CN112308303B - High fault tolerance energy supply group load scheduling method and device based on deviation distribution and terminal equipment - Google Patents
High fault tolerance energy supply group load scheduling method and device based on deviation distribution and terminal equipment Download PDFInfo
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Abstract
The invention is applicable to the technical field of energy equipment operation management, and provides a high fault tolerance energy supply group load scheduling method and device based on deviation distribution and terminal equipment, wherein the method comprises the following steps: the method comprises the steps of obtaining a scheduling scheme output by a scheduling algorithm aiming at an energy supply group, comparing actual field states of equipment to be started and equipment to be started aiming at the energy supply group in the scheduling scheme, determining equipment with inconsistent start-stop states to calculate load deviation, obtaining total load difference, and performing load deviation secondary distribution on the total load difference to form real-time mapping of the scheduling scheme and the actual field states of the energy supply group.
Description
Technical Field
The invention belongs to the technical field of energy equipment operation management, and particularly relates to a high fault tolerance energy supply group load scheduling method and device based on deviation distribution and terminal equipment.
Background
With the development of energy supply forms such as distributed, multi-combined supply and comprehensive energy, group energy supply modes of combined energy supply of a plurality of similar devices are increasingly common, and the differences of the performances and the efficiencies of single devices in the energy supply groups bring the potential of load optimization scheduling.
At present, less research is conducted on a real-time load scheduling algorithm of an energy supply group, main research is focused on daily or time-sharing steady-state scheduling, actual load change is dynamic, a device operation mode is also dynamic, and how to ensure the accuracy and flexibility of the load distribution of each device under the condition of real-time dynamic is a problem which is difficult to solve at present.
Disclosure of Invention
In view of the technical problems in the background art, the embodiment of the invention provides a high fault tolerance energy supply group load scheduling method and device based on deviation distribution and terminal equipment.
In a first aspect of the present invention, a high fault tolerance energy supply group load scheduling method based on bias distribution is provided, which includes: acquiring a scheduling scheme output by a scheduling algorithm aiming at an energy supply group; comparing the actual on-site states of the to-be-started devices of the energy supply group and the to-be-started devices in the scheduling scheme, and determining devices with inconsistent start-stop states; carrying out load deviation calculation one by one aiming at the equipment with inconsistent start-stop states to obtain a total load difference; performing load deviation secondary distribution on the total load difference in the equipment actually started by the energy supply group to form real-time mapping of the scheduling scheme and the actual field state of the energy supply group; and outputting a scheduling scheme after load deviation secondary distribution.
In some embodiments, the scheduling scheme includes at least: the proposed start-stop status and the specified load for each device in the powered group.
In some embodiments, comparing the actual on-site states of the power-on-off devices for the power-on group and the power-on-off devices in the scheduling scheme, determining the devices with inconsistent start-stop states includes determining the states of each device in the power-on group in the scheduling scheme one by one: when the scheduling scheme of the equipment is to be started and the load is appointed, judging whether the equipment is not started at the present place or not: if yes, determining that the equipment is inconsistent in start-stop state; when the scheduling scheme of the equipment is to be closed, judging whether the equipment is opened and bears load at the present place; if yes, determining that the equipment is inconsistent in start-stop state.
In some embodiments, load deviation calculation is performed one by one for the devices with inconsistent start-stop states to obtain a total load difference, which specifically includes: for devices whose scheduling scheme is to be on and specify a non-on-site state: aiming at the equipment with inconsistent start-stop states, the on-site opening state is maintained and the load is not changed; the equipment site load bearing is counted in the opposite number and the total load difference is calculated, and for equipment with a scheduling scheme of which the equipment is to be closed but the site is in an open state: the on-site opening state is kept, and the load is not changed; and taking the opposite number of the field load bearing load of the equipment, and then accounting the total load difference, wherein the total load difference is initially zero.
In some embodiments, performing load deviation secondary distribution on the total load difference in the equipment with the energy supply group being actually started to form a real-time mapping of the scheduling scheme and the actual state of the energy supply group field, including: acquiring a preset distribution coefficient of equipment actually started in an energy supply group; and carrying out load deviation secondary distribution on the total load difference in the equipment actually started in the energy supply group according to the distribution coefficient to form real-time mapping of the scheduling scheme and the field actual state of the energy supply group.
