CN117498399B - Multi-energy collaborative configuration method and system considering elastic adjustable energy entity access - Google Patents
Multi-energy collaborative configuration method and system considering elastic adjustable energy entity access Download PDFInfo
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Abstract
The invention discloses a multi-energy collaborative configuration method and a system considering elastic adjustable energy entity access; aiming at the problem that the utilization rate of energy is low when an elastic energy entity participates in energy coordination; calculating the supply and demand bearing capacity of the corresponding power supply blocks when the elastic adjustable energy entity is connected by analyzing the energy supply and demand relation of each power supply block in different time domains, and determining an energy storage adjustable sequence and a load adjustable sequence based on the supply and demand bearing capacity; determining a power supply access point of each elastic energy storage entity and each elastic load entity based on the supply-demand relation of the energy storage adjustable sequence and the corresponding sequence bit of the load adjustable sequence; generating an elastic adjustable energy storage entity configuration strategy based on an elastic energy storage entity contained in the power supply access point and generating an elastic adjustable load entity configuration strategy by an elastic load entity; the scheme realizes a cross-regional energy collaborative configuration strategy through dynamic sensing and analysis of global energy supply and demand; the energy utilization rate of the elastic energy entity in energy coordination can be greatly improved.
Description
Technical Field
The invention relates to the technical field of information processing, in particular to a multi-energy collaborative configuration method and system considering elastic adjustable energy entity access.
Background
In the prior art, the supply and demand relationship of energy sources is balanced by adopting a mode that an elastic energy source is connected into a power grid to participate in energy source storage and release. However, conventional energy storage and release techniques have some bottleneck problems; mainly expressed in the following aspects:
a. the existing energy storage power station is limited by the geographical distribution and the installation capacity of the energy storage power station, so that the energy storage power station has limited participation energy regulation capacity and cannot meet the increasing energy demand change; b. due to the lack of pre-sensing of the dynamic energy supply and demand relationship, the regulation speed is low, and the rapid regulation of the energy supply in a short time cannot be realized; c. the traditional energy storage and release technology is limited to a specific power supply block due to the lack of dynamic sensing and analysis on the global energy supply and demand, so that the energy balance across areas is difficult to realize; therefore, when the energy demand in the area is unbalanced, the energy capacity of some power supply blocks is abundant, and the energy capacity of some power supply blocks is short; resulting in low energy utilization; there is a need for an effective energy coordination mechanism for zone-collapsing regulation.
Disclosure of Invention
The invention aims to solve the problem of low energy utilization rate when elastic energy entities participate in energy coordination, and provides a multi-energy collaborative configuration method and a system considering elastic adjustable energy entity access; calculating the supply and demand bearing capacity of the corresponding power supply blocks when the elastic adjustable energy entity is connected by analyzing the energy supply and demand relation of each power supply block in different time domains, and determining an energy storage adjustable sequence and a load adjustable sequence based on the supply and demand bearing capacity; determining a power supply access point of each elastic energy storage entity and each elastic load entity based on the supply-demand relation of the energy storage adjustable sequence and the corresponding sequence bit of the load adjustable sequence; generating an elastic adjustable energy storage entity configuration strategy based on an elastic energy storage entity contained in the power supply access point and generating an elastic adjustable load entity configuration strategy by an elastic load entity; the scheme realizes a cross-regional energy collaborative configuration strategy through dynamic sensing and analysis of global energy supply and demand; the energy utilization rate of the elastic energy entity in energy coordination can be greatly improved.
In a first aspect, a technical solution provided in an embodiment of the present invention is a multi-energy collaborative configuration method considering elastic adjustable energy entity access, including the following steps:
S1, acquiring an energy supply chain and an energy consumption chain of each power supply block when an elastic adjustable energy entity is not connected based on an energy supply and demand balance relation; extracting energy supply and demand non-overlapping areas of an energy supply chain and an energy consumption chain corresponding to each power supply block in a time domain, and acquiring an initial supply and demand unbalanced sequence in the time domain based on each energy supply and demand non-overlapping area;
s2, acquiring a first connection degree between an accessible elastic energy storage entity and an adjacent power supply access point, and classifying the elastic energy storage entity based on the first connection degree to obtain an elastic energy storage entity set belonging to each power supply access point; acquiring the maximum adjustment capacity of the elastic energy storage entity accessed into the power supply block under the matching time domain based on the elastic energy storage entity set; updating the initial supply-demand unbalance sequence based on the maximum regulation capacity to obtain a first supply-demand unbalance sequence; calculating first supply and demand bearing capacity of the power supply block under the time domain corresponding to each first supply and demand unbalanced sequence, and screening out a first energy storage adjustable sequence and a second energy storage adjustable sequence based on the first supply and demand bearing capacity;
s3, obtaining second coupling degrees between the accessible elastic load entities and all power supply access points, and classifying the elastic load entities based on the second coupling degrees to obtain elastic load entity sets belonging to each power supply access point; acquiring the maximum required capacity of the elastic load entity accessed to the power supply block under the matching time domain based on the elastic load entity set; updating the initial supply-demand unbalanced sequence based on the maximum demand capacity to obtain a second supply-demand unbalanced sequence; calculating a second supply-demand bearing capacity of the power supply block under the time domain corresponding to each second supply-demand unbalanced sequence, and screening out a first load adjustable sequence and a second load adjustable sequence based on the second supply-demand bearing capacity;
S4, carrying out fusion calculation based on the first supply-demand unbalance sequence and the second supply-demand unbalance sequence to obtain a fusion unbalance sequence;
s5, generating an elastic adjustable energy storage entity configuration strategy based on the fusion unbalanced sequence, the first energy storage adjustable sequence and the second load adjustable sequence;
s6, generating an elastic adjustable load entity configuration strategy based on the fusion unbalanced sequence, the second energy storage adjustable sequence and the first load adjustable sequence.
In the scheme, aiming at the problem of low energy utilization rate when an elastic energy entity participates in energy coordination, an energy supply chain and an energy consumption chain of each power supply block are firstly dynamically acquired, and supply and demand non-overlapping areas of the power supply blocks in a time domain are analyzed; the energy supply and demand states of all the blocks are tracked and understood in real time; secondly, dynamically determining attribution of the elastic energy storage entity by calculating a first connection degree of the elastic energy storage entity and the power supply access point, and calculating the maximum adjustment capacity of the elastic energy storage entity under a specific time domain, wherein the time domain represents a specific time scale and a specific power supply area, and the energy state of each power supply block under the time domain is dynamically changed; the energy storage entity can flexibly adjust energy according to actual conditions, so that supply and demand changes can be responded dynamically; synchronously, like the energy storage entity, the synchronization takes into account the second degree of association of the elastic load entity with the power supply access point and calculates its maximum required capacity in a specific time domain. The load entity can be dynamically configured and adjusted according to actual requirements; based on the dynamic analysis corresponding to the supply and the demand, the supply and demand unbalance sequence can be dynamically updated, so that the supply and demand bearing capacity of each power supply block is calculated, the efficient utilization of energy is ensured, and the waste is reduced. Based on the fused unbalanced sequence and the energy storage and load adjustable sequence, a configuration strategy aiming at the elastic adjustable energy entity can be dynamically generated, and the configuration strategy not only responds to the current energy condition, but also can predict and adapt to future changes; the stability and reliability of the whole energy system can be dynamically enhanced due to the adjustment capability and supply and demand conditions of various elastic entities, so that the energy system can keep high-efficiency operation in the face of various uncertain factors. Through dynamic sensing and analysis of global energy supply and demand, a cross-regional energy collaborative configuration strategy is realized; the energy utilization rate of the elastic energy entity in energy coordination can be greatly improved.
Preferably, the energy supply chain and the energy consumption chain of each power supply block when the elastic adjustable energy entity is not accessed are obtained based on the energy supply and demand balance relation; extracting energy supply and demand non-overlapping areas of an energy supply chain and an energy consumption chain corresponding to each power supply block in a time domain, and acquiring an initial supply and demand unbalanced sequence in the time domain based on each energy supply and demand non-overlapping area; the method comprises the following steps:
dividing the topology of the power distribution network according to the regional hierarchy to obtain a plurality of power supply blocks, and obtaining the historical energy supply quantity of each power supply block when the elastic adjustable energy entity is not connected to construct an energy supply chain and the historical energy consumption quantity to construct an energy consumption chain;
taking time as a horizontal axis and energy as a vertical axis to acquire an energy supply curve corresponding to an energy supply chain and an energy consumption curve corresponding to an energy consumption chain;
acquiring an energy supply area by integrating an energy supply curve in a time domain; acquiring an energy consumption area by integrating an energy consumption curve in a time domain;
the energy supply and demand non-overlapping area is obtained through superposition of the energy supply area and the energy consumption area on the time domain;
and dividing the non-overlapping area of the energy supply and demand based on a sampling scale to construct an initial supply and demand unbalanced sequence, wherein the corresponding value of the sequence bit of the initial supply and demand unbalanced sequence is the energy capacity.
