Intelligent load management and control power distribution system and method for distributed photovoltaic-energy storage system

Abstract

The invention relates to the technical field of distributed photovoltaic-energy storage system management and control in an intelligent power grid, in particular to an intelligent load management and control power distribution system and method for a distributed photovoltaic-energy storage system. And the medium-voltage power distribution network sends a control instruction to a main node in each low-voltage power distribution network based on the output power of each power distribution transformer, so that the main node and a plurality of non-main nodes in the low-voltage power distribution network carry out continuous iteration updating of consistency variables based on a consistency algorithm. And enabling the main nodes and the non-main nodes in the plurality of low-voltage power distribution networks to reach a system balance state, thereby realizing intelligent load management and control of the distributed photovoltaic-energy storage system. According to the invention, the consistency among the photovoltaic power generation fluctuation, the charging and discharging state of the energy storage system and the grid-connected demand of the power grid is realized, and the problems of voltage out-of-limit and overload of the distribution transformer are avoided by using the cooperative control among the plurality of distributed photovoltaic-energy storage systems.

Description

Technical Field

[0001] The present disclosure relates to the technical field of distributed photovoltaic-energy storage system management and control in smart grids, and in particular to an intelligent load management and control distribution system and method for distributed photovoltaic-energy storage systems. Background Art

[0002] New energy is an important cornerstone for implementing the "dual carbon" strategy and ensuring energy security. At present, my country's installed capacity of new energy power generation has exceeded 1.18 billion kilowatts, accounting for 38.4% of the total installed capacity of power generation, becoming the largest power source. However, distributed new energy power generation is affected by factors such as weather and uneven temporal and spatial distribution, and is highly random, intermittent, and volatile, which has led to an increase in local imbalances in the distribution network, seriously threatening the safe and stable operation of the power grid, among which the problems of voltage over-limit and distribution transformer overload are particularly prominent. For distributed photovoltaic energy storage systems, after being connected to the grid, they may change the flow direction (current flow direction) of electric energy in the power grid, resulting in reverse flow; voltage over-limit will cause damage to power grid equipment, affect the quality of power supply, and cause power outages, causing inconvenience to social and economic activities and residents' daily lives. Summary of the invention

[0003] In order to solve the problems in the related art, the embodiments of the present disclosure provide an intelligent load control and distribution system and method for a distributed photovoltaic-energy storage system.

[0004] In a first aspect, an embodiment of the present disclosure provides an intelligent load control distribution system for a distributed photovoltaic-energy storage system, the distribution system comprising: a medium-voltage distribution network and a plurality of distribution transformers connected to the medium-voltage distribution network, the distribution transformers being connected to one or more low-voltage distribution networks, the low-voltage distribution network comprising a plurality of distributed photovoltaic-energy storage systems, one distributed photovoltaic-energy storage system in the low-voltage distribution network being a master node, and the remaining distributed photovoltaic-energy storage systems being non-master nodes;

[0005] For each of the multiple distribution transformers, the medium-voltage distribution network obtains the output power of the distribution transformer, and calculates the active power adjustment amount of each low-voltage distribution network in the multiple low-voltage distribution networks connected to the distribution transformer according to the power limit of each low-voltage distribution network and the output power, thereby sending a control instruction to the master node in each low-voltage distribution network according to the active power adjustment amount of each low-voltage distribution network;

[0006] For each low-voltage distribution network, after receiving the control instruction, the master node iteratively updates the consistency variable of the master node according to the active power regulation amount of the low-voltage distribution network; each of the multiple non-master nodes calculates the state transfer coefficient from the adjacent node to the non-master node according to the network topology structure of the low-voltage distribution network, and iteratively updates the consistency variable of the non-master node based on the state transfer coefficient and the updated consistency variable of the adjacent node; the master node and the multiple non-master nodes continuously iteratively update the corresponding consistency variables until the master node and all the non-master nodes reach a system equilibrium state, wherein the adjacent node is the master node or other non-master nodes;

[0007] For the low-voltage distribution network connected to the multiple distribution transformers, the one-time variables of the main node and all non-main nodes in the low-voltage distribution network are continuously iterated and updated until the main node and all non-main nodes in the low-voltage distribution network reach a system balance state, thereby realizing intelligent load control of the distributed photovoltaic-energy storage system.

[0008] According to an embodiment of the present disclosure, the calculating the active power regulation amount of each low-voltage distribution network in a plurality of low-voltage distribution networks connected to the distribution transformer according to the power limit of each low-voltage distribution network and the output power includes:

[0009] For each low-voltage distribution network, the medium-voltage distribution network calculates the active power adjustment amount of the low-voltage distribution network according to the maximum active power and the minimum active power of the low-voltage distribution network and the obtained output power of the distribution transformer connected to the low-voltage distribution network.

[0010] According to an embodiment of the present disclosure, the active power adjustment amount of the low-voltage distribution network is calculated according to the maximum active power and the minimum active power of the low-voltage distribution network, and the output power of the distribution transformer connected to the low-voltage distribution network, including calculating the active power adjustment amount using the following formula:

[0011]

[0012] Among them, the is the active power regulation value of the j-th low-voltage distribution network, is the output power of the distribution transformer connected to the j-th low-voltage distribution network, is the maximum active power of the j-th low-voltage distribution network, is the minimum active power of the j-th low-voltage distribution network.

