CN112906964B - Distributed energy storage combination method considering polymerization effect - Google Patents
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Abstract
The application belongs to the technical field of distributed power generation and energy storage, and particularly relates to a distributed energy storage combination method considering a polymerization effect. The method comprises the steps of obtaining operation parameters of energy storage of each subsection; establishing an aggregation evaluation index of distributed energy storage; establishing a distributed energy storage aggregation model based on tabu search; determining the polymerization potential entropy of the optimal polymerization energy storage combination in the obtained preferred table, and determining the output sequence of the polymerization energy storage combination according to the potential entropy; calculating the output external characteristics of the aggregation energy storage according to the output sequence of the optimal aggregation energy storage combination; and aggregating the energy storage into an equivalent centralized model for the dispatching center to perform power distribution and dispatching according to the external characteristics of the optimal aggregate energy storage combination. The application can realize the external characteristics of distributed energy storage meeting the application requirements of the power grid and provide technical support for the application of a unified distributed energy storage aggregation model connected to the power grid.
Description
Technical Field
The application belongs to the technical field of distributed power generation and energy storage, in particular to a distributed energy storage combination method considering an aggregation effect, and particularly relates to a method for an optimal combination mode of distributed energy storage considering the aggregation effect based on tabu search.
Background
Compared with a centralized energy storage power station, the distributed energy storage can be flexibly installed at different places, so that the construction loss and investment of a newly-added line are reduced; but distributed energy storage output, randomness of access points, and unpredictability present challenges to the traditional mode of operation of large power grids.
At present, aiming at large-scale distributed energy storage access, no effective scheduling measures exist temporarily, if distributed energy storage is used as a large number of random disturbance power supplies to be accessed into a power grid in disorder, certain influence is generated on the frequency, voltage and electric energy quality of the power grid, and meanwhile, unreasonable utilization of energy storage resources is caused. Therefore, how to perform "aggregation" after optimization combination on widely dispersed energy storage resources and realize unification of external output characteristics becomes a direction of important research. The unified regulation and control of diversified and numerous distributed energy storage with a certain idle rate and fragmentation dispersion becomes the centralized direction of domestic and foreign researches.
According to the current research situation at home and abroad, the unified aggregation of distributed energy storage resources for power grids is formed at the beginning of the countries such as Mains, germany and the like, however, the aggregated energy storage resources and application modes are still single, the aggregation scale is limited, and particularly, the method aims at the power system and the power grid structure of China, and although the technical theory for reference exists, the core problem is still not reached. In addition, the concept of distributed energy storage aggregation, an aggregation combination method and the like are involved, wherein the involved aggregation method and combination mode have reference value, but the specific key problems of the system are to be overcome in the aspect of the distributed energy storage aggregation combination technology, namely, the selection of aggregation evaluation indexes of energy storage resources is first needed, and then the optimal combination is carried out on the distributed energy storage clusters based on what mode, so that the technical support is provided for the aggregation application of the distributed energy storage system with the multi-point layout.
Disclosure of Invention
Aiming at the defects in the prior art, the application provides a distributed energy storage combination method considering the polymerization effect. The method aims at constructing an optimal combination mode of the distributed energy storage based on tabu search by considering the aggregation effect index of the distributed energy storage, and achieving the purpose of meeting the external characteristics of the distributed energy storage aggregation of the application requirements of a power grid.
The technical scheme adopted by the application for achieving the purpose is as follows:
a distributed energy storage combining method taking into account polymerization effects, comprising the steps of:
step 1, obtaining operation parameters of energy storage of each subsection;
step 2, establishing an aggregation evaluation index of distributed energy storage;
step 3, establishing a distributed energy storage aggregation model based on tabu search;
step 4, determining the polymerization potential entropy of the optimal polymerization energy storage combination in the obtained optimal table based on a tabu search distributed energy storage polymerization model, and determining the output sequence of the polymerization energy storage combination according to the potential entropy;
step 5, calculating the output external characteristics of the aggregation energy storage according to the output sequence of the optimal aggregation energy storage combination;
and 6, aggregating the energy storage into an equivalent centralized model for the dispatching center to perform power distribution and dispatching according to the external characteristics of the optimal aggregate energy storage combination.
