CN116207771A - A novel distribution network co-evolution method based on evolution co-entropy - Google Patents

Abstract

The invention discloses a novel power distribution network co-evolution method based on evolution co-entropy, which comprises the following steps: s1: firstly, dividing a main stage of the cooperative evolution of a novel power distribution network by combining a development target and a main task of the novel power distribution network; s2: then cutting in from the angle of the source network charge storage, and providing a source network charge storage evolution path; s3: constructing an evolution collaborative entropy for evaluating the source network charge storage collaborative situation, and performing data processing on the evolution collaborative entropy by adopting a shannon theory; s4: and evaluating the benefits of the co-evolution on carbon emission reduction by adopting a carbon emission intensity model and a carbon emission economic benefit model. The method can accurately evaluate and analyze each stage of distribution network evolution, provide effective approaches for each participating evolution main body, promote the construction of a novel power distribution network, reflect the carbon emission condition in the cooperative evolution process of the power distribution network, promote carbon emission reduction and improve the carbon emission benefit.

Description

A new distribution network collaborative evolution method based on evolutionary collaborative entropy

Technical Field

The present invention relates to the technical field of distribution network, and in particular to a novel distribution network collaborative evolution method based on evolutionary collaborative entropy.

Background Art

As the requirements for power supply capacity, transmission efficiency and transmission quality of distribution networks gradually increase, the importance of coordinated development of internal resources of new distribution networks continues to increase. It is urgent to build a new generation of distribution networks with information technology and big data processing technology as the core. However, the current distribution network has problems such as uncoordinated source, grid, load and storage, excessive carbon emissions, and low economic benefits of carbon emissions. Therefore, if we want to reasonably promote the construction of a new distribution network, we must first establish a path for the coordinated evolution of source, grid, load and storage, promote carbon emission reduction, and build a new distribution network with multi-energy complementarity. The existing distribution network coordinated evolution methods generally lack a specific description of the path for the distribution network to reach the future distribution network.

Summary of the invention

The purpose of the present invention is to provide a new distribution network collaborative evolution method based on evolutionary collaborative entropy to solve the problems raised in the above background technology.

To achieve the above object, the present invention provides the following technical solution: a novel distribution network collaborative evolution method based on evolutionary collaborative entropy, comprising the following steps:

S1: First, based on the development goals and main tasks of the new distribution network, the main stages of the coordinated evolution of the new distribution network are divided;

S2: Then, from the perspective of source, grid, load and storage, the evolution path of source, grid, load and storage is proposed;

S3: Construct the evolutionary synergy entropy for evaluating the synergy between source, grid, load and storage, and use Shannon theory to digitize the evolutionary synergy entropy;

S4: Use the carbon emission intensity model and carbon emission economic benefit model to evaluate the benefits of co-evolution for carbon emission reduction.

Preferably, the new distribution network evolution stage in step S1 includes three core characteristics: development period, transformation period and intelligent integration period.

Preferably, the distribution network in the development stage mainly relies on large units and large power grids to provide power input and carry a certain proportion of renewable energy. The development stage relies on ultra-high voltage AC and DC transmission and coordinated strong transmission methods of AC power of various voltage levels to achieve a large-scale resource optimization configuration capability of the distribution network;

The transformation period is a stage in which a high penetration rate of renewable power sources is achieved, friendly access is achieved, a certain proportion of load-side response capability is achieved, and the distribution network is artificially intelligent;

The intelligent integration period is the stage of improvement and maturity of the future distribution network, when the AC/DC hybrid distribution network will be fully built and carbon neutrality will be achieved.

Preferably, the new distribution network collaborative evolution path in step S2 is an integrated collaborative development evolution path of "source-grid-load-storage", which is used to ensure real-time transmission of power information and form a real-time, safe and stable power production, transportation and use mode;

The integrated coordinated development evolution path of “source-grid-load-storage” also includes:

The co-evolutionary path between “sources”;

The co-evolution path between “source-network”;

The co-evolutionary path between “networks”;

The collaborative evolution path between “storage-grid”;

The co-evolution path between "荷-荷".

