County power grid comprehensive regulation and control system and method comprehensively considering distributed power generation consumption and energy storage benefits

Abstract

The invention discloses a county power grid comprehensive regulation and control system and method comprehensively considering distributed power generation absorption and energy storage benefits, and the system comprises a data collection unit which is used for collecting power grid operation data, photovoltaic power generation capacity, wind power generation capacity and an energy storage state in real time; the control unit is used for deciding an energy storage operation strategy, a distributed power generation operation strategy and a county power grid branch line interconnection switch connection strategy according to the collected data; the execution unit is used for executing the decision of the control unit and regulating power grid operation; through real-time data collection, intelligent control decision and automatic execution, an energy storage operation strategy, a distributed power generation operation strategy and a county power grid branch line interconnection switch connection strategy are optimized, and maximization of power grid economic benefits and optimization of distributed power generation consumption are realized.

Description

Technical Field

[0001] The present invention relates to a county power grid integrated control system and method, and in particular to a county power grid integrated control system and method that comprehensively considers distributed power generation, consumption and energy storage benefits, and belongs to the technical field of power grid control. Background Art

[0002] With the large-scale grid connection of renewable energy, the distribution network faces the trade-off between economy, stability and renewable energy absorption capacity. Single-objective optimization methods are difficult to meet these requirements at the same time.

[0003] At present, distributed generation, especially photovoltaic and wind power generation, is continuously increasing its penetration rate in the power grid. However, the volatility and unpredictability of these distributed generation resources pose challenges to grid regulation. At the same time, as an important means of grid regulation, the energy storage system's charging and discharging strategy has a significant impact on the stability and economic benefits of the grid. The present invention aims to optimize the operation of distributed generation and energy storage systems through intelligent regulation, thereby improving the regulation efficiency and economy of the power grid. In contrast, the patent represented by application number CN202311499035.X does not consider economic benefits. Summary of the invention

[0004] Purpose of the invention: The purpose of the present invention is to provide a county power grid comprehensive control system and method that can improve the utilization rate of photovoltaic and wind power generation and comprehensively consider the benefits of distributed power generation, consumption and energy storage.

[0005] Technical solution: The present invention provides a county power grid comprehensive control system that comprehensively considers the benefits of distributed generation, consumption and energy storage, including:

[0006] Data collection unit, used to collect real-time grid operation data, photovoltaic power generation, wind power generation and energy storage status;

[0007] A control unit is used to make decisions on energy storage operation strategy, distributed generation operation strategy and county power grid branch line connection and switching connection strategy based on the collected data;

[0008] The execution unit is used to execute the decisions of the control unit and regulate the operation of the power grid.

[0009] Furthermore, the data collection unit comprises:

[0010] Photovoltaic power generation monitoring module, used to collect photovoltaic power generation data;

[0011] Wind power generation monitoring module, used to collect wind power generation data;

[0012] A power grid operation monitoring module, used to collect power grid operation data;

[0013] The energy storage system monitoring module is used to collect energy storage status data.

[0014] Furthermore, the data collection unit also includes a preset data collection frequency, and pre-processes the collected data, and stores the pre-processed data in a database, wherein the pre-processing includes:

[0015] The initially collected data are filled with missing data; when the data at a certain moment is missing, the weighted average of the data at the two moments before and after is used to fill the missing data; when the data at a certain time period is missing, the Lagrange interpolation method is used to fill the missing data;

[0016] Clean the filled data and use wavelet transform to remove outliers and noise;

[0017] The minimum-maximum normalization is used for standardization to convert the cleaned data into a unified dimension;

[0018] Features are extracted from the standardized data, including electricity sales price, grid load demand, photovoltaic power generation output power, wind power generation output power, energy storage discharge power, battery replacement cost, battery design cycle life, battery usage cycle number, time, and capacity parameters.

[0019] Furthermore, the control unit comprises:

[0020] The energy storage operation strategy module is used to determine the charging and discharging plan of the energy storage system and optimize the energy storage benefits through the benefit optimization model;

[0021] Distributed generation operation strategy module, which is used to optimize the output of photovoltaic and wind power generation through output optimization model, and reduce the abandonment of photovoltaic and wind power;

[0022] The county power grid branch line interconnection switch interconnection strategy module is used to adjust the interconnection status of the branch line interconnection switch according to the power grid load and electricity price by adjusting the optimization model.