Further, the operating parameters include: energy storage capacity, charge and discharge rate, state of charge and parameters of charge and discharge power.
Further, the establishing the aggregate evaluation index of the distributed energy storage includes: aggregate capacity contribution, aggregate power contribution, effective aggregate ratio, effective state ratio, and system stability capability.
Further, the aggregate capacity contribution g 1 The capacity contribution capability of the aggregated energy storage for the frequency modulation and peak shaving actions of the power grid is calculated according to the following formula:
wherein: s is S apk The energy storage is adjustable total capacity; s is S ap The demand capacity is the demand capacity when energy storage is scheduled; t is a scheduling period; p (P) s (i) The output power of the distributed energy storage at the moment i;
the aggregate power contribution g 2 The power contribution capability of the aggregated energy storage for the frequency modulation and peak shaving actions of the power grid is calculated according to the following formula:
wherein: p (P) Bk Outputting power for the kth energy storage system; p (P) load The load output power of the point i; p (P) G The total output power is sent by the unit; p (P) DGj Outputting power for the j-th distributed generation unit; n (N) s Is the number of energy storage devices; n (N) bus The number of nodes for the system; n (N) DG The number of distributed power sources; p (P) D The power required during the dispatching of the distributed energy storage; ρ k Energy storage power conversion efficiency for distributed energy storage;
the effective polymerization ratio g 3 The energy storage aggregation capability which is effectively invoked according to the system requirement is calculated according to the following formula:
in which Q is D The number of demands of the system for the distributed energy storage is called; q (Q) Bk Total number of schedules available for distributed energy storage;
the effective state ratio g 4 The energy storage aggregation capability in a charge-discharge response state according to the system requirement is calculated according to the following formula:
wherein: s is S Bk Representing the current running state of the distributed battery energy storage system, S Bk =1 denotes energy storage positive charge, S Bk = -1 represents positive discharge of energy storage, S Bk =0 indicates that the stored energy is in a hot standby state; s is S D Representing the action state of the distributed energy storage when the current system schedules the distributed energy storage,S D =1 indicates that energy storage charging is required, S D -1 represents the need for energy storage discharge;
system stability g 5 Refers to the stabilization capability of the energy storage basic unit after polymerization, and is calculated according to the following formula:
g 5 ＝(1-η k )
in eta k And the fault rate of the distributed energy storage basic unit in the scheduled time period is set.
Further, the establishment of the distributed energy storage aggregation model based on tabu search is to take an evaluation index as a consideration factor of a combination method after single distributed energy storage passes through an aggregation effect, so as to obtain an energy storage output sequence, external characteristics, a unified model and a power distribution mode;
the tabu search flow includes the following steps:
step (1) constructing an aggregation characteristic criterion, an aggregation special criterion and an aggregation preference criterion based on tabu search;
the aggregation characteristic criterion refers to that the operation parameters of the energy storage of each subsection have the following formula relation:
wherein: SOC (State of Charge) t Is the energy storage charge state; SOC (State of Charge) 0 Is the initial value of the energy storage charge state; p (P) c And P d The charging and discharging power of the stored energy; η (eta) c And eta d Is the charge and discharge rate of the stored energy; Δt is a duration of charge and discharge; s is S rate Is the energy storage capacity;
the aggregated privilege criterion is to construct an evaluation function for judging the goodness of the candidate energy storage object, take the objective function as the evaluation function, and set the evaluation function as follows according to the objective function of the article:
in the formula g i Is a polymerizationEvaluating the index; omega i Is a weight coefficient of the aggregate evaluation index;
the aggregation preference criterion is that the aggregation potential index lambda of each distributed energy storage is calculated i The method comprises the steps of carrying out a first treatment on the surface of the The greater the distributed energy storage convergence potential index, the better the combined mode of the aggregate energy storage:
in the above, lambda i Aggregation potential index for distributed energy storage g i Is an aggregation assessment index;
sequencing the output of each aggregation energy storage combination based on the magnitude of the aggregation potential index of the distributed energy storage;
step (2) randomly selecting distributed energy storage as an initial solution of input, calculating operation parameters of each energy storage, and judging whether the operation parameters meet aggregation characteristic criteria; if yes, generating primary energy storage optimal combination mode entering tabu; if not, generating a candidate energy storage object;
step (3) calculating an aggregation evaluation index of the generated energy storage optimal combination mode, and judging whether the candidate energy storage object meets an aggregation privilege criterion; if yes, the energy storage object enters a privilege table, and replaces the object which enters the tabu table earliest to update the optimal state; if not, replacing the object which enters the tabu table earliest with the non-tabu object, and repeating the step (3);
and (4) calculating the polymerization potential entropy of the generated energy storage optimal combination mode, judging whether the optimal combination mode meets the polymerization optimal selection criterion, generating an optimal table if the optimal combination mode meets the optimal polymerization energy storage optimal combination mode, and repeating the step (1) and the step (2) if the optimal combination mode does not meet the optimal polymerization energy storage optimal combination mode.