Preferably, in S2, a first connection degree between the accessible elastic energy storage entity and the adjacent power supply access point is obtained, and the elastic energy storage entity is classified based on the first connection degree to obtain an elastic energy storage entity set belonging to each power supply access point; the method comprises the following steps:
acquiring adjacent power supply access points closest to the space distance of each elastic energy storage entity based on geographic position distribution; calculating a first connection degree of the elastic energy storage entity and the adjacent power supply access point according to the historical access time length, the frequency, the energy and the failure rate;
classifying the elastic energy storage entity to a power supply access point corresponding to the maximum value of the first connection degree; and constructing an elastic energy storage entity set based on the elastic energy storage entity corresponding to each power supply access point.
Preferably, in S2, a first supply-demand bearing capacity of the power supply block in a time domain corresponding to each first supply-demand unbalanced sequence is calculated, and a first energy storage adjustable sequence and a second energy storage adjustable sequence are screened out based on the first supply-demand bearing capacity, including the following steps:
calculating first supply and demand bearing capacity based on the energy supply quantity, the energy state parameter k and the energy allowance of each access point in the corresponding time domain of each first supply and demand unbalance sequence;
Screening out sequence bits with the first supply and demand bearing capacity greater than or equal to 0 corresponding to sequence bits in the first supply and demand unbalanced sequence to construct a first energy storage adjustable sequence;
and screening out sequence bits with the first supply and demand bearing capacity smaller than 0 corresponding to the sequence bits in the first supply and demand unbalanced sequence to construct a second energy storage adjustable sequence.
Preferably, in S3, a second degree of association between the accessible elastic load entity and all the power supply access points is obtained, and the elastic load entity is classified based on the second degree of association to obtain an elastic load entity set belonging to each power supply access point; the method comprises the following steps:
calculating second coupling degrees between the accessible elastic load entity and all power supply access points in a time domain according to the historical access duration, the frequency, the energy and the failure rate;
and classifying the elastic load entities to the corresponding power supply access points when the second coupling degree is maximum, and acquiring the elastic load entities corresponding to each power supply access point to construct an elastic load entity set.
Preferably, in S3, calculating a second supply-demand bearing capacity of the power supply block in a time domain corresponding to each second supply-demand unbalanced sequence, and screening out the first load adjustable sequence and the second load adjustable sequence based on the second supply-demand bearing capacity; the method comprises the following steps:
Calculating a second supply and demand bearing capacity based on the energy demand, the energy state parameter k and the energy allowance of each access point in the corresponding time domain of each second supply and demand unbalanced sequence;
screening out sequence bits with the second supply and demand bearing capacity greater than or equal to 0 corresponding to sequence bits in the second supply and demand unbalanced sequence to construct a first load adjustable sequence;
and screening out sequence bits with the second supply and demand bearing capacity smaller than 0 corresponding to the sequence bits in the second supply and demand unbalanced sequence to construct a second load adjustable sequence.
Preferably, S4, carrying out fusion calculation based on the first supply-demand unbalanced sequence and the second supply-demand unbalanced sequence to obtain a fusion unbalanced sequence; the method comprises the following steps:
calculating the maximum adjustment capacity of the elastic energy storage entity in the matching time domain when being connected into the power supply block based on the energy storage accumulated value of each elastic energy storage entity in the elastic energy storage entity set, and updating the sequence bit of the initial supply-demand unbalance sequence based on the sum of the maximum adjustment capacity and the corresponding sequence value to obtain a first supply-demand unbalance sequence;
calculating the maximum demand capacity of the elastic load entity in the matching time domain to be connected to the power supply block based on the energy demand accumulated value of each elastic load entity in the elastic load entity set, and updating the sequence bit of the initial supply-demand unbalanced sequence based on the sum of the maximum demand capacity and the corresponding sequence value to obtain a second supply-demand unbalanced sequence;
And summing the sequence values of the sequence bits corresponding to the first supply and demand unbalanced sequence and the second supply and demand unbalanced sequence to obtain the fusion unbalanced sequence.
Preferably, S5, generating an elastic adjustable energy storage entity configuration strategy based on the fusion unbalanced sequence, the first energy storage adjustable sequence and the second load adjustable sequence; the method comprises the following steps:
acquiring the maximum energy margin of each sequence bit in the fusion unbalanced sequence based on the first energy storage adjustable sequence;
acquiring the maximum energy demand of each sequence bit in the fused unbalanced sequence based on the second load adjustable sequence;
screening an elastic energy storage entity set of a power supply access point corresponding to the maximum energy allowance according to the maximum supply and demand balance rate to obtain a target elastic energy storage entity, and removing the target elastic energy storage entity in the elastic energy storage entity set to construct an adjustable energy storage entity set;
and distributing the elastic energy storage entities in the adjustable energy storage entity set to the power supply access point corresponding to the maximum energy demand based on the first connection degree.
Preferably, S6, generating an elastic adjustable load entity configuration strategy based on the fusion unbalanced sequence, the second energy storage adjustable sequence and the first load adjustable sequence; the method comprises the following steps:
Acquiring the minimum energy demand of each sequence bit in the fused unbalanced sequence based on the second energy storage adjustable sequence;
obtaining the minimum energy margin of each sequence bit in the fused unbalanced sequence based on the first load adjustable sequence,
screening an elastic load entity set of a power supply access point corresponding to the minimum energy demand according to the maximum supply and demand balance rate to obtain a target elastic load entity, and eliminating the target elastic load entity in the elastic load entity set to construct an adjustable load entity set;
and distributing the elastic load entities in the adjustable load entity set to the power supply access points corresponding to the minimum energy allowance based on the second coupling degree.
In a second aspect, a technical solution provided in an embodiment of the present invention is a multi-energy collaborative configuration system, which is adapted to a multi-energy collaborative configuration method considering access of an elastic adjustable energy entity, including:
the construction module comprises: acquiring an energy supply chain and an energy consumption chain of each power supply block when an elastic adjustable energy entity is not accessed based on an energy supply and demand balance relation; extracting energy supply and demand non-overlapping areas of an energy supply chain and an energy consumption chain corresponding to each power supply block in a time domain, and acquiring an initial supply and demand unbalanced sequence in the time domain based on each energy supply and demand non-overlapping area;
A first splitting module: acquiring a first connection degree between an accessible elastic energy storage entity and an adjacent power supply access point, and classifying the elastic energy storage entity based on the first connection degree to obtain an elastic energy storage entity set belonging to each power supply access point; acquiring the maximum adjustment capacity of the elastic energy storage entity accessed into the power supply block under the matching time domain based on the elastic energy storage entity set; updating the initial supply-demand unbalance sequence based on the maximum regulation capacity to obtain a first supply-demand unbalance sequence; calculating first supply and demand bearing capacity of the power supply block under the time domain corresponding to each first supply and demand unbalanced sequence, and screening out a first energy storage adjustable sequence and a second energy storage adjustable sequence based on the first supply and demand bearing capacity;
and a second splitting module: acquiring second coupling degrees between the accessible elastic load entities and all power supply access points, and classifying the elastic load entities based on the second coupling degrees to obtain an elastic load entity set belonging to each power supply access point; acquiring the maximum required capacity of the elastic load entity accessed to the power supply block under the matching time domain based on the elastic load entity set; updating the initial supply-demand unbalanced sequence based on the maximum demand capacity to obtain a second supply-demand unbalanced sequence; calculating a second supply-demand bearing capacity of the power supply block under the time domain corresponding to each second supply-demand unbalanced sequence, and screening out a first load adjustable sequence and a second load adjustable sequence based on the second supply-demand bearing capacity;
And a fusion module: based on the first supply-demand unbalance sequence and the second supply-demand unbalance sequence, carrying out fusion calculation to obtain a fusion unbalance sequence;
a first configuration module: generating an elastic adjustable energy storage entity configuration strategy based on the fusion unbalanced sequence, the first energy storage adjustable sequence and the second load adjustable sequence;
and a second configuration module: and generating an elastic adjustable load entity configuration strategy based on the fusion unbalanced sequence, the second energy storage adjustable sequence and the first load adjustable sequence.
