Regional source network load storage autonomous method and system based on embedded EMS

Abstract

The invention discloses a regional source network load storage autonomous method and system based on an embedded EMS. The method comprises the steps of obtaining feature data of a first object; according to the feature data, judging whether a second object needs to adjust the first object or not; the second object is constrained; and controlling the feature data of the first object to maintain stable by using the optimization target. Reliable, economical and autonomous operation of regional source network load storage and cooperative operation with a large power grid can be achieved, meanwhile, the regional source network load storage autonomous system is developed and achieved based on a lightweight embedded EMS device, and good generalizability is achieved under the condition that the energy management hardware cost of the regional source network load storage system is limited.

Description

Technical Field

[0001] The present invention relates to the technical field of power system control, and in particular to a regional source-grid-load-storage autonomy method and system based on embedded EMS. Background Art

[0002] Carbon emissions in my country's energy sector account for about 90% of the total carbon emissions in the society, of which carbon emissions in the power industry account for about half of the carbon emissions in the energy sector. The energy structure dominated by coal is accelerating the diversification of clean energy such as water, wind and light. However, new energy generation such as solar and wind power has the characteristics of volatility, intermittency and randomness, which brings new challenges to the safe and stable operation of the power grid. The construction of a regional source-grid-load-storage (power source, power grid, load, energy storage) integrated system and its coordinated control are one of the core technologies to promote the large-scale consumption of new energy. It aims to achieve the optimal scheduling and active management of various distributed resources at the in-depth level, give full play to the complementarity of power sources, the flexibility of power grids, and the flexible controllability of loads and energy storage, improve the distribution network's ability to absorb new energy, and ensure the reliability and economy of the distribution network operation.

[0003] In recent years, regional source-grid-load-storage coordinated control has become a research hotspot in the field of electric power. In the article "Day-ahead operation optimization of regional source-grid-load-storage system based on target cascade analysis", the interests of different entities, energy suppliers and load users, are balanced in the source-grid-load-storage system, and an optimization operation model with the goal of minimizing energy supply costs and maximizing electricity satisfaction is established. Most of the existing studies on regional source-grid-load-storage control consider the maximization of benefits of different entities and the goal of new energy consumption. There is still insufficient research on the reliable autonomous operation of source-grid-load-storage and its coordinated operation with the large power grid. In addition, regional source-grid-load-storage systems are usually not operated by power grid companies, and their requirements for hardware cost control of energy management are higher than those of power grid companies. The existing research has not considered the hardware configuration of energy management. Therefore, it is necessary to further study the regional source-grid-load-storage autonomous methods and systems based on lightweight hardware. Summary of the invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a regional source-grid-load-storage autonomous method based on embedded EMS, comprising:

[0006] Acquiring feature data of a first object;

[0007] determining, based on the characteristic data, whether the second object needs to be adjusted toward the first object;

[0008] constraining the second object;

[0009] By using the optimization target, the characteristic data of the first object is controlled to be stable.

[0010] As a preferred solution of the regional source-grid-load-storage autonomous method based on embedded EMS described in the present invention, wherein: the characteristic data includes, during the working process of the first object, characteristics that can reflect the working situation;

[0011] The second object is capable of regulating the operation of the first object.

[0012] As a preferred solution of the regional source-grid-load-storage autonomous method based on embedded EMS described in the present invention, wherein: when the second object adjusts the first object, the second object is constrained, including but not limited to inherent constraints and conditional constraints;

[0013] The inherent constraints include constraints given by the second object according to limitations of its own performance;

[0014] The conditional constraints include constraints given by the second object according to conditions of a control target.

[0015] As a preferred solution of the regional source-grid-load-storage autonomous method based on embedded EMS described in the present invention, wherein: the optimization target includes controlling the second object involved in the regulation so that the control process can achieve the expected results.

[0016] As a preferred solution of the regional source-grid-load-storage autonomous method based on embedded EMS described in the present invention, wherein: the expectation includes but is not limited to an objective function and an adjustment function.