Further, the energy storage is aggregated into an equivalent centralized model for the dispatching center to perform power distribution and dispatching according to the external characteristics of the optimal aggregate energy storage combination, wherein the external characteristics of the aggregate require equivalent centralized rated power, rated capacity and charge and discharge efficiency to represent the whole aggregate energy storage system:
wherein: p (P) all-rate 、S all-rate 、η all Is equivalent concentrated energy storage charging and discharging power, rated capacity and equivalent charging and discharging efficiency.
Further, the algorithm of the tabu search comprises the following steps:
(1) Giving tabu search algorithm parameters, randomly generating an initial solution x, and setting a tabu table to be empty;
(2) Judging whether an algorithm termination condition is satisfied: if yes, ending the algorithm and outputting an optimization result; otherwise, continuing the following steps;
(3) Generating all or a plurality of neighborhood solutions by using a neighborhood function of the current solution, and determining a plurality of candidate solutions from the neighborhood solutions;
(4) Judging whether the scofflaw is satisfied for the candidate solution: if yes, substituting x with the optimal state y meeting the scofflaw to become a new current solution, namely x=y, substituting the tabu object which enters the tabu table earliest with the tabu object corresponding to y, substituting the best so far state with y, and then turning to the step (6); otherwise, continuing the following steps;
(5) Judging the tabu attribute of each object corresponding to the candidate solution, selecting the optimal state corresponding to the non-tabu object in the candidate solution set as a new current solution, and simultaneously replacing the tabu object entering the tabu table earliest by the tabu object corresponding to the new current solution;
(6) Judging whether an algorithm termination condition is satisfied: if yes, ending the algorithm and outputting an optimization result: otherwise, turning to the step (3).
A computer storage medium having a computer program stored thereon, which when executed by a processor performs the steps of the distributed energy storage combination method taking into account aggregation effects.
The application has the following beneficial effects and advantages:
the application can more effectively and reliably aggregate the distributed energy storage with a certain range of operating parameters and better evaluation indexes, and provides technical support for the application of a unified distributed energy storage aggregation model connected to a power grid.
The application can improve the aggregation efficiency of energy storage and reduce distributed energy storage access with weak aggregation characteristics. Improving the economy of the aggregation quantity of the stored energy and the technology of the external output of the stored energy aggregation. Aiming at the problems that the original energy storage aggregation mode has complicated aggregation process and cannot obtain an optimal energy storage combination mode, tabu search is adopted to utilize different aggregation criteria to carry out multiple iterations so as to avoid losing an optimal solution in the search process, and the aggregation efficiency of energy storage is improved.
According to the application, the energy storage optimal combination mode with good polymerization indexes is explored, so that the energy storage access with low polymerization characteristics and low aggregation potential is reduced, and the stability and reliability of energy storage polymerization output are improved.
The application also has the characteristics of easy implementation and convenient commercialized development. According to the application, on the basis of a distributed energy storage combination method, a tabu search is added, so that an energy storage optimal combination mode of an optimal aggregation index can be explored in a certain range. Algorithmically easy to implement; meanwhile, the aggregation effect index is considered, and the practical application of the real energy storage evaluation is easy. With the increase of the random access of the distributed energy storage as a large number of random disturbance power supplies to the power grid, the development of the distributed energy storage combination method with the aggregation effect necessarily has larger requirements and more remarkable commercial development prospect.