Preferably, the evolutionary synergy entropy in step S3 is specifically to construct an effective indicator for measuring the synergy evolution effect of the overall distribution network, find the evolution characteristics of each evolution stage in the evolution process, and adopt the dissipation theory and the Brussels model to propose a distribution network evolution synergy entropy indicator, and then translate the original Brussels model, that is, transform the meanings represented by A, B, D, E, X, and Y into relevant concepts of distribution network synergy evolution.

Preferably, the data processing of the evolutionary collaborative entropy in step S3 specifically includes the following steps:

S31: To calculate the evolutionary synergy entropy, we first need to define the total amount of information entropy;

S32: Secondly, based on the Brussels model structure, the total number of associated paths of the co-evolution of the distribution network is calculated;

S33: Then, the number of positive and negative paths of the co-evolutionary participants is calculated based on the entropy weight method;

S34: Finally, according to the relationship between probability and Shannon entropy function, the evolutionary synergy entropy of the distribution network is calculated.

Preferably, the carbon emission intensity assessment model in step S4 includes assessment from four aspects: distributed generation, transmission lines, loads and energy storage;

The carbon emission economic benefit model in step S4 includes constructing a carbon economic benefit evaluation model from four aspects: carbon emission cost, electric energy benefit, low-carbon benefit contribution factor and carbon emission compensation time.

Preferably, the evaluation co-evolution in step S4 includes co-evolution in the development period, co-evolution in the metamorphosis period and co-evolution in the intelligence-fusion period.

Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention plans the evolution stage of the new distribution network, and from the perspective of source, grid, load and storage, proposes the source, grid, load and storage evolution path, then uses the Brussels model to construct the co-evolution entropy of the distribution network, and adopts the Shannon entropy function to solve it, and finally adopts the carbon emission intensity model and the carbon emission economic benefit model to evaluate the benefits of co-evolution for carbon emission reduction. It can accurately evaluate and analyze the various stages of distribution network evolution, provide an effective way for each participant in the evolution, promote the construction of a new distribution network, reflect the carbon emissions in the process of co-evolution of the distribution network, promote carbon emission reduction, and improve carbon emission benefits.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a block diagram of the collaborative evolution problem among “source-grid-load-storage” of the present invention;

FIG2 is a block diagram of the collaborative evolution path between “source-grid-load-storage” of the present invention;

FIG3 is a bar graph of the entropy value of the co-evolution during the development period of the present invention;

FIG4 is a bar graph of the entropy value of the co-evolution during the metamorphosis period of the present invention;

FIG5 is a bar graph showing the entropy value of the co-evolution of the intelligent integration period of the present invention.

DETAILED DESCRIPTION

The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

Referring to FIG. 1 to FIG. 5 , the present invention provides a technical solution: a novel distribution network collaborative evolution method based on evolutionary collaborative entropy, comprising the following steps:

S1: First, based on the development goals and main tasks of the new distribution network, the main stages of the coordinated evolution of the new distribution network are divided;

S2: Then, from the perspective of source, grid, load and storage, the evolution path of source, grid, load and storage is proposed;

S3: Construct the evolutionary synergy entropy for evaluating the synergy between source, grid, load and storage, and use Shannon theory to digitize the evolutionary synergy entropy;

S4: Use the carbon emission intensity model and carbon emission economic benefit model to evaluate the benefits of co-evolution for carbon emission reduction.

Furthermore, the new distribution network evolution stage in step S1 includes three core characteristics: development period, transformation period and intelligent integration period.

Furthermore, the distribution network in the development period mainly relies on large units and large power grids to provide power input and carry a certain proportion of renewable energy. The development period relies on ultra-high voltage AC and DC transmission and coordinated strong transmission methods of AC power of various voltage levels to achieve a large-scale resource optimization allocation capability of the distribution network;

The transformation period is a stage in which a high penetration rate of renewable power sources is achieved, friendly access is achieved, a certain proportion of load-side response capability is achieved, and the distribution network is artificially intelligent;

The intelligent integration period is the stage of improvement and maturity of the future distribution network, when the AC/DC hybrid distribution network will be fully built and carbon neutrality will be achieved.

