CN116885796A - Intelligent adjustment method and system for power system - Google Patents
Intelligent adjustment method and system for power system Download PDFInfo
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- CN116885796A CN116885796A CN202310741064.6A CN202310741064A CN116885796A CN 116885796 A CN116885796 A CN 116885796A CN 202310741064 A CN202310741064 A CN 202310741064A CN 116885796 A CN116885796 A CN 116885796A
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- 238000004422 calculation algorithm Methods 0.000 claims abstract description 17
- 239000003344 environmental pollutant Substances 0.000 claims abstract description 12
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- 238000010248 power generation Methods 0.000 claims abstract description 10
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
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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
- H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
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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 application relates to the technical field of power system dispatching, and provides an intelligent power system adjusting method and system, comprising the following steps: acquiring relevant parameters of a power system; initializing a plurality of unit output forces based on related parameters of the power system; the method comprises the steps of optimizing the output of a unit by using a multi-target Harris eagle optimization algorithm with minimum power generation cost and minimum pollutant gas emission as objective functions to obtain the optimal output of the unit; the calculation of escape energy adopted by the multi-target Harris eagle optimization algorithm is mainly based on a sine function and an exponential function, and is assisted by a random number. The problem that the output power of the generator to be optimized in the power system is excessive, and the optimal unit output is difficult to obtain is solved.
Description
Technical Field
The application belongs to the technical field of power system dispatching, and particularly relates to an intelligent power system adjusting method and system.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
With the increasing aggravation of environmental pollution, the power system multi-objective optimization scheduling method comprehensively considering environmental protection and economic benefits becomes a research hotspot.
However, the existing multi-objective optimization scheduling method of the power system mainly comprises a traditional multi-objective genetic algorithm, a double-layer consistency algorithm and the like, and the fact that the excessive output power of a generator to be optimized in the power system is not considered, so that an optimal result can be obtained only after a long time is needed, or the optimal result is easily obtained, or the optimal unit output is difficult to obtain.
Disclosure of Invention
In order to solve the technical problems in the background art, the application provides the intelligent regulation method and the intelligent regulation system for the electric power system, and solves the problems that the output power of a generator to be optimized in the electric power system is excessive and the optimal unit output is difficult to obtain.
In order to achieve the above purpose, the present application adopts the following technical scheme:
a first aspect of the present application provides an intelligent regulation method for an electric power system, comprising:
acquiring relevant parameters of a power system;
initializing a plurality of unit output forces based on related parameters of the power system;
the method comprises the steps of optimizing the output of a unit by using a multi-target Harris eagle optimization algorithm with minimum power generation cost and minimum pollutant gas emission as objective functions to obtain the optimal output of the unit;
the calculation of escape energy adopted by the multi-target Harris eagle optimization algorithm is mainly based on a sine function and an exponential function, and is assisted by a random number.
Further, the escape energy E is:
E＝rand×(exp(-50/(T×t))×sin(T×t/50))
wherein, the rand random number, T is the iteration number, and T represents the maximum iteration number.
Further, the power system related parameters include a generator generation cost parameter, a pollutant gas emission amount parameter, a line loss coefficient, a generator output constraint parameter, and a load demand parameter.
Further, a unit output includes the output power of all generators.
A second aspect of the present application provides an intelligent regulation system for an electrical power system, comprising:
a data acquisition module configured to: acquiring relevant parameters of a power system;
an initialization module configured to: initializing a plurality of unit output forces based on related parameters of the power system;
an optimization module configured to: the method comprises the steps of optimizing the output of a unit by using a multi-target Harris eagle optimization algorithm with minimum power generation cost and minimum pollutant gas emission as objective functions to obtain the optimal output of the unit;
the calculation of escape energy adopted by the multi-target Harris eagle optimization algorithm is mainly based on a sine function and an exponential function, and is assisted by a random number.
A third aspect of the application provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps in a power system intelligent regulation method as described above.
