A method and system for coordinated control of power grid considering distributed sources and loads

Abstract

The present invention belongs to the technical field of electric power dispatching, and specifically relates to a method and system for coordinated control of a power grid taking into account distributed sources and loads, comprising: obtaining the output power and load power of distributed power sources; constructing a two-dimensional cloud model of the dynamic evolution process of distributed source-load energy interaction based on the acquired power; calculating the power transfer probability of the distributed source-load energy interaction process based on the constructed two-dimensional cloud model; constructing a distributed source-load interaction aggregation model based on the acquired power and the power transfer probability; and performing coordinated control of the power grid based on the constructed distributed source-load interaction aggregation model to achieve coordinated control of the power grid taking into account distributed sources and loads.

Description

Technical Field

[0001] The present invention belongs to the technical field of power dispatching, and specifically relates to a power grid coordinated control method and system considering distributed sources and loads. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] In the face of energy shortages and the pressure of energy conservation and emission reduction, building a clean, reliable, interactive and efficient smart grid has become an important means to promote economic transformation and develop a low-carbon economy. The construction of smart grids with distributed sources and loads is particularly critical, and its research work on grid connection standards, energy efficiency interaction mechanisms and coordinated control has received widespread attention.

[0004] According to the inventors' understanding, relevant studies have proposed a global optimization algorithm for active distribution networks based on optimal power flow and a regional autonomous control algorithm for active distribution networks based on power control errors, ensuring their effectiveness in real-time scheduling of active distribution networks; relevant scholars have improved the voltage and frequency regulation performance of power grids by studying distributed control strategies for distributed power source access in different microgrid scenarios; research on decentralized control based on a combination of voltage controllers and fast current controllers can achieve fast tracking, robustness and fast transient recovery functions of power grids; relevant scholars have also studied the impact of distributed power sources on distribution network operation and corresponding strategies from the aspects of cooperative game theory and power flow characteristics; however, existing relevant research usually focuses on the coordinated control of distributed power sources connected to the grid, and there is little research on coordinated control of power grids considering multi-dimensional interactions of distributed sources and loads. Summary of the invention

[0005] To solve the above problems, the present invention proposes a grid collaborative control method and system taking into account distributed sources and loads. From the perspective of uncertainty in the output power of distributed power sources and the load level of the distribution network, the distributed sources and loads participating in the grid interaction are improved by combining a two-dimensional cloud model and a restraint control algorithm to achieve large-scale high-density distributed sources and loads participating in the interactive coordination of the grid.

[0006] According to some embodiments, a first solution of the present invention provides a method for coordinated control of a power grid considering distributed sources and loads, which adopts the following technical solutions:

[0007] A method for coordinated control of a power grid considering distributed sources and loads, comprising:

[0008] Obtain the output power and load power of distributed power sources;

[0009] A two-dimensional cloud model of the dynamic evolution of distributed source and energy interaction is constructed based on the acquired power;

[0010] The power transfer probability of the distributed source-load energy interaction process is calculated based on the constructed two-dimensional cloud model;

[0011] Combining the acquired power and power transfer probability, a distributed source-load interaction aggregation model is constructed;

[0012] Based on the constructed distributed source-load interactive aggregation model, the coordinated control of the power grid is carried out to realize the coordinated control of the power grid taking the distributed source-load into consideration.

[0013] As a further technical limitation, the constructed distributed source-load interaction aggregation model is: Among them, a ij is the element of the active power dynamic transfer matrix, that is, the active power transfer probability of the jth small interval in the i-th large interval, x l (k,i) and x l (k+1,i) represents the load power in the i-th interval at time k and time k+1 respectively; P ij is the active power transfer probability; v c (k,i) represents the power change in the i-th interval caused by external factors at time k.

[0014] As a further technical limitation, a double-layer nested discretization process is performed on the distributed power-load cluster, that is, the distributed power-load cluster is discretized into N large state intervals and then further subdivided into n small state intervals, and the power transfer probability cloud model of the distributed source-energy interaction process is obtained, namely: Among them, P (i,j)→i+1 (k) represents the probability of active power in the power-load cluster transferring from the jth small interval of the i-th large interval to the i+1th large interval at time k; Indicates the lower boundary value of the distributed power output power of the i+1th large interval; represents the lower boundary value of the output power of the distributed power generation in the jth small area in the ith large area; according to the characteristics of the cloud model, the load power obeys a certain probability density distribution f(P l );P lmax and P lmin They are the upper and lower limits of the adjustable load power respectively.