[0013] According to an embodiment of the present disclosure:

[0014] In the When , the j-th low-voltage distribution network absorbs power relative to the medium-voltage distribution network;

[0015] In the When , the j-th low-voltage distribution network outputs power relative to the medium-voltage distribution network;

[0016] In the When , the j-th low-voltage distribution network is in a system balanced state.

[0017] According to an embodiment of the present disclosure, sending a control instruction to a master node in each low-voltage distribution network according to the active power adjustment amount of each low-voltage distribution network includes:

[0018] In the j-th low-voltage distribution network, or When the medium voltage distribution network sends a control instruction to the master node in the j-th low voltage distribution network, the control instruction includes an active power adjustment instruction.

[0019] According to an embodiment of the present disclosure, the master node iteratively updates the consistency variable of the master node according to the active power regulation amount of the low-voltage distribution network, including:

[0020] For any node among the master node and / or non-master node, calculate the active power adjustment amount of any node updated in the kth iteration, when the active power adjustment amount updated in the kth iteration is 0 or less than the set threshold, any node reaches the system equilibrium state, wherein when any node is the master node, k=k1, and when any node is the non-master node, k=k2.

[0021] According to an embodiment of the present disclosure, the master node performs a k1th iterative update on the consistency variable of the master node according to the consistency variable of the master node that has been iteratively updated k1-1 times and the active power adjustment amount of the low-voltage distribution network, including performing a k1th iterative update on the consistency variable of the master node according to the following formula:

[0022]

[0023] Among them, the is the consistency variable updated by the master node for the k1th iteration, is the consistency variable of the master node after k1-1 iterations of updates, where a is a convergence control parameter, 1≤k1≤K, where K is a preset maximum number of iterations.

[0024] According to an embodiment of the present disclosure, the step of calculating a state transfer coefficient from an adjacent node to the non-master node according to the network topology of the low-voltage distribution network includes:

[0025] The non-master node i+n calculates a state transfer coefficient from the adjacent node i to the non-master node i+n according to the total number of communication information received by the non-master node i+n.

[0026] According to an embodiment of the present disclosure, the non-primary node i+n calculates the state transfer coefficient from the adjacent node i to the non-primary node i+n according to the total number of communication information received by the non-primary node i+n, including calculating the state transfer coefficient from the adjacent node i to the non-primary node i+n according to the following formula:

[0027]

[0028] Among them, the d i,i+n is the state transfer coefficient from the adjacent node i to the non-primary node i+n, is the total number of communication messages received by the non-master node i+n, and b is the communication line in the low-voltage distribution network.

[0029] According to an embodiment of the present disclosure, the iterative updating of the consistency variables of the non-primary nodes based on the state transfer coefficient and the updated consistency variables of the adjacent nodes includes performing a k2-th iterative update of the consistency variables of the non-primary nodes according to the following formula:

[0030] u i+n,t (k2) = ∑ i+n∈c d i,i+n u i,t (k2-1);

[0031] Among them, the u i+n,t (k2) is the consistency variable after the non-primary node i+n performs the k2th iteration update, and u i,t (k2-1) is the consistency variable after the adjacent node i is iteratively updated k2-1 times, c is the set of nodes in the low-voltage distribution network, 1≤k2≤K, and K is the preset maximum number of iterations.

[0032] According to an embodiment of the present disclosure, the master node and all non-master nodes reach a system balance state, including:

[0033] For any node among the master node and / or non-master node, calculate the active power adjustment amount of any node updated in the kth iteration, when the active power adjustment amount updated in the kth iteration is 0 or less than the set threshold, any node reaches the system equilibrium state, wherein when any node is the master node, k=k1, and when any node is the non-master node, k=k2.

[0034] According to an embodiment of the present disclosure, the consistency variables of the master node and / or non-master node are related to the charging and discharging status of the corresponding master node and / or non-master node, the output power of photovoltaic power generation and the change in power grid power demand.

[0035] According to an embodiment of the present disclosure, the system further comprises: a power measurement device;

[0036] The power measuring device is arranged between the low voltage power distribution network and the distribution transformer, so as to measure the output power of the distribution transformer.

[0037] According to an embodiment of the present disclosure, the master node is a distributed photovoltaic-energy storage system in the low-voltage distribution network that is closest to a distribution transformer connected to the low-voltage distribution network.

[0038] In a second aspect, an embodiment of the present disclosure provides an intelligent load control method for a distributed photovoltaic-energy storage system, wherein the distributed photovoltaic-energy storage system is arranged in a power distribution system, wherein the power distribution system comprises: a medium-voltage distribution network and a plurality of distribution transformers connected to the medium-voltage distribution network, wherein the distribution transformers are connected to one or more low-voltage distribution networks, wherein the low-voltage distribution network comprises a plurality of distributed photovoltaic-energy storage systems, wherein one distributed photovoltaic-energy storage system in the low-voltage distribution network is a master node and the remaining distributed photovoltaic-energy storage systems are non-master nodes; the method comprises:

[0039] For each of the multiple distribution transformers, the medium-voltage distribution network obtains the output power of the distribution transformer, and calculates the active power adjustment amount of each low-voltage distribution network in the multiple low-voltage distribution networks connected to the distribution transformer according to the power limit of each low-voltage distribution network and the output power, thereby sending a control instruction to the master node in each low-voltage distribution network according to the active power adjustment amount of each low-voltage distribution network;

[0040] For each low-voltage distribution network, after receiving the control instruction, the master node iteratively updates the consistency variable of the master node according to the active power regulation amount of the low-voltage distribution network; each of the multiple non-master nodes calculates the state transfer coefficient from the adjacent node to the non-master node according to the network topology structure of the low-voltage distribution network, and iteratively updates the consistency variable of the non-master node based on the state transfer coefficient and the updated consistency variable of the adjacent node; the master node and the multiple non-master nodes continuously iteratively update the corresponding consistency variables until the master node and all the non-master nodes reach a system equilibrium state, wherein the adjacent node is the master node or other non-master nodes;

[0041] For the multiple distribution transformers, repeat the above steps until the master node and all non-master nodes in the low-voltage distribution network connected to the multiple distribution transformers reach a system balance state, thereby realizing intelligent load control of the distributed photovoltaic-energy storage system.

[0042] In a third aspect, an embodiment of the present disclosure provides a computer-readable storage medium having computer instructions stored thereon, which, when executed by a processor, implement the method described in the second aspect.

[0043] In a fourth aspect, an embodiment of the present disclosure provides a computer program product, comprising computer instructions, which, when executed by a processor, implement the method as claimed in the second aspect.

[0044] The present disclosure uses a medium-voltage distribution network and multiple distribution transformers connected to the medium-voltage distribution network, and one or more low-voltage distribution networks connected to the distribution transformers in a distribution system to perform intelligent load control on a distributed photovoltaic-energy storage system composed of multiple distributed photovoltaic-energy storage systems included in each low-voltage distribution network; wherein the medium-voltage distribution network outputs control instructions to the master node in the low-voltage distribution network according to the output power of the distribution transformer, and the master node and each non-master node perform continuous iterative updates of consistency variables until the master node and multiple non-master nodes in the low-voltage distribution network reach a system equilibrium state, thereby realizing intelligent load control of the distributed photovoltaic-energy storage system. The present disclosure achieves consistency between photovoltaic power generation fluctuations, the charging and discharging state of the energy storage system, and the grid connection requirements of the power grid, and utilizes collaborative control between multiple distributed photovoltaic-energy storage systems to avoid voltage over-limit and distribution transformer overload problems.

[0045] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Other features, objectives and advantages of the present disclosure will become more apparent through the following detailed description of non-limiting embodiments in conjunction with the accompanying drawings. In the accompanying drawings:

[0047] Figure 1 A schematic diagram of the structure of an intelligent load control and distribution system for a distributed photovoltaic-energy storage system according to an embodiment of the present disclosure is shown;

[0048] Figure 2 A schematic diagram showing a topological structure of a master node in a low-voltage distribution network according to an embodiment of the present disclosure is shown;

[0049] Figure 3 A flow chart of an intelligent load control method for a distributed photovoltaic-energy storage system according to an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0050] Hereinafter, exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings so that those skilled in the art can easily implement them. In addition, for the sake of clarity, parts not related to the description of the exemplary embodiments are omitted in the accompanying drawings.

[0051] In the present disclosure, it should be understood that terms such as "include" or "have" are intended to indicate the presence of features, numbers, steps, behaviors, components, parts, or a combination thereof disclosed in the present specification, and are not intended to exclude the possibility that one or more other features, numbers, steps, behaviors, components, parts, or a combination thereof exist or are added.

[0052] It should also be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present disclosure may be combined with each other. The present disclosure will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0053] As mentioned above, distributed renewable energy generation is affected by factors such as weather and uneven spatial and temporal distribution, and is highly random, intermittent and volatile, which leads to the aggravation of local imbalance in the distribution network, seriously threatening the safe and stable operation of the power grid, among which the problems of voltage over-limit and distribution transformer overload are particularly prominent. After the distributed photovoltaic system is connected to the grid, it may change the flow direction of electric energy in the grid (current flow direction), resulting in reverse flow; voltage over-limit will cause damage to grid equipment, affect the power supply quality, and even cause power outages.

[0054] With the grid connection of distributed photovoltaic-energy storage systems, while bringing flexibility and power supply reliability, it also introduces some drawbacks that cannot be ignored. For example, in addition to being greatly affected by weather and time factors, the application and development of distributed photovoltaic-energy storage systems are restricted due to the limitations of energy storage technology (such as limited energy storage capacity, low energy storage efficiency, limited life of energy storage media, etc.). The access of distributed photovoltaic-energy storage systems will have a certain impact on the operation and management of the power grid, such as changes in the power grid flow direction, increased difficulty in reactive power balance, etc. The inventors found that in order to ensure the safe and stable operation of the power grid, it is necessary to strengthen the adaptability research and transformation of the power grid.