In some embodiments, the preset allocation coefficients for the actually turned-on devices in the energy supply group include: dividing the actually opened devices in the energy supply group into a load peak regulation role device group and a load basic role device group; determining the distribution coefficient of each device in the load peak regulation role device group as ai=2/(2y1+y2); and determining the distribution coefficient of each device in the first load basic role device group as ai=1/(2y1+y2), wherein Y1 is the number of devices in the load peak regulation role device group, Y2 is the number of devices in the load basic role device group, and the sum of the distribution coefficients of each device is 1.
In some embodiments, according to the allocation coefficient, performing load deviation secondary allocation on the total load difference in the equipment actually started in the energy supply group to form a real-time mapping between the scheduling scheme and the actual field state of the energy supply group, and specifically including: aiming at the equipment which is to be started and assigned with load by a scheduling scheme in the energy supply group and is actually started, the real-time load value is equal to the sum of the assigned load and the load deviation obtained by secondary distribution; for the equipment which is actually started and bears the load in the energy supply group and is not started by the scheduling scheme, the real-time load value is equal to the sum of the load bearing load and the load deviation secondary distribution.
In some embodiments, the scheduling scheme after the output load deviation is secondarily allocated includes: and outputting the load deviation scheduling scheme after secondary distribution to each on-site actual opened device.
In a second aspect of the present invention, there is provided a high fault tolerance energy supply group load scheduling apparatus based on bias distribution, comprising: a scheduling scheme acquisition module configured to acquire a scheduling scheme output by a scheduling algorithm for the energy supply group; the comparison module is configured to compare the actual on-site states of the to-be-started devices for the energy supply group and the to-be-started devices in the scheduling scheme, and determine the devices with inconsistent start-stop states; the load total difference calculation module is configured to calculate load deviation one by one aiming at the equipment with inconsistent start-stop states to obtain load total difference; the load total difference distribution module is configured to carry out load deviation secondary distribution on the load total difference in the equipment actually started by the energy supply group to form real-time mapping of the scheduling scheme and the field actual state of the energy supply group; and the scheduling scheme output module is configured to output the scheduling scheme after the load deviation is secondarily distributed.
A third aspect of the embodiments of the present invention provides a terminal device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the above method when executing the computer program.
The beneficial effects of the invention are as follows: according to the invention, the scheduling scheme output by the scheduling algorithm is compared with the actual running state of each device in the energy supply group, the device with inconsistent start-stop states is subjected to load adjustment according to the comparison result, and the load total difference generated based on the adjustment is subjected to load deviation secondary distribution in other devices, so that the real-time mapping between the scheduling scheme and the actual field state of the energy supply group is maintained, and the effect of ensuring the accuracy and flexibility of the load distribution of each device under the condition of real-time dynamic is realized.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a system architecture of a high fault tolerance energy supply group load scheduling method or device based on bias distribution, which is provided by the present embodiment;
FIG. 2 is a flow chart of a high fault tolerance energy group load scheduling method based on bias distribution provided in an embodiment of the present invention;
FIG. 3 is a flowchart of step S220 shown in the embodiment of FIG. 2 in one embodiment;
FIG. 4 is a flowchart of step S230 shown in the embodiment of FIG. 2 in one embodiment;
FIG. 5 is a flowchart of step S240 shown in the embodiment of FIG. 2 in one embodiment;
FIG. 6 is a flowchart of step S520 shown in the embodiment of FIG. 5 in one embodiment;
FIG. 7 is a schematic diagram of a high fault tolerance energy group load scheduling apparatus according to an embodiment of the present invention based on bias distribution.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system configurations, techniques, etc., in order to provide a thorough understanding of embodiments of the present invention, it will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details, and in other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.
In order to illustrate the technical scheme of the invention, the following description is made by specific examples.
First embodiment
Referring to fig. 1, a system architecture to which the high fault tolerance energy supply group load scheduling method or apparatus based on bias distribution of the present invention can be applied is provided in this embodiment.
As shown in fig. 1, the system architecture 100 includes an energizing group 120 and a scheduling algorithm 110 for the energizing group 120 for outputting a scheduling scheme for the energizing group 120, which is an ideal operating scheme for the energizing group 120 in the global, and in conjunction with fig. 1, a plurality of energizing devices (hereinafter referred to as devices) may be included in the energizing group 120, such as devices 121, 122, 123.
In particular, the energy supply group 120 may be embodied as an energy device group, such as a boiler group.