[0017] As a preferred solution of the regional source-grid-load-storage autonomous method based on embedded EMS described in the present invention, wherein: the power grid is taken as the first object and the energy storage system is taken as the second object;

[0018] When the second object adjusts the first object, there are two adjustment modes: frequency increase and frequency decrease;

[0019] In both scenarios, the inherent constraints and conditional constraints of each unit in the energy storage system include:

[0020] S oc,i,2m S bs,i,max ≤S bs,i ≤S oc,i,max S bs,i,max ,i=1,L,n s

[0021] S oc,1,2m -S oc,1,min =L=S oc,i,2m -Soc,i,min =L=S oc,ns,2m -S oc,ns,min

[0022] Among them, S bs,i is the storage capacity of energy storage i; S bs,i,max is the rated capacity of energy storage i; S oc,i,max and S oc,i,min are the highest state of charge and the lowest state of charge of energy storage respectively; n s is the amount of energy storage; S oc,i,2m To store energy to ensure the remaining charge state of regional load power supply in case of grid failure;

[0023]

[0024] Where: P m is the maximum load that may be expected in the region; T is a time length greater than 2 minutes to ensure that the energy storage can supply power to the regional load for more than 2 minutes.

[0025] As a preferred solution of the regional source-grid-load-storage autonomous method based on embedded EMS described in the present invention, wherein: in the frequency reduction scenario, with the goal of reducing the source-load resource adjustment cost, the non-new energy power generation and the load of the adjustable load are calculated by the objective function:

[0026]

[0027] Where p is the current electricity price; P s,j is the active power generated by non-renewable energy generation j; g j is the power generation cost function of non-renewable energy power generation j or the quotation function in the power spot market; P s,j,max is the maximum active power of non-renewable energy generation j; P L,k is the load of the adjustable load k; h k is the load utilization benefit function of the adjustable load; P L,k.max is the maximum load of the adjustable load k;

[0028] In the frequency increase scenario, the goal is to achieve self-balancing of regional source-load power while taking into account the reduction of source-load resource adjustment costs, and to control renewable energy generation, non-renewable energy generation and adjustable loads:

[0029]

[0030] Among them, P L For non-adjustable load; P rn The active power generated by renewable energy; P rn,max is the maximum active power of renewable energy generation; c 1 and c 2is a constant representing the target weight, and its value satisfies c 1 >>c;

[0031] When new energy or load fluctuates, the energy storage is controlled by adjusting the function to be used for regional real-time power self-balancing:

[0032]

[0033] Among them, P bs,i is the active power generated by energy storage i; P bs,i,max is the rated charge and discharge power of energy storage i; Γ is the oc,i,2m S bs,i,max <S bs,i <S oc,i,max S bs,i,max The energy storage number set;

[0034] When the source and load adjust the power according to the optimization control model to achieve stability, the power of each energy storage is controlled to 0.

[0035] On the other hand, a regional source-grid-load-storage autonomous system based on embedded EMS adopting the method described in the present invention comprises three parts: data acquisition and control instruction issuance, regional source-grid-load-storage autonomous method and Web display interface;

[0036] The data acquisition and control instruction issuing function module is based on Modbus, MQTT, and IEC supported by embedded EMS 104. DL / T645 communication protocol is configured accordingly according to the communication protocols adopted by the regional load, power source, energy storage and power grid to realize source-grid-load-storage data collection. The collected data is used as input data of the regional source-grid-load-storage autonomous method function module and stored in the embedded database. At the same time, the module receives the control instructions of the regional source-grid-load-storage autonomous method function module and sends them to the equipment; the regional source-grid-load-storage autonomous method function module performs regional source-grid-load-storage autonomous calculation based on the data collected by the data collection and control instruction sending function module and the fixed parameter data in the embedded database, sends the calculated control instructions and the manual control instructions received from the Web display interface to the data collection and control instruction sending function module, and stores them in the embedded database, and sends the calculation result data to the Web display interface; the Web display interface is based on the report and wiring diagram display function supported by the embedded EMS, and associates and configures and displays the source-grid-load-storage device data that needs to be displayed in the regional source-grid-load-storage. At the same time, the module supports manual setting of control instructions on the interface and sending them to the regional source-grid-load-storage autonomous method function module.