[0023] Furthermore, the energy storage operation strategy module adopts a linear programming method to solve a benefit optimization model, and the benefit optimization model is as follows:

[0024]

[0025] Where T is the total number of time periods, P sell (t) is the electricity price of the power grid at time t, P charge (t) is the energy storage charging power at time t;

[0026] Set up an energy balance constraint:

[0027] P load (t) = P grid (t)+P discharge(t)-P charge (t)-P pv (t)-P wind (t)

[0028] Among them, P discharge (t) is the energy storage discharge power at time t, P grid (t) is the power obtained from the grid at time t, P load (t) is the total load power at time t, P pv (t) is the photovoltaic power generation power, P wind (t) is the wind power generation power;

[0029] To set capacity limits:

[0030] E min ≤E(t)≤E max

[0031] Among them, E(t) is the energy storage state at time t, E min and E max is the minimum and maximum power of the energy storage system;

[0032] To set the power constraint:

[0033]

[0034] Among them, P charge_max and P discharge_max are the maximum charging power and the maximum discharging power respectively;

[0035] Furthermore, the output optimization model of the distributed generation operation strategy module is as follows:

[0036] Set the objective function as follows:

[0037] P PV (t)+P Wind (t)+P Storage (t)≈L(t)

[0038] Where L(t) is the grid load demand at time t, P PV (t) is the output power of photovoltaic power generation at time t, P Wind (t) is the output power of wind power generation at time t, P Storage (t) is the power of the energy storage system at time t;

[0039] Set charging constraints:

[0040]

[0041] Where SOC(t) is the charging state of the energy storage system at time t; D chargeis the charging signal of the energy storage system. When the value is 0, it means not to execute, and when the value is 1, it means to execute. ANFIS() is an adaptive neural network model used to determine the control priority.

[0042] Set the discharge constraints:

[0043]

[0044] Among them, D discharge It is the discharge signal of the energy storage system. When the value is 0, it means not to execute, and when the value is 1, it means to execute.

[0045] The energy storage of the energy storage operation strategy module and the discharge of the distributed generation operation strategy module are both based on the priority scheduling predicted by ANFIS:

[0046]

[0047] in, is the load demand of branch line i, is the sum of load demands; Priority indicates the priority of regulation, Priority∈{1,2,3,4}, where level 1 represents no regulation, 2 represents energy storage, 3 represents discharge, and 4 represents priority discharge; ANFIS is based on the input value SOC(t),P sell (t) and The historical data is used for learning, and the output value is the Priority at the current time t.

[0048] Furthermore, the fuzzy rules of the ANFIS are designed as follows:

[0049] When SOC(t) is not saturated, P sell (t) is a low price, For low demand, the Priority is rated as energy storage;

[0050] When SOC(t) is not saturated, P sell (t) is a low price, For high demand, the Priority is rated as discharge;

[0051] When SOC(t) is not saturated, P sell (t) is a high price, For low demand, Priority assessment does not participate in regulation;

[0052] When SOC(t) is not saturated, P sell (t) is a high price, For high demand, the Priority is rated as discharge;

[0053] When SOC(t) is saturated, Psell (t) is a low price, For low demand, the Priority is assessed as not participating in regulation;

[0054] When SOC(t) is saturated, P sell (t) is a low price, For high demand, the Priority is rated as discharge;

[0055] When SOC(t) is saturated, P sell (t) is a high price, For low demand, the Priority is assessed as not participating in regulation;

[0056] When SOC(t) is saturated, P sell (t) is the high price, ∑ i For high demand, Priority is rated as priority discharge;

[0057] The fuzzy formula is described as follows:

[0058]

[0059] Furthermore, the adjustment optimization model of the county power grid branch line connection switch interconnection strategy module is as follows:

[0060] Set the objective function:

[0061]

[0062] Among them, P sell (t) is the electricity price of the power grid at time t, P discharge (t) is the energy storage discharge power at time t, is the operating cost of tie switch j;

[0063] Set up constraints:

[0064]

[0065] in, is the load demand of branch line i, is the power transferred by tie switch j, is the energy storage discharge power of branch line i,

[0066] Energy storage discharge cost of branch line i as follows:

[0067]

[0068] Among them, C replace is the battery maintenance cost, N cycleDesign cycle life for the battery, N used The number of battery cycles.

[0069] Furthermore, the execution unit includes:

[0070] Energy storage system execution interface: responsible for receiving control instructions and controlling the charging and discharging operations of energy storage equipment;

[0071] Distributed generation execution interface: responsible for receiving control instructions and adjusting the output of photovoltaic and wind power generation systems;

[0072] Tie switch control interface: responsible for receiving control instructions and executing the connection and disconnection of branch line tie switches.

