Electric heating load control method, device and system suitable for power grid regulation and control

Abstract

The invention discloses an electric heating load control method, device and system suitable for power grid regulation and control, and aims to provide an efficient and flexible solution for power grid regulation and control by fully utilizing the leading-edge sensing technology, the Internet of Things communication means and the intelligent algorithm processing capacity. According to the method, the high efficiency of system operation is ensured, the comfort and convenience of a user are fully considered while energy conservation and consumption reduction are achieved, and user-friendly control over the electric heating system is achieved; meanwhile, through the unique dynamic decomposition strategy, the change of the power grid load can be responded in real time, the distribution of power resources is optimized, the energy waste is reduced, and the stability and reliability of the power grid are improved.

Description

Technical Field

[0001] The present invention relates to a smart grid control method, and in particular to an electric heating load control method, device and system suitable for grid control. Background Art

[0002] With the energy crisis and the increasing awareness of environmental protection, the traditional centralized heating method is gradually unable to meet the needs of modern society due to its high energy consumption, low efficiency, and inflexible regulation. The popularity of electric heating has significantly increased the load of the power grid in winter, especially during the peak usage period in cold areas, which puts higher requirements on the stable operation of the power grid. The traditional power grid peak-shaving means are insufficient when facing high-power loads such as electric heating, and more flexible and efficient peak-shaving technologies and management measures need to be developed. The application of smart grid technology provides new possibilities for electric heating control. Through intelligent management, the interaction between electric heating equipment and the power grid can be realized, and the allocation of power resources can be optimized. However, the existing intelligent management model lacks effective analysis methods for real-time fluctuating load data, users' electricity consumption behavior patterns, and the operating status of the power grid, and there is no feedback on the system response and regulation effect after the control command is issued. Therefore, the timeliness and accuracy of the precise dynamic scheduling of electric heating loads need to be improved urgently. Summary of the invention

[0003] Purpose of the invention: In view of the above problems, the present invention proposes an electric heating load control method, device and system suitable for power grid regulation, which can respond to changes in power grid load in real time, improve the timeliness and accuracy of precise dynamic scheduling of electric heating load, and optimize the allocation of power resources, reduce energy waste, and improve the stability and reliability of the power grid.

[0004] Technical solution: The technical solution adopted by the present invention is an electric heating load control method adapted to power grid regulation, comprising the following steps:

[0005] (1) Collecting adjustable resource information;

[0006] (2) Determine whether the regulation demand is executed according to the load regulation amount and verification rules output by the upper-level power grid control system; if so, proceed to the next step;

[0007] (3) Determine the adjustable resources according to the decomposition strategy, and decompose the load regulation amount to obtain the electric heating load control instruction according to the load regulation amount output by the upper-level power grid control system and the decomposition strategy;

[0008] (4) sending the electric heating load control instruction to the target regulating device;

[0009] (5) Collecting real-time adjustment status data of the adjustable terminal and collecting adjustment result data;

[0010] (6) Monitor whether the adjustable terminal status is normal. If there is an abnormality, handle the abnormal terminal;

[0011] (7) After the set control time ends, determine whether the control is effective according to the effectiveness judgment rules. If effective, calculate the evaluation result according to the post-evaluation rules and send the evaluation result to the upper-level power grid control system; if not effective, return the current real-time regulation status data and regulation result data to the upper-level power grid control system.

[0012] (8) Repeat steps (2) to (7) until the control takes effect.

[0013] The decomposition strategy can adopt any existing electric heating load decomposition scheme. As a preferred scheme of the electric heating load control method adapted to power grid regulation, the present invention proposes a proportional sharing strategy decomposition algorithm and a sorting allocation strategy decomposition algorithm.

[0014] The proportional sharing strategy decomposition algorithm includes the following steps:

[0015] (1) Calculate the comprehensive adjustment coefficient based on the normalized evaluation coefficients of each resource dimension and the influencing factors of different allocation preferences;

[0016] (2) Calculate the allocation adjustment amount of each terminal based on the comprehensive adjustment coefficient and the upper limit of the adjustment capacity of each adjustable resource;

[0017] (3) Determine whether the adjustment amount of all resource allocations is not greater than the corresponding resource adjustment capacity. If so, generate a decomposition result; if not, proceed to the next step;

[0018] (4) Calculate the unallocated total adjustment amount and unallocated resources, and return to step (1) to allocate again until the load adjustment amount is allocated.

[0019] According to the normalized evaluation coefficients of each dimension of resources and the influencing factors of different allocation preferences, the comprehensive adjustment coefficient is calculated as follows:

[0020] a k =η k1 w1+η k2 w2+η k3 w3

[0021] where a k is the comprehensive adjustment coefficient of terminal k, w represents the influencing factor of different allocation preferences, w1 represents the adjustment comfort allocation factor, w2 represents the adjustment performance allocation factor, and w3 represents the resource importance allocation factor; w1+w2+w3=1; η k1 , η k2 , η k3is the normalized evaluation coefficient of each dimension of the resource, and the normalized range is [0,1], η k1 represents the adjustment comfort coefficient corresponding to terminal k; η k2 represents the regulation performance coefficient corresponding to terminal k; η k3 Represents the importance coefficient of the load corresponding to resource k.