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The foregoing and/or additional aspects and advantages of the application will become apparent and may be better understood from the following description of embodiments taken in conjunction with the accompanying drawings in which:
FIG. 1 is a general flow chart of the method of the present application;
FIG. 2 is a tabu search flow chart of the present application;
FIG. 3 is a schematic diagram of a preferred combination mode of distributed energy storage based on the effect of polymerization in accordance with the present application;
FIG. 4a is a constraint simulation plot of the distribution of aggregate stored energy during dispatch versus maintaining relative balance of SOC in the present application;
fig. 4b is a simulation plot of the preferred dispense output of the aggregate stored energy during the dispatch process in accordance with the present application.
Detailed Description
In order that the above-recited objects, features and advantages of the present application will be more clearly understood, a more particular description of the application will be rendered by reference to the appended drawings and appended detailed description. It should be noted that, without conflict, the embodiments of the present application and features in the embodiments may be combined with each other.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application, however, the present application may be practiced in other ways than those described herein, and therefore the scope of the present application is not limited to the specific embodiments disclosed below.
The following describes some embodiments of the present application with reference to fig. 1-4.
Example 1
The application relates to a distributed energy storage combination method considering polymerization effect, as shown in fig. 1, and fig. 1 is a general flow chart of the method.
The application discloses a distributed energy storage combination method considering aggregation effect, which is characterized in that an aggregation effect index of distributed energy storage is considered, a distributed energy storage object is selected as an initial solution of input in a tabu search-based model, and an optimal combination mode of the distributed energy storage is constructed by considering the aggregation effect index, the aggregation characteristic criterion, the aggregation special priority criterion and the aggregation preference criterion of the distributed energy storage, so that the external characteristics of the distributed energy storage aggregation meeting the application requirements of a power grid are realized.
The method specifically comprises the following steps:
step 1, obtaining operation parameters of energy storage of each subsection;
the operating parameters include: energy storage capacity S ap Charge-discharge rate eta, state of charge SOC t Charge and discharge power P Bk Parameters of (2);
step 2, establishing an aggregation evaluation index of distributed energy storage;
comprising the following steps: aggregate capacity contribution, aggregate power contribution, effective aggregate ratio, effective state ratio, and system stability capability;
the aggregate capacity contribution g 1 The capacity contribution capability of the aggregated energy storage for the frequency modulation and peak shaving actions of the power grid is calculated according to the following formula:
wherein: s is S apk The energy storage is adjustable total capacity; s is S ap The demand capacity is the demand capacity when energy storage is scheduled; t is a scheduling period; p (P) s (i) The output power at the moment i is the distributed energy storage.
The aggregate power contribution g 2 The power contribution capability of the aggregated energy storage for the frequency modulation and peak shaving actions of the power grid is calculated according to the following formula:
wherein: p (P) Bk Outputting power for the kth energy storage system; p (P) load The load output power of the point i; p (P) G The total output power is sent by the unit; p (P) DGj Outputting power for the j-th distributed generation unit; n (N) s Is an energy storage deviceIs the number of (3); n (N) bus The number of nodes for the system; n (N) DG The number of distributed power sources; p (P) D The power required during the dispatching of the distributed energy storage; ρ k The energy storage power conversion efficiency is the energy storage of the distributed type.
The effective polymerization ratio g 3 The energy storage aggregation capability which is effectively invoked according to the system requirement is calculated according to the following formula:
in which Q is D The number of demands of the system for the distributed energy storage is called; q (Q) Bk The total number of schedules available for distributed energy storage.
The effective state ratio g 4 The energy storage aggregation capability in a charge-discharge response state according to the system requirement is calculated according to the following formula:
wherein: s is S Bk Representing the current running state of the distributed battery energy storage system, S Bk =1 denotes energy storage positive charge, S Bk = -1 represents positive discharge of energy storage, S Bk =0 indicates that the stored energy is in a hot standby state; s is S D Representing the action state of needing distributed energy storage when the current system schedules the distributed energy storage, S D =1 indicates that energy storage charging is required, S D = -1 indicates that an energy storage discharge is required.
System stability g 5 Refers to the stabilization capability of the energy storage basic unit after polymerization, and is calculated according to the following formula:
g 5 ＝(1-η k )
in eta k And the fault rate of the distributed energy storage basic unit in the scheduled time period is set.
