CN112054522A - Micro-grid optimization scheduling method and system - Google Patents
Micro-grid optimization scheduling method and system Download PDFInfo
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- CN112054522A CN112054522A CN202010978421.7A CN202010978421A CN112054522A CN 112054522 A CN112054522 A CN 112054522A CN 202010978421 A CN202010978421 A CN 202010978421A CN 112054522 A CN112054522 A CN 112054522A
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/001—Methods to deal with contingencies, e.g. abnormalities, faults or failures
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—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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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
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Abstract
The invention discloses a microgrid optimization scheduling method and a microgrid optimization scheduling system in the technical field of power scheduling, wherein local environment parameters, electricity utilization habit parameters and working condition parameters of a microgrid are fully considered, and blindness of a scheduling scheme can be well avoided, so that the microgrid scheduling scheme is more in line with actual requirements, and value maximization is realized. The method comprises the following steps: a. selecting a configuration scheme to configure the micro-grid system based on the environmental characteristics and historical electricity utilization habits of the location of the micro-grid system; b. acquiring current working condition parameters of each power generation subsystem in the microgrid system and current environment parameters of the location of each power generation subsystem; c. and outputting a joint scheduling scheme of each power generation system in the microgrid system based on the current working condition parameters of each power generation system, the current environment parameters of the location of each power generation system and the current power utilization habit model.
Description
Technical Field
The invention belongs to the technical field of power dispatching, and particularly relates to a microgrid optimization dispatching method and a microgrid optimization dispatching system.
Background
The Micro-Grid (Micro-Grid) is also translated into a Micro-Grid, which refers to a small power generation and distribution system composed of a distributed power supply, an energy storage device, an energy conversion device, a load, a monitoring and protecting device and the like. The micro-grid aims to realize flexible and efficient application of distributed power supplies and solve the problem of grid connection of the distributed power supplies with large quantity and various forms. The development and extension of the micro-grid can fully promote the large-scale access of distributed power sources and renewable energy sources, realize the high-reliability supply of various energy source types of loads, and is an effective mode for realizing an active power distribution network, so that the traditional power grid is transited to a smart power grid. However, the existing microgrid scheduling method generally adopts an independent scheduling mode, and the scheduling scheme has certain blindness, which easily causes unreasonable and unsafe microgrid scheduling results.
Disclosure of Invention
In order to overcome the defects in the prior art, the invention provides the microgrid optimization scheduling method and the microgrid optimization scheduling system, which fully consider local environment parameters, electricity utilization habit parameters and working condition parameters of the microgrid, and can well avoid the blindness of the scheduling scheme, so that the microgrid scheduling scheme is more in line with the actual requirements, and the value is maximized.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows: a microgrid optimization scheduling method comprises the following steps: a. selecting a configuration scheme to configure the micro-grid system based on the environmental characteristics and historical electricity utilization habits of the location of the micro-grid system; b. acquiring current working condition parameters of each power generation subsystem in the microgrid system and current environment parameters of the location of each power generation subsystem; c. and outputting a joint scheduling scheme of each power generation system in the microgrid system based on the current working condition parameters of each power generation system, the current environment parameters of the location of each power generation system and the current power utilization habit model.
Further, in the step a, the method for selecting the configuration scheme includes: firstly, selecting a micro-grid system configuration scheme which can adapt to local environmental characteristics, then selecting a configuration scheme which can meet the historical electricity utilization habits, and finally, obtaining the configuration scheme with the highest comprehensive benefit by adopting multi-packet differential evolution algorithm optimization calculation.
Further, in the step c, the method further includes: and performing real-time working condition evaluation on each power generation system based on the current working condition parameters of each power generation system, and outputting a fine adjustment scheme based on a joint scheduling scheme and the result of the working condition evaluation.
And further, when the result of the working condition evaluation falls into a preset fault threshold, starting an early warning scheme.
Further, in the step c, the method further includes: and performing real-time environment evaluation on each power generation system based on the current environment parameters of the location of each power generation system, and calling an emergency scheduling scheme when the environment evaluation result falls into a preset severe environment.
Further, the emergency scheduling scheme is as follows: and (4) turning the power generation subsystem in the severe environment to a dormant state, and simultaneously awakening the large power grid corresponding to the region for emergency power supply.
A microgrid optimized dispatch system comprising: the system configuration module is used for selecting a configuration scheme to configure the micro-grid system based on the environmental characteristics and the historical electricity utilization habits of the location of the micro-grid system; the data acquisition module is used for acquiring the current working condition parameters of each power generation subsystem in the microgrid system and the current environment parameters of the location of each power generation subsystem; and the optimized scheduling module is used for outputting a joint scheduling scheme of each power generation system in the microgrid system based on the current working condition parameters of each power generation system, the current environment parameters of the location of each power generation system and the current power utilization habit model.
