CN109193807B - Economic dispatching method and system for power system - Google Patents

Economic dispatching method and system for power system Download PDF

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CN109193807B
CN109193807B CN201811343248.2A CN201811343248A CN109193807B CN 109193807 B CN109193807 B CN 109193807B CN 201811343248 A CN201811343248 A CN 201811343248A CN 109193807 B CN109193807 B CN 109193807B
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power
power system
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李学平
李安燚
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Baoding Trillion Micro Software Technology Co ltd
Hebei Kaitong Information Technology Service Co ltd
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Yanshan University
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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
    • 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
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Abstract

The invention discloses an economic dispatching method and system for an electric power system. The scheduling method comprises the following steps: establishing an economic dispatching model; clustering and dividing a plurality of machine sets according to the characteristics and the dividing strategy of each machine set, clustering the power system into a coarse particle, and dividing the plurality of machine sets into a plurality of fine particles; correcting the output power of the plurality of fine particles according to the economic dispatching model to obtain the corrected fine particle output power; and calculating the output result of each fine particle according to an economic dispatching model, and performing iterative optimization on the output result for multiple times to obtain the lowest power generation cost. The economic dispatching method of the power system can obtain the lowest power generation cost and improve the precision of the output dispatching result of the unit.

Description

Economic dispatching method and system for power system
Technical Field
The invention relates to the field of power systems, in particular to an economic dispatching method and system for a power system.
Background
The economic dispatch of the power system aims to optimize the output of the generator set and reduce the power generation cost of the power system to the maximum extent. The scheduling is carried out according to an equal micro-increment rate method and a coordination equation, is an important tool for realizing the economic operation of the power system, is a scientific method in an operation link, and is a scheduling principle commonly adopted by various countries in the world at present. At present, problems in actual production also need to be considered in economic dispatching, otherwise, the solving precision of economic dispatching is obviously affected, such as valve point effect of a unit, line loss in a transmission network, forbidden intervals and climbing constraints.
The economic dispatching of the power system is a high-dimensional, non-convex and non-linear constrained optimization problem, and the processing of the mutually coupled constraint conditions is very difficult. Long-term adherence to centralized scheduling of power systems. The centralized scheduling makes the solution of the economic scheduling of the power system more difficult, the economic scheduling is performed by adopting an optimization algorithm in the prior art, the accuracy of the economic scheduling result is low, and the method is not suitable for large-scale power systems.
Disclosure of Invention
The invention aims to provide an economic dispatching method and system for an electric power system, which can improve the economic dispatching precision of the electric power system.
In order to achieve the purpose, the invention provides the following scheme:
an economic dispatching method of an electric power system, the dispatching method comprising:
establishing an economic dispatching model;
clustering and dividing a plurality of machine sets according to the characteristics and the dividing strategy of each machine set, clustering the power system into a coarse particle, and dividing the plurality of machine sets into a plurality of fine particles;
correcting the output power of the plurality of fine particles according to the economic dispatching model to obtain the corrected fine particle output power;
and calculating the output result of each fine particle according to an economic dispatching model, and performing iterative optimization on the output result for multiple times to obtain the lowest power generation cost.
Optionally, the establishing an economic dispatch model specifically includes:
the economic dispatching model meets an objective function and a constraint condition;
the objective function is a lowest total power generation cost of the generators of the power system;
total cost of power generation
Figure GDA0002436961270000021
Wherein, ai,bi,ci,ei,fiAll the cost coefficients are the cost coefficients of the ith unit; piThe output result of the ith unit is obtained; n is the total number of the units of the power system; pi minThe lower limit of the output of the ith unit;
the constraint conditions include: the power balance constraint of the power system, the upper and lower limits of the output of the conventional unit and the forbidden interval constraint;
power balance constraint of the power system
Figure GDA0002436961270000022
Wherein, PDIs the total load of the power system;
total loss of the power system
Figure GDA0002436961270000023
Wherein, Bij,B0i,B00Are all the network loss coefficient, PjThe output result of the jth unit is obtained;
the upper and lower output limits of the unit meet the conditions that:
Pi min≤Pi≤Pi max(4)
wherein, Pi minIs the minimum value of the unit output, Pi maxThe maximum value of the unit output is obtained;
the forbidden interval constraint
Figure GDA0002436961270000024
Wherein n isiThe number of the forbidden intervals of the ith unit.