[0015] Furthermore, the power transfer probability P i,i+1 (k) Among them, n0 and n1 are P g0 (i) and P g1 (i) The number of the small interval corresponding to the i-th large interval.

[0016] As a further technical definition, the cloud model vector of the output power of distributed power generation and load power composed of expectation, entropy and super entropy, and the two-dimensional cloud model of the dynamic evolution process of distributed source and energy interaction are: Among them, (P g ,P l ) represents the two-dimensional cloud model vector of the distributed source-i; is the first-order absolute center distance of the distributed power output power, that is, the expectation, is the first-order absolute center distance of the load power, i.e., the expectation; E g is the entropy of the distributed power output, E l is the entropy of load power; H g is the super entropy of the distributed power output, H l is the excess entropy of the load power.

[0017] As a further technical limitation, the process of coordinated control of the power grid based on the constructed distributed source-load interaction aggregation model is as follows: Where D = diag[d1,…,d N ] is the load frequency characteristic of the control area; H is the equivalent area inertia; R i Indicates the speed reduction characteristic; ΔP li is the active power of distributed load; represents the active operating power of the jth load aggregator; ΔP L is the mismatched active power in the control area; ΔP gi is the active power output of the distributed power supply; ΔP ci is the active power of the control area; T ti and T gi are the operating moments of the governor and turbine, respectively.

[0018] As a further technical limitation, according to the forward cloud model algorithm and the obtained distributed power output power and load power, the cloud model vectors of the distributed power output power and the load power are obtained respectively; combined with the obtained cloud model vectors, the two-dimensional cloud model of the distributed source and load is obtained, (P g , P l )Right now

[0019]

[0020] Among them, (P g , P l ) represents a two-dimensional cloud model of distributed sources-he; is the first-order absolute center distance of the distributed power output power, that is, the expectation, is the first-order absolute center distance of the load power, i.e., the expectation; Eg is the entropy of the distributed power output, E l is the entropy of load power; H g is the super entropy of the distributed power output, H l is the excess entropy of the load power.

[0021] According to some embodiments, a second solution of the present invention provides a power grid coordinated control system considering distributed sources and loads, adopting the following technical solutions:

[0022] A power grid coordinated control system considering distributed sources and loads, comprising:

[0023] An acquisition module, configured to acquire output power and load power of a distributed power source;

[0024] An analysis module configured to construct a two-dimensional cloud model of a dynamic evolution process of distributed source and energy interaction based on the acquired power;

[0025] A calculation module, which is configured to calculate the power transfer probability of the distributed source-load energy interaction process according to the constructed two-dimensional cloud model;

[0026] a modeling module configured to construct a distributed source-load interaction aggregation model by combining the acquired power and the power transfer probability;

[0027] The control module is configured to perform coordinated control of the power grid based on the constructed distributed source-load interactive aggregation model, thereby realizing coordinated control of the power grid taking into account the distributed source-load.

[0028] According to some embodiments, a third solution of the present invention provides a computer-readable storage medium, which adopts the following technical solution:

[0029] A computer-readable storage medium stores a program thereon, which, when executed by a processor, implements the steps of the power grid coordinated control method considering distributed sources and loads as described in the first solution of the present invention.

[0030] According to some embodiments, a fourth solution of the present invention provides an electronic device, which adopts the following technical solution:

[0031] An electronic device comprises a memory, a processor and a program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps in the method for coordinated control of a power grid taking into account distributed sources and loads as described in the first solution of the present invention are implemented.

[0032] Compared with the prior art, the present invention has the following beneficial effects:

[0033] Starting from the uncertainty of distributed power output power and distribution network load level, the present invention adopts a forward cloud model to generate cloud model vectors representing the uncertain characteristics of distributed power output power and load power in the source-load interaction process, and comprehensively considers the uncertainty and fuzziness of the real-time load power.