[0037] A computer device comprises: a memory and a processor; the memory stores a computer program, wherein: the processor implements the steps of any one of the methods of the present invention when executing the computer program.

[0038] A computer-readable storage medium stores a computer program, wherein: when the computer program is executed by a processor, the steps of any one of the methods of the present invention are implemented.

[0039] Beneficial effects of the present invention: The regional source-grid-load-storage autonomous method based on embedded EMS provided by the present invention can generate a regional source-grid-load-storage autonomous control strategy that takes into account multiple objectives such as supporting the grid frequency, reserving sufficient power for regional loads in case of faults, and reducing the source-load resource regulation cost when the grid frequency is low; and can generate an autonomous control strategy that takes into account multiple objectives such as regional source-load power self-balancing, reserving sufficient power for regional loads in case of faults, and reducing the source-load resource regulation cost when the grid frequency is high. It can realize reliable and economic autonomous operation of regional source-grid-load-storage and coordinated operation with the large power grid. At the same time, the regional source-grid-load-storage autonomous system is developed and implemented based on a lightweight embedded EMS device, and has good scalability under the condition of limited hardware cost of energy management of the regional source-grid-load-storage system. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0041] Figure 1 An overall flow chart of a regional source-grid-load-storage autonomous method based on embedded EMS provided in the first embodiment of the present invention;

[0042] Figure 2 A structural diagram of a regional source-grid-load-storage autonomous system based on embedded EMS provided in the second embodiment of the present invention. DETAILED DESCRIPTION

[0043] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0044] Example 1, reference Figure 1 , as an embodiment of the present invention, provides a regional source-grid-load-storage autonomous method based on embedded EMS, including:

[0045] S1: Acquire feature data of a first object.

[0046] The characteristic data includes characteristics that can reflect the working conditions during the working process of the first object.

[0047] Collecting characteristic data is a core step in the operation and control of the power grid. Characteristic data can reflect the current state, operation trends and potential problems of the power grid. By collecting and analyzing this data, the system can achieve multi-faceted optimization and regulation. Characteristic data reflects the operation of the power grid in different time periods, helping operators to monitor the health of the system. If the data fluctuates abnormally, it may mean potential power grid problems or impending failures. Characteristic data provides a basis for the control system, enabling the autonomous system to dynamically adjust power generation, load, energy storage and other links according to the current power grid status to ensure power grid stability and power supply security.

[0048] In an embodiment of the present application, the first object is a power grid, and the characteristic data of the power grid is frequency. The frequency of the power grid reflects the real-time balance between power generation and load. When the power generation is greater than the load, the frequency increases; when the power generation is less than the load, the frequency decreases. Therefore, frequency is the most direct parameter to measure the balance state of the power grid. If the power grid frequency deviates from the rated value, it means that there is an imbalance in the power system and the system needs to be adjusted. The frequency of the power grid needs to be kept within a very small deviation range (for example, 50Hz or 60Hz±0.1Hz). Once the deviation exceeds the allowable range, it may cause equipment damage, generator set disconnection and even large-scale power outages. Therefore, monitoring and controlling the power grid frequency is crucial and can effectively avoid power grid collapse. When the power grid frequency fluctuates abnormally, it usually means that there is a problem with the system, such as a failure of power generation equipment, a sharp change in load, or external power grid interference. By monitoring the frequency, the system can identify the risk of failure in a timely manner and respond quickly to reduce losses and restore power grid stability.

[0049] In an optional embodiment, the first object may also be an electric vehicle charging pile, in which case the characteristic data is the power of a single charging terminal; the electric vehicle charging pile is used as the first object, and the process in which the energy storage system participates in the regulation is the same as in the present application. Electric vehicle charging piles usually include multiple charging terminals, and the power of each terminal directly determines the load level of the entire charging station. If the characteristic data is the power of a single charging terminal, the system can more accurately regulate the load distribution to ensure that each terminal operates efficiently while avoiding the total load exceeding the carrying capacity of the power grid or charging station. Selecting the power of a single charging terminal as the characteristic data can provide accurate load management, dynamic adjustment, and optimized energy efficiency for the electric vehicle charging pile system, thereby improving the overall operating efficiency of the charging station and reducing the impact on the power grid.