In a third aspect, a technical solution provided in an embodiment of the present invention is an electronic device, including a memory and a processor, where the memory stores a computer program, and the processor implements a step of a multi-energy collaborative configuration method that considers access of an elastic adjustable energy entity when invoking the computer program in the memory.
In a fourth aspect, a technical solution provided in an embodiment of the present invention is a storage medium, where computer executable instructions are stored in the storage medium, where the computer executable instructions implement steps of a method for multi-energy collaborative configuration considering access of an elastic adjustable energy entity when loaded and executed by a processor.
The invention has the beneficial effects that: the invention designs a multi-energy collaborative configuration method and a system considering the access of an elastic adjustable energy entity, which are used for calculating the supply and demand bearing capacity of a corresponding power supply block when the elastic adjustable energy entity is accessed by analyzing the energy supply and demand relation of each power supply block in different time domains and determining an energy storage adjustable sequence and a load adjustable sequence based on the supply and demand bearing capacity; determining a power supply access point of each elastic energy storage entity and each elastic load entity based on the supply-demand relation of the energy storage adjustable sequence and the corresponding sequence bit of the load adjustable sequence; generating an elastic adjustable energy storage entity configuration strategy based on an elastic energy storage entity contained in the power supply access point and generating an elastic adjustable load entity configuration strategy by an elastic load entity; through dynamic sensing and analysis of global energy supply and demand, a cross-regional energy collaborative configuration strategy is realized; so that the energy supply between different areas can be mutually supplemented and supported; the energy utilization rate of the elastic energy entity in energy coordination can be greatly improved, and the stability and reliability of the whole power distribution network system are further improved.
The foregoing summary is merely an overview of the present invention, and is intended to be implemented in accordance with the teachings of the present invention in order that the same may be more fully understood, and in order that the same or additional objects, features and advantages of the present invention may be more fully understood.
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Other features, objects and advantages of the present invention will become more apparent upon reading of the detailed description of non-limiting embodiments made with reference to the following drawings. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to designate like parts throughout the figures.
Fig. 1 is a flowchart of a method for multi-energy collaborative configuration considering access of an elastic tunable energy entity according to the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail with reference to the accompanying drawings and examples, it being understood that the detailed description herein is merely a preferred embodiment of the present invention, which is intended to illustrate the present invention, and not to limit the scope of the invention, as all other embodiments obtained by those skilled in the art without making any inventive effort fall within the scope of the present invention.
Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart depicts operations (or steps) as a sequential process, many of the operations (or steps) can be performed in parallel, concurrently, or at the same time. Furthermore, the order of the operations may be rearranged. The process may be terminated when its operations are completed, but may have additional steps not included in the figures; the processes may correspond to methods, functions, procedures, subroutines, and the like.
Embodiment one:
as shown in fig. 1, a multi-energy collaborative configuration method considering elastic adjustable energy entity access includes the following steps:
s1, acquiring an energy supply chain and an energy consumption chain of each power supply block when an elastic adjustable energy entity is not connected based on an energy supply and demand balance relation; and extracting energy supply and demand non-overlapping areas of the energy supply chain and the energy consumption chain corresponding to each power supply block in the time domain, and acquiring an initial supply and demand unbalanced sequence in the time domain based on each energy supply and demand non-overlapping area.
Specifically, the method comprises the following steps:
Dividing the topology of the power distribution network according to the regional hierarchy to obtain a plurality of power supply blocks, and obtaining the historical energy supply quantity of each power supply block when the elastic adjustable energy entity is not connected to construct an energy supply chain and the historical energy consumption quantity to construct an energy consumption chain;
taking time as a horizontal axis and energy as a vertical axis to acquire an energy supply curve corresponding to an energy supply chain and an energy consumption curve corresponding to an energy consumption chain;
acquiring an energy supply area by integrating an energy supply curve in a time domain; acquiring an energy consumption area by integrating an energy consumption curve in a time domain;
the energy supply and demand non-overlapping area is obtained through superposition of the energy supply area and the energy consumption area on the time domain;
and dividing the non-overlapping area of the energy supply and demand based on a sampling scale to construct an initial supply and demand unbalanced sequence, wherein the corresponding value of the sequence bit of the initial supply and demand unbalanced sequence is the energy capacity.
In this embodiment, there is complexity and uncertainty in the energy supply and consumption as the energy production, transmission, distribution and consumption are dynamically varied. In the embodiment, the distribution network topology is divided according to the regional hierarchy, so that the distribution network can be divided into a plurality of power supply blocks, and the energy supply and consumption of each block can be managed and regulated more finely; by acquiring and analyzing the historical energy supply amount and the historical energy consumption amount: the energy supply and consumption conditions of each power supply block can be known, and a data basis is provided for the follow-up optimization of energy configuration and the improvement of energy utilization efficiency; acquiring an energy supply curve corresponding to an energy supply chain and an energy consumption curve corresponding to an energy consumption chain: the energy supply and consumption conditions of each power supply block can be intuitively known in the time domain, and a basis is provided for subsequent supply and demand balance analysis; the non-overlapping areas of energy supply and demand are obtained through superposition of the energy supply area and the energy consumption area on the time domain, so that the situation of unbalanced supply and demand in which time periods or power supply areas exist can be identified, and a direction is provided for subsequent optimization and adjustment; dividing the non-overlapping area of energy supply and demand based on a sampling scale to construct an initial supply and demand unbalanced sequence: the method can quantify the unbalanced supply and demand condition to obtain an initial unbalanced supply and demand sequence, and provide basis for subsequent strategy generation.
It can be understood that when there are 10 power supply blocks in a more geographical hierarchy in the management domain, for example, D1 to D10; the energy supply and demand of each power supply block in the current time domain are changed, and an energy supply chain and an energy consumption chain can be obtained according to historical energy supply and demand data; for example, a daily sampling scale of two hours, 12 sets of data may be sampled daily, where the energy supply chain may be g1-g2-g3-g4-g5-g6-g7-g8-g9-g10-g11-g12, and the energy consumption chain may be x1-x2-x3-x4-x5-x6-x7-x8-x9-x10-x11-x12; the energy consumption area corresponding to the energy consumption chain and the energy supply area corresponding to the energy supply chain can be constructed by establishing a coordinate system to perform linear fitting; the initial supply-demand unbalance sequences a1= [ A1, a2, a3, a4, a5, a6, a7, a8, a9, a10, a11, a12] can be obtained by superimposing (subtracting in value) both the energy supply region and the energy consumption region.
S2, acquiring a first connection degree between an accessible elastic energy storage entity and an adjacent power supply access point, and classifying the elastic energy storage entity based on the first connection degree to obtain an elastic energy storage entity set belonging to each power supply access point; acquiring the maximum adjustment capacity of the elastic energy storage entity accessed into the power supply block under the matching time domain based on the elastic energy storage entity set; updating the initial supply-demand unbalance sequence based on the maximum regulation capacity to obtain a first supply-demand unbalance sequence; and calculating the first supply-demand bearing capacity of the power supply block under the time domain corresponding to each first supply-demand unbalanced sequence, and screening out a first energy storage adjustable sequence and a second energy storage adjustable sequence based on the first supply-demand bearing capacity.
In this embodiment, how to effectively manage and utilize the elastic energy storage entity is an important issue in energy management, and the energy storage entity can provide storage and release of energy, which is helpful for balancing energy supply and consumption and improving energy utilization efficiency. The embodiment firstly obtains the accessible elastic energy storage entityThe first connection degree between the power supply access points and the adjacent power supply access points can be used for knowing the historical connection relation between the energy storage entity and the power supply access points, and providing basis for subsequent classification and configuration. Classifying the elastic energy storage entities based on the first connection degree to obtain an elastic energy storage entity set belonging to each power supply access point, wherein the energy storage entities can be classified according to the connection relation between the energy storage entities and the power supply access points to obtain the elastic energy storage entity set belonging to each power supply access point; based on the elastic energy storage entity set, the maximum adjustment capacity of the elastic energy storage entity in the matching time domain, which is connected to the power supply blocks, can be obtained, the maximum adjustment capacity of each power supply block can be received in the specific time domain, and the basis is provided for the subsequent supply and demand balance analysis, wherein the maximum adjustment capacity=energy storage densityAn energy storage area; energy storage density = number of arrangement points of elastically adjustable energy storage entity +. >Corresponding to the total energy capacity/the number of power supply access points; energy storage area = integral value of unbalanced sequence fit curve on time scale; updating the initial supply-demand imbalance sequence based on the maximum adjustment capacity to obtain a first supply-demand imbalance sequence, which may be combined with the adjustment capacity of the energy storage entity to obtain a more accurate first supply-demand imbalance sequence B, e.g. b1= [ B1, B2, B3, B4, B5, B6, B7, B8, B9, B10, B11, B12]The method comprises the steps of carrying out a first treatment on the surface of the The first supply and demand bearing capacity of each power supply block under the corresponding time domain of each first supply and demand unbalanced sequence is calculated, the first energy storage adjustable sequence and the second energy storage adjustable sequence are screened out based on the first supply and demand bearing capacity, the supply and demand bearing capacity of each power supply block can be evaluated, and the energy storage entity sequence needing to be regulated is screened out according to the supply and demand bearing capacity.