Specifically, the scheduling algorithm 110 may be a computer program or a program module installed on another computer system, taking the energy supply group 120 as an example of the boiler, and when the computer program corresponding to the scheduling algorithm 110 is read and run by the processor, an optimal running load for each boiler in the boiler group may be output.
In an implementation application, the scheduling algorithm 110 may be various modeling solution algorithms based on data driving, for example, modeling methods based on evolutionary algorithm alone or linear programming, and since the scheduling algorithm 110 may be a prior art, it is not described herein in detail.
Second embodiment
Fig. 2 is a flowchart of a high fault tolerance energy supply group load scheduling method based on bias distribution according to an embodiment of the present invention, where in this embodiment, the execution body of the high fault tolerance energy supply group load scheduling method based on bias distribution may be any device, for example, the device 121 shown in fig. 1.
Referring to fig. 2, the high fault tolerance energy supply group load scheduling method based on deviation allocation specifically includes steps S210 to S250:
s210: a scheduling scheme output by a scheduling algorithm for the powered group is obtained.
As shown in fig. 1, the scheduling algorithm is a prior art, and this embodiment is not discussed, where the scheduling scheme obtained by the scheduling algorithm may be an optimization scheme for energy supply group operation, such as load optimization.
In an exemplary embodiment, the scheduling scheme includes at least: the proposed start-stop status and the specified load for each device in the powered group.
S220: and comparing the actual on-site states of the to-be-started devices of the energy supply group with the actual on-site states of the to-be-started devices in the scheduling scheme, and determining the devices with inconsistent start-stop states.
On the basis of the above example, please refer to fig. 3, which shows a flowchart of step S220 in an embodiment, as shown in fig. 3, the step S220 may specifically include:
s310: when the scheduling scheme of the equipment is to be started and the load is appointed, judging whether the equipment is not started at the present place or not: if yes, determining that the equipment is inconsistent in start-stop state;
s320: when the scheduling scheme of the equipment is to be closed, judging whether the equipment is opened and bears load at the present place; if yes, determining that the equipment is inconsistent in start-stop state.
In the two situations of determining the equipment with inconsistent start-stop states, namely if the scheduling scheme is about to start a certain equipment and designates a load, the equipment is determined to be the equipment with inconsistent start-stop states if the field equipment is not started, if the scheduling scheme is about to close the certain equipment, but the field actual equipment is started and bears the load, the equipment is determined to be the equipment with inconsistent start-stop states, and all the field equipment which is inconsistent with the output result of the initial scheduling scheme can be screened out through real-time mapping of the scheduling scheme and the field equipment.
S230: and carrying out load deviation calculation one by one aiming at the equipment with inconsistent start-stop states to obtain a total load difference.
In connection with the above example, referring to fig. 4, a flowchart of the above step S230 is shown in an embodiment for a device with inconsistent start-stop states in two situations, and as shown in fig. 4, the step S230 may be implemented as the following steps S410-S420:
s410: for devices whose scheduling scheme is to be on and assigned but not on site: aiming at the equipment with inconsistent start-stop states, keeping a field unopened state; and accounting the total load difference of the designated load to be allocated to the equipment in the scheduling scheme.
S420: for a device whose scheduling scheme is to be off but whose site is on: the on-site opening state is kept, and the load is not changed; and taking the opposite number of the field load bearing load of the equipment, and then accounting the total load difference, wherein the total load difference is initially zero.
The embodiment keeps the on-site state of the equipment, can enable the equipment to quickly respond to the scheduling scheme, and when the scheduling scheme of the equipment is adjusted, the statistics is carried out to generate the total load difference, and obviously the total load difference is positive and negative, and the initial value of the total load difference is zero.
S240: and carrying out load deviation secondary distribution on the total load difference in the equipment with the energy supply group being actually started to form a real-time mapping of the scheduling scheme and the field actual state of the energy supply group.
It should be noted that, since the scheduling scheme is a global scheme, which is equivalent to a complete system, in order to ensure the level of the system, when the scheduling scheme of some devices changes, the load total difference caused by the change needs to be redistributed in the system, so that the scheduling scheme is suitable for the energy supply group.