[0073] Based on the same inventive concept, the present invention also provides a control method for a county power grid comprehensive control system that comprehensively considers distributed generation, consumption and energy storage benefits according to any of the above items, including:

[0074] Step 1: Collect grid operation data, photovoltaic power generation, wind power generation and energy storage status in real time;

[0075] Step 2: Determine the charging and discharging plan of the energy storage system through the benefit optimization model to optimize the energy storage benefits;

[0076] Step 3: Optimize the output of photovoltaic and wind power generation through the output optimization model to reduce the abandonment of photovoltaic and wind power;

[0077] Step 4: By adjusting the optimization model, the connection status of the branch line tie switch is adjusted according to the grid load and electricity price;

[0078] Step 5: Execute the energy storage operation strategy, distributed generation operation strategy and county power grid branch line interconnection and switching interconnection strategy output from steps 2 to 4 to regulate the operation of the power grid.

[0079] The present invention has the following beneficial effects: Compared with the prior art, the present invention reduces the phenomenon of abandoned solar and wind power by optimizing the distributed power generation operation strategy, and improves the utilization rate of photovoltaic and wind power generation; utilizes the energy storage system and the interconnection switch interconnection strategy, combined with the peak-valley electricity price difference, to achieve economic benefit optimization and reduce the grid operation cost. By adjusting the charging and discharging of the energy storage system and the connection state of the interconnection switch in real time, the grid load is effectively balanced, the stability and reliability of the grid are improved, and it shows a wide range of application prospects and practical value. BRIEF DESCRIPTION OF THE DRAWINGS

[0080] Figure 1 is a system schematic diagram of an embodiment of the present invention;

[0081] Figure 2 A schematic diagram of the design of the ANFIS auxiliary layer according to an embodiment of the present invention;

[0082] Figure 3 Schematic diagram of ANFIS auxiliary layer reasoning according to an embodiment of the present invention. DETAILED DESCRIPTION

[0083] In order to enable those skilled in the art to better understand the present application, the following will be combined with the drawings in the embodiments of the present application to show how the system and method of the present invention are applied in actual county power grids. The following implementation methods are only for illustrating the technical concept and features of the present invention, and their purpose is to enable people familiar with this technology to understand the content of the present invention and implement it accordingly, and cannot be used to limit the scope of protection of the present invention. All equivalents or modifications made according to the spirit of the present invention should be included in the scope of protection of the present invention.

[0084] like Figure 1 As shown, the control system of the county power grid comprehensive control system of this embodiment that comprehensively considers the distributed generation and energy storage benefits includes:

[0085] Data collection unit, used to collect real-time grid operation data, photovoltaic power generation, wind power generation and energy storage status;

[0086] A control unit is used to make decisions on energy storage operation strategy, distributed generation operation strategy and county power grid branch line connection and switching connection strategy based on the collected data;

[0087] The execution unit is used to execute the decisions of the control unit and regulate the operation of the power grid.

[0088] Specifically, the data collection unit includes a photovoltaic power generation monitoring module, a wind power generation monitoring module, a power grid operation monitoring module, and an energy storage system monitoring module; it is mainly used to collect power grid operation data, photovoltaic power generation, wind power generation and energy storage status in real time.

[0089] The data collection unit also includes a preset data collection frequency, which is once per minute, and pre-processes the collected data and stores the pre-processed data in a database, wherein the pre-processing includes:

[0090] Data filling: To ensure that the data are of the same time scale, the initially collected data are filled with missing data.

[0091] Data cleaning: After data filling, outliers and noise are removed to ensure data reliability.

[0092] Data standardization: After data cleaning, data of different dimensions are converted into a unified dimension to facilitate subsequent processing.

[0093] Feature extraction: After data standardization, features that have an important impact on power grid regulation are extracted.

[0094] In data filling, the present invention has two solutions for dealing with data missing:

[0095] (1) When data at a certain moment is missing, the present invention uses the weighted average of the data at the previous and next moments to fill in the missing data.

[0096] (2) When data for a certain period of time is missing, the present invention uses Lagrange interpolation to fill in the missing data.

[0097] During data cleaning, the present invention adopts wavelet transform to remove noise components.

[0098] In data normalization, the present invention adopts minimum-maximum normalization for normalization.

[0099] In feature extraction, the present invention extracts features such as electricity sales price, grid load demand, photovoltaic power generation output power, wind power generation output power, energy storage discharge power, battery replacement cost, battery design cycle life, battery usage cycle number, time, capacity and other parameters.