Specifically, in S2, a first connection degree between an accessible elastic energy storage entity and an adjacent power supply access point is obtained, and the elastic energy storage entity is classified based on the first connection degree to obtain an elastic energy storage entity set belonging to each power supply access point; the method comprises the following steps:
acquiring adjacent power supply access points closest to the space distance of each elastic energy storage entity based on geographic position distribution; calculating a first connection degree of the elastic energy storage entity and the adjacent power supply access point according to the historical access time length, the frequency, the energy and the failure rate;
Classifying the elastic energy storage entity to a power supply access point corresponding to the maximum value of the first connection degree; and constructing an elastic energy storage entity set based on the elastic energy storage entity corresponding to each power supply access point.
It can be appreciated that, acquiring the adjacent power supply access point closest to the spatial distance of each elastic energy storage entity based on the geographic position distribution can determine the spatial distance between each energy storage entity and the closest power supply access point, and provide a basis for subsequent calculation of the coupling degree; the first connection degree of the elastic energy storage entity and the adjacent power supply access point is calculated according to the historical access duration, the frequency, the energy and the failure rate, various factors in historical data can be comprehensively considered, the connection degree between the energy storage entity and the power supply access point is calculated, and the formula form of the first connection degree can be designed according to actual conditions. For example, the following equation form may be considered: first degree of coupling =Historical access duration + and + of>Historical access frequency + for>Historical energy +Failure rate, wherein->、/>、/>And->Is a weight coefficient, and can be adjusted according to actual conditions. Classifying the elastic energy storage entities into power supply access points corresponding to the maximum value of the first connection degree, and classifying the energy storage entities into power supply access points with the maximum connection degree to obtain an elastic energy storage entity set belonging to each power supply access point; an elastic energy storage entity set is built based on the elastic energy storage entity corresponding to each power supply access point, so that the elastic energy storage entity set under each power supply access point can be obtained, and a basis is provided for subsequent supply and demand balance analysis, for example, the elastic energy storage entity set corresponding to the power supply block D1 is f1= (F1, F2, F3, F4, F5, F6, F7, F8).
Specifically, in S2, a first supply-demand bearing capacity of the power supply block in a time domain corresponding to each first supply-demand unbalanced sequence is calculated, and a first energy storage adjustable sequence and a second energy storage adjustable sequence are screened out based on the first supply-demand bearing capacity, including the following steps:
calculating first supply and demand bearing capacity based on the energy supply quantity, the energy state parameter k and the energy allowance of each access point in the corresponding time domain of each first supply and demand unbalance sequence;
screening out sequence bits with the first supply and demand bearing capacity greater than or equal to 0 corresponding to sequence bits in the first supply and demand unbalanced sequence to construct a first energy storage adjustable sequence;
and screening out sequence bits with the first supply and demand bearing capacity smaller than 0 corresponding to the sequence bits in the first supply and demand unbalanced sequence to construct a second energy storage adjustable sequence.
It can be understood that the first supply and demand bearing capacity is calculated based on the energy supply amount, the energy state parameter k and the energy margin of each access point in the time domain corresponding to each first supply and demand unbalance sequence, and by comprehensively considering various factors, the supply and demand bearing capacity of the power supply block can be more accurately estimated, and the supply and demand bearing capacity represents the energy adjustable capacity of the power supply block corresponding to the power supply access point. Wherein, the first supply and demand bearing capacity= (energy supply amount +k) Energy balance)/energy supply; when the value of the sequence bit of the first supply-demand unbalance sequence is larger than 0, the energy state parameter k=1; when the value of the sequence bit of the first supply-demand unbalance sequence is smaller than 0, the energy state parameter k= -1; screening out sequence bits with a first supply and demand bearing capacity greater than or equal to 0 corresponding to sequence bits in the first supply and demand unbalanced sequence, and constructing a first energy storage adjustable sequence B1-1, for example, B1-1= [ B2, B4, B6, B8, B10, B12]The energy storage entity with the adjustment capability in a specific time domain can be identified, and a direction is provided for subsequent optimization and adjustment; screening out sequence bits with first supply and demand bearing capacity smaller than 0 corresponding to sequence bits in the first supply and demand unbalanced sequence, and constructing a second energy storage adjustable sequence B1-2, such as B1-2= [ B1, B3, B5, B7, B9, B11]The power supply block which needs to be supplemented with energy under a specific time domain can be identified, and a direction is provided for subsequent optimization and adjustment.
S3, obtaining second coupling degrees between the accessible elastic load entities and all power supply access points, and classifying the elastic load entities based on the second coupling degrees to obtain elastic load entity sets belonging to each power supply access point; acquiring the maximum required capacity of the elastic load entity accessed to the power supply block under the matching time domain based on the elastic load entity set; updating the initial supply-demand unbalanced sequence based on the maximum demand capacity to obtain a second supply-demand unbalanced sequence; and calculating the second supply-demand bearing capacity of the power supply block under the time domain corresponding to each second supply-demand unbalanced sequence, and screening out the first load adjustable sequence and the second load adjustable sequence based on the second supply-demand bearing capacity.
In this embodiment, the second association degree between the accessible elastic load entity and all the power supply access points is obtained, so that the connection relationship and association degree between each load entity and all the power supply access points can be known, and a basis is provided for subsequent classification and configuration; classifying elastic load entities based on the second linkage degree to obtain elastic load entity sets belonging to each power supply access point, classifying the load entities according to the connection relation between the elastic load entity sets and the power supply access points to obtain elastic load entity sets belonging to each power supply access point, acquiring the maximum demand capacity of the elastic load entity connected with a power supply block in a matching time domain based on the elastic load entity sets, knowing the maximum demand capacity which can be met by each power supply block in a specific time domain, and providing a basis for subsequent supply and demand balance analysis, wherein the maximum demand capacity is the total energy demand of elastic adjustable load entities contained by each power supply access point; updating the initial supply-demand imbalance sequence based on the maximum demand capacity to obtain a second supply-demand imbalance sequence, wherein the supply-demand imbalance condition can be combined with the demand capability of the load entity to obtain a more accurate second supply-demand imbalance sequence C, such as c1= [ C1, C2, C3, C4, C5, C6, C7, C8, C9, C10, C11, C12]; calculating a second supply-demand bearing capacity of the power supply block under the time domain corresponding to each second supply-demand unbalanced sequence, and screening out a first load adjustable sequence and a second load adjustable sequence based on the second supply-demand bearing capacity: the supply and demand bearing capacity of each power supply block can be evaluated, and a load entity sequence to be regulated is screened out according to the supply and demand bearing capacity; the technical effects of improving the energy utilization efficiency, enhancing the system stability, optimizing the resource configuration and enhancing the transparency of the system can be realized through the means.
Specifically, in S3, a second degree of association between the accessible elastic load entity and all the power supply access points is obtained, and the elastic load entity is classified based on the second degree of association to obtain an elastic load entity set belonging to each power supply access point; the method comprises the following steps:
calculating second coupling degrees between the accessible elastic load entity and all power supply access points in a time domain according to the historical access duration, the frequency, the energy and the failure rate;
and classifying the elastic load entities to the corresponding power supply access points when the second coupling degree is maximum, and acquiring the elastic load entities corresponding to each power supply access point to construct an elastic load entity set.