[0050] S2: judging whether the second object needs to be adjusted toward the first object according to the characteristic data.

[0051] The second object can adjust the operation of the first object. In the present application, the second object is an energy storage system.

[0052] Similarly, in other possible implementations, the second object may also be a power generation system, etc.

[0053] When the grid frequency is lower than a certain value of the rated frequency, autonomous control of regional sources, grids, loads and storage is carried out with the goal of supporting the grid frequency, backing up sufficient power for regional loads in the event of a fault, and reducing the cost of source-load resource regulation.

[0054] When the grid frequency is lower than the rated frequency and exceeds a certain threshold, it is determined as a frequency drop scenario. As shown in the following formula:

[0055] f<f e -f Δl

[0056] Where: f is the grid frequency; f e is the rated frequency of the power grid; f Δl It is the frequency deviation threshold when it is lower than the rated frequency.

[0057] When the grid frequency is higher than the rated frequency and exceeds a certain threshold, it is determined as a frequency increase scenario. As shown in the following formula:

[0058] f>f e +f Δh

[0059] Where: f Δh is the frequency deviation threshold when it is higher than the rated frequency.

[0060] S3: constraining the second object.

[0061] When the second object adjusts the first object, the second object is constrained, including but not limited to inherent constraints and conditional constraints. The inherent constraints include constraints given by the second object according to the limitations of its own performance. The conditional constraints include constraints given by the second object according to the conditions of the control target.

[0062] In the embodiment of the present application, the regional renewable energy power generation is controlled to operate in the maximum power point tracking control mode to support the grid frequency; according to the national power industry standard "DL / T 814-2013 Technical Specifications for Distribution Automation Systems", the distribution automation system should meet the automatic recovery time of non-fault sections <2min, so the remaining power in the control energy storage can be independently supplied to the regional load for more than 2 minutes to ensure that the regional load does not lose power in the event of a fault. The inherent constraints and conditional constraints of each energy storage capacity are as follows:

[0063] S oc,i,2m S bs,i,max≤S bs,i ≤S oc,i,max S bs,i,max ,i=1,L,n s

[0064]

[0065] Among them, S bs,i is the storage capacity of energy storage i; S bs,i,max is the rated capacity of energy storage i; S oc,i,max and S oc,i,min are the highest state of charge and the lowest state of charge of energy storage respectively; n s is the amount of energy storage; S oc,i,2m It is a residual charge state that ensures regional load power supply by storing energy in case of grid failure.

[0066]

[0067] Where: P m is the maximum load that may be expected in the region; T is a time length greater than 2 minutes to ensure that the energy storage can supply power to the regional load for more than 2 minutes.

[0068] In an optional embodiment, the inherent constraints and conditional constraints may also be the following:

[0069] Inherent constraints: The power output of each energy storage unit cannot exceed its rated charge and discharge power to prevent equipment overload or damage. The charge and discharge power of the energy storage system must be kept within its rated power range to avoid overcharging or discharging. The operating temperature of the energy storage system cannot exceed the safe temperature range to avoid overheating of the equipment, resulting in reduced efficiency or safety issues. The temperature of each energy storage unit must be within the safe operating temperature range to prevent overheating from adversely affecting the equipment. The charging rate of the energy storage system cannot exceed the safety threshold to protect the life of the energy storage equipment.

[0070] Conditional constraints: When the energy storage power is insufficient, priority is given to powering high-priority loads, such as critical infrastructure (hospitals, transportation systems). In an emergency, the energy storage system must prioritize powering high-priority loads to ensure the stable operation of critical facilities. When the electricity price is below a certain threshold, the system prioritizes charging; when the electricity price is above the threshold, the system reduces charging or discharges to the grid. When renewable energy (such as solar or wind energy) is available, the energy storage system prioritizes charging with renewable energy rather than relying on grid power. The energy storage system must discharge or charge when the grid frequency deviates from a certain range to assist in stabilizing the grid frequency.