A fourth aspect of the application provides a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps in the power system intelligent regulation method as described above when the program is executed.
Compared with the prior art, the application has the beneficial effects that:
the application provides an intelligent regulation method of an electric power system, which considers the problem that the output power of a generator to be optimized in the electric power system is too much, and the optimal unit output is difficult to obtain, and adopts the oscillation trend of escape energy to take a sine function and an exponential function as main parts and a random number as auxiliary parts, so that the overall cross jump between positive and negative is ensured, and the oscillation attenuation trend is presented, so that the overall optimization is carried out; however, no positive and negative cross jump exists between the adjacent iteration steps, so that local optimization is performed, and the output of the optimal unit is further ensured.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application.
Fig. 1 is a flowchart of an intelligent power system adjusting method according to a first embodiment of the present application.
Detailed Description
The application will be further described with reference to the drawings and examples.
It should be noted that the following detailed description is illustrative and is intended to provide further explanation of the application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
Example 1
The embodiment provides an intelligent regulation method for a power system.
The intelligent power system adjusting method provided by the embodiment, as shown in fig. 1, includes the following steps:
step 1, acquiring relevant parameters of an electric power system, including a generator power generation cost parameter, a pollutant gas emission amount parameter, a line loss coefficient, a generator output constraint parameter and a load demand parameter;
step 2, initializing a population based on related parameters of the power system and combining an equality constraint condition and an inequality constraint condition of a multi-objective optimization scheduling model of the power system, wherein one individual in the population represents one set output (including the output power of all generators), namely initializing a plurality of sets output;
and 3, optimizing the population (unit output) by using the minimum power generation cost and the minimum pollutant gas emission as objective functions and using a multi-objective Harris eagle optimization algorithm MOHHO to obtain the optimal unit output.
The patent of the power system multi-objective optimization scheduling method based on the double-layer consistency algorithm can refer to an objective function with minimum power generation cost and minimum pollutant gas emission, wherein the objective function comprises power system related parameters, equation constraint conditions and inequality constraint conditions of a power system multi-objective optimization scheduling model, and can refer to application number 201811268437.8.
The existing MOHHO adopts escape energy to perform conversion of different states, wherein the calculation method of the escape energy E comprises the following steps:
E＝rand×(1-t/T)
wherein rand is a random number within [ -2,2], T is the number of iterations, and T represents the maximum number of iterations.
It can be seen that the oscillation of escape energy adopted in the existing multi-target Harris eagle optimization algorithm completely depends on random number rand, and if the random number is too small in the earlier stage, the random number is easy to sink into local optimum, so that global optimization is not facilitated; in addition, the later escape energy E is repeatedly and transversely jumped between positive and negative, so that the searching of a local optimal value is not facilitated; the ideal escape energy should be the whole to jump across between positive and negative, and present the trend of vibration attenuation, make it carry on the overall optimization; however, no positive and negative cross jump exists between the adjacent iteration steps, so that local optimization is performed. Thus, the escape energy E employed in this embodiment is:
E＝rand×(exp(-50/(T×t))×sin(T×t/50))
wherein rand is a random number in (0, 2), T is the number of iterations, and T represents the maximum number of iterations.
According to the application, the problem that the output power of the generator to be optimized in the power system is too high, so that the optimal unit output is difficult to obtain is solved, the oscillation trend of the escape energy is mainly a sine function and an exponential function, and the random number is used as an auxiliary, so that the overall cross jump between positive and negative is ensured, the oscillation attenuation trend is presented, and the overall optimization is performed; however, no positive and negative cross jump exists between the adjacent iteration steps, so that local optimization is performed, and the output of the optimal unit is further ensured.