It can be understood that the second coupling degree between the accessible elastic load entity and all the power supply access points in the time domain is calculated according to the historical access time length, frequency, energy and failure rate, and various factors in the historical data can be comprehensively considered to calculate the load entity and the power supply access pointsA second degree of coupling between the entry points. The second degree of association characterizes the degree of association of each elastically adjustable load entity (for example, an electric automobile) with each new energy power station; the second degree of coupling may be formulated as: first degree of coupling = Historical access duration + and + of>Historical access frequency + for>Historical energy +.>Failure rate, wherein->、/>、/>And->The weight coefficient can be adjusted according to actual conditions; the elastic load entity is classified to correspond to the power supply access points when the second coupling degree is maximum, and the elastic load entity corresponding to each power supply access point is obtained to construct an elastic load entity set: through this step, the load entity can be classified into the power supply access point with the largest second coupling degree, and the elastic load entity set belonging to each power supply access point is obtained. For example, the set of elastic load entities corresponding to the power supply block D1 is e1= (E1, E2, E3, E4, E5, E6, E7, E8).
Specifically, in S3, calculating a second supply-demand bearing capacity of the power supply block in a time domain corresponding to each second supply-demand unbalanced sequence, and screening out a first load adjustable sequence and a second load adjustable sequence based on the second supply-demand bearing capacity; the method comprises the following steps:
calculating a second supply and demand bearing capacity based on the energy demand, the energy state parameter k and the energy allowance of each access point in the corresponding time domain of each second supply and demand unbalanced sequence;
screening out sequence bits with the second supply and demand bearing capacity greater than or equal to 0 corresponding to sequence bits in the second supply and demand unbalanced sequence to construct a first load adjustable sequence;
And screening out sequence bits with the second supply and demand bearing capacity smaller than 0 corresponding to the sequence bits in the second supply and demand unbalanced sequence to construct a second load adjustable sequence.
In this embodiment, the second supply-demand bearing capacity is calculated based on the energy demand, the energy status parameter k and the energy margin of each access point in the time domain corresponding to each second supply-demand unbalanced sequence, and by comprehensively considering various factors, the supply-demand bearing capacity of the power supply block can be estimated more accurately. The supply and demand bearing capacity represents the energy adjustable capacity of a power supply block corresponding to the power supply access point. Wherein the second supply and demand bearing capacity= (energy demand-k)Energy balance)/energy demand; when the value of the sequence bit of the second supply-demand unbalance sequence is larger than 0, the energy state parameter k=1; when the value of the sequence bit of the second supply-demand unbalanced sequence is smaller than 0, the energy state parameter k= -1; screening out sequence bits with a second supply and demand bearing capacity greater than or equal to 0 corresponding to sequence bits in the second supply and demand unbalanced sequence, and constructing a first load adjustable sequence C1-1, for example, C1-1= [ C2, C4, C6, C8, C10, C12]The method comprises the steps of carrying out a first treatment on the surface of the A load entity having an adjustment capability in a specific time domain can be identified; screening out sequence bits with second supply and demand bearing capacity smaller than 0 corresponding to sequence bits in the second supply and demand unbalanced sequence, and constructing a second load adjustable sequence C1-2, such as C1-2= [ C1, C3, C5, C7, C9, C11 ]The power supply block which needs to be supplemented with energy under a specific time domain can be identified, and a direction is provided for subsequent optimization and adjustment.
S4, carrying out fusion calculation based on the first supply-demand unbalance sequence and the second supply-demand unbalance sequence to obtain a fusion unbalance sequence.
Specifically, the method comprises the following steps:
calculating the maximum adjustment capacity of the elastic energy storage entity in the matching time domain when being connected into the power supply block based on the energy storage accumulated value of each elastic energy storage entity in the elastic energy storage entity set, and updating the sequence bit of the initial supply-demand unbalance sequence based on the sum of the maximum adjustment capacity and the corresponding sequence value to obtain a first supply-demand unbalance sequence;
calculating the maximum demand capacity of the elastic load entity in the matching time domain to be connected to the power supply block based on the energy demand accumulated value of each elastic load entity in the elastic load entity set, and updating the sequence bit of the initial supply-demand unbalanced sequence based on the sum of the maximum demand capacity and the corresponding sequence value to obtain a second supply-demand unbalanced sequence;
and summing the sequence values of the sequence bits corresponding to the first supply and demand unbalanced sequence and the second supply and demand unbalanced sequence to obtain the fusion unbalanced sequence.
In this embodiment, the maximum adjustment capacity of the elastic energy storage entity in the matching time domain to be connected to the power supply block is calculated based on the energy storage accumulated value of each elastic energy storage entity in the elastic energy storage entity set: the energy storage accumulated value of the elastic energy storage entity can be comprehensively considered, and the maximum adjustment capacity of the elastic energy storage entity connected to the power supply block in a specific time domain is calculated; the sequence bit updating is performed on the initial supply and demand unbalanced sequence based on the sum of the maximum adjustment capacity and the corresponding sequence value to obtain a first supply and demand unbalanced sequence, and the sum of the maximum adjustment capacity and the corresponding sequence value is used for updating the initial supply and demand unbalanced sequence to obtain the first supply and demand unbalanced sequence, which may be, for example: b1 = [ b1, b2, b3, b4, b5, b6, b7, b8, b9, b10, b11, b12]; calculating the maximum demand capacity of the elastic load entity connected to the power supply block in the matching time domain based on the energy demand accumulated value of each elastic load entity in the elastic load entity set, and calculating the maximum demand capacity of the elastic load entity connected to the power supply block in the specific time domain by comprehensively considering the energy demand accumulated value of the elastic load entity; the sequence bit updating is performed on the initial supply-demand unbalanced sequence based on the sum of the maximum demand capacity and the corresponding sequence value to obtain a second supply-demand unbalanced sequence, and the sum of the maximum demand capacity and the corresponding sequence value is used for updating the initial supply-demand unbalanced sequence to obtain the second supply-demand unbalanced sequence, which may be, for example: for example c1= [ C1, C2, C3, C4, C5, C6, C7, C8, C9, C10, C11, C12]; the sequence values of the sequence bits corresponding to the first supply-demand unbalanced sequence and the second supply-demand unbalanced sequence are summed to obtain a fusion unbalanced sequence, and the obtained fusion unbalanced sequence can truly realize standard dynamic energy supply-demand conditions, such as fusion unbalanced sequences H1= [ b1-c1, b2-c2, b3-c3, b4-c4, b5-c5, b6-c6, b7-c7, b8-c8, b9-c9, b10-c10, b11-c11, b12-c12].
S5, generating an elastic adjustable energy storage entity configuration strategy based on the fusion unbalanced sequence, the first energy storage adjustable sequence and the second load adjustable sequence.
Specifically, the method comprises the following steps:
acquiring the maximum energy margin of each sequence bit in the fusion unbalanced sequence based on the first energy storage adjustable sequence;
acquiring the maximum energy demand of each sequence bit in the fused unbalanced sequence based on the second load adjustable sequence;
screening an elastic energy storage entity set of a power supply access point corresponding to the maximum energy allowance according to the maximum supply and demand balance rate to obtain a target elastic energy storage entity, and removing the target elastic energy storage entity in the elastic energy storage entity set to construct an adjustable energy storage entity set;
and distributing the elastic energy storage entities in the adjustable energy storage entity set to the power supply access point corresponding to the maximum energy demand based on the first connection degree.
In this embodiment, the maximum energy margin of each sequence bit in the fused unbalanced sequence is obtained based on the first energy storage adjustable sequence: the maximum energy allowance of each sequence position in the fusion unbalanced sequence can be obtained by analyzing the first energy storage adjustable sequence; for example, the first energy storage adjustable sequence B1-1= [ B2, B4, B6, B8, B10, B12]; fusion unbalanced sequence h1= [ b1-c1, b2-c2, b3-c3, b4-c4, b5-c5, b6-c6, b7-c7, b8-c8, b9-c9, b10-c10, b11-c11, b12-c12]; it can be seen that the corresponding maximum energy margin [ b2-c2, b4-c4, b6-c6, b8-c8, b10-c10, b12-c12], based on the second load adjustable sequence, obtains the maximum energy requirement for each sequence bit in the fused unbalanced sequence: by analyzing the second load adjustable sequence, the maximum energy demand of each sequence bit in the fused unbalanced sequence can be obtained. The maximum energy demand is [ b1-c1, b3-c3, b5-c5, b7-c7, b9-c9, b11-c11] by the same method; screening the elastic energy storage entity set of the power supply access point corresponding to the maximum energy allowance according to the maximum supply and demand balance rate to obtain a target elastic energy storage entity: screening out an elastic energy storage entity set of a corresponding power supply access point according to the maximum energy allowance, and sorting according to the maximum supply and demand balance rate to obtain a target elastic energy storage entity; eliminating target elastic energy storage entities in the elastic energy storage entity set to construct an adjustable energy storage entity set: removing the target elastic energy storage entity from the elastic energy storage entity set to obtain an adjustable energy storage entity set; for example, the set of elastic energy storage entities f1= (F1, F2, F3, F4, F5, F6, F7, F8), the target elastic energy storage entities being F2, F3, F4, F5; the adjustable energy storage entity set is obtained as F1-1= (F5, F6, F7, F8); distributing elastic energy storage entities in the adjustable energy storage entity set to power supply access points corresponding to the maximum energy demand based on the first connection degree: and according to the first connection degree, the elastic energy storage entities in the adjustable energy storage entity set are distributed to the power supply access points corresponding to the maximum energy demand, for example, the elastic energy storage loads which can be accessed by the power supply access points corresponding to the first power supply block are f6 and f7.