[0071] Except for the device constraints for the second object, other condition constraints are formulated according to the application environment of the solution.

[0072] Furthermore, in an embodiment of the present invention, if the energy storage charge state is less than S oc,i,2m , and the regional source-grid-load-storage system is connected to the grid and operates normally, then the energy storage is controlled to charge at rated power until the state of charge is greater than or equal to S oc,i,2m . When the energy storage charge state is greater than or equal to S oc,i,2m Based on the constraints of S, each energy storage is controlled to discharge at rated power to support the grid frequency. If the energy storage charge state drops to S oc,i,2m Then stop discharging.

[0073] S4: Using the optimization target, controlling the feature data of the first object to maintain stability.

[0074] The optimization goal includes controlling the second object involved in the regulation so that the control process can achieve the expected results.

[0075] In the embodiment of the present application, the expectation includes but is not limited to an objective function and an adjustment function. In the frequency reduction scenario, with the goal of reducing the source load resource adjustment cost, the non-new energy power generation and the load of the adjustable load are calculated by the objective function:

[0076]

[0077] Where p is the current electricity price; P s,j is the active power generated by non-renewable energy generation j; g j is the power generation cost function of non-renewable energy power generation j or the quotation function in the power spot market; P s,j,max is the maximum active power of non-renewable energy generation j; P L,k is the load of the adjustable load k; h k is the load utilization benefit function of the adjustable load; P L,k.max is the maximum load of the adjustable load k.

[0078] In the frequency increase scenario, the goal is to achieve self-balancing of regional source-load power while taking into account the reduction of source-load resource adjustment costs, and to control renewable energy generation, non-renewable energy generation and adjustable loads:

[0079]

[0080] Among them, P L For non-adjustable load; P rn The active power generated by renewable energy; P rn,max is the maximum active power of renewable energy generation; c 1 and c 2 is a constant representing the target weight, and its value satisfies c 1 >>c.

[0081] When new energy or load fluctuates, the energy storage is controlled by adjusting the function to be used for regional real-time power self-balancing:

[0082]

[0083] Among them, P bs,i is the active power generated by energy storage i; P bs,i,max is the rated charge and discharge power of energy storage i; Γ is the oc,i,2m S bs,i,max <S bs,i <S oc,i,max S bs,i,max A collection of energy storage numbers.

[0084] When the source and load adjust the power according to the optimization control model to achieve stability, the power of each energy storage is controlled to 0.

[0085] In an optional embodiment, the optimization goal can also be: maximize the utilization of renewable energy. Goal: While maintaining the stability of the power grid, maximize the use of renewable energy such as wind power and solar energy, and reduce dependence on fossil fuel power generation. Implementation method: Prioritize the dispatch of renewable energy power generation and minimize the use of non-new energy power generation, unless the grid frequency or load requires additional support. At the same time, the energy storage system can be charged during the peak period of renewable energy output and release electricity during the valley period.

[0086] In an optional embodiment, the optimization goal may also be: minimizing carbon emissions, minimizing grid losses, optimizing electricity price arbitrage, and the like.

[0087] Example 2, reference Figure 2 , as an embodiment of the present invention, provides a regional source-grid-load-storage autonomous system based on embedded EMS.

[0088] The functions of the regional source-grid-load-storage autonomous system include data collection and control command issuance, regional source-grid-load-storage autonomous method and Web display interface. The system architecture is as follows: Figure 2As shown in the figure, the data acquisition and control instruction issuing function module is based on Modbus, MQTT, IEC 104, DL / T supported by embedded EMS. 645 communication protocol, and corresponding configuration is performed according to the communication protocols adopted by the regional load, power source, energy storage and power grid to realize source-grid-load-storage data collection. The collected data is used as the input data of the regional source-grid-load-storage autonomous method function module and stored in the embedded database. At the same time, the module receives the control instructions of the regional source-grid-load-storage autonomous method function module and sends them to the equipment; the regional source-grid-load-storage autonomous method function module performs regional source-grid-load-storage autonomous calculation based on the data collected by the data collection and control instruction sending function module and the fixed parameter data in the embedded database, and sends the calculated control instructions and the manual control instructions received from the Web display interface to the data collection and control instruction sending function module, and stores them in the embedded database, and sends the calculation result data to the Web display interface; the Web display interface is based on the report and wiring diagram display function supported by the embedded EMS, and the source-grid-load-storage device data that needs to be displayed by the regional source-grid-load-storage is associated and configured and displayed. At the same time, the module supports manual setting of control instructions on the interface and sending them to the regional source-grid-load-storage autonomous method function module.