[0055] The present disclosure provides an intelligent load control distribution system for a distributed photovoltaic-energy storage system, the distribution system comprising: a medium-voltage distribution network and a plurality of distribution transformers connected to the medium-voltage distribution network, the distribution transformers being connected to one or more low-voltage distribution networks, the low-voltage distribution network comprising a plurality of distributed photovoltaic-energy storage systems, one distributed photovoltaic-energy storage system in the low-voltage distribution network being a master node, and the remaining distributed photovoltaic-energy storage systems being non-master nodes;

[0056] For each of the multiple distribution transformers, the medium-voltage distribution network obtains the output power of the distribution transformer, and calculates the active power regulation amount of each low-voltage distribution network according to the power limit of each low-voltage distribution network in the multiple low-voltage distribution networks connected to the distribution transformer and the output power, so as to send a control instruction to the master node in each low-voltage distribution network according to the active power regulation amount of each low-voltage distribution network; for each low-voltage distribution network, after receiving the control instruction, the master node iteratively updates the consistency variable of the master node according to the active power regulation amount of the low-voltage distribution network; each of the multiple non-master nodes calculates the adjacent nodes according to the network topology structure of the low-voltage distribution network. The state transfer coefficient to the non-master node is determined, and the consistency variables of the non-master nodes are iteratively updated based on the state transfer coefficient and the updated consistency variables of the adjacent nodes; the master node and the multiple non-master nodes continuously iteratively update the corresponding consistency variables until the master node and all non-master nodes reach a system equilibrium state, wherein the adjacent nodes are the master nodes or other non-master nodes; for the low-voltage distribution network connected to the multiple distribution transformers, the one-time variables of the master node and all non-master nodes in the low-voltage distribution network are continuously iteratively updated until the master node and all non-master nodes in the low-voltage distribution network reach a system equilibrium state, thereby realizing intelligent load control of the distributed photovoltaic-energy storage system.

[0057] The present invention achieves consistency among photovoltaic power generation fluctuations, the charging and discharging status of the energy storage system, and the grid connection requirements of the power grid, and utilizes collaborative control between multiple distributed photovoltaic-energy storage systems to avoid voltage over-limit and distribution transformer overload problems, thereby improving the stability of the power grid, realizing intelligent management and control of the power grid, and promoting the construction of a new power system.

[0058] Figure 1 A schematic structural diagram of an intelligent load control and distribution system for a distributed photovoltaic-energy storage system according to an embodiment of the present disclosure is shown.

[0059] The power distribution system includes: a medium-voltage distribution network and multiple distribution transformers connected to the medium-voltage distribution network, the distribution transformers are connected to one or more low-voltage distribution networks, the low-voltage distribution network includes multiple distributed photovoltaic-energy storage systems, one distributed photovoltaic-energy storage system in the low-voltage distribution network is a master node, and the remaining distributed photovoltaic-energy storage systems are non-master nodes.

[0060] In the present disclosure, the master node is the distributed photovoltaic-energy storage system in the low-voltage distribution network that is closest to the distribution transformer connected to the low-voltage distribution network. The node (distributed photovoltaic-energy storage system) closest to the distribution transformer is selected as the master node because it is easy to communicate with the node, making the monitoring and control of the power grid more convenient.

[0061] like Figure 1 As shown, assuming that the medium-voltage distribution network is connected to m distribution transformers, each distribution transformer is connected to j low-voltage distribution networks, where m>1, j≥1; then when j=1, the distribution transformer is connected to one low-voltage distribution network, and when j>1, the distribution transformer is connected to multiple low-voltage distribution networks, and the number of low-voltage distribution networks connected to each distribution transformer can be the same or different, for example, for the first distribution transformer, j=10, for the second distribution transformer, j=20, etc. Those skilled in the art can understand that the values ​​of m and j are not used as technical means to limit the scope of protection of the present disclosure.

[0062] According to an embodiment of the present disclosure, for each distribution transformer among the multiple distribution transformers, the medium-voltage distribution network obtains the output power of the distribution transformer, and calculates the active power adjustment amount of each low-voltage distribution network among the multiple low-voltage distribution networks connected to the distribution transformer according to the power limit of each low-voltage distribution network and the output power, thereby sending a control instruction to the main node in each low-voltage distribution network according to the active power adjustment amount of each low-voltage distribution network.

[0063] The medium-voltage distribution network only sends control instructions to the distributed photovoltaic-energy storage system as the master node according to the active power regulation required by each low-voltage distribution network. The master node will start to update its own consistency variables according to these instructions, and distribute the control instructions (regulation scheme) to other nodes (distributed photovoltaic-energy storage systems) through the consistency algorithm. This control method reduces the dependence on communication, simplifies the method of intelligent load control, and improves the processing speed.

[0064] Among them, for each low-voltage distribution network, the medium-voltage distribution network calculates the active power adjustment amount of the low-voltage distribution network according to the maximum active power and the minimum active power of the low-voltage distribution network, and the output power of the distribution transformer connected to the low-voltage distribution network. Specifically, the active power adjustment amount is calculated using the following formula:

[0065]

[0066] Among them, the is the active power regulation value of the j-th low-voltage distribution network, is the output power of the distribution transformer connected to the j-th low-voltage distribution network, is the maximum active power of the j-th low-voltage distribution network, is the minimum active power of the j-th low-voltage distribution network.

[0067] From the above formula, we can know that:

[0068] In the When , the j-th low-voltage distribution network absorbs power relative to the medium-voltage distribution network;

[0069] In the When , the j-th low-voltage distribution network outputs power relative to the medium-voltage distribution network;

[0070] In the When , the j-th low-voltage distribution network is in a system balanced state.