S6, generating an elastic adjustable load entity configuration strategy based on the fusion unbalanced sequence, the second energy storage adjustable sequence and the first load adjustable sequence.
Specifically, the method comprises the following steps:
acquiring the minimum energy demand of each sequence bit in the fused unbalanced sequence based on the second energy storage adjustable sequence;
obtaining the minimum energy margin of each sequence bit in the fused unbalanced sequence based on the first load adjustable sequence,
screening an elastic load entity set of a power supply access point corresponding to the minimum energy demand according to the maximum supply and demand balance rate to obtain a target elastic load entity, and eliminating the target elastic load entity in the elastic load entity set to construct an adjustable load entity set;
and distributing the elastic load entities in the adjustable load entity set to the power supply access points corresponding to the minimum energy allowance based on the second coupling degree.
In this embodiment, the minimum energy demand of each sequence bit in the fused unbalanced sequence is obtained based on the second energy storage adjustable sequence, and the minimum energy demand of each sequence bit in the fused unbalanced sequence can be obtained by analyzing the second energy storage adjustable sequence. For example, the second energy storage adjustable sequence b1_2= [ B1, B3, B5, B7, B9, B11]; fusion unbalanced sequence h1= [ b1-c1, b2-c2, b3-c3, b4-c4, b5-c5, b6-c6, b7-c7, b8-c8, b9-c9, b10-c10, b11-c11, b12-c12]; it is clear that the corresponding maximum energy margins [ b1-c1, b3-c3, b5-c5, b7-c7, b9-c9, b11-c11]; acquiring the minimum energy margin of each sequence bit in the fused unbalanced sequence based on the first load adjustable sequence: by analyzing the first load adjustable sequence, the minimum energy margin of each sequence bit in the fused unbalanced sequence can be obtained. The maximum energy demand is [ b2-c2, b4-c4, b6-c6, b8-c8, b10-c10, b12-c12] by the same method; screening the elastic load entity set of the power supply access point corresponding to the minimum energy demand according to the maximum supply and demand balance rate to obtain a target elastic load entity: and screening out the elastic load entity set of the corresponding power supply access point according to the minimum energy demand, and sorting according to the maximum supply and demand balance rate to obtain the target elastic load entity. Eliminating target elastic load entities in the elastic load entity set to construct an adjustable load entity set: and eliminating the target elastic load entity from the elastic load entity set to obtain an adjustable load entity set. For example, the elastic load entity set e1= (E1, E2, E3, E4, E5, E6, E7, E8), the target elastic energy storage entity is E2, E3, E4, E5; the set of adjustable load entities can be obtained as e1-1= (E5, E6, E7, E8); distributing elastic load entities in the adjustable load entity set to power supply access points corresponding to the minimum energy allowance based on the second coupling degree: according to the second degree of coupling, distributing elastic load entities in the adjustable load entity set to power supply access points corresponding to the minimum energy allowance; for example, the elastic load accessible by the power supply access point corresponding to the first power supply block is e6, e7, e8.
In this embodiment, the maximum energy margin of each sequence bit in the fused unbalanced sequence is obtained based on the first energy storage adjustable sequence: the maximum energy allowance of each sequence position in the fusion unbalanced sequence can be obtained by analyzing the first energy storage adjustable sequence; for example, the first energy storage adjustable sequence B1-1= [ B2, B4, B6, B8, B10, B12]; fusion unbalanced sequence h1= [ b1-c1, b2-c2, b3-c3, b4-c4, b5-c5, b6-c6, b7-c7, b8-c8, b9-c9, b10-c10, b11-c11, b12-c12]; it can be seen that the corresponding maximum energy margin [ b2-c2, b4-c4, b6-c6, b8-c8, b10-c10, b12-c12], based on the second load adjustable sequence, obtains the maximum energy requirement for each sequence bit in the fused unbalanced sequence: by analyzing the second load adjustable sequence, the maximum energy demand of each sequence bit in the fused unbalanced sequence can be obtained. The maximum energy demand is [ b1-c1, b3-c3, b5-c5, b7-c7, b9-c9, b11-c11] by the same method; screening the elastic energy storage entity set of the power supply access point corresponding to the maximum energy allowance according to the maximum supply and demand balance rate to obtain a target elastic energy storage entity: screening out an elastic energy storage entity set of a corresponding power supply access point according to the maximum energy allowance, and sorting according to the maximum supply and demand balance rate to obtain a target elastic energy storage entity; eliminating target elastic energy storage entities in the elastic energy storage entity set to construct an adjustable energy storage entity set: removing the target elastic energy storage entity from the elastic energy storage entity set to obtain an adjustable energy storage entity set; for example, the set of elastic energy storage entities f1= (F1, F2, F3, F4, F5, F6, F7, F8), the target elastic energy storage entities being F2, F3, F4, F5; the adjustable energy storage entity set is obtained as F1-1= (F5, F6, F7, F8); distributing elastic energy storage entities in the adjustable energy storage entity set to power supply access points corresponding to the maximum energy demand based on the first connection degree: and according to the first connection degree, the elastic energy storage entities in the adjustable energy storage entity set are distributed to the power supply access points corresponding to the maximum energy demand, for example, the elastic energy storage loads which can be accessed by the power supply access points corresponding to the first power supply block are f6 and f7.
Embodiment two:
the embodiment of the invention also provides a technical scheme of the multi-energy collaborative configuration system, which is suitable for a multi-energy collaborative configuration method considering the access of an elastic adjustable energy entity, and comprises the following steps:
the construction module comprises: acquiring an energy supply chain and an energy consumption chain of each power supply block when an elastic adjustable energy entity is not accessed based on an energy supply and demand balance relation; extracting energy supply and demand non-overlapping areas of an energy supply chain and an energy consumption chain corresponding to each power supply block in a time domain, and acquiring an initial supply and demand unbalanced sequence in the time domain based on each energy supply and demand non-overlapping area;
a first splitting module: acquiring a first connection degree between an accessible elastic energy storage entity and an adjacent power supply access point, and classifying the elastic energy storage entity based on the first connection degree to obtain an elastic energy storage entity set belonging to each power supply access point; acquiring the maximum adjustment capacity of the elastic energy storage entity accessed into the power supply block under the matching time domain based on the elastic energy storage entity set; updating the initial supply-demand unbalance sequence based on the maximum regulation capacity to obtain a first supply-demand unbalance sequence; calculating first supply and demand bearing capacity of the power supply block under the time domain corresponding to each first supply and demand unbalanced sequence, and screening out a first energy storage adjustable sequence and a second energy storage adjustable sequence based on the first supply and demand bearing capacity;
And a second splitting module: acquiring second coupling degrees between the accessible elastic load entities and all power supply access points, and classifying the elastic load entities based on the second coupling degrees to obtain an elastic load entity set belonging to each power supply access point; acquiring the maximum required capacity of the elastic load entity accessed to the power supply block under the matching time domain based on the elastic load entity set; updating the initial supply-demand unbalanced sequence based on the maximum demand capacity to obtain a second supply-demand unbalanced sequence; calculating a second supply-demand bearing capacity of the power supply block under the time domain corresponding to each second supply-demand unbalanced sequence, and screening out a first load adjustable sequence and a second load adjustable sequence based on the second supply-demand bearing capacity;
and a fusion module: based on the first supply-demand unbalance sequence and the second supply-demand unbalance sequence, carrying out fusion calculation to obtain a fusion unbalance sequence;
a first configuration module: generating an elastic adjustable energy storage entity configuration strategy based on the fusion unbalanced sequence, the first energy storage adjustable sequence and the second load adjustable sequence;
and a second configuration module: and generating an elastic adjustable load entity configuration strategy based on the fusion unbalanced sequence, the second energy storage adjustable sequence and the first load adjustable sequence.