Among them, the distribution network in the development stage mainly relies on large units and large power grids to provide power input and carry a certain proportion of renewable energy. The main characteristics are that it relies on ultra-high voltage AC and DC transmission and coordinated strong transmission methods of AC power of various voltage levels to achieve a large range of resource optimization allocation capabilities of the distribution network. Carbon emissions continue to increase year by year. The penetration rate of renewable power generation capacity is between 10% and 35%, and the penetration rate of non-hydro renewable power generation capacity is between 5% and 20%. The grid structure at this stage is not strong enough, the level of intelligence is low, the intelligent interactive load is small, and the coordination and mutual assistance ability of the power grid and the external system is weak;

The transformation period is the stage of achieving high penetration and friendly access of renewable power sources, having a certain proportion of load-side response capabilities, and the artificial intelligence of the distribution network. During this period, through the formulation of specifications and technological improvements, friendly access to renewable energy, especially new energy, is achieved, the boundaries of "rights, responsibilities and interests" of renewable energy access are clarified, carbon emissions reach a peak, the penetration rate of renewable power generation is increased to 40%, electrochemical energy storage technology is mass-produced above 100MW, a certain proportion of bidirectional loads participate in power response control, and a microgrid, micro energy network, integrated energy station and other energy supply systems are formed. The Internet of Things and artificial intelligence technologies are integrated into all aspects of power production, greatly improving productivity;

The intelligent integration period is the stage of improvement and maturity of the future distribution network. The AC/DC hybrid distribution network will be fully built, carbon neutrality will be achieved, renewable energy will become the main power source, distributed power sources, energy storage and a wide range of load groups will have the ability to respond and regulate, and clean electricity will be the main, all links will be intelligently controllable, and widely interconnected and comprehensive coordination will be achieved. The core position of electricity will be consolidated and enhanced, and flexible interconnection and joint dispatch of power grids, gas grids, heat grids and transportation networks with electricity as the core will be realized.

Further, as shown in FIG2 , the new distribution network collaborative evolution path in step S2 is an integrated collaborative development evolution path of “source-grid-load-storage”, which is used to ensure the real-time transmission of power information and form a real-time, safe and stable power production, transportation and use mode;

The integrated coordinated development evolution path of “source-grid-load-storage” also includes:

The co-evolutionary path between “sources”;

In order to solve the problem of the coordinated evolution between renewable energy and traditional energy, we must first improve the accuracy of renewable energy generation prediction and then improve the renewable energy generation technology. Both of these points ensure the stability of renewable energy power supply. The key is to coordinate the interests between renewable energy and traditional power, avoid "coal power regional protection", and achieve a new power supply mode with renewable energy as the main power generation and traditional energy as the auxiliary peak load regulation.

The co-evolution path between “source-network”;

In order to solve the problem of the coordinated evolution between renewable energy generation and grid transmission, it is still necessary to improve the accuracy of renewable energy generation forecasts and confirm the more accurate supply of renewable energy generation. Then, it is necessary to further improve grid technology to achieve the goal of ensuring both safety and stability, aiming to ensure that the access of renewable energy power to the grid will not have a serious impact on the grid. Finally, it is necessary to coordinate the interests between renewable energy generation and the grid to ensure that the grid will not refuse to accept the access of renewable energy power to the grid due to interests.

The co-evolutionary path between “networks”;

In order to solve the problem of the coordinated evolution between microgrids and main grids, we must first improve the safety and flexibility of both to ensure their stable operation and safe supply. The main grid emphasizes its integration, that is, the degree of acceptance of various types of electricity, while the microgrid pays more attention to its cleanliness and renewability according to local conditions. Then, after clarifying the interest relationship between the main grid and the microgrid, the microgrid and the main grid are connected, which not only needs to ensure the balance of power supply and demand between them, but also needs to ensure the convenience and intelligence of electricity use in the covered communities.

The collaborative evolution path between “storage-grid”;

In order to solve the problem of the coordinated evolution between the power grid and energy storage devices, we first need to innovate the technology of energy storage devices and reduce their application costs from the perspective of technological innovation and industrial upgrading. Then, through the technical support of the power grid, we can improve the flexibility of the power grid and make it easier to connect with the energy storage devices, so that the power can penetrate, support and fill each other. Finally, we need to coordinate the interests of the energy storage devices and the power grid, and finally form the coordinated evolution of "grid-storage".