Optionally, the clustering and partitioning of the multiple machine sets according to the characteristics and the partitioning policy of each machine set is performed, the power system is clustered into a coarse particle, and the partitioning of the multiple machine sets into multiple fine particles specifically includes:
calculating the calculation result of the output of each unit;
comparing the calculation results of each unit for multiple times, and clustering the corresponding units with different calculation results into the same fine grain; and sequencing the rest units in an ascending order according to the upper limit of the calculation result of the output force, and sequentially distributing the rest units to the rest fine particles.
Optionally, the modifying the output power of the plurality of fine particles according to the economic scheduling model to obtain a modified fine particle output power specifically includes:
the objective function is the power generation cost of the power system
Figure GDA0002436961270000031
Wherein, FgThe power generation cost of the fine particles g is shown, and M is the number of the fine particles;
constraint conditions
The upper and lower output limits of the fine particles are equivalent:
Figure GDA0002436961270000032
Figure GDA0002436961270000033
Figure GDA0002436961270000034
is the minimum equivalent force of the fine particles g,
Figure GDA0002436961270000035
the maximum equivalent output force of the fine particles g is obtained; mgThe number of the units contained in the fine particles g is determined;
output power balance constraint of the fine particles:
Figure GDA0002436961270000036
the sum of the fine particle output and the load and line loss required by the power system keep power balance;
the upper and lower output limits of the fine particles are as follows:
Figure GDA0002436961270000037
constraint processing
And (3) constraining by adopting a penalty function method:
Figure GDA0002436961270000038
wherein, sigma is a penalty factor;
and correcting the output result of the fine particles according to the penalty factor sigma.
Optionally, the correcting the output result of the fine particles according to the penalty factor σ specifically includes:
judging the output P of each fine particlegWhether the constraint condition of the upper and lower output limits of the fine particles is met or not;
the output of each fine particle is corrected according to a formula (12);
Figure GDA0002436961270000041
wherein k represents the number of iterations if
Figure GDA0002436961270000042
Or
Figure GDA0002436961270000043
Setting a variable TgAnd (3) if not, then,
Figure GDA0002436961270000044
calculating the difference delta between the output result of the corresponding fine particles and the load under the current iteration times;
judging whether the difference value | delta | is larger than zero, if so, correcting the output of the corresponding fine particles under the current iteration times by adopting a formula (13)
Figure GDA0002436961270000045
To satisfy a balance constraint (9);
Figure GDA0002436961270000046
otherwise, checking the output of the corresponding fine particles under the current iteration number
Figure GDA0002436961270000047
If the fine particle output force P exceeds the limit, returning to judge whether the fine particle output force P exceeds the limitgWhether the constraint conditions of the upper and lower output limits of the fine particles are met, or else, the output of the corresponding fine particles under the current iteration number
Figure GDA0002436961270000048
The corrected fine particle output is obtained.
Optionally, the calculating an output result of each fine particle according to an economic dispatch model, and performing multiple iterative optimization on the output result to obtain the lowest power generation cost specifically includes:
the power generation cost of the fine particles g is the sum of the low power generation costs of all units in the fine particles g, and the objective function is the power generation cost of the fine particles g
Figure GDA0002436961270000049
Wherein M isgThe number of units contained in the fine particles g is counted;
constraint conditions are as follows:
and (3) unit power balance constraint:
Figure GDA00024369612700000410
the formula (15) is that the total output of the fine particles g calculated by the coarse particles is balanced with the sum of the outputs of all the units contained in the fine particles g;
and (3) restraining the upper and lower limits of the unit output:
Pi min≤Pi≤Pi max(16)；
forbidden interval constraint:
Figure GDA0002436961270000051
the objective function for adding the penalty term is:
Figure GDA0002436961270000052
an electrical power system economic dispatch system, the dispatch system comprising:
the model establishing module is used for establishing an economic dispatching model;
the cluster partitioning module is used for clustering and partitioning a plurality of machine sets according to the characteristics and the partitioning strategy of each machine set, clustering the power system into a coarse particle, and partitioning the plurality of machine sets into a plurality of fine particles;
the fine particle correction module is used for correcting the output power of the plurality of fine particles according to the economic dispatching model to obtain the corrected fine particle output power;
and the fine particle optimization module is used for calculating the output result of each fine particle according to an economic dispatching model, and obtaining the lowest power generation cost by carrying out iterative optimization on the output result for multiple times.