[0100] The preprocessed data is stored in the database for historical data analysis and long-term trend prediction.

[0101] In this system, ANFIS (Adaptive Neuro-Fuzzy Inference System) is integrated into the control unit to extract long-term trends from pre-processed historical data.

[0102] A control unit is used to make decisions on energy storage operation strategy, distributed generation operation strategy and county power grid branch line connection switching connection strategy based on the collected data and preset algorithms;

[0103] The energy storage operation strategy module is used to determine the charging and discharging plan of the energy storage system, and to achieve the best benefits based on parameters such as the electricity price and the capacity limit of the energy storage battery;

[0104] Before formulating the energy storage operation strategy, the characteristics of the energy storage system should be analyzed in depth, including key parameters such as energy storage capacity, cycle life, battery replacement and maintenance costs, etc. These parameters determine the potential role and limitations of the energy storage system in grid regulation.

[0105] The operating objectives of energy storage systems in the power grid mainly include:

[0106] Maximize economic benefits: Utilize the difference between peak and valley electricity prices to rationally arrange the charging and discharging plan of the energy storage system and reduce the operating costs of the power grid;

[0107] Support grid stability: discharge when grid load is peak or renewable energy generation is peak, charge when grid load is low or renewable energy generation is low, and balance grid supply and demand.

[0108] Construct a mathematical model of the energy storage operation strategy, including the objective function and constraints. The objective function is the economic benefit of the energy storage system operation, and the constraints include the charging and discharging restrictions of the energy storage system, the grid demand, etc. The mathematical model is as follows:

[0109] 1. Objective Function

[0110]

[0111] 2. Energy balance constraints

[0112] P load (t) = P grid (t)+P discharge (t)-P charge (t)-P pv (t)-P wind (t)

[0113] 3. Capacity Limitation

[0114] E min ≤E(t)≤E max

[0115] 4. Power Constraints

[0116]

[0117] Where: T is the total number of time periods, P sell (t) is the electricity price of the power grid at time t, P discharge (t) is the energy storage discharge power at time t. grid (t) is the power obtained from the grid at time t. charge (t) is the energy storage charging power at time t, P charge_max and P discharge_max are the maximum charging and discharging powers respectively. load (t) is the total load power at time t, P pv (t) is the photovoltaic power generation power, P wind (t) is the wind power generation power, E(t) is the energy storage state (electricity) at time t, E min and E max are the minimum and maximum capacities of the energy storage system.

[0118] The objective function is to maximize the benefits of energy storage. When the electricity price is the lowest, energy storage is carried out to maximize economic benefits. The constraints are to ensure that the charging power and discharging power meet the load range of the power grid; the battery capacity must be guaranteed to be within the capacity range, and the energy of the power grid system must be conserved.

[0119] Distributed generation operation strategy module, used to optimize the output of photovoltaic and wind power generation and reduce the abandonment of photovoltaic and wind power;

[0120] The operating objectives of distributed generation systems mainly include:

[0121] Maximizing absorption: ensuring that photovoltaic and wind power generation can be absorbed by the power grid to the greatest extent possible, reducing the phenomenon of abandoned solar and wind power.

[0122] Optimization of economic benefits: Maximize the economic benefits of distributed power generation while meeting the needs of the power grid.

[0123] Grid support: Provide necessary support to the grid by adjusting the output of distributed generation when the grid load is at peak or low.

[0124] The mathematical model of distributed generation operation strategy is constructed, including objective function and constraints. The objective function is the economic benefit of distributed generation, and the constraints include the operation limit of the power generation equipment, the grid demand, etc. The mathematical model is as follows: (1) Objective function

[0125] P PV (t)+P Wind (t)+P Storage (t)≈L(t)

[0126] Where L(t) is the grid load demand at time t. PV (t) is the output power of photovoltaic power generation at time t. Wind (t) is the output power of wind power generation at time t;

[0127] (2) Charging constraints

[0128]

[0129] Where SOC(t) is the charging state of the energy storage system at time t; D charge is the charging signal of the energy storage system. When the value is 0, it means not to execute, and when the value is 1, it means to execute. ANFIS() is an adaptive neural network model used to determine the control priority.

[0130] (3) Discharge constraint conditions

[0131]

[0132] Among them, D discharge It is the discharge signal of the energy storage system. When the value is 0, it means not to execute, and when the value is 1, it means to execute.