In this embodiment, aiming at the problem of low energy utilization rate when an elastic energy entity participates in energy coordination, firstly, an energy supply chain and an energy consumption chain of each power supply block are dynamically obtained, and supply and demand non-overlapping areas of the power supply blocks in a time domain are analyzed; the energy supply and demand states of all the blocks are tracked and understood in real time; secondly, dynamically determining attribution of the elastic energy storage entity by calculating a first connection degree of the elastic energy storage entity and the power supply access point, and calculating the maximum adjustment capacity of the elastic energy storage entity under a specific time domain, wherein the time domain represents a specific time scale and a specific power supply area, and the energy state of each power supply block under the time domain is dynamically changed; the energy storage entity can flexibly adjust energy according to actual conditions, so that supply and demand changes can be responded dynamically; synchronously, like the energy storage entity, the synchronization takes into account the second degree of association of the elastic load entity with the power supply access point and calculates its maximum required capacity in a specific time domain. The load entity can be dynamically configured and adjusted according to actual requirements; based on the dynamic analysis corresponding to the supply and the demand, the supply and demand unbalance sequence can be dynamically updated, so that the supply and demand bearing capacity of each power supply block is calculated, the efficient utilization of energy is ensured, and the waste is reduced. Based on the fused unbalanced sequence and the energy storage and load adjustable sequence, a configuration strategy aiming at the elastic adjustable energy entity can be dynamically generated, and the configuration strategy not only responds to the current energy condition, but also can predict and adapt to future changes; the stability and reliability of the whole energy system can be dynamically enhanced due to the adjustment capability and supply and demand conditions of various elastic entities, so that the energy system can keep high-efficiency operation in the face of various uncertain factors. Through dynamic sensing and analysis of global energy supply and demand, a cross-regional energy collaborative configuration strategy is realized; the energy utilization rate of the elastic energy entity in energy coordination can be greatly improved.
Embodiment III:
the technical scheme provided by the embodiment of the invention is that the electronic equipment comprises a memory and a processor, wherein the memory stores a computer program, and the processor realizes the steps of a multi-energy collaborative configuration method considering the access of an elastic adjustable energy entity when calling the computer program in the memory.
Embodiment four:
the technical scheme provided by the embodiment of the invention is a storage medium, wherein computer executable instructions are stored in the storage medium, and when the computer executable instructions are loaded and executed by a processor, the steps of a multi-energy collaborative configuration method considering the access of an elastic adjustable energy entity are realized.
From the foregoing description of the embodiments, it will be appreciated by those skilled in the art that, for convenience and brevity of description, only the above-described division of functional modules is illustrated, and in practical application, the above-described functional allocation may be implemented by different functional modules according to needs, i.e. the internal structure of a specific apparatus is divided into different functional modules to implement all or part of the functions described above.
In the embodiments provided in this application, it should be understood that the disclosed structures and methods may be implemented in other ways. For example, the embodiments described above with respect to structures are merely illustrative, e.g., the division of modules or units is merely a logical functional division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another structure, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via interfaces, structures or units, which may be in electrical, mechanical or other forms.
The units described as separate parts may or may not be physically separate, and the parts shown as units may be one physical unit or a plurality of physical units, may be located in one place, or may be distributed in a plurality of different places. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a readable storage medium. Based on such understanding, the technical solution of the embodiments of the present application may be essentially or a part contributing to the prior art or all or part of the technical solution may be embodied in the form of a software product stored in a storage medium, including several instructions to cause a device (may be a single-chip microcomputer, a chip or the like) or a processor (processor) to perform all or part of the steps of the methods of the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read Only Memory (ROM), a random access memory (random access memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The above embodiments are preferred embodiments of the method and system for flexibly adjusting energy entity access according to the present invention, and are not limited to the specific embodiments, but the scope of the invention includes equivalent changes according to the shape and structure of the invention.
Claims (12)
1. The multi-energy collaborative configuration method considering the access of the elastic adjustable energy entity is characterized in that: the method comprises the following steps:
s1, acquiring an energy supply chain and an energy consumption chain of each power supply block when an elastic adjustable energy entity is not connected based on an energy supply and demand balance relation; extracting energy supply and demand non-overlapping areas of an energy supply chain and an energy consumption chain corresponding to each power supply block in a time domain, and acquiring an initial supply and demand unbalanced sequence in the time domain based on each energy supply and demand non-overlapping area;
s2, acquiring a first connection degree between an accessible elastic energy storage entity and an adjacent power supply access point, and classifying the elastic energy storage entity based on the first connection degree to obtain an elastic energy storage entity set belonging to each power supply access point; acquiring the maximum adjustment capacity of the elastic energy storage entity accessed into the power supply block under the matching time domain based on the elastic energy storage entity set; updating the initial supply-demand unbalance sequence based on the maximum regulation capacity to obtain a first supply-demand unbalance sequence; calculating first supply and demand bearing capacity of the power supply block under the time domain corresponding to each first supply and demand unbalanced sequence, and screening out a first energy storage adjustable sequence and a second energy storage adjustable sequence based on the first supply and demand bearing capacity;
S3, obtaining second coupling degrees between the accessible elastic load entities and all power supply access points, and classifying the elastic load entities based on the second coupling degrees to obtain elastic load entity sets belonging to each power supply access point; acquiring the maximum required capacity of the elastic load entity accessed to the power supply block under the matching time domain based on the elastic load entity set; updating the initial supply-demand unbalanced sequence based on the maximum demand capacity to obtain a second supply-demand unbalanced sequence; calculating a second supply-demand bearing capacity of the power supply block under the time domain corresponding to each second supply-demand unbalanced sequence, and screening out a first load adjustable sequence and a second load adjustable sequence based on the second supply-demand bearing capacity;
s4, carrying out fusion calculation based on the first supply-demand unbalance sequence and the second supply-demand unbalance sequence to obtain a fusion unbalance sequence;
s5, generating an elastic adjustable energy storage entity configuration strategy based on the fusion unbalanced sequence, the first energy storage adjustable sequence and the second load adjustable sequence;
s6, generating an elastic adjustable load entity configuration strategy based on the fusion unbalanced sequence, the second energy storage adjustable sequence and the first load adjustable sequence.
2. The method for multi-energy collaborative configuration considering elastic adjustable energy entity access according to claim 1, wherein the method comprises the following steps:
The energy supply chain and the energy consumption chain of each power supply block are obtained based on the energy supply and demand balance relation when the elastic adjustable energy entity is not accessed; extracting energy supply and demand non-overlapping areas of an energy supply chain and an energy consumption chain corresponding to each power supply block in a time domain, and acquiring an initial supply and demand unbalanced sequence in the time domain based on each energy supply and demand non-overlapping area; the method comprises the following steps:
dividing the topology of the power distribution network according to the regional hierarchy to obtain a plurality of power supply blocks, and obtaining the historical energy supply quantity of each power supply block when the elastic adjustable energy entity is not connected to construct an energy supply chain and the historical energy consumption quantity to construct an energy consumption chain;
taking time as a horizontal axis and energy as a vertical axis to acquire an energy supply curve corresponding to an energy supply chain and an energy consumption curve corresponding to an energy consumption chain;
acquiring an energy supply area by integrating an energy supply curve in a time domain; acquiring an energy consumption area by integrating an energy consumption curve in a time domain;
the energy supply and demand non-overlapping area is obtained through superposition of the energy supply area and the energy consumption area on the time domain;
and dividing the non-overlapping area of the energy supply and demand based on a sampling scale to construct an initial supply and demand unbalanced sequence, wherein the corresponding value of the sequence bit of the initial supply and demand unbalanced sequence is the energy capacity.
3. The method for multi-energy collaborative configuration considering elastic adjustable energy entity access according to claim 1, wherein the method comprises the following steps:
s2, acquiring a first connection degree between an accessible elastic energy storage entity and an adjacent power supply access point, and classifying the elastic energy storage entity based on the first connection degree to obtain an elastic energy storage entity set belonging to each power supply access point; the method comprises the following steps:
acquiring adjacent power supply access points closest to the space distance of each elastic energy storage entity based on geographic position distribution; calculating a first connection degree of the elastic energy storage entity and the adjacent power supply access point according to the historical access time length, the frequency, the energy and the failure rate;
classifying the elastic energy storage entity to a power supply access point corresponding to the maximum value of the first connection degree; and constructing an elastic energy storage entity set based on the elastic energy storage entity corresponding to each power supply access point.