[0071] According to an embodiment of the present disclosure, in the j-th low-voltage distribution network, or When the medium voltage distribution network sends a control instruction to the master node in the j-th low voltage distribution network, the control instruction includes an active power adjustment instruction.

[0072] That is, only when the j-th low-voltage distribution network absorbs power or outputs power relative to the medium-voltage distribution network, the medium-voltage distribution network sends a control instruction to the main node in the j-th low-voltage distribution network, and when the j-th low-voltage distribution network is in a system balanced state, no control instruction is sent, that is, at this time, there is no need to perform active power regulation on the main node in the low-voltage distribution network.

[0073] According to an embodiment of the present disclosure, the system further includes: a power measurement device; the power measurement device is arranged between the medium voltage distribution network and the distribution transformer to measure the output power of the distribution transformer. The power measurement device can be a power meter, a power quality analyzer, etc.

[0074] According to an embodiment of the present disclosure, for each low-voltage distribution network, after receiving the control instruction, the master node iteratively updates the consistency variable of the master node according to the active power regulation amount of the low-voltage distribution network. The master node continuously iteratively updates its consistency variable until the master node reaches a system balance state.

[0075] The master node iteratively updates the consistency variable of the master node according to the active power regulation amount of the low-voltage distribution network, including:

[0076] The master node performs a k1th iteration update on the consistency variable of the master node according to the consistency variable of the master node that has been iteratively updated k1-1 times and the active power regulation amount of the low-voltage distribution network. Specifically, the consistency variable of the master node is iteratively updated for the k1th time according to the following formula:

[0077]

[0078] Among them, the is the consistency variable updated by the master node for the k1th iteration, The consistency variable is the one that has been iteratively updated k1-1 times by the master node, a is a convergence control parameter, 1≤k1≤K, where K is the preset maximum number of iterations, and t represents that the iterative update of the consistency variable changes dynamically over time.

[0079] Furthermore, the convergence control parameters can be set according to the response characteristics of the distributed photovoltaic-energy storage system, the accuracy requirements of the control target, and the communication cost of the power grid.

[0080] According to an embodiment of the present disclosure, for each low-voltage distribution network, after receiving the control instruction, each non-main node among the multiple non-main nodes calculates the state transfer coefficient from the adjacent node to the non-main node according to the network topology structure of the low-voltage distribution network, and iteratively updates the consistency variables of the non-main node based on the state transfer coefficient and the updated consistency variables of the adjacent nodes, wherein the multiple non-main nodes continuously iteratively update the corresponding consistency variables until all the non-main nodes reach a system equilibrium state, wherein the adjacent node is the main node or other non-main nodes.

[0081] Specifically, the non-master node continuously iterates and updates its consistency variable according to the control instruction assigned by the master node based on the consistency algorithm.

[0082] The general expression of the consensus algorithm is: i (k+1)=∑ j∈v d i,j x j (k); where x j (k) is the state variable of node i; k is the number of iterations, which is preset by the experiment; d i,j is the state transfer coefficient from node i to node j.

[0083] The state transfer coefficient from the adjacent node to the non-main node is calculated according to the network topology of the low-voltage distribution network, including: the non-main node i+n calculates the state transfer coefficient from the adjacent node i to the non-main node i+n according to the total number of communication information received by the non-main node i+n. Specifically, the state transfer coefficient from the adjacent node i to the non-main node i+n is calculated according to the following formula:

[0084]

[0085] Among them, the d i,i+n is the state transfer coefficient from the adjacent node i to the non-primary node i+n, is the total number of communication messages received by the non-master node i+n, and b is the communication line in the low-voltage distribution network.

[0086] Furthermore, the adjacent node i is a node directly connected to the non-main node i+n in the communication network, and the distance between the adjacent node i and the main node is closer than the distance between the non-main node i+n and the main node. When n=0, the adjacent node i is the main node; since the total number of communication information received by different nodes in the communication network is different, the state transfer coefficient between different non-main nodes i+n and adjacent nodes i is different.

[0087] The total amount of communication information includes power regulation commands, voltage levels, frequencies or other signals related to grid operation, etc. By calculating the state transfer coefficient between adjacent nodes based on the total amount of communication information, each node can coordinate its own behavior to respond to the global needs of the grid without centralized control.

[0088] Figure 2 A schematic diagram of a topological structure of a main node in a low-voltage distribution network according to an embodiment of the present disclosure is shown.

[0089] like Figure 2 As shown, the non-master node i+1 and the non-master node i+2 have the same adjacent node i. When calculating the state transfer coefficient from the adjacent node i to the non-master node i+1, it is necessary to calculate based on the total number of communication information received by the non-master node i+1, and when calculating the state transfer coefficient from the adjacent node i to the non-master node i+2, it is necessary to calculate based on the total number of communication information received by the non-master node i+2.

[0090] Further, the iterative updating of the consistency variables of the non-primary nodes based on the state transfer coefficient and the updated consistency variables of the adjacent nodes includes performing a k2-th iterative updating of the consistency variables of the non-primary nodes according to the following formula:

[0091] u i+n,t (k2) = ∑ i+n∈c d i,i+n u i,t (k2-1);

[0092] Among them, the u i+n,t (k2) is the consistency variable after the non-primary node i+n performs the k2th iteration update, and u i,t (k2-1) is the consistency variable after the adjacent node i is iteratively updated k2-1 times, c is the set of nodes in the low-voltage distribution network, 1≤k2≤K, and K is the preset maximum number of iterations.