The co-evolutionary path between “load-load”;

To address the problem of co-evolution between loads and load classification, we first need to classify existing loads, including controllable loads and conventional loads. The former have power that can be adjusted within a certain range, and the latter are ordinary users in urban areas or autonomous electricity users such as factories. Secondly, by updating power load forecasting technology, the accuracy of load forecasting can be improved. Finally, flexible loads can be allowed to enter the power grid, ultimately achieving the co-evolution between "loads".

Among them, the integration of "source-grid-load-storage" is the final state of coordinated development, emphasizing mutual coordination and integration, ensuring the real-time transmission of power information, and forming a real-time, safe and stable power production, transportation and use mode. Only when each participating entity reaches a state of coordinated evolution can the ultimate goal of the integration of "source-grid-load-storage" be achieved.

Furthermore, the evolutionary synergy entropy in step S3 is specifically to construct an effective indicator for measuring the synergy evolution effect of the overall distribution network, to find the evolutionary characteristics of each evolutionary stage in the evolutionary process, and to propose a distribution network evolution synergy entropy indicator by using dissipation theory and the Brussels model. Then, the original Brussels model is paraphrased, that is, the meanings represented by A, B, D, E, X, and Y are transformed into relevant concepts of the synergy evolution of the distribution network.

Among them, let A and B be the components of the relationship entropy of the evolutionary participants of the distribution network, that is, A is the positive entropy generated by the evolutionary participants, B is the negative entropy formed by the evolutionary participants accepting related association behaviors, D and E are two possible states under the interaction of A and B; D is a non-dissipative structure state, that is, the group relationship of each evolutionary participant is unclear; E is a dissipative structure state, that is, the group relationship of each evolutionary participant is clear, X and Y are quantifiable indicators that affect the clarity of the group relationship of the evolutionary participants, where X represents a quantifiable positive entropy indicator and Y represents a quantifiable negative entropy indicator;

According to the above definition, the present invention constructs the Brussels model of the coordinated evolution of the distribution network, as shown in the following formula:

；

;

The evolutionary collaborative entropy represents the changes in the state coefficients of the system in the irreversible process of the subjects participating in the evolution of each distribution network and the factors affecting the evolution, in which the effective energy conversion efficiency decreases and the ineffective energy consumption increases. According to the characteristics of the entropy value, in the collaborative evolution process of the distribution network, the larger the collaborative entropy value, the worse the collaborative evolution effect between the subjects participating in the evolution; conversely, the better the collaborative evolution effect between the subjects participating in the evolution.

Furthermore, the data processing of the evolutionary collaborative entropy in step S3 specifically includes the following steps:

S31: To calculate the evolutionary synergy entropy, we first need to define the total amount of information entropy;

S32: Secondly, based on the Brussels model structure, the total number of associated paths of the co-evolution of the distribution network is calculated;

S33: Then, the number of positive and negative paths of the co-evolutionary participants is calculated based on the entropy weight method;

S34: Finally, according to the relationship between probability and Shannon entropy function, the evolutionary synergy entropy of the distribution network is calculated.

It can be understood that firstly, the multiple discrete events in the system s are expressed as a discrete event set S = {E ₁ ,E ₂ ,E ₃ ,...,E _n }, where the probability of each event occurring randomly is P = {P ₁ ,P ₂ ,...,P _n }, so the information entropy (i.e. the total amount of information) can be defined as shown in the formula:

Based on the Brussels model structure of the above distribution network collaborative evolution, it is assumed that in the evolution process of the distribution network, _fi is the number of collaborative paths from the ith evolutionary subject to other evolutionary subjects, and _fi ' is the number of collaborative paths from the ith evolutionary subject to other evolutionary subjects. Assuming that there are n distribution network evolutionary subjects in total, the total number of associated paths of the distribution network collaborative evolution is as shown in the formula:

The phased directed weighted distribution network collaborative evolution network structure is constructed, and the weight concept is integrated into the statistics of the number of collaborative paths. The paths with different weights are normalized and integrated into a unified path. The path weights are divided into three levels, represented as q _i (i = 1, 2, 3). The number of positive and negative paths of the evolution participant i after adding weight information is shown in the formula:

f _i ＝q ₁ f _i1 +q ₂ f _i2 +q ₃ f _i3 ,i＝1,2,...,n;

f _i ′＝q ₁ f′ _i1 +q ₂ f′ _i2 +q ₃ f′ _i3 ,i＝1,2,...,n;

因此，按照概率及香农熵函数之间的关系，就可以得到配电网的演化协同熵表达式如式所示：Here, P is denoted as

Therefore, according to the relationship between probability and Shannon entropy function, the evolutionary cooperative entropy expression of the distribution network can be obtained as shown in the formula:

Furthermore, the carbon emission intensity assessment model in step S4 includes assessment from four aspects: distributed generation, transmission lines, loads and energy storage, as shown in the formula:

In the formula, P is the total carbon emissions consumed by generating unit electricity in a certain stage; _Pi is the load power of node i; _Vi is the carbon emissions per unit electricity; ρ represents the line loss rate per unit length of the transmission line; L represents the length of the transmission line; Ω represents the source-grid-load-storage system; _Pj represents the flow value of node j; _Vr represents the carbon emissions required for the load to consume unit electricity; _Vs represents the carbon emissions required for the energy storage end to store unit electricity;

The carbon emission economic benefit model in step S4 includes constructing a carbon economic benefit evaluation model from four aspects: carbon emission cost, electric energy benefit, low-carbon benefit contribution factor and carbon emission compensation time;

The carbon emission cost includes the unit carbon emission cost of distributed power generation and traditional power generation, as well as the carbon emission cost of transmission lines, loads, and energy storage, as shown in the formula:

Where _C0 is the carbon emission cost of distributed generation and traditional generation as well as transmission lines, loads, and energy storage; _ct is the unit carbon emission cost of the four sources, grids, loads, and storage;

Taking into account the carbon emission costs of the new distribution network with the coordinated evolution of source, grid, load and storage, an energy efficiency index that takes into account the carbon emission costs can be proposed in combination with the electricity sales benefits. The energy efficiency is shown in the formula:

E＝P _r ( _ps +p ₀ )-C ₀ -P _C ;

Where E is the electricity benefit of carbon emission cost; _ps is the electricity price; _p0 is the government environmental subsidy per unit of distributed generation; _PC is the economic cost of source, grid, load and storage;

In order to further evaluate the economic benefits of the coordinated evolution of source, grid, load and storage in the new distribution network, the carbon emission reduction efficiency contribution factor is reconstructed as shown in the formula:

In the formula, VE is the carbon emission benefit;

Therefore, a carbon emission benefit evaluation model with the minimum carbon emission cost as the goal is constructed, and its objective function and constraints are shown as follows:

；

;

In the formula, _PFmin and _PFmax represent the lower and upper limits of power generation respectively; _PCmin and _PCmax represent the lower and upper limits of energy storage respectively; _Smax represents the power flow margin of the transmission line.

Furthermore, the evaluation co-evolution in step S4 includes co-evolution in the development period, co-evolution in the metamorphosis period and co-evolution in the intelligence integration period.

Among them, in order to verify the consistency between the new distribution network co-evolution path and the change of carbon emission intensity, the present invention sets 14 user entities participating in the co-evolution of the distribution network from 4 aspects, including policy-making entities, policy regulatory entities, financial institutions, international organizations, public behavior entities, power generation companies, power transmission and distribution companies, residential users, industrial users, scientific research institutions, technology production entities, large-scale renewable energy power generation users, energy storage end users, and distributed renewable energy power generation users from the perspective of government, civil society, market, and technology;

Based on the relevant data and policies of the distribution network over the years, the correlation matrix of each stage of the distribution network co-evolution is established, so as to construct the correlation diagram of the corresponding evolution stage. According to the correlation diagram, the changes in the entropy values of the evolution participants and the overall distribution network at each stage and each evolution level are compared, and the evolutionary coordination degree of the distribution network at each stage is comprehensively evaluated. Based on the analysis results of the evolutionary coordination degree, the law of the distribution network co-evolution is revealed.