Optionally, the model building module specifically includes:
an objective function establishing unit, configured to establish the objective function as a lowest total power generation cost of the power generators of the power system;
a power balance constraint unit for establishing a power balance constraint of the power system
Figure GDA0002436961270000053
The upper and lower limit restraining unit of the output of the conventional unit is used for establishing that the upper and lower limits of the output of the unit meet the conditions as follows:
Pi min≤Pi≤Pi max(4)
wherein, Pi minIs the minimum value of the unit output, Pi maxThe maximum value of the unit output is obtained;
a forbidden interval constraint unit, configured to establish an upper and lower output limit of the fine particles:
Figure GDA0002436961270000054
according to the specific embodiment provided by the invention, the invention discloses the following technical effects: the invention provides an economic dispatching method and system for an electric power system, which can improve the economic dispatching precision of the electric power system. The economic dispatching problem is solved and decomposed into the calculation problem of the fine particles, the calculation dimensionality is reduced, the particle partitioning strategy for clustering the units in the power system into the fine particles is provided according to the characteristics of the units, the calculation dimensionality is reduced, and the accuracy of the economic dispatching result considering the valve point effect is improved through the particle partitioning strategy. The economic dispatching method of the power system can obtain the lowest power generation cost and improve the precision of the output dispatching result of the unit.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments 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 it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
FIG. 1 is a flow chart of a power system economic dispatch method provided by the present invention;
FIG. 2 is a block diagram of an economic dispatch system for an electrical power system according to the present invention;
FIG. 3 is a schematic diagram of the unit division of the 10-unit system provided by the present invention;
fig. 4 is a schematic diagram of a specific process of a scheduling method of an electric power system provided by the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention aims to provide an economic dispatching method and system for an electric power system, which can improve the economic dispatching precision of the electric power system.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
As shown in fig. 1, a method for economically scheduling an electric power system includes:
step 100: establishing an economic dispatching model;
step 200: clustering and dividing a plurality of machine sets according to the characteristics and the dividing strategy of each machine set, clustering the power system into a coarse particle, and dividing the plurality of machine sets into a plurality of fine particles;
step 300: correcting the output power of the plurality of fine particles according to the economic dispatching model to obtain the corrected fine particle output power;
step 400: and calculating the output result of each fine particle according to an economic dispatching model, and performing iterative optimization on the output result for multiple times to obtain the lowest power generation cost.
Step 100: the establishing of the economic dispatching model specifically comprises the following steps:
the economic dispatching model meets an objective function and a constraint condition;
the objective function is a lowest total power generation cost of the generators of the power system;
total cost of power generation
Figure GDA0002436961270000071
Wherein, ai,bi,ci,ei,fiAll the cost coefficients are the cost coefficients of the ith unit; piThe output result of the ith unit is obtained; n is the total number of the units of the power system; pi minThe lower limit of the output of the ith unit;
the constraint conditions include: the power balance constraint of the power system, the upper and lower limits of the output of the conventional unit and the forbidden interval constraint;
power balance constraint of the power system
Figure GDA0002436961270000072
Wherein, PDIs the total load of the power system;
total loss of the power system
Figure GDA0002436961270000073
Wherein, Bij,B0i,B00Are all the network loss coefficient, PjThe output result of the jth unit is obtained;
the upper and lower output limits of the unit meet the conditions that:
Pi min≤Pi≤Pi max(4)
wherein, Pi minIs the minimum value of the unit output, Pi maxThe maximum value of the unit output is obtained;
the forbidden interval constraint
Figure GDA0002436961270000074
Wherein n isiThe number of the forbidden intervals of the ith unit.
Step 200: the method comprises the following steps of clustering and dividing a plurality of units according to the characteristics and the dividing strategy of each unit, clustering the power system into a coarse particle, and dividing the plurality of units into a plurality of fine particles specifically comprises the following steps:
calculating the calculation result of the output of each unit;
comparing the calculation results of each unit for multiple times, and clustering the corresponding units with different calculation results into the same fine grain; and sequencing the rest units in an ascending order according to the upper limit of the calculation result of the output force, and sequentially distributing the rest units to the rest fine particles.