[0093] According to an embodiment of the present disclosure, the consistency variables of the master node and / or non-master node are related to the charging and discharging status of the corresponding master node and / or non-master node, the output power of photovoltaic power generation and the change in power grid power demand.

[0094] For each of the master nodes and / or non-master nodes:

[0095] The charge and discharge state is represented by the ratio of the energy storage power of the node to the installed capacity of the node, specifically: Among them, P PCC,i is the energy storage power of node i, S PV,i is the installed capacity of node i.

[0096] The output power of photovoltaic power generation is not only affected by the charging and discharging state of the energy storage system, but also related to factors such as the installation angle of photovoltaic power generation, the topological position in the power system, and the intensity of solar radiation. The output power of photovoltaic power generation under the influence of the above-mentioned multiple factors is also an influencing factor that cannot be ignored for the consistency variables of the master node and / or non-master node.

[0097] The power demand change of the power grid is the ratio of the power exchanged between the node and the power grid to the rated power of the node within the time interval of two adjacent iterative updates, specifically: Among them, P ESS,i is the grid-connected power of node i, Δt is the time interval between two adjacent iterative updates, S ESS,i is the rated power of node i.

[0098] According to an embodiment of the present disclosure, the master node and all non-master nodes reach a system balance state, including:

[0099] For any node among the master node and / or non-master node, calculate the active power adjustment amount of any node updated in the kth iteration, when the active power adjustment amount updated in the kth iteration is 0 or less than the set threshold, any node reaches the system equilibrium state, wherein when any node is the master node, k=k1, and when any node is the non-master node, k=k2.

[0100] Specifically, for any one of the master node and / or non-master node, the active power adjustment amount of any one of the node i at the kth iteration is calculated according to the following formula:

[0101]

[0102] Among them, P ESS,i,t (k) is the active power regulation value of any node i in the kth iteration, u i,t (k) is the consistency variable updated by any node i in the kth iteration, S ESS,i is the rated power of any node i, S PV,i is the installed capacity of any node i, p PV,i is the photovoltaic power of any node i, S PV,i is the installed capacity of any node i.

[0103] According to an embodiment of the present disclosure, for a low-voltage distribution network connected to the multiple distribution transformers, continuous iterative update of one-time variables of the main node and all non-main nodes in the low-voltage distribution network is performed until the main node and all non-main nodes in the low-voltage distribution network reach a system balance state, thereby realizing intelligent load control of the distributed photovoltaic-energy storage system.

[0104] The present disclosure achieves consistency among photovoltaic power generation fluctuations, the charging and discharging status of the energy storage system, and the grid connection requirements, thereby maximizing the energy utilization efficiency of the entire distribution system. The coordinated control between the distributed photovoltaic-energy storage systems can more effectively balance electricity demand and supply, thereby reducing voltage fluctuations, improving the stability of the grid, avoiding voltage over-limit and distribution transformer overload problems, and further realizing intelligent management and control of the grid, promoting the rapid development of smart grids, and providing a reference basis for the access and grid connection of other new energy sources (such as wind energy and thermal energy).

[0105] Figure 3 A flow chart of a smart load control method for a distributed photovoltaic-energy storage system according to an embodiment of the present disclosure is shown. The distributed photovoltaic-energy storage system is arranged in a power distribution system, and the power distribution system comprises: a medium-voltage distribution network and a plurality of distribution transformers connected to the medium-voltage distribution network, the distribution transformers are connected to one or more low-voltage distribution networks, the low-voltage distribution network comprises a plurality of distributed photovoltaic-energy storage systems, one distributed photovoltaic-energy storage system in the low-voltage distribution network is a master node, and the remaining distributed photovoltaic-energy storage systems are non-master nodes.

[0106] like Figure 3 As shown, the method includes the following steps S301 to S303:

[0107] In the step S301, for each distribution transformer among the multiple distribution transformers, the medium voltage distribution network obtains the output power of the distribution transformer, and calculates the active power adjustment amount of each low-voltage distribution network in the multiple low-voltage distribution networks connected to the distribution transformer according to the power limit and the output power of each low-voltage distribution network, thereby sending a control instruction to the main node in each low-voltage distribution network according to the active power adjustment amount of each low-voltage distribution network.

[0108] In the step S302, for each low-voltage distribution network, after receiving the control instruction, the master node iteratively updates the consistency variable of the master node according to the active power regulation amount of the low-voltage distribution network; each of the multiple non-master nodes calculates the state transfer coefficient from the adjacent node to the non-master node according to the network topology structure of the low-voltage distribution network, and iteratively updates the consistency variable of the non-master node based on the state transfer coefficient and the updated consistency variable of the adjacent node; the master node and the multiple non-master nodes continuously iteratively update the corresponding consistency variables until the master node and all non-master nodes reach a system equilibrium state, wherein the adjacent node is the master node or other non-master nodes.

[0109] In step S303, the above steps are repeated for the multiple distribution transformers until the master nodes and all non-master nodes in the low-voltage distribution network connected to the multiple distribution transformers reach a system balance state, thereby realizing intelligent load control of the distributed photovoltaic-energy storage system.