[0133] In this embodiment, the main goal of the design of the distributed generation operation strategy is to achieve a dynamic balance state of the load within the power grid system, which is shown in the objective function. The charging constraint condition refers to the situation when the output power of wind power generation and photovoltaic power generation is greater than the load minus the energy storage capacity, and the battery is in a state of being less than full, and the energy storage operation can be performed; the discharge constraint condition refers to the situation that the battery has reached a state of being saturated, and the discharge operation can be performed;

[0134] The energy storage strategy of the energy storage operation strategy module and the power generation strategy of the distributed generation operation strategy module are both based on the priority scheduling strategy predicted by ANFIS.

[0135]

[0136] in, is the load demand of branch line i, is the sum of load demands; Priority indicates the priority of regulation, Priority∈{1,2,3,4}, where level 1 represents no regulation, 2 represents energy storage, 3 represents discharge, and 4 represents priority discharge; ANFIS is based on the input value SOC(t),P sell (t) and The historical data is used to learn, and the output value is the Priority of the current time t;

[0137] In this embodiment, the implementation of the priority scheduling strategy predicted by ANFIS must meet the corresponding constraints before it can be implemented. The prediction result for charging must meet the constraints of the energy storage operation strategy module, and the prediction result for discharging must meet the constraints of the distributed generation operation strategy module.

[0138] In this embodiment, the ANFIS adaptive neural network is used as the priority of decision-making regulation, which is determined by SOC(t), P sell (t) and The three are used as input to assess the priority of regulation, and there are four levels:

[0139] (1) Not involved in regulation.

[0140] (2) Energy storage.

[0141] (3) Discharge.

[0142] (4) Priority discharge.

[0143] In this embodiment, the priority of (1) is represented by '1', the priority of (2) is represented by '2', the priority of (3) is represented by '3', and the priority of (4) is represented by '4'.

[0144] Among them, non-participation in regulation in (1) refers to the situation where the economic benefits of charging or discharging are not high, or the results do not meet the load demand. Situation (4) priority discharge refers to the situation where the economic benefits are the best and the load demand is best met.

[0145] In this embodiment, the fuzzy rules of ANFIS are designed as follows:

[0146] 1. When SOC(t) is not saturated, P sell (t) is a low price, For low demand, the Priority is rated as energy storage;

[0147] 2. When SOC(t) is not saturated, P sell (t) is a low price, For high demand, the Priority is rated as discharge;

[0148] 3. When SOC(t) is not saturated, P sell (t) is a high price, For low demand, Priority assessment does not participate in regulation;

[0149] 4. When SOC(t) is not saturated, P sell (t) is a high price, For high demand, the Priority is rated as discharge;

[0150] 5. When SOC(t) is saturated, P sell (t) is a low price, For low demand, the Priority is assessed as not participating in regulation;

[0151] 6. When SOC(t) is saturated, P sell (t) is a low price, For high demand, the Priority is rated as discharge;

[0152] 7. When SOC(t) is saturated, P sell (t) is a high price, For low demand, the Priority is assessed as not participating in regulation;

[0153] 8. When SOC(t) is saturated, P sell (t) is a high price, For high demand, Priority is rated as priority discharge;

[0154] like Figure 3 As shown, its fuzzy formula is described as follows:

[0155]

[0156] Its design is as follows Figure 2 shown.

[0157] The county power grid branch line interconnection switch interconnection strategy module is used to adjust the interconnection status of the branch line interconnection switch according to the power grid load and peak and valley electricity prices.

[0158] Tie switches play a key role in the power grid. Their main goal is to optimize the flow of power between branches based on the real-time load and electricity price differences of the power grid to minimize costs and maximize grid stability.

[0159] Construct a mathematical model for the interconnection switching strategy, including the objective function and constraints. The objective function is the total cost of grid operation, and the constraints include branch line capacity restrictions, grid stability requirements, etc. The mathematical model is as follows:

[0160] 1. Objective Function

[0161]

[0162] Among them, P sell (t) is the electricity price of the power grid at time t, P discharge (t) is the energy storage discharge power at time t, is the operating cost of tie switch j;

[0163] 2. Constraints

[0164]

[0165] in, is the load demand of branch line i, is the power transferred by tie switch j, is the energy storage discharge power of branch line i,

[0166] 3. Calculation method of energy storage discharge cost of branch line i

[0167]

[0168] Among them, C replace is the battery maintenance cost, N cycle Design cycle life for the battery, N used The number of battery cycles.

[0169] Among them, the formulation of the interconnection switch interconnection strategy is to maximize the economic benefits of electricity sales, that is, the maximum sales price plus the minimum cost of adjusting the interconnection switch is to maximize the economic benefits of electricity sales. The setting of constraints is to prevent the load of the interconnection branch from being overloaded, so the total load demand is required to be greater than the energy storage and transferred power of the interconnection branch.