Step 300: the modifying the output power of the plurality of fine particles according to the economic scheduling model to obtain the modified fine particle output power specifically includes:
the objective function is the power generation cost of the power system
Figure GDA0002436961270000081
Wherein, FgThe power generation cost of the fine particles g is shown, and M is the number of the fine particles;
constraint conditions
The upper and lower output limits of the fine particles are equivalent:
Figure GDA0002436961270000082
Figure GDA0002436961270000083
Figure GDA0002436961270000084
is the minimum equivalent force of the fine particles g,
Figure GDA0002436961270000085
the maximum equivalent output force of the fine particles g is obtained; mgThe number of the units contained in the fine particles g is determined;
output power balance constraint of the fine particles:
Figure GDA0002436961270000086
the sum of the fine particle output and the load and line loss required by the power system keep power balance;
the upper and lower output limits of the fine particles are as follows:
Figure GDA0002436961270000087
constraint processing
And (3) constraining by adopting a penalty function method:
Figure GDA0002436961270000088
wherein, sigma is a penalty factor;
and correcting the output result of the fine particles according to the penalty factor sigma.
The correcting the output result of the fine particles according to the penalty factor sigma specifically includes:
judging the output P of each fine particlegWhether the constraint condition of the upper and lower output limits of the fine particles is met or not;
the output of each fine particle is corrected according to a formula (12);
Figure GDA0002436961270000091
wherein k represents the number of iterations if
Figure GDA0002436961270000092
Or
Figure GDA0002436961270000093
Setting a variable TgAnd (3) if not, then,
Figure GDA0002436961270000094
calculating the difference delta between the output result of the corresponding fine particles and the load under the current iteration times;
judging whether the difference value | delta | is larger than zero, if so, correcting the output of the corresponding fine particles under the current iteration times by adopting a formula (13)
Figure GDA0002436961270000095
To satisfy a balance constraint (9);
Figure GDA0002436961270000096
otherwise, checking the output of the corresponding fine particles under the current iteration number
Figure GDA0002436961270000097
If the fine particle output force P exceeds the limit, returning to judge whether the fine particle output force P exceeds the limitgWhether the constraint conditions of the upper and lower output limits of the fine particles are met, or else, the output of the corresponding fine particles under the current iteration number
Figure GDA0002436961270000098
The corrected fine particle output is obtained.
Step 400: the calculating the output result of each fine particle according to the economic dispatching model, and performing multiple iterative optimization on the output result to obtain the lowest power generation cost specifically comprises the following steps:
the power generation cost of the fine particles g is the sum of the low power generation costs of all units in the fine particles g, and the objective function is the power generation cost of the fine particles g
Figure GDA0002436961270000099
Wherein M isgThe number of units contained in the fine particles g is counted;
constraint conditions are as follows:
and (3) unit power balance constraint:
Figure GDA00024369612700000910
the formula (15) is that the total output of the fine particles g calculated by the coarse particles is balanced with the sum of the outputs of all the units contained in the fine particles g;
and (3) restraining the upper and lower limits of the unit output:
Pi min≤Pi≤Pi max(16)；
forbidden interval constraint:
Figure GDA0002436961270000101
the objective function for adding the penalty term is:
Figure GDA0002436961270000102
as shown in fig. 2, an economic dispatch system for an electric power system, the dispatch system comprising:
the model building module 1 is used for building an economic dispatching model;
the cluster partitioning module 2 is used for performing cluster partitioning on a plurality of machine sets according to the characteristics and the partitioning strategy of each machine set, clustering the power system into a coarse particle, and partitioning the plurality of machine sets into a plurality of fine particles;
the fine particle correction module 3 is configured to correct output power of the plurality of fine particles according to the economic scheduling model, and obtain corrected fine particle output power;
and the fine particle optimization module 4 is used for calculating the output result of each fine particle according to an economic dispatching model, and performing iterative optimization on the output result for multiple times to obtain the lowest power generation cost.
As shown in fig. 1, the model building module 1 specifically includes:
an objective function establishing unit 1-1, configured to establish the objective function as a lowest total power generation cost of the power generators of the power system;
a power balance constraint unit 1-2 for establishing a power balance constraint of the power system
Figure GDA0002436961270000103
The upper and lower limit restraining units 1-3 for the output of the conventional unit are used for establishing that the upper and lower limits of the output of the unit meet the conditions that:
Pi min≤Pi≤Pi max(4)
wherein, Pi minIs the minimum value of the unit output, Pi maxThe maximum value of the unit output is obtained;
a forbidden interval constraint unit 1-4, configured to establish an upper and lower output limit of the fine particles:
Figure GDA0002436961270000104
as shown in fig. 4:
inputting basic parameters of all units, including: a isi，bi，ci，ei，fi，Pi min，Pi max，PDAnd Bij，B0i，B0。
And (4) dividing the particles.