As shown in Figure 3, in the development period, the evolutionary synergy entropy values at the technical level are all negative, and the degree of negative value is relatively low. This indirectly shows that although the influence of scientific and technological research and development exists, the influence is relatively weak, the evolutionary subject from the technical perspective has not yet fully developed, and the number of evolutionary participants and the ability of synergy evolution are relatively small. In the synergy evolution development period, the evolutionary synergy entropy value of the overall distribution network is about 0.04, which is in the positive entropy range. The entropy values of government factors and technical factors are both negative, and civil society factors and enterprise factors have higher positive entropy values. Combined with the development status at that time, it can be seen that the government has a strong dominant influence and guides the evolution direction of the overall distribution network. Therefore, the entropy value of government factors is negative, and the negative entropy value is relatively large; The development of technical factors has just started, the influence of scientific and technological research and development factors is very weak, there are fewer evolutionary participants, and the collaborative evolution capabilities of each participant are also weak, because the matching degree between the technical layer and the overall system has not yet been demonstrated, so the evolutionary synergy entropy value of the overall technical factors is negative, but the value is very small; civil society factors and enterprise factors are in a larger positive entropy range, and the influence of public society and market-driven influence is relatively low, but the network evolution status of the power generation end, transmission and distribution end, and power consumption end under the government's monopoly management is very high, so the evolutionary synergy entropy values of each evolutionary participant of civil society factors and enterprise factors are all positive, which also proves that the original distribution network system is very stable;

According to the entropy value of each evolution subject, the entropy value of each level and the entropy value change of the overall distribution network, the evolution effect of China's distribution network in the non-cooperative evolution stage is depicted, as shown in the figure: from the perspective of evolution participants, the negative entropy value of policy makers and policy supervision is the largest, which also verifies that the government-led influence is the main driving force of cooperative evolution; the entropy values of the power generation end, the transmission and distribution end and the two power consumption ends are all 0.08, which not only proves that the influence of market driving force and civil society influence is very low, but also proves that under the background of monopoly operation of distribution network, the cooperative evolution ability of each evolution participant is weak, they only maintain their own system functions and do not participate in the update of other evolution functions; the evolutionary cooperative entropy values of scientific research institutions and innovative technology suppliers are all negative, and the negative value is relatively low, which indirectly shows that although the influence of scientific and technological research and development exists, the influence is relatively weak, the evolution subject of technical factors has not yet fully developed, and the number of evolution participants and the ability of cooperative evolution are relatively small;

As shown in Figure 4, in the co-evolution stage of the transformation period, the evolutionary synergy entropy value of the overall distribution network is about 0.05, which is in the positive entropy range and greater than the co-evolution development stage. The entropy value of the government factor remains negative, which is also slightly greater than the uncoordinated evolution stage. This proves that the pressure of the policy continues to increase, and the influence of the government's leading influence still occupies a dominant position; the entropy value of the technical factor becomes 0. At this stage, not only two micro-niche evolution participants are added, but these two new evolution participants also have higher positive entropy values. The change in the entropy value of the technical factor proves that the influence of the scientific and technological research and development factor has increased compared with the previous stage, but the matching degree between the new evolution participants and the overall system is not high, and their own co-evolution ability is not strong; the evolutionary synergy entropy value of each evolution participant in the civil society factor and the enterprise factor is still positive, but the positive entropy degree has decreased. The influence of civil society is still weak, but the market-driven influence has been enhanced under the promotion of the electricity reform policy;