[0034] The present invention quantitatively analyzes the dynamic evolution process of distributed source-load energy interaction, derives the expected active power transfer probability during the dynamic evolution process, constructs an intelligent grid energy efficiency interaction mechanism and energy regulation strategy including distributed sources and loads, and improves the efficiency of energy flow between distributed power sources and distributed controllable loads and the potential for participating in grid interaction.

[0035] The present invention takes into account the uncertainty of energy flow in the process of distributed source-load interaction. On the basis of improving the traditional automatic power generation control framework based on centralized proportional integral, a control method for distributed source-load interaction based on distributed control algorithm is constructed, which reduces the regulation pressure of the AGC system and improves the stability of power system operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The drawings in the specification that constitute a part of this embodiment are used to provide a further understanding of this embodiment. The schematic embodiments of this embodiment and their descriptions are used to explain this embodiment and do not constitute improper limitations on this embodiment.

[0037] Figure 1 This is a flow chart of a method for coordinated control of a power grid taking into account distributed sources and loads in Embodiment 1 of the present invention;

[0038] Figure 2 This is a structural block diagram of a power grid coordinated control system considering distributed sources and loads in the second embodiment of the present invention. DETAILED DESCRIPTION

[0039] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0040] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present application belongs.

[0041] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0042] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0043] Embodiment 1

[0044] Embodiment 1 of the present invention introduces a method for coordinated control of a power grid taking into account distributed sources and loads.

[0045] like Figure 1 A power grid coordinated control method considering distributed sources and loads is shown, comprising:

[0046] Obtain the output power and load power of distributed power sources;

[0047] A two-dimensional cloud model of the dynamic evolution of distributed source and energy interaction is constructed based on the acquired power;

[0048] The power transfer probability of the distributed source-load energy interaction process is calculated based on the constructed two-dimensional cloud model;

[0049] Combining the acquired power and power transfer probability, a distributed source-load interaction aggregation model is constructed;

[0050] Based on the constructed distributed source-load interactive aggregation model, the coordinated control of the power grid is carried out to realize the coordinated control of the power grid taking the distributed source-load into consideration.

[0051] This embodiment starts from the perspective of the uncertainty of distributed power output power and distribution network load level, constructs a two-dimensional cloud model of the dynamic evolution process of distributed source energy interaction, derives the expected active power transfer probability, and constructs a distributed source interaction aggregation model based on the cloud model; combined with the distributed source interaction aggregation model based on the cloud model, the traditional automatic power generation control framework based on centralized proportional integral is improved, and the coordinated control of distributed sources participating in the power grid based on the containment control algorithm is realized.

[0052] As one or more implementation methods, according to the basic cloud model algorithm, cloud model vectors composed of expectation, entropy and super entropy of distributed power output power and load power are obtained respectively, and the two-dimensional cloud model construction process of the dynamic evolution process of distributed source and energy interaction is as follows:

[0053]

[0054] Among them, (P g ,P l ) represents the two-dimensional cloud model vector of the distributed source-i; is the first-order absolute center distance of the distributed power output power, that is, the expectation, is the first-order absolute center distance of the load power, i.e., the expectation; E g is the entropy of the distributed power output, El is the entropy of load power; H g is the super entropy of the distributed power output, H l is the excess entropy of the load power.

[0055] As one or more implementation modes, the expected active power transfer probability specifically includes:

[0056] A double-layer nested discretization process is performed on the distributed power-load cluster, that is, the distributed power-load cluster is discretized into N large state intervals and then further subdivided into n small state intervals, and the power transfer probability cloud model description of the distributed source-energy interaction process is obtained:

[0057]

[0058] Among them, P (i,j)→i+1 (k) represents the probability of active power in the power-load cluster transferring from the jth small interval of the i-th large interval to the i+1th large interval at time k; Indicates the lower boundary value of the distributed power output power of the i+1th large interval; represents the lower boundary value of the output power of the distributed power generation in the jth small area in the ith large area; according to the characteristics of the cloud model, it can be known that the load power obeys a certain probability density distribution f(P l );P lmax and P lmin are the upper and lower limits of the adjustable load power respectively;

[0059] Since the i-th large interval is divided into n small intervals, the expected transition probability P i,i+1 (k) is:

[0060]

[0061] Where: n0 and n1 are P g0 (i) and P g1 (i) The number of the small interval corresponding to the i-th large interval.