[0089] In the above technical scheme, further, the purpose of regional source, grid, load and storage autonomy is divided into two situations. When the grid frequency is lower than the rated frequency by a certain value, the regional source, grid, load and storage autonomous control is carried out with the goal of supporting the grid frequency, reserving sufficient power for regional loads in case of faults, and reducing the source and load resource regulation costs; when the grid frequency is higher than the rated frequency by a certain value, the regional source, grid, load and storage autonomous control is carried out with the goal of controlling the self-balancing of regional source and load power, reserving sufficient power for regional loads in case of faults, and reducing the source and load resource regulation costs.

[0090] If the above functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0091] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0092] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0093] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0094] Example 3 is an embodiment of the present invention, which provides a regional source-grid-load-storage autonomy method based on embedded EMS. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0095] The effectiveness of the proposed method is verified by using a regional source-grid-load-storage system case that includes renewable energy generation, non-renewable energy generation, energy storage, adjustable loads, and non-adjustable loads. e =50Hz, frequency deviation threshold f Δl =0.05Hz, f Δh=0.05Hz, the maximum load P that may occur in the area m =816kW, T=10min, P s,1,max =500kW, P L,1.max =200kW, P rn,max =300kW, c 1 =1, c 2 =10 -3 , the power generation cost function of non-renewable energy power generation is g 1 (P s,1 )=1.53×10 -4 ×P s,1 2 +0.455P s,1 Yuan, the load utilization benefit function of the adjustable load is h 1 (P L,1 ) = -6.67 × 10 -4 ×P L,1 2 +0.66P L,1 Yuan, of which P s,1 and P L,1 The unit is kW. This area contains 2 sets of energy storage devices. The specific parameters are shown in Table 1:

[0096] Table 1 Parameter record table

[0097] Serial number <![CDATA[S bs,i,max / kWh]]> <![CDATA[P bs,i,max / kW]]> <![CDATA[S oc,i,2m ]]> <![CDATA[S oc,i,max ]]> <![CDATA[S oc,i,min ]]> Initial state of charge 1 800 500 20.5％ 100％ 10％ 35.8％ 2 500 400 16.5％ 100％ 6％ 20.5％

[0098] The length of the period verified in this case is 15 minutes. The frequency of the power grid is 49.96Hz from the 1st minute to the 4th minute, and the frequency rises to 50.07Hz from the 5th minute to the 10th minute. A fault occurs in the 11th minute. The frequency is 50.03Hz from the 11th minute to the 15th minute. The electricity price from the 1st minute to the 4th minute is 0.596 yuan / kWh, and the electricity price from the 5th minute to the 15th minute is 0.518 yuan / kWh. The regional source, grid, load and storage initially operate in a way to support the grid frequency.

[0099] According to the proposed regional source-grid-load-storage autonomous method, the active power of regional renewable energy generation, non-renewable energy generation, energy storage, and adjustable load in each period is calculated as shown in Table 2:

[0100] Table 2 Data record table

[0101]

[0102]

[0103] It can be seen from the above table that from the 1st minute to the 4th minute, the renewable energy power generation operates in the maximum power point tracking control mode, and the two energy storages discharge to support the grid frequency. At the 4th minute, the state of charge of energy storage 2 dropped to 16.5%. In order to ensure that the regional load does not lose power in the event of a fault, energy storage 2 stops discharging at this time. According to the above table, it is easy to verify that the marginal cost of non-renewable energy power generation and the marginal benefit of adjustable loads are equal to the electricity price of 0.596 yuan / kWh. Therefore, at this time, non-renewable energy power generation and adjustable loads are operating in a state of maximum benefit;

