Multi-dimensional composite energy storage control system based on adaptive topological optimization

Abstract

The invention discloses a multi-dimensional composite energy storage control system based on adaptive topological optimization, and relates to the technical field of power systems, and the system comprises a data real-time monitoring and analysis unit which is used for collecting the real-time operation data of a multi-dimensional composite energy storage electrical system, the real-time operation state of the multi-dimensional composite energy storage electrical system is determined based on the real-time operation data; the self-adaptive topological optimization unit is used for carrying out self-adaptive adjustment on the topological structure of the multi-dimensional composite energy storage electrical system based on the real-time operation data and the real-time operation state in combination with the obtained interference control instruction to obtain an optimized topological structure; and the control instruction generation and execution unit is used for generating an adjustment control instruction of the multi-dimensional composite energy storage electrical system based on the optimized topological structure, and sending the adjustment control instruction to a corresponding execution unit in the multi-dimensional composite energy storage electrical system. The technical problems that in the prior art, energy management efficiency is low, and fault response is not timely are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of power systems, and in particular to a multi-dimensional composite energy storage control system based on adaptive topology optimization. Background Art

[0002] With the widespread application of renewable energy (especially photovoltaics) and the intelligent development of power systems, the role of multi-circuit composite energy storage electrical systems as core energy management and scheduling devices has become increasingly prominent. However, the control systems in the prior art are often based on fixed topology structures, and are not adaptable enough to complex factors such as photovoltaic output fluctuations, diesel generator working conditions, load changes, power grid supply and demand relationships, and internal faults in energy storage systems, resulting in problems such as low energy management efficiency and untimely fault response. In addition, the prior art has an imperfect monitoring and early warning mechanism for multi-circuit energy storage system faults, which cannot fully explore the internal topology optimization potential of the system, nor can it detect and effectively handle potential faults in a timely manner, increasing the risk of system operation. Summary of the invention

[0003] The purpose of the present invention is to provide a multi-dimensional composite energy storage control system based on adaptive topology optimization in order to solve at least one of the above technical problems.

[0004] In a first aspect, an embodiment of the present invention provides a multidimensional composite energy storage control system based on adaptive topology optimization, which is applied to a multidimensional composite energy storage electrical system; it includes: a real-time data monitoring and analysis unit, an adaptive topology optimization unit and a control instruction generation and execution unit; wherein the real-time data monitoring and analysis unit is used to collect real-time operation data of the multidimensional composite energy storage electrical system, and determine the real-time operation status of the multidimensional composite energy storage electrical system based on the real-time operation data; the adaptive topology optimization unit is used to adaptively adjust the topological structure of the multidimensional composite energy storage electrical system based on the real-time operation data and the real-time operation status, and in combination with the obtained interference control instructions, to obtain an optimized topological structure; the control instruction generation and execution unit is used to generate an adjustment control instruction of the multidimensional composite energy storage electrical system based on the optimized topological structure, and send the adjustment control instruction to the corresponding execution unit in the multidimensional composite energy storage electrical system.

[0005] Furthermore, it also includes an intelligent monitoring and fault warning unit for monitoring the real-time operating status of the multi-dimensional composite energy storage electrical system, and when a fault is detected in the multi-dimensional composite energy storage electrical system, adjusting the topology structure to isolate the fault and generating warning information.

[0006] Furthermore, the multi-dimensional composite energy storage electrical system includes a photovoltaic array, a diesel generator, a load, a power grid and an energy storage system; the real-time operation data includes: photovoltaic array data, diesel generator data, load power consumption data, power grid power supply data and energy storage system status data.

[0007] Furthermore, the adaptive topology optimization unit is also used to: adjust the configuration mode of the diesel generator and the photovoltaic array grid-connected, optimize the access mode of the energy storage inverter and the battery of the energy storage system, and dynamically adjust the separate / parallel operation mode of the transformer of the power grid.

[0008] Furthermore, the adaptive topology optimization unit is also used to calculate the grid-connected configuration of the diesel generator and the photovoltaic array based on the real-time operation data and using a mixed integer linear programming algorithm; wherein the goal of the mixed integer linear programming algorithm is to minimize the system operation cost.

[0009] Furthermore, the adjustment control instructions include: start and stop instructions for the photovoltaic array, start and stop instructions for the diesel generator, adjustment instructions for the transformer bus tie switch of the power grid, instructions for the connection form between the energy storage converter and the battery of the energy storage system, and power control instructions for the interconnection line of the power grid.