4. The method for multi-energy collaborative configuration considering elastic adjustable energy entity access according to claim 3, wherein:
s2, calculating a first supply and demand bearing capacity of a power supply block under a time domain corresponding to each first supply and demand unbalanced sequence, and screening a first energy storage adjustable sequence and a second energy storage adjustable sequence based on the first supply and demand bearing capacity, wherein the method comprises the following steps:
Calculating first supply and demand bearing capacity based on the energy supply quantity, the energy state parameter k and the energy allowance of each access point in the corresponding time domain of each first supply and demand unbalance sequence;
screening out sequence bits with the first supply and demand bearing capacity greater than or equal to 0 corresponding to sequence bits in the first supply and demand unbalanced sequence to construct a first energy storage adjustable sequence;
and screening out sequence bits with the first supply and demand bearing capacity smaller than 0 corresponding to the sequence bits in the first supply and demand unbalanced sequence to construct a second energy storage adjustable sequence.
5. The method for multi-energy collaborative configuration considering elastic adjustable energy entity access according to claim 1, wherein the method comprises the following steps:
s3, obtaining second coupling degrees between the accessible elastic load entities and all power supply access points, and classifying the elastic load entities based on the second coupling degrees to obtain elastic load entity sets belonging to each power supply access point; the method comprises the following steps:
calculating second coupling degrees between the accessible elastic load entity and all power supply access points in a time domain according to the historical access duration, the frequency, the energy and the failure rate;
and classifying the elastic load entities to the corresponding power supply access points when the second coupling degree is maximum, and acquiring the elastic load entities corresponding to each power supply access point to construct an elastic load entity set.
6. The method for multi-energy collaborative configuration considering elastic adjustable energy entity access according to claim 5, wherein:
s3, calculating a second supply and demand bearing capacity of the power supply block under the time domain corresponding to each second supply and demand unbalanced sequence, and screening out a first load adjustable sequence and a second load adjustable sequence based on the second supply and demand bearing capacity; the method comprises the following steps:
calculating a second supply and demand bearing capacity based on the energy demand, the energy state parameter k and the energy allowance of each access point in the corresponding time domain of each second supply and demand unbalanced sequence;
screening out sequence bits with the second supply and demand bearing capacity greater than or equal to 0 corresponding to sequence bits in the second supply and demand unbalanced sequence to construct a first load adjustable sequence;
and screening out sequence bits with the second supply and demand bearing capacity smaller than 0 corresponding to the sequence bits in the second supply and demand unbalanced sequence to construct a second load adjustable sequence.
7. The method for multi-energy collaborative configuration considering elastic adjustable energy entity access according to claim 1, wherein the method comprises the following steps:
s4, carrying out fusion calculation based on the first supply-demand unbalance sequence and the second supply-demand unbalance sequence to obtain a fusion unbalance sequence; the method comprises the following steps:
Calculating the maximum adjustment capacity of the elastic energy storage entity in the matching time domain when being connected into the power supply block based on the energy storage accumulated value of each elastic energy storage entity in the elastic energy storage entity set, and updating the sequence bit of the initial supply-demand unbalance sequence based on the sum of the maximum adjustment capacity and the corresponding sequence value to obtain a first supply-demand unbalance sequence;
calculating the maximum demand capacity of the elastic load entity in the matching time domain to be connected to the power supply block based on the energy demand accumulated value of each elastic load entity in the elastic load entity set, and updating the sequence bit of the initial supply-demand unbalanced sequence based on the sum of the maximum demand capacity and the corresponding sequence value to obtain a second supply-demand unbalanced sequence;
and summing the sequence values of the sequence bits corresponding to the first supply and demand unbalanced sequence and the second supply and demand unbalanced sequence to obtain the fusion unbalanced sequence.
8. A method for multi-energy collaborative configuration considering access of an elastically-tunable energy entity according to claim 1 or 3, characterized in that:
s5, generating an elastic adjustable energy storage entity configuration strategy based on the fusion unbalanced sequence, the first energy storage adjustable sequence and the second load adjustable sequence; the method comprises the following steps:
acquiring the maximum energy margin of each sequence bit in the fusion unbalanced sequence based on the first energy storage adjustable sequence;
Acquiring the maximum energy demand of each sequence bit in the fused unbalanced sequence based on the second load adjustable sequence;
screening an elastic energy storage entity set of a power supply access point corresponding to the maximum energy allowance according to the maximum supply and demand balance rate to obtain a target elastic energy storage entity, and removing the target elastic energy storage entity in the elastic energy storage entity set to construct an adjustable energy storage entity set;
and distributing the elastic energy storage entities in the adjustable energy storage entity set to the power supply access point corresponding to the maximum energy demand based on the first connection degree.
9. The method for multi-energy collaborative configuration considering elastic adjustable energy entity access according to claim 1 or 5, wherein the method comprises the following steps:
s6, generating an elastic adjustable load entity configuration strategy based on the fusion unbalanced sequence, the second energy storage adjustable sequence and the first load adjustable sequence; the method comprises the following steps:
acquiring the minimum energy demand of each sequence bit in the fused unbalanced sequence based on the second energy storage adjustable sequence;
obtaining the minimum energy margin of each sequence bit in the fused unbalanced sequence based on the first load adjustable sequence,
screening an elastic load entity set of a power supply access point corresponding to the minimum energy demand according to the maximum supply and demand balance rate to obtain a target elastic load entity, and eliminating the target elastic load entity in the elastic load entity set to construct an adjustable load entity set;
And distributing the elastic load entities in the adjustable load entity set to the power supply access points corresponding to the minimum energy allowance based on the second coupling degree.
10. A multi-energy co-configuration system adapted to a multi-energy co-configuration method according to any of claims 1-9, wherein the multi-energy co-configuration method is adapted to take into account access of an elastically tunable energy entity, comprising:
the construction module comprises: acquiring an energy supply chain and an energy consumption chain of each power supply block when an elastic adjustable energy entity is not accessed based on an energy supply and demand balance relation; extracting energy supply and demand non-overlapping areas of an energy supply chain and an energy consumption chain corresponding to each power supply block in a time domain, and acquiring an initial supply and demand unbalanced sequence in the time domain based on each energy supply and demand non-overlapping area;
a first splitting module: acquiring a first connection degree between an accessible elastic energy storage entity and an adjacent power supply access point, and classifying the elastic energy storage entity based on the first connection degree to obtain an elastic energy storage entity set belonging to each power supply access point; acquiring the maximum adjustment capacity of the elastic energy storage entity accessed into the power supply block under the matching time domain based on the elastic energy storage entity set; updating the initial supply-demand unbalance sequence based on the maximum regulation capacity to obtain a first supply-demand unbalance sequence; calculating first supply and demand bearing capacity of the power supply block under the time domain corresponding to each first supply and demand unbalanced sequence, and screening out a first energy storage adjustable sequence and a second energy storage adjustable sequence based on the first supply and demand bearing capacity;
And a second splitting module: acquiring second coupling degrees between the accessible elastic load entities and all power supply access points, and classifying the elastic load entities based on the second coupling degrees to obtain an elastic load entity set belonging to each power supply access point; acquiring the maximum required capacity of the elastic load entity accessed to the power supply block under the matching time domain based on the elastic load entity set; updating the initial supply-demand unbalanced sequence based on the maximum demand capacity to obtain a second supply-demand unbalanced sequence; calculating a second supply-demand bearing capacity of the power supply block under the time domain corresponding to each second supply-demand unbalanced sequence, and screening out a first load adjustable sequence and a second load adjustable sequence based on the second supply-demand bearing capacity;
and a fusion module: based on the first supply-demand unbalance sequence and the second supply-demand unbalance sequence, carrying out fusion calculation to obtain a fusion unbalance sequence;
a first configuration module: generating an elastic adjustable energy storage entity configuration strategy based on the fusion unbalanced sequence, the first energy storage adjustable sequence and the second load adjustable sequence;
and a second configuration module: and generating an elastic adjustable load entity configuration strategy based on the fusion unbalanced sequence, the second energy storage adjustable sequence and the first load adjustable sequence.
11. An electronic device comprising a memory and a processor, the memory having stored therein a computer program, the processor implementing the steps of the multi-energy co-configuration method according to any one of claims 1 to 9 taking into account the access of an elastically tunable energy entity when invoking the computer program in the memory.
12. A storage medium having stored therein computer executable instructions which when loaded and executed by a processor implement the steps of the method for multi-energy co-configuration taking into account access of elastically tunable energy entities as claimed in any of claims 1 to 9.
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