Step 3, establishing a distributed energy storage aggregation model based on tabu search; as shown in fig. 2, fig. 2 is a flow chart of tabu search according to the present application;
further, after single distributed energy storage is subjected to a polymerization effect, an evaluation index is taken as a consideration factor of a combination method, and an energy storage output sequence, external characteristics, a unified model and a power distribution mode are obtained;
the tabu search flow of the application comprises the following steps:
step (1) constructing an aggregation characteristic criterion, an aggregation special criterion and an aggregation preference criterion based on tabu search;
the aggregation characteristic criterion refers to that the operation parameters of the energy storage of each subsection have the following formula relation:
wherein: SOC (State of Charge) t Is the energy storage charge state; SOC (State of Charge) 0 Is the initial value of the energy storage charge state; p (P) c And P d The charging and discharging power of the stored energy; η (eta) c And eta d Is the charge and discharge rate of the stored energy; Δt is a duration of charge and discharge; s is S rate Is the energy storage capacity.
The aggregated privilege criterion is to construct an evaluation function for judging the goodness of the candidate energy storage object, take the objective function as the evaluation function, and set the evaluation function as follows according to the objective function of the article:
in the formula g i Is an aggregation assessment index; omega i Is a weight coefficient of the aggregate evaluation index.
The aggregation preference criterion is that the aggregation potential index lambda of each distributed energy storage is calculated i The method comprises the steps of carrying out a first treatment on the surface of the The greater the distributed energy storage convergence potential index, the better the combined mode of the aggregate energy storage:
in the above, lambda i Aggregation potential index for distributed energy storage g i Is an aggregate evaluation index.
Further, the output of each aggregate energy storage combination is ranked based on the magnitude of the aggregate potential index of the distributed energy storage.
Step (2) randomly selecting distributed energy storage as an initial solution of input, calculating operation parameters of each energy storage, and judging whether the operation parameters meet aggregation characteristic criteria; if yes, generating primary energy storage optimal combination mode entering tabu; if not, generating a candidate energy storage object;
step (3) calculating an aggregation evaluation index of the generated energy storage optimal combination mode, and judging whether the candidate energy storage object meets an aggregation privilege criterion; if yes, the energy storage object enters a privilege table, and replaces the object which enters the tabu table earliest to update the optimal state; if not, replacing the object which enters the tabu table earliest with the non-tabu object, and repeating the step (3);
step (4) calculating the polymerization potential entropy of the generated energy storage optimal combination mode, judging whether the optimal combination mode meets the polymerization optimal selection criterion, if so, generating an optimal list, and if not, repeating the step (1) and the step (2);
step 4, determining the polymerization potential entropy of the optimal polymerization energy storage combination in the obtained optimal selection table, and determining the output sequence of the polymerization energy storage combination according to the potential entropy; as shown in fig. 3, fig. 3 is a schematic diagram of a preferred combination mode of distributed energy storage based on polymerization effect according to the present application.
Step 5, calculating the output external characteristics of the aggregation energy storage according to the output sequence of the optimal aggregation energy storage combination, so as to meet the application requirements of the power grid;
and 6, aggregating the energy storage into an equivalent centralized model for the dispatching center to perform power distribution and dispatching according to the external characteristics of the optimal aggregate energy storage combination. As shown in fig. 4, fig. 4 is a relatively balanced simulation curve of the present application where the power distribution of the stored energy during the scheduling process is reasonable and the SOC is maintained.
The external characteristics of the aggregation can represent the whole aggregate energy storage system by the requirement of equivalent concentrated rated power, rated capacity and charge and discharge efficiency:
wherein: p (P) all-rate 、S all-rate 、η all Is equivalent concentrated energy storage charging and discharging power, rated capacity and equivalent charging and discharging efficiency.
Further, a plurality of energy stores are aggregated into an equivalent concentrated energy store for a dispatching center to dispatch. Only one charge and discharge variable for centralized energy storage is needed in dispatching optimization calculation. In order to enable the power distribution of each energy storage to be reasonable and keep the relative balance of the SOC in the scheduling process, the rated power and the SOC value of each energy storage are adopted to jointly determine the charging power and the discharging power of each energy storage.