In order to improve the accuracy of the calculation result, the particle division is an important step in the invention. In order to make a particle partitioning strategy, the characteristics of each unit are known. Therefore, it is necessary to perform a preparatory calculation using an intelligent algorithm with all the units as optimization variables. Through several iterations, the result of each calculation is recorded. And comparing the multiple calculation results of each set, and dividing the set with different results each time into a first fine particle. After the first fine particle is determined, the other units are divided into other fine particles according to the ascending order of the output upper limit of the unit, so that the diversity of the maximum output of the unit in each fine particle is ensured. Generally, each fine particle comprises 5-10 machine sets, and the method can obtain ideal results.
The specific process of unit division is shown in fig. 3 as a 10-unit system.
Calculating the characteristics of each unit by the previous preparation calculation, and obtaining two fine particles V by clustering 10 units according to the characteristics of each unit by the particle division strategy1And V2. Wherein fine particles V1The system comprises 5 units (1#, 4#, 6#, 7#, 10 #). Fine particles V2The system comprises 5 units (2#, 3#, 5#, 8#, 9 #). Two fine particles constitute one coarse particle. The output of two fine particles, i.e. the calculated load of each fine particle, can be obtained by coarse particle calculation. When considering the net loss, the optimal result of the iteration is used as the calculated value of the net loss in the next coarse particle calculation.
And calculating coarse particles. In the coarse particle calculation, the calculation result of the fine particles is used as the optimal variable of the intelligent optimization algorithm, and the optimal value is obtained through each iteration. The coarse particle calculation result is assigned to the fine particle.
And (5) calculating fine particles. And the fine particles calculate the output power of all the units by adopting an intelligent optimization algorithm, and after the calculation of all the fine particles is completed, the next coarse particle calculation iteration is carried out. In the first coarse particle calculation iteration, the output power of each unit is not available, and an initial line loss value larger than an actual value needs to be set before calculation.
And repeating the coarse particle calculation step until the maximum iteration number is reached, and finally obtaining an optimized solution.
In the method, the intelligent optimization algorithm is applied to the economic dispatching grain calculation method considering the valve point effect by adopting differential evolution, and in the method, coarse grain calculation optimization, fine grain calculation optimization and grain division are all applied to the differential evolution algorithm.
The differential evolution algorithm starts by selecting a random value within the upper and lower force limit constraints according to formula (19):
Figure GDA0002436961270000121
wherein U (0,1) is a uniformly distributed random number within the interval (0,1),
Figure GDA0002436961270000122
and
Figure GDA0002436961270000123
respectively, the upper and lower limits of the ith element.
According to the formula (20), three individuals can obtain a mutation vector
Figure GDA0002436961270000124
Figure GDA0002436961270000125
Wherein j1，j2And j3Is three different individuals randomly selected from the current population, and F is a mutation factor.
Figure GDA0002436961270000126
Is composed of
Figure GDA0002436961270000127
And
Figure GDA0002436961270000128
inheritance, by hybridization probability (CR ∈ [0,1 ]]) Determine, equation (21):
Figure GDA0002436961270000129
wherein, randiIs a uniformly distributed random number, i, within the interval (0,1)nIs the interval [1, n]The random numbers are evenly distributed.
The selection operation of the DE is a fitness-based greedy selection, equation (22):
Figure GDA00024369612700001210
the above steps are repeated until the stop condition is satisfied.
To improve the calculation accuracy, the mutation factor F is set to decrease linearly, calculated according to equation (23):
Figure GDA00024369612700001211
wherein FmaxAnd FminThe maximum and minimum values of F, respectively; t is tmaxIs the maximum number of iterations.
On the basis of a large number of experiments, whether the network loss influences the setting of the cross probability or not is considered. The crossover probability CR is set to increase linearly according to equation (24) to improve population diversity and global convergence, without considering the network loss.
Figure GDA00024369612700001212
Wherein CRmaxAnd CRminRespectively, the maximum and minimum values of CR. When considering the loss, CR is set to linearly decrease to find the optimal solution faster, see equation (25).