And further, the system also comprises a data mining module which is used for reading and storing all executed scheduling schemes and public data of each power generation subsystem between the two scheduling schemes.
Compared with the prior art, the invention has the following beneficial effects: according to the method, local environmental parameters, electricity utilization habit parameters and working condition parameters of the micro-grid system are fully considered, so that the blindness of a scheduling scheme can be well avoided, the micro-grid scheduling scheme can better meet the actual requirement, and the value maximization is realized; by adopting a joint scheduling mode, the advantages of different power generation subsystems in different weather environments can be utilized to realize the maximization of the generated energy and finally realize the maximization of the value; the mode of adopting the scheduling scheme and the working condition data of each micro-grid power generation system to be fully recorded realizes the full tracing of the whole micro-grid power generation system working process, and simultaneously improves the running stability and safety of the micro-grid system.
Drawings
Fig. 1 is a schematic flowchart of a microgrid optimization scheduling method according to an embodiment of the present invention;
fig. 2 is a schematic flowchart of a microgrid optimization scheduling method according to a second embodiment of the present invention;
fig. 3 is a schematic flowchart of a microgrid optimization scheduling method according to a third embodiment of the present invention.
Detailed Description
The invention is further described below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present invention is not limited thereby.
The first embodiment is as follows:
as shown in fig. 1, a microgrid optimization scheduling method includes:
s1, configuring the microgrid system according to the environmental characteristics of the location of the microgrid system and the historical electricity utilization habit characteristics with the highest comprehensive benefit; firstly, selecting a micro-grid system configuration scheme which can adapt to local environment characteristics, then selecting a configuration scheme which can meet the characteristics of the historical power utilization habits, and finally obtaining a configuration scheme with the highest comprehensive benefit by adopting multi-packet differential evolution algorithm optimization calculation;
s2, acquiring working condition parameters of each power generation subsystem in the microgrid system based on a working condition acquisition module carried on the microgrid system, and acquiring current environmental parameters based on weather sensors carried near each power generation subsystem in the microgrid system;
and S3, outputting a joint scheduling scheme of each power generation system in the microgrid system based on the current working condition parameters of each power generation system, the current environment parameters of the location of each power generation system and the current power utilization habit model.
In this embodiment, the electricity usage habit model is constructed based on a historical electricity usage parameter (electricity demand).
Example two:
as shown in fig. 2, the difference between this embodiment and the first embodiment is that in this embodiment, the following steps are further included:
s4, performing real-time working condition evaluation on each power generation system based on the current working condition parameters of each power generation system, and outputting a fine adjustment scheme based on a joint scheduling scheme and the result of the working condition evaluation; when the result of the working condition evaluation falls into a preset fault threshold, starting an early warning scheme, wherein the step comprises the following steps of: starting a short message automatic editing module to send a result of the working condition evaluation to a maintainer terminal;
performing real-time environment evaluation on each power generation system based on the current environment parameters of the location of each power generation system, and calling an emergency scheduling scheme when the environment evaluation result falls into a preset severe environment; the emergency scheduling scheme is as follows: and (4) turning the power generation subsystem in the severe environment to a dormant state, and simultaneously awakening the large power grid corresponding to the region for emergency power supply.
EXAMPLE III
As shown in fig. 3, the difference between this embodiment and the second embodiment is that in this embodiment, the following steps are further included:
and S5, realizing the summary registration of all executed scheduling schemes and the public data of each power generation subsystem in the microgrid system between the two scheduling schemes in the form of an EXCEL table based on the data mining module, thereby realizing the traceability of all scheduling schemes.
According to the method, local environment parameters, electricity utilization habit parameters and working condition parameters of the microgrid system are fully considered, so that the blindness of a scheduling scheme can be well avoided, the microgrid scheduling scheme can better meet the actual requirements, and the value maximization is realized; by adopting a joint scheduling mode, the advantages of different power generation subsystems in different weather environments can be utilized to realize the maximization of the generated energy and finally realize the maximization of the value; the mode of adopting the scheduling scheme and the working condition data of each micro-grid power generation system to be fully recorded realizes the full tracing of the whole micro-grid power generation system working process, and simultaneously improves the running stability and safety of the micro-grid system.