From the perspective of evolutionary subjects, the negative entropy value of government policymakers has slightly decreased, but the positive entropy value of financial institutions has decreased significantly, which shows that the ability of financial institutions to coordinate evolution has gradually increased. The combined changes of the two have led to a further increase in the negative entropy value of government factors, which also proves that the government's leading influence is still the main force guiding the evolution of the distribution network; the entropy values of the power generation end, the transmission and distribution end, and the two power consumption ends are still positive, but the values have decreased slightly, which proves that under the policy drive, the effect of market driving force has been strengthened, but the influence of civil society is still relatively low. The changes in the entropy values of these four evolutionary subjects also prove that It is clear that their co-evolution capabilities have increased, especially with the addition of some new functions of smart distribution networks. However, they still need to strengthen their own capabilities to achieve co-evolution. The evolutionary synergy entropy values of scientific research institutions and innovative technology suppliers have increased and decreased compared with the previous stage, and the overall entropy value has decreased, which proves that the co-evolution capability of innovative technology suppliers has increased, and the influence of scientific and technological research and development factors has increased. However, the entropy values of the two newly-added evolutionary entities: renewable energy power generation groups and energy storage facilities are both positive, which shows that the integration of the newly-added evolutionary entities with the distribution network is poor, and their co-evolution capability is also low.

As shown in Figure 5, in the collaborative evolution stage of the intelligent integration period, the evolutionary collaborative entropy value of the overall distribution network is -0.154, and the entropy value enters the negative entropy range. The system evolution has also entered a relatively collaborative stage. The entropy value of the government factor continues to decrease, and the pressure of the macro environment on the overall system continues to increase, but the influence of the government's leading influence has slightly decreased; the entropy value of the technical factor has dropped below -0.1, and a new niche has been added - distributed renewable energy power generation devices. The change in the entropy value of the technical factor proves that the influence of the scientific and technological research and development factor continues to increase; the evolutionary collaborative entropy value of each evolutionary subject in the civil society factor and the enterprise factor is still positive, but the positive entropy degree continues to decline. At the same time, the influence of civil society has begun to increase, and the influence of market-driven has also begun to increase. Under the influence of these two influencing factors, the meso-system of the overall distribution network tends to be open and flexible;

From the perspective of evolutionary subjects, the negative entropy value of government policymakers continued to decline, but the entropy value of financial institutions changed from positive to negative. It can be seen that the newly added system functions of financial institutions have effectively improved their co-evolution capabilities, and the public influence has gradually increased. This behavior has led to an increase in the role of civil society; the entropy values of the power generation end, the transmission and distribution end, and the residential power consumption end are still positive, and the values continue to decline. However, the entropy value of the industrial power supply end has increased, which proves that under the influence of market-driven factors, the increase in system functions at the power consumption end has affected its co-evolution capabilities; the co-evolution entropy value of scientific research institutions has changed slightly, the evolutionary co-entropy value of innovative technology suppliers has become 0, the entropy value of the newly added distributed renewable energy power generation end is positive, and the niche entropy value entering the system in the previous stage has become negative. This change proves that the influence of scientific and technological research and development has promoted the coordinated development of technology participants.

Specifically, the present invention firstly emphasizes the coordination and integration of each other through the final state of the coordinated evolution of "source, grid, load and storage", ensures the real-time transmission of power information, and forms a real-time, safe and stable power production, transportation and use mode. Only when each participating subject reaches the coordinated evolution state can the ultimate goal of "source-grid-load-storage" integration be achieved. At the same time, the coordinated evolution effect of the overall distribution network is measured, and the evolution characteristics of each evolution stage in the evolution process are sought. The dissipation theory and the Brussels model are adopted to propose the distribution network evolution coordinated entropy index, and the original Brussels model is paraphrased. To calculate the evolutionary coordinated entropy, it is first necessary to define the total amount of information entropy, and secondly, based on the Brussels model, the total amount of information entropy is required to be defined. The model structure calculates the total number of associated paths of the coordinated evolution of the distribution network. Then, based on the entropy weight method, the number of positive and negative paths of the coordinated evolution participants is calculated. Finally, according to the relationship between probability and Shannon entropy function, the evolutionary coordinated entropy of the distribution network is calculated. A carbon emission intensity assessment model is constructed from four aspects: distributed generation, transmission lines, loads, and energy storage. The carbon emissions are assessed. The present invention can accurately assess and analyze each stage of distribution network evolution, provide an effective way for each participant in the evolution, and promote the construction of a new distribution network. At the same time, through the carbon emission intensity model and the economic model, it can reflect the carbon emissions in the coordinated evolution of the distribution network, promote carbon emission reduction, and improve carbon emission benefits.

Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims (8)

1. The novel distribution network co-evolution method based on evolution co-entropy, is characterized in that, comprises the following steps: S1: First, combine the development goals and main tasks of the new distribution network to divide the main stages of the collaborative evolution of the new distribution network; S2: Then, from the perspective of source-network-load-storage, the evolution path of source-network-load-storage is proposed; S3: Construct the evolutionary synergy entropy for evaluating the synergy between source, network, load and storage, and use Shannon theory to process the evolutionary synergy entropy into data; S4: Use the carbon emission intensity model and the carbon emission economic benefit model to evaluate the benefits of co-evolution for carbon emission reduction. 2. The new distribution network collaborative evolution method based on evolutionary synergy entropy according to claim 1, characterized in that, the evolution stages of the new distribution network in the step S1 include the development period, the metamorphosis period and the intelligent integration period. a core feature. 3. The new distribution network collaborative evolution method based on evolution synergy entropy according to claim 2, characterized in that, the distribution network in the development period mainly relies on large units and large power grids to provide electric energy input, and carries a certain proportion of possible Renewable energy, the development stage relies on the UHV AC-DC transmission and the coordinated and strong transmission mode of AC power of various voltage levels to realize the optimal allocation of resources in a wide range of distribution networks; The metamorphosis period is the stage of realizing the friendly access of renewable power sources with a high penetration rate, having a certain proportion of load-side response capabilities, and the stage of artificial intelligence in the distribution network; The intelligent financing period is the perfect and mature stage of the future distribution network, and the AC and DC hybrid distribution network will be fully completed to achieve carbon neutrality. 4. The novel distribution network collaborative evolution method based on evolution synergy entropy according to claim 3, characterized in that, in the step S2, the new distribution network collaborative evolution path is "source-network-load-storage" integration The collaborative development evolution path is used to ensure the real-time transmission of power information and form a real-time, safe and stable power production, transportation and use mode; The integrated coordinated development evolution path of "source-network-load-storage" also includes: The path of co-evolution between "source-source"; The path of co-evolution between "source-network"; Co-evolution path between "network-network"; Co-evolution path between "storage-network"; The co-evolutionary path between "He-He". 5. The novel distribution network collaborative evolution method based on evolution synergy entropy according to claim 4, characterized in that, the evolution synergy entropy in the step S3 is specifically to construct an effective index for measuring the overall distribution network Co-evolution effect, looking for the evolution characteristics of each evolution stage in the evolution process, and using the dissipation theory and the Brussels model, put forward the co-entropy index of distribution network evolution, and then escape the original Brussels model, that is, A, B, D The meanings represented by , E, X, and Y are transformed into related concepts of distribution network co-evolution. 6. The novel distribution network co-evolution method based on evolution co-entropy according to claim 5, characterized in that, in the step S3, performing data processing on the co-entropy evolution comprises the following steps: S31: First of all, to calculate the evolutionary collaborative entropy, it is first necessary to define the total amount of information entropy; S32: Secondly, based on the structure of the Brussels model, calculate the total number of associated paths of the co-evolution of the distribution network; S33: Then, calculate the number of positive and negative paths of co-evolution participants based on the entropy weight method; S34: Finally, calculate the evolution synergy entropy of the distribution network according to the relationship between the probability and the Shannon entropy function. 7. The novel distribution network co-evolution method based on evolution co-entropy according to claim 6, characterized in that the carbon emission intensity assessment model in the step S4 includes distributed generation, transmission lines, loads and energy storage Four aspects are evaluated; The carbon emission economic benefit model in the step S4 includes constructing a carbon economic benefit assessment model from four aspects: carbon emission cost, electric energy benefit, low-carbon benefit contribution rate factor and carbon emission compensation time. 8. The new distribution network co-evolution method based on evolution co-entropy according to claim 7, characterized in that the co-evolution evaluation in the step S4 includes co-evolution in the development period, co-evolution in the metamorphosis period and co-evolution in the intelligent integration period evolution.

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