[0062] As one or more implementation modes, the distributed source-interaction aggregation model based on the cloud model is constructed as follows:

[0063]

[0064] Among them, a ij is the element of the active power dynamic transfer matrix, i.e., the active power transfer probability of the jth small interval in the i-th large interval; x l (k,i) and x l (k+1,i) represents the load power in the i-th interval at time k and time k+1 respectively; P ijis the active power transfer probability; v c (k,i) represents the power change in the i-th interval caused by external factors at time k;

[0065] The distributed source-to-source interaction aggregation model expressed in N-dimensional linear state space is simplified as follows:

[0066]

[0067] Among them, x l (k) = [x l (k,1),x l (k,2),…,x l (k,N)] T , is an N-dimensional column vector; v l (k) is an N-dimensional column vector with the same structure; y(k) represents the output power of the distributed power-load cluster at time k; C is the output matrix, which is an N-dimensional unit row vector; A l is the state matrix.

[0068] The improved traditional automatic power generation control framework based on centralized proportional integral in this embodiment has a specific theoretical explanation as follows: the generator set is controlled by a traditional centralized control strategy, the distributed power source-load cluster is controlled by a cloud control algorithm, and the power mismatch is shared by the AGC unit and the distributed power source-load cluster.

[0069] In this embodiment, the process of distributed sources participating in the coordinated control of the power grid based on the pinning control algorithm is as follows:

[0070]

[0071] Where D = diag[d1,…,d N ] is the load frequency characteristic of the control area; H is the equivalent area inertia; R i Indicates the speed reduction characteristic; ΔP li is the active power of distributed load; represents the active operating power of the jth load aggregator, ΔP L is the mismatched active power in the control area; ΔP gi is the active power output of the distributed power source, N is the total time; ΔP ci is the active power of the control area; T ti and T gi are the operating moments of the governor and turbine, respectively.

[0072] The state space model of the frequency modulation control system is simplified, and the coordinated control of the power grid is achieved by adjusting the load frequency. The obtained state space model is:

[0073]

[0074] Where x = (ΔP g1 ,…ΔP gi ,ΔP m1 ,…,ΔP mi ,Δf) T ,ΔP c =(ΔP c1 ,…,ΔP ci ) T ; A, B, C, and E are the coefficient matrices of the model respectively.

[0075] This embodiment starts from the perspective of the uncertainty of distributed power output power and distribution network load level, and adopts a forward cloud model to generate cloud model vectors representing the uncertain characteristics of distributed power output power and load power in the process of source-load interaction, taking into account the uncertainty and fuzziness of the real-time load power; quantitatively analyzes the dynamic evolution process of distributed source-load energy interaction, and derives the expected active power transfer probability in the dynamic evolution process, constructs an energy efficiency interaction mechanism and energy regulation strategy for smart grids including distributed sources and loads, improves the efficiency of energy flow between distributed power sources and distributed controllable loads and the potential for participating in grid interaction; considering the uncertainty of energy flow in the process of distributed source-load interaction, on the basis of improving the traditional automatic power generation control framework based on centralized proportional integral, a control method for distributed sources and loads participating in grid interaction based on a distributed containment control algorithm is constructed, which reduces the regulation pressure of the AGC system and improves the stability of power system operation.

[0076] Embodiment 2

[0077] Embodiment 2 of the present invention introduces a power grid coordinated control system taking distributed sources and loads into consideration.

[0078] like Figure 2 A power grid coordinated control system considering distributed sources and loads is shown, comprising:

[0079] An acquisition module, configured to acquire output power and load power of a distributed power source;

[0080] An analysis module configured to construct a two-dimensional cloud model of a dynamic evolution process of distributed source and energy interaction based on the acquired power;

[0081] A calculation module, which is configured to calculate the power transfer probability of the distributed source-load energy interaction process according to the constructed two-dimensional cloud model;

[0082] a modeling module configured to construct a distributed source-load interaction aggregation model by combining the acquired power and the power transfer probability;

[0083] The control module is configured to perform coordinated control of the power grid based on the constructed distributed source-load interactive aggregation model, thereby realizing coordinated control of the power grid taking into account the distributed source-load.

