability demand data, and voltage class demand data; the grading the campus into a plurality of levels of electricity utilization zones according to the power grid multi-source data comprises the following steps:
and grading the campus into a plurality of levels of the electricity utilization film areas according to at least one of the load demand data, the electricity utilization reliability demand data and the voltage level demand data.
5. The power system-based multi-energy prediction and dispatch method of claim 4, wherein the grading the campus into multiple levels of electricity utilization tiles according to the grid multi-source data further comprises:
Determining a plurality of first campus areas in the same load demand level in the campus according to the load demand data, and determining a plurality of second campus areas in the same reliability demand level in the campus according to the electricity consumption reliability demand data;
determining a coincidence zone of the first campus area and the second campus area;
and determining the classification of the electricity consumption area according to the load demand level and the reliability demand level of the overlapping area.
6. The power system-based multi-energy prediction and dispatch method of claim 5, wherein said determining a hierarchy of said power utilization zones based on said load demand level and said reliability demand level of said coincident regions comprises:
when the load demand level of the overlapping area is higher than a preset load level and the reliability demand level of the overlapping area is higher than a preset reliability demand level, determining the overlapping area as a second-level power consumption area; when the load demand level of the overlapping area is lower than the preset load level and the reliability demand level of the overlapping area is lower than the preset reliability demand level, determining the overlapping area as a third-level electricity consumption area;
Otherwise, determining the overlapping area as the first-level power consumption area, wherein the level of the second-level power consumption area is higher than that of the first-level power consumption area, and the level of the first-level power consumption area is higher than that of the third-level power consumption area.
7. The power system-based multi-energy prediction and dispatch method of any one of claims 1-6, wherein the campus includes a plurality of wind power plants and a plurality of photovoltaic plants arranged in a distributed manner; the constructing a plurality of multi-energy power supply combination schemes according to the new energy output comprises the following steps:
combining at least one of said wind power plants and at least one of said photovoltaic power plants to obtain said multi-energy power combining scheme; or (b)
And combining the partial power supply of the wind power station with the partial power supply of the photovoltaic power station to obtain the multi-energy power supply combination scheme.
8. The power system-based multi-energy prediction and dispatch method of any one of claims 1-6, wherein the grid multi-source data includes grid historical load data, grid topology, numerical weather, outage plans, and industry characteristics;
predicting the electricity load of each electricity consumption region according to the multi-source data of the power grid comprises the following steps:
Inputting the historical load data of the power grid, the topological relation of the power grid, the numerical weather, the power outage plan and the industry characteristics of each power utilization zone into a preset load fusion prediction model to obtain daily system load, ultra-short-term system load, daily bus and distribution transformer load, ultra-short-term bus and distribution transformer load of each power utilization zone;
predicting new energy output of the park according to the power grid multi-source data comprises:
and inputting the power grid topological relation and the numerical meteorological into a preset output fusion prediction model to obtain the daily wind power station power, the ultra-short-term wind power station power, the daily photovoltaic power station power and the ultra-short-term photovoltaic power station power.
9. A computing device comprising a computer readable storage medium storing a computer program and a processor, the computer program implementing the power system based multi-energy prediction and scheduling method of any one of claims 1-8 when read and executed by the processor.
10. A computer readable storage medium, characterized in that it stores a computer program, which when read and run by a processor, implements the power system based multi-energy prediction and scheduling method according to any of claims 1-8.
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