[0110] The present disclosure can achieve power allocation and scheduling optimization between distributed photovoltaic-energy storage systems by collaboratively calculating consistency variables, more effectively balance power demand and supply, thereby reducing voltage fluctuations, improving the stability of the power grid, and further realizing intelligent management and control of the power grid.

[0111] In particular, according to an embodiment of the present disclosure, the method described above can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program tangibly contained on a machine-readable medium, and the computer program includes a program code for executing the above method. In such an embodiment, the computer program can be downloaded and installed from a network through a communication part, and / or installed from a removable medium.

[0112] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0113] The units or modules involved in the embodiments described in the present disclosure may be implemented by software or programmable hardware. The units or modules described may also be set in a processor, and the names of these units or modules do not constitute limitations on the units or modules themselves in some cases.

[0114] As another aspect, the present disclosure further provides a computer-readable storage medium, which may be a computer-readable storage medium included in the electronic device or computer system in the above embodiment; or a computer-readable storage medium that exists independently and is not assembled into a device. The computer-readable storage medium stores one or more programs, and the programs are used by one or more processors to execute the method described in the present disclosure.

[0115] The above description is only a preferred embodiment of the present disclosure and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the present disclosure is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the inventive concept. For example, the above features are replaced with the technical features with similar functions disclosed in the present disclosure (but not limited to) by each other.

Claims

1. An intelligent load control and distribution system for a distributed photovoltaic-energy storage system, characterized in that: The power distribution system comprises: a medium-voltage distribution network and a plurality of distribution transformers connected to the medium-voltage distribution network, wherein the distribution transformers are connected to one or more low-voltage distribution networks, wherein the low-voltage distribution network comprises a plurality of distributed photovoltaic-energy storage systems, wherein one distributed photovoltaic-energy storage system in the low-voltage distribution network is a master node, and the remaining distributed photovoltaic-energy storage systems are non-master nodes; For each of the multiple distribution transformers, the medium-voltage distribution network obtains the output power of the distribution transformer, and calculates the active power adjustment amount of each low-voltage distribution network in the multiple low-voltage distribution networks connected to the distribution transformer according to the power limit of each low-voltage distribution network and the output power, thereby sending a control instruction to the master node in each low-voltage distribution network according to the active power adjustment amount of each low-voltage distribution network; For each low-voltage distribution network, after receiving the control instruction, the master node iteratively updates the consistency variable of the master node according to the active power regulation amount of the low-voltage distribution network; each of the multiple non-master nodes calculates the state transfer coefficient from the adjacent node to the non-master node according to the network topology structure of the low-voltage distribution network, and iteratively updates the consistency variable of the non-master node based on the state transfer coefficient and the updated consistency variable of the adjacent node; the master node and the multiple non-master nodes continuously iteratively update the corresponding consistency variables until the master node and all the non-master nodes reach a system equilibrium state, wherein the adjacent node is the master node or other non-master nodes; For the low-voltage distribution network connected to the multiple distribution transformers, the one-time variables of the main node and all non-main nodes in the low-voltage distribution network are continuously iterated and updated until the main node and all non-main nodes in the low-voltage distribution network reach a system balance state, thereby realizing intelligent load control of the distributed photovoltaic-energy storage system.

2. The system according to claim 1, characterized in that The calculating the active power regulation amount of each low-voltage distribution network according to the power limit of each low-voltage distribution network among the multiple low-voltage distribution networks connected to the distribution transformer and the output power comprises: For each low-voltage distribution network, the medium-voltage distribution network calculates the active power adjustment amount of the low-voltage distribution network according to the maximum active power and the minimum active power of the low-voltage distribution network and the obtained output power of the distribution transformer connected to the low-voltage distribution network.

3. The system according to claim 2, characterized in that The active power adjustment amount of the low-voltage distribution network is calculated according to the maximum active power and the minimum active power of the low-voltage distribution network and the obtained output power of the distribution transformer connected to the low-voltage distribution network, including calculating the active power adjustment amount using the following formula: Among them, the ΔP j A is the active power regulation value of the j-th low-voltage distribution network, the P j DT is the output power of the distribution transformer connected to the j-th low-voltage distribution network, is the maximum active power of the j-th low-voltage distribution network, is the minimum active power of the j-th low-voltage distribution network.

4. The system according to claim 3, characterized in that: In the ΔP j A >0, the j-th low-voltage distribution network is absorbing power relative to the medium-voltage distribution network; In the ΔP j A <0, the j-th low-voltage distribution network outputs power relative to the medium-voltage distribution network; In the ΔP j A =0, the j-th low-voltage distribution network is in a system balance state.

5. The system according to claim 4, characterized in that The sending of a control instruction to a master node in each low-voltage distribution network according to the active power adjustment amount of each low-voltage distribution network comprises: In the j-th low-voltage distribution network, ΔP j A >0 or ΔP j A <0, the medium voltage distribution network sends a control instruction to the master node in the j-th low voltage distribution network, wherein the control instruction includes an active power adjustment instruction.