[0170] Among them, the interconnection switch interconnection strategy is determined by the decision priority in the distributed power generation operation strategy. For the branch line with high priority, the interconnection switch adjustment interconnection strategy decision is made first. The interconnection switch that meets the constraint conditions is first determined, and then the final result is locked by the objective function. The minimum value of the interconnection switches that meet the conditions is the result of the decision. The corresponding interconnection switch is closed to achieve the effect of branch line interconnection and reduce the burden on the power system.

[0171] In this embodiment, the interconnection status of the interconnection switch is dynamically adjusted according to the real-time changes in the grid load and the fluctuations in electricity prices. Automated interconnection status adjustment is achieved. Before actual application, the effectiveness of the interconnection switch interconnection strategy is verified by simulating different grid load and electricity price scenarios. The performance of the strategy in reducing grid operation costs and improving grid stability is evaluated. The optimized interconnection switch interconnection strategy is applied to the actual grid. The interconnection status and power flow of the interconnection switch are monitored to ensure that it operates according to the established strategy, and timely adjustments are made to cope with changes in the grid state. Based on actual operation data and monitoring feedback, the interconnection switch interconnection strategy is continuously optimized and iterated. The ANFIS adaptive neural network is used to assist decision-making, so that the system can adapt to changes in grid operation and improve the accuracy and efficiency of decision-making.

[0172] The execution unit is used to execute the decisions of the control unit and regulate the operation of the power grid.

[0173] The system execution unit consists of multiple subsystems, mainly including:

[0174] Energy storage system execution interface: responsible for receiving control instructions and controlling the charging and discharging operations of energy storage equipment.

[0175] Distributed generation execution interface: responsible for receiving control instructions and adjusting the output of photovoltaic and wind power generation systems.

[0176] Tie switch control interface: responsible for receiving control instructions and executing the connection and disconnection of branch line tie switches.

[0177] The execution unit has the following steps:

[0178] S301: Control instruction analysis: the execution unit first analyzes the instruction from the control unit to clarify the operation requirements of each device, including charging and discharging power, power generation output adjustment and contact switch status.

[0179] S302: Device control logic: Develop detailed control logic for each device to ensure that the device can accurately perform operations according to control instructions. The control logic includes steps such as device startup, operation monitoring, exception handling, and device shutdown.

[0180] S303: Synchronize the execution process and coordinate the operation processes of different devices to ensure that the control instructions of the energy storage system, distributed generation system and tie switch can be executed synchronously to achieve optimal control of the power grid.

[0181] S304: Real-time data feedback. During the execution process, the operation data of the equipment is collected in real time, including the actual charging and discharging power, the actual power generation and the contact switch status, and the data is fed back to the control unit.

[0182] S305: Abnormal detection and processing. The execution unit has the ability to detect abnormalities. When the equipment operating status is abnormal or inconsistent with the control instructions, it can identify and take measures in time.

[0183] S306: User interface interaction: Provide a user interface to enable operators to monitor the operating status of the execution unit, manually input instructions or intervene in the automatic control process. The user interface should have functions such as data visualization, operation log recording and alarm prompts.

[0184] S307: Safety and reliability design ensures the safety and reliability of the execution unit, including equipment redundancy design, automatic fault switching and system self-checking mechanisms to improve the system's fault tolerance and stability.

[0185] S308: Execution effect evaluation: regularly evaluate the operation effect of the execution unit, including equipment response time, control accuracy and power grid regulation effect, to ensure that the system execution meets the expected goals.

[0186] S309: Execution record and audit, record all operation history of the execution unit, including control instructions, equipment response and operation data, etc., to facilitate operation audit and problem tracking.

[0187] A comprehensive feedback system is established that can monitor and record key indicators of grid operation in real time, including the charging and discharging status of the energy storage system, the actual output of distributed generation, the real-time status of the tie switch, and the change of grid load. The collected data is deeply analyzed and processed to extract useful information.

[0188] Establish a real-time feedback loop to ensure that the system can quickly respond to changes in the state of the power grid. When the power grid operation data deviates from expectations, the system automatically adjusts the control strategy to maintain the optimal operation of the power grid. Regularly update the optimization strategy to adapt to changes in power grid operation and changes in the external environment. Use historical data and forecasting models to predict the long-term trend of the power grid.