Specifically, referring to fig. 5, in a flowchart of the step S240 in an embodiment, as shown in fig. 5, the step S240 may specifically include steps S510 to S520:
s510: acquiring a preset distribution coefficient of equipment actually started in an energy supply group;
s520: and carrying out load deviation secondary distribution on the total load difference in the equipment actually started in the energy supply group according to the distribution coefficient to form real-time mapping of the scheduling scheme and the field actual state of the energy supply group.
The distribution coefficient is set so that the devices in the energy supply group can reasonably bear loads, for example, the devices with good performance bear stable high loads, and the devices with poor performance bear low loads with large fluctuation.
For example, the preset allocation coefficient for the actually turned-on devices in the energy supply group may be implemented as:
dividing the actually opened devices in the energy supply group into a load peak regulation role device group and a load basic role device group; determining the distribution coefficient of each device in the load peak regulation role device group as ai=2/(2y1+y2); and determining the distribution coefficient of each device in the first load basic role device group as ai=1/(2y1+y2), wherein Y1 is the number of devices in the load peak regulation role device group, Y2 is the number of devices in the load basic role device group, and the sum of the distribution coefficients of each device is 1.
For another example, the preset allocation coefficient for the actually turned-on devices in the energy supply group may also be implemented as: and determining the distribution coefficient according to the characteristics of each device, wherein the devices ai with high load adjustment rate are higher, the devices ai with low adjustment rate are lower, and the sum of deviation distribution coefficients is ensured to be 1.
Illustratively, the total load bias is distributed according to a distribution coefficient: for devices with deviation distribution coefficients, i.e. devices that are actually on site, the load deviation assigned to each device is fi=ai×z.
The energy supply group equipment divides the on-site actual starting equipment into a load peak regulation role equipment group Y1 and a load basic role equipment group Y2 according to the on-site conditions, the load fluctuation conditions and the like according to a certain proportion.
Specifically, according to the actual condition of the field device, the operator designates the actual on-site boiler as a load peak regulation role group Y1 and a load basic role group Y2 according to the actual condition of the field device, if the ratio of the peak regulation device to the basic device is manually designated to be 1:2 and the actual on-site boiler is 6, the equipment can be divided into 2 peak regulation devices and 4 basic devices according to the ratio, and the ratio can be automatically allocated by a person skilled in the art according to the actual condition of the field device and is not described herein.
In addition, referring to fig. 6, in an embodiment, as shown in fig. 6, the step S520 may specifically include steps S610 to S620:
s610: aiming at the equipment which is to be started and assigned with load by a scheduling scheme in the energy supply group and is actually started, the real-time load value is equal to the sum of the assigned load and the load deviation secondary distribution.
For example, for the devices that are actually started on site and the scheduling scheme is to be started, if the load originally allocated to the devices by the scheduling scheme is Ei, the real-time load value designated by each boiler after the deviation allocation is P 'i, and then P' i=fi+ei exists.
S620: for the equipment which is actually started and bears the load in the energy supply group and is not started by the scheduling scheme, the real-time load value is equal to the sum of the load bearing load and the load deviation secondary distribution.
For example, for a device whose field is actually on and the scheduling scheme is not output as on, if the load actually borne by the device on the field is E 'i, the real-time load value designated by each boiler after the deviation allocation is P' i, and P 'i=fi+e' i.
S250: and outputting a scheduling scheme after load deviation secondary distribution.
Specifically, the load deviation scheduling scheme after secondary distribution is output to each on-site actual opened device.
In summary, the method can ensure that the total load of the scheduling scheme and the actual field operation equipment is equal in real time, parallel mapping of virtual strategies and real scenes can be realized through the method no matter how large deviation of the number of the started equipment and the actual operation equipment is, stable fault-tolerant operation of groups can be realized under the unconventional conditions of abnormal equipment shutdown and the like, and meanwhile, real-time multi-strategy parallelism can be realized by adjusting the distribution coefficient of single equipment.
It should be understood that the sequence number of each step in the foregoing embodiment does not mean the sequence of execution sequence, and the execution sequence of each process should be determined by its energy supply and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.
Third embodiment
Under the general inventive concept with the second embodiment, the present embodiment also provides a high fault tolerance energy supply group load scheduling device based on deviation distribution.
Referring to fig. 7, a schematic diagram of a high fault tolerance power group load dispatching apparatus based on bias distribution according to an embodiment of the present invention is shown. In a specific implementation, the high fault tolerance energy supply group load scheduling device based on bias distribution in this embodiment may be used for installation in the apparatus shown in fig. 1.