[0010] Furthermore, the control instruction generation and execution unit is also used to receive execution feedback information of the adjustment control instruction from the execution unit of the multi-dimensional composite energy storage electrical system, and evaluate the instruction execution effect based on the execution feedback information.

[0011] The present invention provides a multi-dimensional composite energy storage control system based on adaptive topology optimization. With its integrated real-time data monitoring and analysis, adaptive topology optimization, control instruction generation and execution, intelligent monitoring and fault isolation and other innovative functions, it significantly improves the energy management efficiency, fault response speed, operation stability and reliability of the multi-dimensional composite energy storage electrical system, and alleviates the technical problems of low energy management efficiency and untimely fault response in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the implementation methods of the present application or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0013] Figure 1 A schematic diagram of a multi-dimensional composite energy storage control system based on adaptive topology optimization provided by an embodiment of the present invention;

[0014] Figure 2 A schematic diagram of an optimization process of an adaptive topology optimization unit provided in an embodiment of the present invention;

[0015] Figure 3 A functional schematic diagram of a control instruction generation and execution unit provided in an embodiment of the present invention;

[0016] Figure 4 A functional schematic diagram of an intelligent monitoring and fault warning unit provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] Figure 1 Schematic diagram of a multi-dimensional composite energy storage control system based on adaptive topology optimization according to an embodiment of the present invention, the control system is applied to a multi-dimensional composite energy storage electrical system. Figure 1 As shown, the control system includes: a real-time data monitoring and analysis unit 10, an adaptive topology optimization unit 20 and a control instruction generation and execution unit 30.

[0019] Specifically, the data real-time monitoring and analysis unit 10 is used to collect real-time operation data of the multi-dimensional composite energy storage electrical system, and determine the real-time operation status of the multi-dimensional composite energy storage electrical system based on the real-time operation data;

[0020] The adaptive topology optimization unit 20 is used to adaptively adjust the topology structure of the multi-dimensional composite energy storage electrical system based on the real-time operation data and the real-time operation status, and in combination with the obtained interference control instructions, to obtain an optimized topology structure;

[0021] The control instruction generation and execution unit 30 is used to generate adjustment control instructions for the multi-dimensional composite energy storage electrical system based on the optimized topological structure, and send the adjustment control instructions to the corresponding execution unit in the multi-dimensional composite energy storage electrical system.

[0022] like Figure 1 As shown, the control system provided by the embodiment of the present invention also includes an intelligent monitoring and fault warning unit 40, which is used to monitor the real-time operating status of the multi-dimensional composite energy storage electrical system, and when a fault is detected in the multi-dimensional composite energy storage electrical system, adjust the topology structure to isolate the fault and generate warning information.

[0023] In an optional implementation provided by an embodiment of the present invention, a multi-dimensional composite energy storage electrical system includes a photovoltaic array, a diesel generator, a load, a power grid and an energy storage system;

[0024] Real-time operation data includes: photovoltaic array data, diesel generator data, load power consumption data, grid power supply data and energy storage system status data.

[0025] Specifically, the main task of the real-time data monitoring and analysis unit 10 is to collect and deeply analyze the comprehensive data of the multi-dimensional composite electrical system in real time. Specifically, the real-time data monitoring and analysis unit 10 collects various key operating data in real time through sensors, metering equipment and communication interfaces arranged on various subsystems of the multi-dimensional composite electrical system, specifically covering the following five aspects:

[0026] (1) Photovoltaic array data: Real-time monitoring of key parameters of the photovoltaic array, such as output power, voltage, and current, to accurately reflect the utilization rate of solar energy resources and the operating status of the photovoltaic system, and to provide basic information for optimizing the coordinated use of photovoltaics and other energy sources;

[0027] (2) Diesel generator data: Pay close attention to performance indicators such as diesel generator output power to accurately judge its working efficiency and equipment health status, ensuring that scheduling decisions can be made quickly when necessary;

[0028] (3) Load power consumption data: Detailed monitoring of the power consumption, load characteristics and other detailed information of each circuit load to accurately grasp the changing trend of power demand and provide a basis for the rational allocation of energy storage and power generation resources;

[0029] (4) Grid power supply data: Comprehensively obtain important parameters such as grid voltage, frequency, power factor, and power flow distribution to accurately describe the grid’s operating status and supply-demand balance, and provide decision support for efficient interaction between energy storage systems and the grid;

[0030] (5) Energy storage system status data: Carefully monitor key data such as the battery pack's state of charge (SOC), charge and discharge current, voltage, temperature, and the operating status and efficiency of the power storage converter (PCS) to ensure the safe and efficient operation of the energy storage equipment and prevent potential problems such as overcharging and over-discharging.