[0189] Based on the same inventive concept, this embodiment also provides a control method for a county power grid comprehensive control system that comprehensively considers distributed generation, consumption and energy storage benefits according to any of the above items, including:

[0190] Step 1: Collect grid operation data, photovoltaic power generation, wind power generation and energy storage status in real time;

[0191] Step 2: Determine the charging and discharging plan of the energy storage system through the benefit optimization model to optimize the energy storage benefits;

[0192] Step 3: Optimize the output of photovoltaic and wind power generation through the output optimization model to reduce the abandonment of photovoltaic and wind power;

[0193] Step 4: By adjusting the optimization model, the connection status of the branch line tie switch is adjusted according to the grid load and electricity price;

[0194] Step 5: Execute the energy storage operation strategy, distributed generation operation strategy and county power grid branch line interconnection and switching interconnection strategy output from steps 2 to 4 to regulate the operation of the power grid.

[0195] The above embodiments are only for illustrating the technical concept and features of the present invention, and their purpose is to enable people familiar with the technology to understand the content of the present invention and implement it accordingly, and they cannot be used to limit the protection scope of the present invention. Any equivalent transformation or modification made according to the spirit of the present invention should be included in the protection scope of the present invention.

Claims

1. A county power grid comprehensive control system that comprehensively considers the benefits of distributed generation, consumption and energy storage, characterized in that: include: Data collection unit, used to collect real-time grid operation data, photovoltaic power generation, wind power generation and energy storage status; A control unit is used to make decisions on energy storage operation strategy, distributed generation operation strategy and county power grid branch line connection and switching connection strategy based on the collected data; The execution unit is used to execute the decisions of the control unit and regulate the operation of the power grid.

2. The county power grid comprehensive control system that comprehensively considers distributed generation, consumption and energy storage benefits according to claim 1 is characterized in that: The data collection unit comprises: Photovoltaic power generation monitoring module, used to collect photovoltaic power generation data; Wind power generation monitoring module, used to collect wind power generation data; A power grid operation monitoring module, used to collect power grid operation data; The energy storage system monitoring module is used to collect energy storage status data.

3. The county power grid comprehensive control system that comprehensively considers distributed generation, consumption and energy storage benefits according to claim 1 is characterized in that: The data collection unit also includes a preset data collection frequency, and pre-processes the collected data, and stores the pre-processed data in a database, wherein the pre-processing includes: The initially collected data are filled with missing data; when the data at a certain moment is missing, the weighted average of the data at the two moments before and after is used to fill the missing data; when the data at a certain time period is missing, the Lagrange interpolation method is used to fill the missing data; Clean the filled data and use wavelet transform to remove outliers and noise; The minimum-maximum normalization is used for standardization to convert the cleaned data into a unified dimension; Features are extracted from the standardized data, including electricity sales price, grid load demand, photovoltaic power generation output power, wind power generation output power, energy storage discharge power, battery replacement cost, battery design cycle life, battery usage cycle number, time, and capacity parameters.

4. The county power grid comprehensive control system that comprehensively considers distributed generation, consumption and energy storage benefits according to claim 1 is characterized in that: The control unit comprises: The energy storage operation strategy module is used to determine the charging and discharging plan of the energy storage system and optimize the energy storage benefits through the benefit optimization model; Distributed generation operation strategy module, which is used to optimize the output of photovoltaic and wind power generation through output optimization model, and reduce the abandonment of photovoltaic and wind power; The county power grid branch line interconnection switch interconnection strategy module is used to adjust the interconnection status of the branch line interconnection switch according to the power grid load and electricity price by adjusting the optimization model.

5. The county power grid comprehensive control system that comprehensively considers distributed generation, consumption and energy storage benefits according to claim 4 is characterized in that: The energy storage operation strategy module uses a linear programming method to solve a benefit optimization model, which is as follows: Where T is the total number of time periods, P sell (t) is the electricity price of the power grid at time t, P charge (t) is the energy storage charging power at time t; Set up an energy balance constraint: P load (t)=P grid (t)+P discharge (t)-P charge (t)-P pv (t)-P wind (t) Among them, P discharge (t) is the energy storage discharge power at time t, P grid (t) is the power obtained from the grid at time t, P load (t) is the total load power at time t, P pv (t) is the photovoltaic power generation power, P wind (t) is the wind power generation power; To set capacity limits: E min ≤E(t)≤E max Among them, E(t) is the energy storage state at time t, E min and E max is the minimum and maximum power of the energy storage system; To set the power constraint: Among them, P charge_max and P discharge_max are the maximum charging power and the maximum discharging power respectively.