[0084] The detailed steps are the same as those of the grid coordinated control method considering distributed sources and loads provided in Example 1, and will not be repeated here.

[0085] Embodiment 3

[0086] Embodiment 3 of the present invention provides a computer-readable storage medium.

[0087] A computer-readable storage medium stores a program thereon, which, when executed by a processor, implements the steps of the power grid coordinated control method considering distributed sources and loads as described in the first embodiment of the present invention.

[0088] The detailed steps are the same as those of the grid coordinated control method considering distributed sources and loads provided in Example 1, and will not be repeated here.

[0089] Embodiment 4

[0090] A fourth embodiment of the present invention provides an electronic device.

[0091] An electronic device comprises a memory, a processor and a program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps in the method for coordinated control of a power grid taking into account distributed sources and loads as described in the first embodiment of the present invention are implemented.

[0092] The detailed steps are the same as those of the grid coordinated control method considering distributed sources and loads provided in Example 1, and will not be repeated here.

[0093] The above description is only a preferred embodiment of the present embodiment and is not intended to limit the present embodiment. For those skilled in the art, the present embodiment may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present embodiment shall be included in the protection scope of the present embodiment.

Claims

1. A method for coordinated control of a power grid considering distributed sources and loads, characterized in that: include: Obtain the output power and load power of distributed power sources; A two-dimensional cloud model of the dynamic evolution of distributed source and energy interaction is constructed based on the acquired power; The power transfer probability of the distributed source-load energy interaction process is calculated based on the constructed two-dimensional cloud model; Combining the acquired power and power transfer probability, a distributed source-load interaction aggregation model is constructed; Based on the constructed distributed source-load interactive aggregation model, the coordinated control of the power grid is carried out to realize the coordinated control of the power grid considering the distributed source-load; The distributed power-load cluster is discretized into two layers: N The large state interval is further divided into n A small state interval is obtained to obtain the power transfer probability cloud model of the distributed source and energy interaction process. in, Expressed as k At this moment, the active power in the power-load cluster changes from i The first j The small area to the i +1 large interval transition probability; Indicates i +1 large interval of lower boundary value of distributed power output power; Indicates i The first j The lower boundary value of the distributed power output power between cells; According to the characteristics of the cloud model, the load power obeys a certain probability density distribution ; and are the upper and lower limits of the adjustable load power respectively; The power transfer probability for ;in, , They are and In the i The number of the small interval corresponding to the large interval.

2. A method for coordinated control of a power grid considering distributed sources and loads as claimed in claim 1, characterized in that: The constructed distributed source-load interaction aggregation model is: in, is the element of the active power dynamic transfer matrix, that is, i The first j The probability of active power transfer between cells is and denote the k moment and k +1 moment i Load power within a range; is the active power transfer probability; express k The external factors caused the i The power variation in the interval.

3. A method for coordinated control of a power grid considering distributed sources and loads as claimed in claim 1, characterized in that: The cloud model vector of the output power of distributed power sources and load power is composed of expectation, entropy and super entropy. The two-dimensional cloud model of the dynamic evolution process of distributed source and energy interaction is: ;in, A two-dimensional cloud model vector representing the distributed source - i; is the first-order absolute center distance of the distributed power output power, that is, the expectation, is the first-order absolute center distance of the load power, i.e., the expectation; is the entropy of the distributed power output, is the entropy of load power; is the super entropy of the distributed power output power, is the excess entropy of the load power.

4. A method for coordinated control of a power grid considering distributed sources and loads as claimed in claim 1, characterized in that: The process of coordinated control of the power grid based on the constructed distributed source-load interactive aggregation model is as follows: in, is the load frequency characteristic of the control area; H is the equivalent area inertia; Indicates the speed reduction characteristic; is the active power of distributed load; represents the active operating power of the jth load aggregator; is the mismatched active power in the control area; is the active power output by the distributed power source; is the active power of the control area; and are the operating moments of the governor and turbine, respectively.