Figure GDA0002436961270000131
In order to verify the effectiveness of the invention more comprehensively, the case simulation of the invention adopts a 13-unit system, and the 13-unit is divided into 2 fine particles according to a particle calculation particle division strategy. The parameter settings are shown in table 1. Table 2 shows a comparison of the 13-unit economic dispatch statistics with and without the present invention.
Table 113 set of example iterations and particle number settings
Figure GDA0002436961270000132
TABLE 213 set of example statistical comparisons
Figure GDA0002436961270000133
Figure GDA0002436961270000141
The maximum value, the minimum value and the average value of the power generation cost in the calculation example are compared, so that the fluctuation range of the result obtained by adopting the economic dispatching method is small, and the average value has obvious superiority compared with other methods, thereby effectively improving the algorithm solving precision and proving the effectiveness of the method. Along with the enlargement of the unit scale, the calculation dimension can be greatly reduced, the result precision can be effectively improved, and the advantages of the invention can be more obviously reflected.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.

Claims (7)

1. An economic dispatching method for an electric power system, characterized in that the dispatching method comprises:
establishing an economic dispatching model;
clustering and dividing a plurality of machine sets according to the characteristics and the dividing strategy of each machine set, clustering the power system into a coarse particle, and dividing the plurality of machine sets into a plurality of fine particles;
correcting the output power of the plurality of fine particles according to the economic dispatching model to obtain the corrected fine particle output power;
calculating the output result of each fine particle according to an economic dispatching model, and performing multiple iterative optimization on the output result to obtain the lowest power generation cost;
the method comprises the following steps of clustering and dividing a plurality of units according to the characteristics and the dividing strategy of each unit, clustering the power system into a coarse particle, and dividing the plurality of units into a plurality of fine particles, wherein the method specifically comprises the following steps:
calculating the calculation result of the output of each unit;
comparing the calculation results of each unit for multiple times, and clustering the corresponding units with different calculation results into the same fine grain; and sequencing the other units in an ascending order according to the upper limit of the calculation result of the output force, and sequentially distributing the other units to the rest fine particles.
2. The economic dispatching method of the power system as claimed in claim 1, wherein the establishing of the economic dispatching model specifically comprises:
the economic dispatching model meets an objective function and a constraint condition;
the objective function is a lowest total power generation cost of the generators of the power system;
total cost of power generation
Figure FDA0002436961260000011
Wherein, ai,bi,ci,ei,fiAll the cost coefficients are the cost coefficients of the ith unit; piThe output result of the ith unit is obtained; n is the total number of the units of the power system; pi minThe lower limit of the output of the ith unit;
the constraint conditions include: the power balance constraint of the power system, the upper and lower limits of the output of the conventional unit and the forbidden interval constraint;
power balance constraint of the power system
Figure FDA0002436961260000012
Wherein, PDIs the total load of the power system;
total loss of the power system
Figure FDA0002436961260000021
Wherein, Bij,B0i,B00Are all the network loss coefficient, PjThe output result of the jth unit is obtained;
the upper and lower output limits of the unit meet the conditions that:
Pi min≤Pi≤Pi max(4)
wherein, Pi minIs the minimum value of the unit output, Pi maxThe maximum value of the unit output is obtained;
the forbidden interval constraint
Figure FDA0002436961260000022
Wherein n isiThe number of the forbidden intervals of the ith unit.
3. The economic dispatching method of the power system according to claim 1, wherein the modifying the output power of the plurality of fine particles according to the economic dispatching model to obtain the modified fine particle output power specifically comprises:
the objective function is the power generation cost of the power system
Figure FDA0002436961260000023
Wherein, FgThe power generation cost of the fine particles g is shown, and M is the number of the fine particles;
constraint conditions
The upper and lower output limits of the fine particles are equivalent:
Figure FDA0002436961260000024
Figure FDA0002436961260000025
Figure FDA0002436961260000026
is the minimum equivalent force of the fine particles g,
Figure FDA0002436961260000027
the maximum equivalent output force of the fine particles g is obtained; mgThe number of the units contained in the fine particles g is determined;
output power balance constraint of the fine particles:
Figure FDA0002436961260000028
the sum of the fine particle output and the load and line loss required by the power system keep power balance;
the upper and lower output limits of the fine particles are as follows:
Figure FDA0002436961260000031
constraint processing
And (3) constraining by adopting a penalty function method:
Figure FDA0002436961260000032
wherein, sigma is a penalty factor;
and correcting the output result of the fine particles according to the penalty factor sigma.