[0104] From the 5th minute to the 10th minute, due to the increase in the grid frequency exceeding 50.05Hz, the regional source-grid-load-storage system switched from supporting the grid frequency operation mode to the regional source-load power self-balancing operation mode. It can be seen that the power input from the grid to the region is 0 at this time. In order to give priority to meeting the main goal of source-load power self-balancing, non-renewable energy power generation and adjustable loads are not operated in a way of maximizing benefits at this time. The marginal cost of non-renewable energy power generation and the marginal benefit of adjustable loads are not equal to the electricity price of 0.518 yuan / kWh, but it is easy to verify that the marginal cost of non-renewable energy power generation and the marginal benefit of adjustable loads are still equal. Therefore, under the condition of regional source-load power self-balancing, the method of the present invention has reduced the source-load resource adjustment cost as much as possible; from the 5th minute to the 6th minute, due to the adjustment rate limit of the non-renewable energy power generation function, the generated power is not immediately adjusted to the calculated active power, so the regional real-time power self-balancing is achieved by controlling the discharge of energy storage 2;

[0105] At the 11th minute, the power grid failed and the regional source-grid-load-storage system was disconnected from the grid. At the same time, the renewable energy power generation equipment tripped and disconnected from the grid due to its own protection. The table above shows that at this time, the regional load was powered by energy storage and non-renewable energy power generation, and no load loss was caused.

[0106] At the 14th minute, the power distribution automation system of the power grid completed the restoration of power supply to the non-faulty sections, and the regional source-grid-load-storage system resumed grid-connected operation. At this time, the grid frequency was still higher than 49.95Hz, so the regional source-grid-load-storage system was still operating in the source-load power self-balancing mode. Since the state of charge of energy storage 2 was less than 16.5% at the initial moment of the 14th minute, the energy storage was controlled to charge at rated power to ensure that the regional load could be reliably powered in the event of subsequent grid failures. Charging was stopped after the state of charge was greater than 16.5% at the 15th minute.

[0107] Based on the above analysis results, it can be seen that the regional source-grid-load-storage autonomous method and system based on embedded EMS proposed in the present invention can generate a regional source-grid-load-storage autonomous control strategy that takes into account multiple objectives such as supporting the grid frequency, reserving sufficient power for regional loads in the event of a fault, and reducing the source-load resource regulation cost when the grid frequency is low. When the grid frequency is high, it can generate an autonomous control strategy that takes into account multiple objectives such as regional source-load power self-balancing, reserving sufficient power for regional loads in the event of a fault, and reducing the source-load resource regulation cost. This can achieve reliable and economic autonomous operation of regional source-grid-load-storage and coordinated operation with the large power grid.

[0108] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A regional source-grid-load-storage autonomous method based on embedded EMS, characterized in that: include: Acquiring feature data of a first object; determining, based on the characteristic data, whether the second object needs to be adjusted toward the first object; constraining the second object; By using the optimization target, the characteristic data of the first object is controlled to be stable.

2. The regional source-grid-load-storage autonomous method based on embedded EMS as claimed in claim 1, characterized in that: The characteristic data includes characteristics that can reflect the working conditions of the first object during its working process; The second object is capable of regulating the operation of the first object.

3. The regional source-grid-load-storage autonomous method based on embedded EMS as claimed in claim 2, characterized in that: When the second object adjusts the first object, constraining the second object, including but not limited to inherent constraints and conditional constraints; The inherent constraints include constraints given by the second object according to limitations of its own performance; The conditional constraints include constraints given by the second object according to conditions of a control target.

4. The regional source-grid-load-storage autonomous method based on embedded EMS as claimed in claim 3, characterized in that: The optimization goal includes controlling the second object involved in the regulation so that the control process can achieve the expected results.

5. The regional source-grid-load-storage autonomous method based on embedded EMS as claimed in claim 4, characterized in that: The prediction includes but is not limited to an objective function and an adjustment function.