6. The system according to claim 3, characterized in that The master node iteratively updates the consistency variable of the master node according to the active power regulation amount of the low-voltage distribution network, including: The master node performs a k1th iterative update on the consistency variables of the master node based on the consistency variables of the master node that have been iteratively updated for k1-1 times and the active power adjustment amount of the low-voltage distribution network.

7. The system according to claim 6, characterized in that The master node performs a k1th iterative update on the consistency variable of the master node according to the consistency variable of the master node that has been iteratively updated k1-1 times and the active power regulation amount of the low-voltage distribution network, including performing a k1th iterative update on the consistency variable of the master node according to the following formula: Among them, the is the consistency variable updated by the master node for the k1th iteration, is the consistency variable of the master node after k1-1 iterations of updates, where a is a convergence control parameter, 1≤k1≤K, where K is a preset maximum number of iterations.

8. The system according to claim 1, characterized in that The calculating the state transfer coefficient from the adjacent node to the non-main node according to the network topology structure of the low-voltage distribution network includes: The non-master node i+n calculates a state transfer coefficient from the adjacent node i to the non-master node i+n according to the total number of communication information received by the non-master node i+n.

9. The system according to claim 8, characterized in that The non-primary node i+n calculates the state transfer coefficient from the adjacent node i to the non-primary node i+n according to the total number of communication information received by the non-primary node i+n, including calculating the state transfer coefficient from the adjacent node i to the non-primary node i+n according to the following formula: Among them, the d i,i+n is the state transfer coefficient from the adjacent node i to the non-primary node i+n, is the total number of communication messages received by the non-master node i+n, and b is the communication line in the low-voltage distribution network.

10. The system according to claim 9, characterized in that The iterative updating of the consistency variable of the non-primary node based on the state transfer coefficient and the updated consistency variable of the adjacent node includes performing a k2-th iterative update of the consistency variable of the non-primary node according to the following formula: u i+n,t (k2)=∑ i+n∈c d i,i+n u i,t (k2-1); Among them, the u i+n,t (k2) is the consistency variable after the non-primary node i+n performs the k2th iteration update, and u i,t (k2-1) is the consistency variable after the adjacent node i is iteratively updated k2-1 times, c is the set of nodes in the low-voltage distribution network, 1≤k2≤K, and K is the preset maximum number of iterations.

11. The system according to claim 10, characterized in that The master node and all non-master nodes have reached a system equilibrium state, including: For any node among the master node and / or non-master node, calculate the active power adjustment amount of any node updated in the kth iteration, when the active power adjustment amount updated in the kth iteration is 0 or less than the set threshold, any node reaches the system equilibrium state, wherein when any node is the master node, k=k1, and when any node is the non-master node, k=k2.

12. The system according to claim 1, characterized in that The consistency variables of the master node and / or non-master node are related to the charging and discharging status of the corresponding master node and / or non-master node, the output power of photovoltaic power generation and the change of power grid power demand.

13. The system according to claim 1, characterized in that The system further comprises: a power measuring device; The power measuring device is arranged between the low voltage power distribution network and the distribution transformer, so as to measure the output power of the distribution transformer.

14. The system according to claim 1, characterized in that The master node is a distributed photovoltaic-energy storage system in the low-voltage distribution network that is closest to a distribution transformer connected to the low-voltage distribution network.

15. An intelligent load control method for a distributed photovoltaic-energy storage system, characterized in that: The distributed photovoltaic-energy storage system is arranged in a power distribution system, the power distribution system comprising: a medium-voltage distribution network and a plurality of distribution transformers connected to the medium-voltage distribution network, the distribution transformers being connected to one or more low-voltage distribution networks, the low-voltage distribution network comprising a plurality of distributed photovoltaic-energy storage systems, one distributed photovoltaic-energy storage system in the low-voltage distribution network being a master node, and the remaining distributed photovoltaic-energy storage systems being non-master nodes; the method comprising: For each of the multiple distribution transformers, the medium-voltage distribution network obtains the output power of the distribution transformer, and calculates the active power adjustment amount of each low-voltage distribution network in the multiple low-voltage distribution networks connected to the distribution transformer according to the power limit of each low-voltage distribution network and the output power, thereby sending a control instruction to the master node in each low-voltage distribution network according to the active power adjustment amount of each low-voltage distribution network; For each low-voltage distribution network, after receiving the control instruction, the master node iteratively updates the consistency variable of the master node according to the active power regulation amount of the low-voltage distribution network; each of the multiple non-master nodes calculates the state transfer coefficient from the adjacent node to the non-master node according to the network topology structure of the low-voltage distribution network, and iteratively updates the consistency variable of the non-master node based on the state transfer coefficient and the updated consistency variable of the adjacent node; the master node and the multiple non-master nodes continuously iteratively update the corresponding consistency variables until the master node and all the non-master nodes reach a system equilibrium state, wherein the adjacent node is the master node or other non-master nodes; For the multiple distribution transformers, repeat the above steps until the master node and all non-master nodes in the low-voltage distribution network connected to the multiple distribution transformers reach a system balance state, thereby realizing intelligent load control of the distributed photovoltaic-energy storage system.

16. A computer-readable storage medium having computer instructions stored thereon, characterized in that: When the computer instructions are executed by a processor, the method according to claim 15 is implemented.

17. A computer program product, characterized in that The method comprises computer instructions, which implement the method of claim 15 when executed by a processor.

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