[0031] Specifically, the adaptive topology optimization unit 20 is also used to: adjust the configuration mode of the diesel generator and the photovoltaic array grid connection, optimize the access mode of the energy storage inverter and the battery of the energy storage system, and dynamically adjust the separate / parallel operation mode of the transformer of the power grid.

[0032] The adaptive topology optimization unit 20 uses adaptive topology optimization to dynamically adjust the system topology structure between diesel generators, photovoltaics, transformers, PCS, batteries and power grid power supply circuits based on the real-time operation data and in-depth analysis results provided by the real-time data monitoring and analysis unit 10, combined with specific control instructions set manually (such as forced operation modes under special working conditions, specific optimization goals, etc.), so as to adapt to various complex working conditions and management goals, and maximize the overall energy efficiency of the system and minimize the operating costs. Figure 2 FIG. 1 is a schematic diagram of an optimization process of an adaptive topology optimization unit according to an embodiment of the present invention. Figure 2 As shown, specifically including:

[0033] (1) Dynamic topology generation: Based on real-time monitoring data, the system adaptively calculates the most suitable system connection path under the current environment. This includes but is not limited to adjusting the configuration of generators and photovoltaic grid connection, optimizing the access form of energy storage PCS and batteries, and dynamically adjusting the transformer's separate / parallel operation mode, etc., in order to flexibly respond to variable factors such as photovoltaic output fluctuations, load demand changes, and grid dispatch instructions.

[0034] This process focuses on the connection configuration of power generation equipment and energy storage equipment, as well as the optimization of internal equipment connection and configuration:

[0035] Connection configuration of power generation equipment and energy storage equipment: The system adjusts the grid-connected configuration of photovoltaic and diesel generators in real time according to the actual output power of the photovoltaic array, the operating status of the diesel generator and the load demand, ensuring the optimization of the energy flow path between the power generation equipment and the energy storage equipment, so as to make full use of renewable energy resources and ensure the stability and reliability of power supply.

[0036] Specifically, the adaptive topology optimization unit 20 is also used to calculate the grid-connected configuration of the diesel generator and the photovoltaic array based on real-time operation data and using a mixed integer linear programming algorithm (MILP); wherein the goal of the mixed integer linear programming algorithm is to minimize the system operation cost.

[0037] Specifically, a mathematical model is constructed to represent the above data and transform them into a linear relationship. The present invention uses the following variables:

[0038] P PV,t : The actual output power of the photovoltaic array at time t;

[0039] P DG,t : Output power of diesel generator at time t;

[0040] P load,t : The total load demand of the system at time t;

[0041] E t: The energy storage capacity of the energy storage device at time t;

[0042] C charge，t and C discharge，t : The charging and discharging rate of the energy storage device at time t.

[0043] The algorithm goal is to optimize the energy flow path, that is, to minimize the system operation cost, which can be expressed as:

[0044]

[0045] Among them, C fuel is the cost coefficient of diesel. In order to ensure the normal operation of the system, a series of constraints need to be added:

[0046] Supply and demand balance: Generation plus storage discharge must equal load demand plus storage charge:

[0047] P PV，t +P DG，t -C disc harge，t =P load，t +C charge，t

[0048] Diesel generator capacity: The output power of the diesel generator should be within the allowable range:

[0049] P min，DG ≤P DG，t ≤P max，DG

[0050] Energy storage status: The change in the amount of energy stored in the energy storage device must comply with the laws of physics:

[0051]

[0052] Among them, η charge and η disc harge They are the charging and discharging efficiency of the energy storage device.

[0053] Energy storage boundary: The amount of energy storage equipment cannot exceed its capacity limit:

[0054] E min ≤E t ≤E max

[0055] Charge and discharge rate: Charge and discharge rate limits of energy storage devices:

[0056] 0≤C c harge，t ≤C max，c harge

[0057] 0≤Cdisc harge，t ≤C max，disc hage

[0058] The MILP solver is used to solve the above optimization problem. The MILP solver tries to find a set of P that satisfies all constraints. DG,t , C charge，t and C discharge，t value so that the objective function is minimized.

[0059] Internal equipment connection and configuration: The system timely adjusts the access form of the energy storage converter (PCS) and the battery, optimizes the transformer's separate / parallel operation mode to adapt to the energy flow requirements and power transmission efficiency under different working conditions, and improves the overall operation efficiency of the system.