As shown in fig. 7, the high fault tolerance energy supply group load scheduling device 700 based on bias distribution may specifically include: a scheduling scheme acquisition module 710 configured to acquire a scheduling scheme output by a scheduling algorithm for an energy group; a comparison module 720 configured to compare the actual on-site states of the power-on devices and the power-on devices in the scheduling scheme, and determine devices with inconsistent start-stop states; the load total difference calculation module 730 is configured to perform load deviation calculation on the devices with inconsistent start-stop states one by one to obtain a load total difference; the total load difference distribution module 740 is configured to perform load deviation secondary distribution on the total load difference in the equipment actually started by the energy supply group, so as to form real-time mapping between the scheduling scheme and the actual field state of the energy supply group; the scheduling scheme output module 750 is configured to output the scheduling scheme after the load deviation is secondarily allocated.
In some embodiments, the scheduling scheme includes at least: the proposed start-stop status and the specified load for each device in the powered group.
In some embodiments, the comparison module 720 specifically includes: a device scheduling scheme determining unit configured to determine a state of each device in the energy supply group in the scheduling scheme one by one: a first device on-site status judging unit configured to judge whether the device is not turned on at the present site when the scheduling scheme of the device is to be turned on and a load is specified; and the first state abnormal equipment determining unit is configured to determine that the equipment is equipment with inconsistent start-stop states if the equipment is configured to be in the state of being out of the state of being the equipment.
In some embodiments, the load total difference calculation module 730 specifically includes: a first device scheduling scheme adjustment unit configured to maintain a field unopened state for devices whose start-stop states are inconsistent; and the first load total difference statistics unit is configured to account the specified load to be allocated to the equipment in the scheduling scheme into the load total difference, and the load total difference is initially zero.
In some embodiments, the comparison module 720 further comprises: a second device on-site status judging unit configured to judge whether the device is on and bears a load at the present site when the scheduling scheme of the device is to be turned off; and the second state abnormal equipment determining unit is configured to determine that the equipment is equipment with inconsistent start-stop states if the equipment is configured to be in the state of being out of the state of being.
In some embodiments, the load total difference calculation module 730 specifically includes: the second equipment scheduling scheme adjusting unit is configured to keep a site open state and bear load unchanged for the equipment with inconsistent start-stop states; and a second load total difference statistics unit configured to count the load total differences of the equipment after taking the opposite numbers of the load on site, wherein the load total differences are initially zero.
In some embodiments, the total load differential module 740 includes: the distribution coefficient acquisition unit is configured to acquire distribution coefficients preset for the devices actually started in the energy supply group; and the load deviation distribution unit is configured to carry out load deviation secondary distribution on the total load difference in the equipment actually started in the energy supply group according to the distribution coefficient, so as to form a real-time mapping of the scheduling scheme and the actual field state of the energy supply group.
In some embodiments, the distribution coefficient obtaining unit specifically includes: the device grouping unit is configured to divide the actually opened devices in the energy supply group into a load peak regulation role device group and a load basic role device group; determining the distribution coefficient of each device in the load peak regulation role device group as ai=2/(2y1+y2); and determining the distribution coefficient of each device in the first load basic role device group as ai=1/(2y1+y2), wherein Y1 is the number of devices in the load peak regulation role device group, Y2 is the number of devices in the load basic role device group, and the sum of the distribution coefficients of each device is 1.
In some embodiments, the load deviation distribution unit specifically includes: the first distribution unit is configured to be started and assigned with a load aiming at a scheduling scheme in the energy supply group, and the real-time load value of the equipment which is actually started is equal to the sum of the assigned load and the load deviation obtained by secondary distribution; and the second distribution unit is configured to output the opened equipment aiming at the actual opened and loaded load in the energy supply group, and the real-time load value is equal to the sum of the loaded load and the load deviation secondary distribution.
It should be noted that, regarding the specific implementation process or principle of the present embodiment and the corresponding technical effects, reference may be made to the above second embodiment, which is not described herein.
The above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention, and are intended to be included in the scope of the present invention.