Example 2
The present application further provides an embodiment, which is a distributed energy storage combination method considering the aggregation effect, as shown in fig. 1, and fig. 1 is a general flow chart of the method of the present application.
In accordance with the calculation steps described in embodiment 1, it should be noted that, as can be seen from the flow chart, the method in this embodiment is based on tabu search, and the aggregation characteristic criterion, the aggregation special priority criterion and the aggregation preference criterion are added in the distributed energy storage combination method taking the aggregation effect into consideration, which is essentially different from other methods.
As shown in fig. 2, fig. 2 is a flow chart of tabu search according to the present application;
the tabu search flow of the application is defined as follows:
the basic idea of the tabu search algorithm is: given a current solution (initial solution) and a neighborhood, several candidate solutions are then determined in the neighborhood of the current solution: if the target value corresponding to the best candidate solution is better than the 'best so far' state, neglecting the tabu characteristic, replacing the current solution and the 'best so far' state by the best candidate solution, adding the corresponding object into the tabu table, and modifying the period of each object in the tabu table at the same time: if the candidate solution does not exist, selecting the optimal state of non-tabu from the candidate solutions as a new current solution, regardless of the advantages and disadvantages of the new current solution, adding the corresponding object into a tabu table, and modifying the period of each object in the tabu table. The above-described alternative search process is repeated as such until the stopping criterion is met.
The tabu search algorithm steps may be described as follows:
(1) Given the tabu search algorithm parameters, an initial solution x is randomly generated, and the tabu table is empty.
(2) Judging whether an algorithm termination condition is satisfied: if yes, ending the algorithm and outputting an optimization result; otherwise, the following steps are continued.
(3) All (or several) neighborhood solutions of the current solution are generated by using the neighborhood function of the current solution, and several candidate solutions are determined from the neighborhood solutions.
(4) Judging whether the scofflaw is satisfied for the candidate solution: if yes, substituting x with the optimal state y meeting the scofflaw to become a new current solution, namely x=y, substituting the tabu object which enters the tabu table earliest with the tabu object corresponding to y, substituting the best so far state with y, and then turning to the step (6); otherwise, the following steps are continued.
(5) Judging the tabu attribute of each object corresponding to the candidate solution, selecting the optimal state corresponding to the non-tabu object in the candidate solution set as a new current solution, and simultaneously replacing the tabu object entering the tabu table earliest by the tabu object corresponding to the new current solution.
(6) Judging whether an algorithm termination condition is satisfied: if yes, ending the algorithm and outputting an optimization result: otherwise, turning to the step (3).
As shown in fig. 3, fig. 3 is a schematic diagram of a preferred combination mode of distributed energy storage based on polymerization effect according to the present application.
As shown in fig. 4a and 4b, fig. 4a is a constraint simulation curve of the distribution output of the aggregate storage during the dispatching process and maintaining the relative balance of the SOC, and fig. 4b is a preferred distribution output simulation curve of the aggregate storage during the dispatching process.
Table 1 method of best combining modes of distributed energy storage considering polymerization effects preferred energy storage output scheme
For the energy storage combination 1, the maximum energy storage output reaches 0.265p.u., and then the SOC drops from 0.5 to 0.12 at a steady output of 0.195p.u. The maximum output of the energy storage combination 2 reaches 0.24p.u., and then the SOC drops from 0.5 to 0.25 at a stable output of 0.18p.u. The maximum output force of the energy storage combination 3 reaches 0.2p.u., and then the energy storage combination is stable at 0.17p.u., and the SOC descending speed is moderate and falls from 0.5 to 0.35. The maximum output force of the energy storage combination 4 reaches 0.16p.u., and the SOC is slowly reduced from 0.5 to 0.4 with 0.16p.u. Stable output. It can be seen that the optimal combination mode of distributed energy storage considering the aggregation effect based on tabu search selects four energy storage output schemes, as shown in table 1, the energy storage output sequence specified according to potential entropy satisfies the requirement of actual energy storage output from high to low, the power distribution of the energy storage in the dispatching process is reasonable, the relative balance of the SOC is kept between 0.1 and 0.5, the cycle service life of the energy storage is prolonged to a certain extent, the overcharge and the discharge of the energy storage are avoided, and the optimal combination mode of distributed energy storage considering the aggregation effect based on tabu search is proved to be feasible, so that the unified distributed energy storage aggregation model application of the power grid can be provided with technical support.