[0060] Based on the results of the MILP solution, the control system will issue instructions to adjust the output power of the diesel generator and the charge and discharge rate of the energy storage device. For example, if the MILP recommends increasing the output power of the diesel generator, the control system will adjust the diesel generator accordingly; if it recommends that the energy storage device start discharging, the control system will start the corresponding discharge process.

[0061] The system will continuously monitor the actual operation status, and constantly update the model parameters based on the latest data, and re-optimize the calculations to respond to environmental changes or emergencies, thereby maintaining the optimal operating state of the system.

[0062] (2) Interference control response: When receiving manually set interference control instructions, the system can ensure that the topology structure is adjusted in real time according to the preset operation strategy or specific operation requirements, ensuring efficient energy management and stable system operation even under special working conditions.

[0063] Specifically, the preset operation strategy refers to a set of pre-set operation plans for dealing with specific situations, including the following:

[0064] Emergency backup power switching: When the main power fails, immediately start the backup diesel generator or other emergency power supply unit.

[0065] Peak load management: Limit the power supply to certain non-critical loads during peak power consumption periods, giving priority to ensuring the power supply to important loads.

[0066] Economic dispatch: Arrange the output sequence of power generation sources with different costs according to electricity price fluctuations to reduce operating costs.

[0067] Maintenance Mode: Automatically enter maintenance mode periodically or based on equipment status to perform necessary inspections and maintenance work.

[0068] Specifically, the adjustment control instructions include: start and stop instructions for the photovoltaic array, start and stop instructions for the diesel generator, adjustment instructions for the transformer bus tie switch of the power grid, instructions for the connection form of the energy storage inverter and battery of the energy storage system, and power control instructions for the interconnection line of the power grid.

[0069] The control instruction generation and execution unit 30 is also used to receive execution feedback information of the execution unit of the multi-dimensional composite energy storage electrical system on the adjustment control instruction, and evaluate the instruction execution effect based on the execution feedback information.

[0070] The control system provided by the embodiment of the present invention is based on the calculation results of the adaptive topology optimization unit 20 and the manually set interference instructions. The control instruction generation and execution unit 30 is responsible for generating accurate control instructions for each component of the system and ensuring the effective execution of the instructions. Figure 3 1 is a functional schematic diagram of a control instruction generation and execution unit provided according to an embodiment of the present invention. Figure 3 As shown, the functions include:

[0071] (1) Command generation: The controller calculates the optimal topology based on the current data, and the system generates a series of specific control commands, such as diesel generator and PV start and stop commands, transformer bus tie switch adjustment commands, PCS and battery connection form commands, and grid tie line power control commands, to ensure that the entire system operates efficiently and orderly according to the optimized topology.

[0072] (2) Instruction execution: The generated control instructions are quickly sent to each execution unit through the built-in communication interface, ensuring that all components operate strictly in accordance with the parameters set by the instructions, thereby achieving the precise implementation of the global control intention.

[0073] (3) Command feedback and adjustment: The system continuously receives feedback from each component on the execution of control commands and evaluates the execution effect of commands in real time. Based on the feedback results, the system makes necessary corrections or recalculations to subsequent commands to ensure that the actual operating status is always consistent with the target topology, thereby achieving closed-loop control and dynamic optimization.

[0074] In the embodiment of the present invention, the intelligent monitoring and fault warning unit 40 continuously monitors the operating status and performance parameters of the multi-dimensional composite energy storage electrical system. When a system fault is detected, the topology structure can be automatically adjusted to isolate the fault and ensure stable operation of the system. Figure 4 1 is a functional schematic diagram of an intelligent monitoring and fault warning unit provided according to an embodiment of the present invention. Figure 4 As shown, the intelligent monitoring and fault warning unit 40 has the following functions:

[0075] (1) Real-time status monitoring: The intelligent monitoring and fault warning unit continuously monitors the operating status and performance parameters of each circuit energy storage system, such as transformer operating status, battery operating status, PCS operating status, photovoltaic and diesel operating status, etc., to build a real-time status portrait of the system. Through real-time monitoring and analysis of these data, the system can predict potential faults in advance and provide detailed data support for rapid response.

[0076] (2) Emergency handling and intervention: Once an abnormal situation or failure risk is detected, the system immediately triggers the early warning mechanism, generates early warning information and sends an alarm signal to the operation and maintenance personnel through the communication interface. At the same time, the system automatically initiates emergency handling measures, such as:

[0077] Faulty equipment isolation: When a PCS fails, the system automatically switches the AC / DC switch of the PCS to bypass mode to prevent the fault from spreading further.