6. The county power grid comprehensive control system that comprehensively considers distributed generation, consumption and energy storage benefits according to claim 4 is characterized in that: The output optimization model of the distributed generation operation strategy module is as follows: Set the objective function as follows: P PV (t)+P Wind (t)+P Storage (t)≈L(t) Where L(t) is the grid load demand at time t, P PV (t) is the output power of photovoltaic power generation at time t, P Wind (t) is the output power of wind power generation at time t, P Storage (t) is the power of the energy storage system at time t; Set charging constraints: Where SOC(t) is the charging state of the energy storage system at time t; D charge is the charging signal of the energy storage system. When the value is 0, it means not to execute, and when the value is 1, it means to execute. ANFIS() is an adaptive neural network model used to determine the control priority. Set the discharge constraints: Among them, D discharge It is the discharge signal of the energy storage system. When the value is 0, it means not to execute, and when the value is 1, it means to execute.

7. The county power grid comprehensive control system that comprehensively considers distributed generation, consumption and energy storage benefits according to claim 4 is characterized in that: The energy storage strategy of the energy storage operation strategy module and the power generation strategy of the distributed generation operation strategy module are both based on the priority scheduling predicted by ANFIS: in, is the load demand of branch line i, is the sum of load demands; Priority indicates the priority of regulation, Priority∈{1,2,3,4}, where level 1 represents no regulation, 2 represents energy storage, 3 represents discharge, and 4 represents priority discharge; ANFIS is based on the input value SOC(t),P sell (t) and The historical data is used to learn, and the output value is the Priority of the current time t; Among them, the fuzzy rules of ANFIS are designed as follows: When SOC(t) is not saturated, P sell (t) is a low price, For low demand, the Priority is rated as energy storage; When SOC(t) is not saturated, P sell (t) is a low price, For high demand, the Priority is rated as discharge; When SOC(t) is not saturated, P sell (t) is a high price, For low demand, Priority assessment does not participate in regulation; When SOC(t) is not saturated, P sell (t) is a high price, For high demand, the Priority is rated as discharge; When SOC(t) is saturated, P sell (t) is a low price, For low demand, the Priority is assessed as not participating in regulation; When SOC(t) is saturated, P sell (t) is a low price, For high demand, the Priority is rated as discharge; When SOC(t) is saturated, P sell (t) is a high price, For low demand, the Priority is assessed as not participating in regulation; When SOC(t) is saturated, P sell (t) is a high price, For high demand, Priority is rated as priority discharge; The fuzzy formula is described as follows:

8. The county power grid comprehensive control system that comprehensively considers distributed generation, consumption and energy storage benefits according to claim 4 is characterized in that: The adjustment optimization model of the county power grid branch line connection switch interconnection strategy module is as follows: Set the objective function: Among them, P sell (t) is the electricity price of the power grid at time t, P discharge (t) is the energy storage discharge power at time t, is the operating cost of tie switch j; Set up constraints: in, is the load demand of branch line i, is the power transferred by tie switch j, is the energy storage discharge power of branch line i, Energy storage discharge cost of branch line i as follows: Among them, C replace is the battery maintenance cost, N cycle Design cycle life for the battery, N used The number of battery cycles.

9. The county power grid comprehensive control system that comprehensively considers distributed generation, consumption and energy storage benefits according to claim 1 is characterized in that: The execution unit comprises: Energy storage system execution interface: responsible for receiving control instructions and controlling the charging and discharging operations of energy storage equipment; Distributed generation execution interface: responsible for receiving control instructions and adjusting the output of photovoltaic and wind power generation systems; Tie switch control interface: responsible for receiving control instructions and executing the connection and disconnection of branch line tie switches.

10. A control method for a county power grid integrated control system that comprehensively considers distributed generation, consumption and energy storage benefits according to any one of claims 1 to 9, characterized in that: The method comprises: Step 1: Collect grid operation data, photovoltaic power generation, wind power generation and energy storage status in real time; Step 2: Determine the charging and discharging plan of the energy storage system through the benefit optimization model to optimize the energy storage benefits; Step 3: Optimize the output of photovoltaic and wind power generation through the output optimization model to reduce the abandonment of photovoltaic and wind power; Step 4: By adjusting the optimization model, the connection status of the branch line tie switch is adjusted according to the grid load and electricity price; Step 5: Execute the energy storage operation strategy, distributed generation operation strategy and county power grid branch line interconnection and switching interconnection strategy output from steps 2 to 4 to regulate the operation of the power grid.

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