5. A method for coordinated control of a power grid considering distributed sources and loads as claimed in claim 1, characterized in that: According to the forward cloud model algorithm and the obtained distributed power output power and load power, the cloud model vectors of the distributed power output power and load power are obtained respectively; combined with the obtained cloud model vectors, the two-dimensional cloud model of the distributed source and load is obtained. Right now in, A two-dimensional cloud model representing distributed sources-- is the first-order absolute center distance of the distributed power output power, that is, the expectation, is the first-order absolute center distance of the load power, i.e., the expectation; is the entropy of the distributed power output, is the entropy of load power; is the super entropy of the distributed power output power, is the excess entropy of the load power.

6. A power grid coordinated control system considering distributed sources and loads, characterized in that: include: An acquisition module, configured to acquire output power and load power of a distributed power source; An analysis module configured to construct a two-dimensional cloud model of a dynamic evolution process of distributed source and energy interaction based on the acquired power; A calculation module, which is configured to calculate the power transfer probability of the distributed source-load energy interaction process according to the constructed two-dimensional cloud model; a modeling module configured to construct a distributed source-load interaction aggregation model by combining the acquired power and the power transfer probability; A control module, which is configured to perform coordinated control of the power grid based on the constructed distributed source-load interactive aggregation model, so as to realize coordinated control of the power grid considering the distributed source-load; The distributed power-load cluster is discretized into two layers: N The large state interval is further divided into n A small state interval is obtained to obtain the power transfer probability cloud model of the distributed source and energy interaction process. in, Expressed as k At this moment, the active power in the power-load cluster changes from i The first j The small area to the i +1 large interval transition probability; Indicates i +1 large interval of lower boundary value of distributed power output power; Indicates i The first j The lower boundary value of the distributed power output power between cells; According to the characteristics of the cloud model, the load power obeys a certain probability density distribution ; and are the upper and lower limits of the adjustable load power respectively; The power transfer probability for ;in, , They are and In the i The number of the small interval corresponding to the large interval.

7. A power grid coordinated control system considering distributed sources and loads as claimed in claim 6, characterized in that: The constructed distributed source-load interaction aggregation model is: in, is the element of the active power dynamic transfer matrix, that is, i The first j The probability of active power transfer between cells is and denote the k moment and k +1 moment i Load power within a range; is the active power transfer probability; express k The external factors caused the i The power variation in the interval.

8. A power grid coordinated control system considering distributed sources and loads as claimed in claim 6, characterized in that: The cloud model vector of the output power of distributed power sources and load power is composed of expectation, entropy and super entropy. The two-dimensional cloud model of the dynamic evolution process of distributed source and energy interaction is: in, A two-dimensional cloud model vector representing the distributed source - i; is the first-order absolute center distance of the distributed power output power, that is, the expectation, is the first-order absolute center distance of the load power, i.e., the expectation; is the entropy of the distributed power output, is the entropy of load power; is the super entropy of the distributed power output power, is the excess entropy of the load power.

9. A power grid coordinated control system considering distributed sources and loads as claimed in claim 6, characterized in that: The process of coordinated control of the power grid based on the constructed distributed source-load interactive aggregation model is as follows: in, is the load frequency characteristic of the control area; H is the equivalent area inertia; Indicates the speed reduction characteristic; is the active power of distributed load; represents the active operating power of the jth load aggregator; is the mismatched active power in the control area; is the active power output by the distributed power source; is the active power of the control area; and are the operating moments of the governor and turbine, respectively.

10. A power grid coordinated control system considering distributed sources and loads as claimed in claim 6, characterized in that: According to the forward cloud model algorithm and the obtained distributed power output power and load power, the cloud model vectors of the distributed power output power and load power are obtained respectively; combined with the obtained cloud model vectors, the two-dimensional cloud model of the distributed source and load is obtained. Right now in, A two-dimensional cloud model representing distributed sources-- is the first-order absolute center distance of the distributed power output power, that is, the expectation, is the first-order absolute center distance of the load power, i.e., the expectation; is the entropy of the distributed power output, is the entropy of load power; is the super entropy of the distributed power output power, is the excess entropy of the load power.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the power grid coordinated control method considering distributed sources and loads as described in any one of claims 1 to 5 are implemented.

12. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the steps of the grid coordinated control method considering distributed sources and loads as described in any one of claims 1-5 are implemented.

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