Example 3
Based on the same inventive concept, the embodiments of the present application further provide a computer storage medium, on which a computer program is stored, which when executed by a processor implements the steps of a distributed energy storage combination method taking into account the aggregation effect as described in embodiment 1 or 2.
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 an entirely hardware embodiment, an entirely 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, disk storage, CD-ROM, 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.
Finally, it should be noted that: the above embodiments are only for illustrating the technical aspects of the present application and not for limiting the same, and although the present application has been described in detail with reference to the above embodiments, it should be understood by those of ordinary skill in the art that: modifications and equivalents may be made to the specific embodiments of the application without departing from the spirit and scope of the application, which is intended to be covered by the claims.
Claims (3)
1. A distributed energy storage combination method considering polymerization effect is characterized in that: the method comprises the following steps: step 1, obtaining operation parameters of energy storage of each subsection; step 2, establishing an aggregation evaluation index of distributed energy storage; step 3, establishing a distributed energy storage aggregation model based on tabu search; step 4, determining the polymerization potential entropy of the optimal polymerization energy storage combination in the obtained optimal table based on a tabu search distributed energy storage polymerization model, and determining the output sequence of the polymerization energy storage combination according to the potential entropy; step 5, calculating the output external characteristics of the aggregation energy storage according to the output sequence of the optimal aggregation energy storage combination; step 6, aggregating the energy storage into an equivalent centralized model for the dispatching center to perform power distribution and dispatching according to the external characteristics of the optimal aggregate energy storage combination; the operating parameters include: parameters of energy storage capacity, charge and discharge rate, charge state and charge and discharge power; the establishing the aggregation evaluation index of the distributed energy storage comprises the following steps: aggregate capacity contribution, aggregate power contribution, effective aggregate ratio, effective state ratio, and system stability capability; the aggregate capacity contribution g 1 The capacity contribution capability of the aggregated energy storage for the frequency modulation and peak shaving actions of the power grid is calculated according to the following formula:
wherein:S apk the energy storage is adjustable total capacity; s is S ap The demand capacity is the demand capacity when energy storage is scheduled; t is a scheduling period; p (P) s (i) The output power of the distributed energy storage at the moment i;
the aggregate power contribution g 2 The power contribution capability of the energy storage after aggregation for the frequency modulation and peak shaving action of the power grid is calculated according to the following formula:
wherein: p (P) Bk Outputting power for the kth energy storage system; p (P) load The load output power of the point i; p (P) G The total output power is sent by the unit; p (P) DGj Outputting power for the j-th distributed generation unit; n (N) s Is the number of energy storage devices; n (N) bus The number of nodes for the system; n (N) DG The number of distributed power sources; p (P) D The power required during the dispatching of the distributed energy storage; ρ k Energy storage power conversion efficiency for distributed energy storage;
the effective polymerization ratio g 3 The energy storage aggregation capability which is effectively invoked according to the system requirement is calculated according to the following formula:
in which Q is D The number of demands of the system for the distributed energy storage is called; q (Q) Bk Total number of schedules available for distributed energy storage;
the effective state ratio g 4 The energy storage aggregation capability in a charge-discharge response state according to the system requirement is calculated according to the following formula:
wherein: s is S Bk Representing the current running state of the distributed battery energy storage system, S Bk =1 denotes energy storage positive charge, S Bk = -1 represents positive discharge of energy storage, S Bk =0 indicates that the stored energy is in a hot standby state; s is S D Representing the action state of needing distributed energy storage when the current system schedules the distributed energy storage, S D =1 indicates that energy storage charging is required, S D -1 represents the need for energy storage discharge;
system stability g 5 Refers to the stabilization capability of the energy storage basic unit after polymerization, and is calculated according to the following formula g 5 ＝(1-η k )
In eta k The failure rate of the distributed energy storage basic unit in the scheduling time period is calculated;
the establishment of the distributed energy storage aggregation model based on tabu search is to take an evaluation index as a consideration factor of a combination method after single distributed energy storage passes through an aggregation effect, so as to obtain an energy storage output sequence, external characteristics, a unified model and a power distribution mode; the tabu search flow includes the following steps:
step (1) constructing an aggregation characteristic criterion, an aggregation special criterion and an aggregation preference criterion based on tabu search;
the aggregation characteristic criterion refers to that the operation parameters of the energy storage of each subsection have the following formula relation:
wherein: SOC (State of Charge) t Is the energy storage charge state; SOC (State of Charge) 0 Is the initial value of the energy storage charge state; p (P) c And P d The charging and discharging power of the stored energy; η (eta) c And eta d Is the charge and discharge rate of the stored energy; Δt is a duration of charge and discharge; s is S rate Is the energy storage capacity;
the aggregated privilege criterion refers to constructing an evaluation function for judging the weatherSelecting the quality of the energy storage object, taking the objective function as an evaluation function, and setting the evaluation function as the objective function according to the article
In the formula g i Is an aggregation assessment index; omega i Is a weight coefficient of the aggregate evaluation index;
the aggregation preference criterion is that the aggregation potential index lambda of each distributed energy storage is calculated i The method comprises the steps of carrying out a first treatment on the surface of the The greater the distributed energy storage convergence potential index, the better the combined mode of the aggregate energy storage:
in the above, lambda i Aggregation potential index for distributed energy storage g i Is an aggregation assessment index;
sequencing the output of each aggregation energy storage combination based on the magnitude of the aggregation potential index of the distributed energy storage;
step (2) randomly selecting distributed energy storage as an initial solution of input, calculating operation parameters of each energy storage, and judging whether the operation parameters meet aggregation characteristic criteria; if yes, generating primary energy storage optimal combination mode entering tabu; if not, generating a candidate energy storage object;
step (3) calculating an aggregation evaluation index of the generated energy storage optimal combination mode, and judging whether the candidate energy storage object meets an aggregation privilege criterion; if yes, the energy storage object enters a privilege table, and replaces the object which enters the tabu table earliest to update the optimal state; if not, replacing the object which enters the tabu table earliest with the non-tabu object, and repeating the step (3);
step (4) calculating the polymerization potential entropy of the generated energy storage optimal combination mode, judging whether the optimal combination mode meets the polymerization optimal selection criterion, if so, generating an optimal list, and if not, repeating the step (1) and the step (2);
the energy storage is aggregated into an equivalent centralized model for a dispatching center to distribute and dispatch power according to the external characteristics of the optimal aggregate energy storage combination, wherein the external characteristics of the aggregate require equivalent centralized rated power, rated capacity and charge and discharge efficiency to represent the whole aggregate energy storage system:
wherein: p (P) all-rate 、S all-rate 、η all Is equivalent concentrated energy storage charging and discharging power, rated capacity and equivalent charging and discharging efficiency.
2. A distributed energy storage combining method taking into account the effects of aggregation as defined in claim 1, wherein: the algorithm of the tabu search comprises the following steps:
(1) Giving tabu search algorithm parameters, randomly generating an initial solution x, and setting a tabu table to be empty;
(2) Judging whether an algorithm termination condition is satisfied: if yes, ending the algorithm and outputting an optimization result; otherwise, continuing the following steps;
(3) Generating all or a plurality of neighborhood solutions by using a neighborhood function of the current solution, and determining a plurality of candidate solutions from the neighborhood solutions;
(4) Judging whether the scofflaw is satisfied for the candidate solution: if yes, substituting x with the optimal state y meeting the scofflaw to become a new current solution, namely x=y, substituting the tabu object which enters the tabu table earliest with the tabu object corresponding to y, substituting the bestsofar state with y, and then turning to the step (6); otherwise, continuing the following steps;
(5) Judging the tabu attribute of each object corresponding to the candidate solution, selecting the optimal state corresponding to the non-tabu object in the candidate solution set as a new current solution, and simultaneously replacing the tabu object entering the tabu table earliest by the tabu object corresponding to the new current solution;
(6) Judging whether an algorithm termination condition is satisfied: if yes, ending the algorithm and outputting an optimization result: otherwise, turning to the step (3).
3. A computer storage medium, characterized by: the computer storage medium has stored thereon a computer program which, when executed by a processor, implements the steps of a distributed energy storage combination method taking into account aggregation effects as claimed in claims 1-2.
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