Example two
The embodiment provides an intelligent regulation system of a power system, which specifically comprises:
a data acquisition module configured to: acquiring relevant parameters of a power system;
an initialization module configured to: initializing a plurality of unit output forces based on related parameters of the power system;
an optimization module configured to: the method comprises the steps of optimizing the output of a unit by using a multi-target Harris eagle optimization algorithm with minimum power generation cost and minimum pollutant gas emission as objective functions to obtain the optimal output of the unit;
the calculation of escape energy adopted by the multi-target Harris eagle optimization algorithm is mainly based on a sine function and an exponential function, and is assisted by a random number.
It should be noted that, each module in the embodiment corresponds to each step in the first embodiment one to one, and the implementation process is the same, which is not described here.
Example III
The present embodiment provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps in the power system intelligent regulation method as described in the above embodiment.
Example IV
The present embodiment provides a computer device, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor, where the steps in the intelligent regulation method of the electric power system according to the first embodiment are implemented when the processor executes the program.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of a hardware embodiment, a software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, magnetic disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Those skilled in the art will appreciate that implementing all or part of the above-described methods in accordance with the embodiments may be accomplished by way of a computer program stored on a computer readable storage medium, which when executed may comprise the steps of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random access Memory (Random AccessMemory, RAM), or the like.
The above description is only of the preferred embodiments of the present application and is not intended to limit the present application, but various modifications and variations can be made to the present application by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the protection scope of the present application.
Claims (10)
1. The intelligent power system adjusting method is characterized by comprising the following steps of:
acquiring relevant parameters of a power system;
initializing a plurality of unit output forces based on related parameters of the power system;
the method comprises the steps of optimizing the output of a unit by using a multi-target Harris eagle optimization algorithm with minimum power generation cost and minimum pollutant gas emission as objective functions to obtain the optimal output of the unit;
the calculation of escape energy adopted by the multi-target Harris eagle optimization algorithm is mainly based on a sine function and an exponential function, and is assisted by a random number.
2. The intelligent regulation method of an electrical power system of claim 1 wherein the escape energy E is:
E＝rand×(exp(-50/(T×t))×sin(T×t/50))
wherein, the rand random number, T is the iteration number, and T represents the maximum iteration number.
3. The power system intelligent regulation method of claim 1, wherein the power system related parameters include a generator power generation cost parameter, a pollutant gas emission amount parameter, a line loss coefficient, a generator output constraint parameter, and a load demand parameter.
4. The power system intelligent regulation method of claim 1 wherein a unit output includes the output power of all generators.
5. Electric power system intelligent regulation system, its characterized in that includes:
a data acquisition module configured to: acquiring relevant parameters of a power system;
an initialization module configured to: initializing a plurality of unit output forces based on related parameters of the power system;
an optimization module configured to: the method comprises the steps of optimizing the output of a unit by using a multi-target Harris eagle optimization algorithm with minimum power generation cost and minimum pollutant gas emission as objective functions to obtain the optimal output of the unit;
the calculation of escape energy adopted by the multi-target Harris eagle optimization algorithm is mainly based on a sine function and an exponential function, and is assisted by a random number.
6. The intelligent regulation system of claim 5 wherein the escape energy E is:
E＝rand×(exp(-50/(T×t))×sin(T×t/50))
wherein, the rand random number, T is the iteration number, and T represents the maximum iteration number.
7. The intelligent regulation system of claim 5, wherein the power system related parameters include a generator generation cost parameter, a pollutant gas emission parameter, a line loss factor, a generator output constraint parameter, and a load demand parameter.
8. The intelligent regulation system of claim 5, wherein a unit output includes the output power of all generators.
9. A computer readable storage medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, realizes the steps in the intelligent regulation method of an electric power system according to any one of claims 1-4.
10. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps in the power system intelligent regulation method according to any of claims 1-4 when the program is executed.
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Cited By (2)
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| CN117439190A (en) * | 2023-10-26 | 2024-01-23 | 华中科技大学 | Water, fire and wind system dispatching method, device, equipment and storage medium |
| CN117439190B (en) * | 2023-10-26 | 2024-06-11 | 华中科技大学 | Water, fire and wind system dispatching method, device, equipment and storage medium |
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