Claims (10)
1. A high fault tolerance energy supply group load scheduling method based on bias distribution, comprising:
acquiring a scheduling scheme output by a scheduling algorithm aiming at an energy supply group;
comparing the actual on-site states of the to-be-started devices of the energy supply group and the to-be-started devices in the scheduling scheme, and determining devices with inconsistent start-stop states;
carrying out load deviation calculation one by one aiming at the equipment with inconsistent start-stop states to obtain a total load difference;
performing load deviation secondary distribution on the total load difference in the equipment actually started by the energy supply group to form real-time mapping of the scheduling scheme and the actual field state of the energy supply group;
and outputting a scheduling scheme after load deviation secondary distribution.
2. The high fault tolerance energy group load scheduling method based on bias distribution according to claim 1, wherein the scheduling scheme at least comprises: the proposed start-stop status and the specified load for each device in the powered group.
3. The high fault tolerance energy supply group load scheduling method based on deviation allocation according to claim 2, wherein determining the device with inconsistent start-stop state compared with the on-site actual state of the energy supply group to be started device in the scheduling scheme comprises determining the state of each device in the energy supply group in the scheduling scheme one by one:
when the scheduling scheme of the equipment is to be started and the load is appointed, judging whether the equipment is not started at the present place or not: if yes, determining that the equipment is inconsistent in start-stop state;
when the scheduling scheme of the equipment is to be closed, judging whether the equipment is opened and bears load at the present place; if yes, determining that the equipment is inconsistent in start-stop state.
4. The high fault tolerance energy supply group load scheduling method based on deviation distribution according to claim 3, wherein the load deviation calculation is performed one by one for the equipment with inconsistent start-stop states to obtain a total load difference, and the method specifically comprises the following steps:
for devices whose scheduling scheme is to be on and assigned but not on site: aiming at the equipment with inconsistent start-stop states, keeping a field unopened state; the designated load to be allocated to the equipment in the scheduling scheme is counted as a total load difference;
for a device whose scheduling scheme is to be off but whose site is on: the on-site opening state is kept, and the load is not changed; and taking the opposite number of the field load bearing load of the equipment, and then accounting the total load difference, wherein the total load difference is initially zero.
5. The high fault tolerance energy supply group load scheduling method based on deviation distribution according to claim 4, wherein the load deviation secondary distribution is performed on the total load difference in the equipment where the energy supply group is actually turned on, so as to form a real-time mapping between the scheduling scheme and the actual state of the energy supply group field, and the method comprises the following steps:
acquiring a preset distribution coefficient of equipment actually started in an energy supply group;
and carrying out load deviation secondary distribution on the total load difference in the equipment actually started in the energy supply group according to the distribution coefficient to form real-time mapping of the scheduling scheme and the field actual state of the energy supply group.
6. The high fault tolerance power group load scheduling method based on bias distribution according to claim 5, wherein the distribution coefficient preset for the devices actually turned on in the power group comprises:
dividing the actually opened devices in the energy supply group into a load peak regulation role device group and a load basic role device group;
determining the distribution coefficient of each device in the load peak regulation role device group as ai=2/(2y1+y2);
determining the distribution coefficient of each device in the first load basic role device group as ai=1/(2y1+y2),
wherein Y1 is the number of devices of the load peak regulation role device group, Y2 is the number of devices of the load basic role device group, and the sum of distribution coefficients of the devices is 1.
7. The high fault tolerance energy supply group load scheduling method based on deviation distribution according to claim 6, wherein load deviation secondary distribution is carried out on the total load difference in the equipment actually started in the energy supply group according to the distribution coefficient, so as to form a real-time mapping between the scheduling scheme and the actual state of the energy supply group field, and the method specifically comprises the following steps:
aiming at the equipment which is to be started and assigned with load by a scheduling scheme in the energy supply group and is actually started, the real-time load value is equal to the sum of the assigned load and the load deviation obtained by secondary distribution;
for the equipment which is actually started and bears the load in the energy supply group and is not started by the scheduling scheme, the real-time load value is equal to the sum of the load bearing load and the load deviation secondary distribution.
8. The high fault tolerance energy group load scheduling method based on bias distribution according to any one of claims 1 to 7, wherein the scheduling scheme after output load bias secondary distribution comprises:
and outputting the load deviation scheduling scheme after secondary distribution to each on-site actual opened device.