6. The regional source-grid-load-storage autonomous method based on embedded EMS as claimed in claim 5, characterized in that: The power grid is taken as the first object and the energy storage system is taken as the second object; When the second object adjusts the first object, there are two adjustment modes: frequency increase and frequency decrease; In both scenarios, the inherent constraints and conditional constraints of each unit in the energy storage system include: S oc,i,2m S bs,i,max ≤S bs,i ≤S oc,i,max S bs,i,max ,i=1,L,n s S oc,1,2m -S oc,1,min =L=S oc,i,2m -S oc,i,min =L=S oc,ns,2m -S oc,ns,min Among them, S bs,i is the storage capacity of energy storage i; S bs,i,max is the rated capacity of energy storage i; S oc,i,max and S oc,i,min are the highest state of charge and the lowest state of charge of energy storage respectively; n s is the amount of energy storage; S oc,i,2m To store energy to ensure the remaining charge state of regional load power supply in case of grid failure; Among them, P m is the maximum load that may be expected in the region; T is a time length greater than 2 minutes to ensure that the energy storage can supply power to the regional load for more than 2 minutes.

7. The regional source-grid-load-storage autonomous method based on embedded EMS as claimed in claim 6, characterized in that: In the frequency reduction scenario, with the goal of reducing the source-load resource adjustment cost, the non-renewable energy generation and the load of the adjustable load are calculated through the objective function: Where p is the current electricity price; P s,j is the active power generated by non-renewable energy generation j; g j is the power generation cost function of non-renewable energy power generation j or the quotation function in the power spot market; P s,j,max is the maximum active power of non-renewable energy generation j; P L,k is the load of the adjustable load k; h k is the load utilization benefit function of the adjustable load; P L,k.max is the maximum load of the adjustable load k; In the frequency increase scenario, the goal is to achieve self-balancing of regional source-load power while taking into account the reduction of source-load resource adjustment costs, and to control renewable energy generation, non-renewable energy generation and adjustable loads: Among them, P L For non-adjustable load; P rn The active power generated by renewable energy; P rn,max is the maximum active power of renewable energy generation; c1 and c2 are constants representing target weights, and their values ​​satisfy c1>>c; When new energy or load fluctuates, the energy storage is controlled by adjusting the function to be used for regional real-time power self-balancing: Among them, P bs,i is the active power generated by energy storage i; P bs,i,max is the rated charge and discharge power of energy storage i; Γ is the oc,i,2m S bs,i,max <S bs,i <S oc,i,max S bs,i,max The energy storage number set; When the source and load adjust the power according to the optimization control model to achieve stability, the power of each energy storage is controlled to 0.

8. A regional source-grid-load-storage autonomous system based on embedded EMS using the method according to any one of claims 1 to 7, characterized in that: It includes three parts: data collection and control command issuance, regional source-grid-load-storage autonomy method, and Web display interface; The data acquisition and control instruction sending function module is based on the Modbus, MQTT, IEC104, and DL / T645 communication protocols supported by the embedded EMS. It is configured accordingly according to the communication protocols adopted by the regional load, power supply, energy storage, and power grid to realize source-grid-load-storage data acquisition. The collected data is used as the input data of the regional source-grid-load-storage autonomous method function module and stored in the embedded database. At the same time, the module receives the control instructions of the regional source-grid-load-storage autonomous method function module and sends them to the equipment; the regional source-grid-load-storage autonomous method function module is based on the data collected by the data acquisition and control instruction sending function module. The data and fixed parameter data in the embedded database are used to perform autonomous calculations of regional source-grid-load-storage, and the calculated control instructions and manual control instructions received from the Web display interface are sent to the data acquisition and control instruction sending function module, and stored in the embedded database. At the same time, the calculation result data is sent to the Web display interface; the Web display interface is based on the report and wiring diagram display functions supported by the embedded EMS, and the source-grid-load-storage device data that needs to be displayed by the regional source-grid-load-storage is associated and configured and displayed. At the same time, this module supports manual setting of control instructions on the interface and sending them to the regional source-grid-load-storage autonomous method function module.

9. A computer device comprising: A memory and a processor; the memory stores a computer program, wherein the processor implements the steps of any method as claimed in claim 1 when executing the computer program.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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