4. The economic dispatching method of the power system as claimed in claim 3, wherein the correcting the output result of the fine particles according to the penalty factor σ specifically comprises:
judging the output P of each fine particlegWhether the constraint condition of the upper and lower output limits of the fine particles is met or not;
the output of each fine particle is corrected according to a formula (12);
Figure FDA0002436961260000033
wherein k represents the number of iterations if
Figure FDA0002436961260000034
Or
Figure FDA0002436961260000035
Setting a variable TgAnd (3) if not, then,
Figure FDA0002436961260000036
calculating the difference delta between the output result of the corresponding fine particles and the load under the current iteration times;
judging whether the difference value | delta | is larger than zero, if so, correcting the output of the corresponding fine particles under the current iteration times by adopting a formula (13)
Figure FDA0002436961260000037
To satisfy a balance constraint (9);
Figure FDA0002436961260000038
otherwise, checking the output of the corresponding fine particles under the current iteration number
Figure FDA0002436961260000039
If the fine particle output force P exceeds the limit, returning to judge whether the fine particle output force P exceeds the limitgWhether the constraint conditions of the upper and lower output limits of the fine particles are met, or else, the output of the corresponding fine particles under the current iteration number
Figure FDA00024369612600000310
The corrected fine particle output is obtained.
5. The economic dispatching method of claim 1, wherein the calculating the output result of each fine particle according to an economic dispatching model and performing multiple iterative optimization on the output result to obtain the lowest power generation cost specifically comprises:
the power generation cost of the fine particles g is the sum of the low power generation costs of all units contained in the fine particles g,
the objective function is the power generation cost of the fine particles g
Figure FDA0002436961260000041
Wherein M isgThe number of units contained in the fine particles g is counted;
constraint conditions are as follows:
and (3) unit power balance constraint:
Figure FDA0002436961260000042
the formula (15) is that the total output of the fine particles g calculated by the coarse particles is balanced with the sum of the outputs of all the units contained in the fine particles g;
and (3) restraining the upper and lower limits of the unit output:
Pi min≤Pi≤Pi max(16)；
forbidden interval constraint:
Figure FDA0002436961260000043
the objective function for adding the penalty term is:
Figure FDA0002436961260000044
6. an economic dispatch system for a power system, the dispatch system comprising:
the model establishing module is used for establishing an economic dispatching model;
the cluster partitioning module is used for clustering and partitioning a plurality of machine sets according to the characteristics and the partitioning strategy of each machine set, clustering the power system into a coarse particle, and partitioning the plurality of machine sets into a plurality of fine particles;
the fine particle correction module is used for correcting the output power of the plurality of fine particles according to the economic dispatching model to obtain the corrected fine particle output power;
the fine particle optimization module is used for calculating the output result of each fine particle according to an economic dispatching model, and obtaining the lowest power generation cost by carrying out iterative optimization on the output result for multiple times;
the method for clustering and partitioning the multiple units according to the characteristics and the partitioning strategy of each unit clusters the power system into a coarse particle, and the partitioning of the multiple units into multiple fine particles specifically comprises the following steps:
calculating the calculation result of the output of each unit;
comparing the calculation results of each unit for multiple times, and clustering the corresponding units with different calculation results into the same fine grain; and sequencing the other units in an ascending order according to the upper limit of the calculation result of the output force, and sequentially distributing the other units to the rest fine particles.
7. The economic dispatch system of claim 6, wherein the model building module specifically comprises:
an objective function establishing unit, configured to establish the objective function as a lowest total power generation cost of the power generators of the power system;
a power balance constraint unit for establishing a power balance constraint of the power system
Figure FDA0002436961260000051
The upper and lower limit restraining unit of the output of the conventional unit is used for establishing that the upper and lower limits of the output of the unit meet the conditions as follows:
Pi min≤Pi≤Pi max(4)
wherein, Pi minIs the minimum value of the unit output, Pi maxThe maximum value of the unit output is obtained;
a forbidden interval constraint unit, configured to establish an upper and lower output limit of the fine particles:
Figure FDA0002436961260000052
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