9. A high fault tolerance energy group load scheduling apparatus based on bias distribution, comprising:
a scheduling scheme acquisition module configured to acquire a scheduling scheme output by a scheduling algorithm for the energy supply group;
the comparison module is configured to compare the actual on-site states of the to-be-started devices for the energy supply group and the to-be-started devices in the scheduling scheme, and determine the devices with inconsistent start-stop states;
the load total difference calculation module is configured to calculate load deviation one by one aiming at the equipment with inconsistent start-stop states to obtain load total difference;
the load total difference distribution module is configured to carry out load deviation secondary distribution on the load total difference in the equipment actually started by the energy supply group to form real-time mapping of the scheduling scheme and the field actual state of the energy supply group;
and the scheduling scheme output module is configured to output the scheduling scheme after the load deviation is secondarily distributed.
10. A terminal device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any of claims 1 to 8 when the computer program is executed.
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Citations (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPS63171124A (en) * | 1987-01-05 | 1988-07-14 | 株式会社東芝 | Load regulator |
CN102097866A (en) * | 2011-03-28 | 2011-06-15 | 国电南瑞科技股份有限公司 | Mid-long-term unit commitment optimizing method |
CN105490268A (en) * | 2015-12-30 | 2016-04-13 | 中国南方电网有限责任公司 | Load tracking method and system for AC/DC interconnected network |
CN105546745A (en) * | 2015-12-29 | 2016-05-04 | 深圳市奥宇节能技术股份有限公司 | Group control method and device for central air conditioner main machine unit |
CN107124002A (en) * | 2017-04-28 | 2017-09-01 | 上海交通大学 | Independent micro-grid energy optimal control method based on bi-fuzzy control |
CN107134811A (en) * | 2017-07-05 | 2017-09-05 | 广东电网有限责任公司电网规划研究中心 | Network load regulation spare capacity appraisal procedure based on frequency shift (FS) probability distribution |
CN110598952A (en) * | 2019-09-23 | 2019-12-20 | 广西电网有限责任公司 | Medium-and-long-term electric power market safety checking and model establishing method and equipment |
CN110635476A (en) * | 2019-09-29 | 2019-12-31 | 合肥工业大学 | Knowledge migration-based cross-regional interconnected power grid dynamic scheduling rapid optimization method |
CN110676846A (en) * | 2019-10-11 | 2020-01-10 | 国网山东省电力公司经济技术研究院 | Power peak regulation method, dispatching center and power peak regulation system |
CN111639793A (en) * | 2020-05-13 | 2020-09-08 | 新奥数能科技有限公司 | Boiler group scheduling optimization method and device |
-
2020
- 2020-10-22 CN CN202011139357.XA patent/CN112308303B/en active Active
Patent Citations (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPS63171124A (en) * | 1987-01-05 | 1988-07-14 | 株式会社東芝 | Load regulator |
CN102097866A (en) * | 2011-03-28 | 2011-06-15 | 国电南瑞科技股份有限公司 | Mid-long-term unit commitment optimizing method |
CN105546745A (en) * | 2015-12-29 | 2016-05-04 | 深圳市奥宇节能技术股份有限公司 | Group control method and device for central air conditioner main machine unit |
CN105490268A (en) * | 2015-12-30 | 2016-04-13 | 中国南方电网有限责任公司 | Load tracking method and system for AC/DC interconnected network |
CN107124002A (en) * | 2017-04-28 | 2017-09-01 | 上海交通大学 | Independent micro-grid energy optimal control method based on bi-fuzzy control |
CN107134811A (en) * | 2017-07-05 | 2017-09-05 | 广东电网有限责任公司电网规划研究中心 | Network load regulation spare capacity appraisal procedure based on frequency shift (FS) probability distribution |
CN110598952A (en) * | 2019-09-23 | 2019-12-20 | 广西电网有限责任公司 | Medium-and-long-term electric power market safety checking and model establishing method and equipment |
CN110635476A (en) * | 2019-09-29 | 2019-12-31 | 合肥工业大学 | Knowledge migration-based cross-regional interconnected power grid dynamic scheduling rapid optimization method |
CN110676846A (en) * | 2019-10-11 | 2020-01-10 | 国网山东省电力公司经济技术研究院 | Power peak regulation method, dispatching center and power peak regulation system |
CN111639793A (en) * | 2020-05-13 | 2020-09-08 | 新奥数能科技有限公司 | Boiler group scheduling optimization method and device |
Non-Patent Citations (1)
Title |
---|
节能发电调度的网厂两级优化方案;牛玉广;谭文;苏凯;刘吉臻;;中国电力(第09期);第15-18页 * |
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