[0078] Circuit switching: timely adjust the AC power supply circuit and DC side battery connection topology corresponding to the faulty PCS, and switch to other normal circuits to ensure the continuity of power supply.

[0079] Operation mode adjustment: Depending on the impact of the fault, it may be necessary to adjust the energy storage system operation mode, such as switching from grid-connected mode to island mode, or adjusting the load power supply priority to ensure that critical loads are not affected.

[0080] (3) Fault detection and early warning: including identifying abnormal conditions or fault risks and generating early warning information.

[0081] From the above description, it can be seen that the embodiment of the present invention provides a multi-dimensional composite energy storage control system based on adaptive topology optimization. With its integrated real-time data monitoring and analysis, adaptive topology optimization, control instruction generation and execution, intelligent monitoring and fault isolation and other innovative functions, it significantly improves the energy management efficiency, fault response speed, operation stability and reliability of the multi-dimensional composite energy storage electrical system. The system is particularly suitable for complex energy network environments that include a variety of energy storage technologies, power generation technologies and load types, and is of great significance for promoting the intelligent and efficient transformation of power systems.

[0082] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

[0083] In addition, it should be understood that although the present specification is described according to implementation modes, not every implementation mode contains only one independent technical solution. This description of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment may also be appropriately combined to form other implementation modes that can be understood by those skilled in the art.

Claims

1. A multi-dimensional composite energy storage control system based on adaptive topology optimization, characterized in that: Applied to multi-dimensional composite energy storage electrical system; including: real-time data monitoring and analysis unit, adaptive topology optimization unit and control instruction generation and execution unit; among which, The data real-time monitoring and analysis unit is used to collect real-time operation data of the multi-dimensional composite energy storage electrical system, and determine the real-time operation status of the multi-dimensional composite energy storage electrical system based on the real-time operation data; The adaptive topology optimization unit is used to adaptively adjust the topology structure of the multi-dimensional composite energy storage electrical system based on the real-time operation data and the real-time operation state, and in combination with the obtained interference control instruction, to obtain an optimized topology structure; The control instruction generation and execution unit is used to generate an adjustment control instruction for the multi-dimensional composite energy storage electrical system based on the optimized topological structure, and send the adjustment control instruction to a corresponding execution unit in the multi-dimensional composite energy storage electrical system.

2. The multi-dimensional composite energy storage control system based on adaptive topology optimization according to claim 1, characterized in that: It also includes an intelligent monitoring and fault warning unit for monitoring the real-time operating status of the multi-dimensional composite energy storage electrical system, and when a fault is detected in the multi-dimensional composite energy storage electrical system, adjusting the topology structure to isolate the fault and generating warning information.

3. The multi-dimensional composite energy storage control system based on adaptive topology optimization according to claim 1, characterized in that: The multi-dimensional composite energy storage electrical system includes a photovoltaic array, a diesel generator, a load, a power grid and an energy storage system; The real-time operation data includes: photovoltaic array data, diesel generator data, load power consumption data, grid power supply data and energy storage system status data.

4. The multi-dimensional composite energy storage control system based on adaptive topology optimization according to claim 3 is characterized in that: The adaptive topology optimization unit is also used to: adjust the configuration mode of the diesel generator and the photovoltaic array grid-connected, optimize the access mode of the energy storage inverter and the battery of the energy storage system, and dynamically adjust the separate / parallel operation mode of the transformer of the power grid.

5. The multi-dimensional composite energy storage control system based on adaptive topology optimization according to claim 4 is characterized in that: The adaptive topology optimization unit is further used for: Based on the real-time operation data and using a mixed integer linear programming algorithm, the grid-connected configuration of the diesel generator and the photovoltaic array is calculated; wherein the goal of the mixed integer linear programming algorithm is to minimize the system operation cost.

6. The multi-dimensional composite energy storage control system based on adaptive topology optimization according to claim 3 is characterized in that: The adjustment control instructions include: start and stop instructions for the photovoltaic array, start and stop instructions for the diesel generator, adjustment instructions for the transformer bus tie switch of the power grid, instructions for the connection form of the energy storage converter and battery of the energy storage system, and power control instructions for the tie line of the power grid.

7. The multi-dimensional composite energy storage control system based on adaptive topology optimization according to claim 1, characterized in that: The control instruction generation and execution unit is also used to receive execution feedback information of the adjustment control instruction from the execution unit of the multi-dimensional composite energy storage electrical system, and evaluate the instruction execution effect based on the execution feedback information.

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