Example four:
based on the microgrid optimization scheduling method according to the first to third embodiments, the present embodiment provides a microgrid optimization scheduling system, including:
the system configuration module is used for selecting a configuration scheme to configure the micro-grid system based on the environmental characteristics and the historical electricity utilization habits of the location of the micro-grid system;
the data acquisition module is used for acquiring the current working condition parameters of each power generation subsystem in the microgrid system and the current environment parameters of the location of each power generation subsystem;
the optimal scheduling module is used for outputting a joint scheduling scheme of each power generation system in the microgrid system based on the current working condition parameters of each power generation system, the current environment parameters of the location of each power generation system and the current power utilization habit model;
and the data mining module is used for reading and storing all executed scheduling schemes and public data of each power generation subsystem between the two scheduling schemes.
The above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the protection scope of the present invention.
Claims (8)
1. A microgrid optimization scheduling method is characterized by comprising the following steps:
a. selecting a configuration scheme to configure the micro-grid system based on the environmental characteristics and historical electricity utilization habits of the location of the micro-grid system;
b. acquiring current working condition parameters of each power generation subsystem in the microgrid system and current environment parameters of the location of each power generation subsystem;
c. and outputting a joint scheduling scheme of each power generation system in the microgrid system based on the current working condition parameters of each power generation system, the current environment parameters of the location of each power generation system and the current power utilization habit model.
2. The microgrid optimization scheduling method of claim 1, wherein in the step a, a method for selecting a configuration scheme is as follows: firstly, selecting a micro-grid system configuration scheme which can adapt to local environmental characteristics, then selecting a configuration scheme which can meet the historical electricity utilization habits, and finally, obtaining the configuration scheme with the highest comprehensive benefit by adopting multi-packet differential evolution algorithm optimization calculation.
3. The microgrid optimized dispatching method of claim 1, wherein in the step c, further comprising: and performing real-time working condition evaluation on each power generation system based on the current working condition parameters of each power generation system, and outputting a fine adjustment scheme based on a joint scheduling scheme and the result of the working condition evaluation.
4. The microgrid optimization scheduling method of claim 3, characterized by the step of starting an early warning scheme when the result of the condition evaluation falls within a preset fault threshold.
5. The microgrid optimized dispatching method of claim 1, wherein in the step c, further comprising: and performing real-time environment evaluation on each power generation system based on the current environment parameters of the location of each power generation system, and calling an emergency scheduling scheme when the environment evaluation result falls into a preset severe environment.
6. The microgrid optimized dispatching method of claim 5, wherein the emergency dispatching scheme is as follows: and (4) turning the power generation subsystem in the severe environment to a dormant state, and simultaneously awakening the large power grid corresponding to the region for emergency power supply.
7. A microgrid optimization scheduling system is characterized by comprising:
the system configuration module is used for selecting a configuration scheme to configure the micro-grid system based on the environmental characteristics and the historical electricity utilization habits of the location of the micro-grid system;
the data acquisition module is used for acquiring the current working condition parameters of each power generation subsystem in the microgrid system and the current environment parameters of the location of each power generation subsystem;
and the optimized scheduling module is used for outputting a joint scheduling scheme of each power generation system in the microgrid system based on the current working condition parameters of each power generation system, the current environment parameters of the location of each power generation system and the current power utilization habit model.
8. The microgrid optimized dispatching system of claim 7, further comprising a data mining module for reading and storing all executed dispatching plans and public data of each power generation subsystem located between the two dispatching plans.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112865088A (en) * | 2021-01-29 | 2021-05-28 | 杭州市电力设计院有限公司余杭分公司 | Double-layer optimized scheduling method for power distribution network |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103825279A (en) * | 2014-02-21 | 2014-05-28 | 华南理工大学 | Micro-grid system voltage stability control method based on robust control |
| CN105869075A (en) * | 2016-04-19 | 2016-08-17 | 东南大学 | Economic optimization scheduling method for cold, heat and electricity combined supply type miniature energy grid |
| CN107798441A (en) * | 2017-12-01 | 2018-03-13 | 北华航天工业学院 | A kind of smart micro-grid system based on distributed power generation |
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Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103825279A (en) * | 2014-02-21 | 2014-05-28 | 华南理工大学 | Micro-grid system voltage stability control method based on robust control |
| CN105869075A (en) * | 2016-04-19 | 2016-08-17 | 东南大学 | Economic optimization scheduling method for cold, heat and electricity combined supply type miniature energy grid |
| CN107798441A (en) * | 2017-12-01 | 2018-03-13 | 北华航天工业学院 | A kind of smart micro-grid system based on distributed power generation |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112865088A (en) * | 2021-01-29 | 2021-05-28 | 杭州市电力设计院有限公司余杭分公司 | Double-layer optimized scheduling method for power distribution network |
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Application publication date: 20201208 |