[0022] According to the comprehensive adjustment coefficient and the upper limit of the adjustment capacity of each adjustable resource, the allocation adjustment amount of each terminal is calculated as follows:

[0023] D k =a k C k / (a1C1+a2C2+...+a n C n )*P total

[0024] Where C1, C2, ...C n are the upper limits of the adjustment capabilities of n adjustable resources, a1~a n is the comprehensive adjustment coefficient of n adjustable resources, P total is the total demand for regulation issued by the dispatcher, a k is the comprehensive adjustment coefficient of terminal k, C k is the upper limit of the adjustment capability of terminal k, D k is the allocation adjustment amount of terminal k.

[0025] The sorting distribution strategy decomposition algorithm comprises the following steps:

[0026] (1) Configure the attribute values ​​used for sorting;

[0027] (2) Sort all adjustable resources according to the sorted attribute values;

[0028] (3) Obtain the highest ranked resource among the remaining unallocated resources;

[0029] (4) allocating the adjustment amount according to the adjustment capacity of the resource with the highest ranking among the remaining unallocated resources;

[0030] (5) Repeat steps (3) to (4) until the load adjustment amount is allocated.

[0031] The attributes designed for sorting in the sorting distribution decomposition algorithm include: taking the load importance level as the first priority sorting attribute, and the composite attribute of user comfort impact and regulation frequency as the second priority sorting attribute.

[0032] The present invention proposes an electric heating load control device adapted to power grid regulation, comprising a control unit and a power detection unit, a temperature detection unit, a power regulation unit, an output interface and a remote control interface connected to the control unit;

[0033] The power detection unit is used to collect adjustable resource information and real-time adjustment status data of the adjustable terminal;

[0034] The control unit is used for: timing control; and is also used for: monitoring whether the state of the adjustable terminal is normal, and if there is an abnormality, processing the abnormal terminal; after the set control time ends, judging whether the control is effective according to the validity judgment rule, and if effective, calculating the evaluation result according to the post-evaluation rule;

[0035] The temperature detection unit is used to: collect adjustment result data;

[0036] The power regulation unit is used to: determine whether the regulation demand is executed according to the load regulation amount and verification rules output by the upper-level power grid control system; determine the adjustable resources according to the decomposition strategy, and decompose the load regulation amount to obtain the electric heating load control instruction according to the load regulation amount and decomposition strategy output by the upper-level power grid control system;

[0037] The output interface is used to send the electric heating load control instruction to the target regulating device;

[0038] The remote control interface is used to receive the load regulation value output by the upper-level power grid control system, and is also used to send the evaluation result to the upper-level power grid control system, and return the current real-time regulation status data and regulation result data to the upper-level power grid control system.

[0039] As a preferred solution for the electric heating load control device adapted to grid regulation, the real-time adjustment status data of the adjustable terminal includes: the current power of the electric heating load, the current energy consumption, and the estimated trend of electric energy consumption.

[0040] The adjustment result data includes: ambient temperature and user set temperature.

[0041] The present invention also proposes an aggregate control system for centralized electric heating, including the electric heating load control device adapted to power grid regulation, which is connected between the upper-level power grid control system and the electric heating load.

[0042] Beneficial effects: Compared with the prior art, the present invention has the following advantages: the method is based on a series of algorithm models, which are carefully designed to comprehensively consider and analyze real-time load data, user electricity consumption behavior patterns and the operating status of the power grid, so as to achieve accurate dynamic decomposition and intelligent scheduling of electric heating loads; the strategy not only stays at the theoretical level, but can convert complex decision-making logic into specific and executable electricity instructions, which are implemented through highly integrated intelligent devices, thereby finely managing the centralized electric heating system. This management method not only ensures the high efficiency of system operation, but also fully considers the user's comfort and convenience while saving energy and reducing consumption, and realizes user-friendly control of the electric heating system; the system and device of the present invention, through its unique dynamic decomposition strategy, can respond to changes in power grid load in real time, optimize the allocation of power resources, reduce energy waste, and improve the stability and reliability of the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 It is an overall flow chart of the electric heating load control method adapted to power grid regulation described in the present invention;

[0044] Figure 2 It is a flow chart of the proportional sharing strategy decomposition algorithm of the present invention;

[0045] Figure 3 It is a flow chart of the sorting distribution strategy decomposition algorithm of the present invention;

[0046] Figure 4 It is an application schematic diagram of the electric heating load device adapted to power grid regulation described in the present invention. DETAILED DESCRIPTION

[0047] The technical solution of the present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0048] Example 1

[0049] The electric heating load control method adapted to grid regulation of the present invention, after receiving the overall regulation demand of load regulation, the overall control process is as follows: Figure 1 As shown, the following steps are included:

[0050] (1) Collecting adjustable resource information;

[0051] (2) Determine whether the regulation demand is executed according to the load regulation amount and verification rules output by the upper-level power grid control system; if so, proceed to the next step;

[0052] (3) Determine the adjustable resources according to the decomposition strategy, and decompose the load regulation amount to obtain the electric heating load control instruction according to the load regulation amount output by the upper-level power grid control system and the decomposition strategy;

[0053] (4) sending the electric heating load control instruction to the target regulating device;

[0054] (5) Collect real-time adjustment status and adjustment result data;

[0055] (6) Monitor whether the adjustable terminal status is normal. If there is an abnormality, handle the abnormal terminal;

[0056] (7) After the set control time ends, determine whether the control is effective according to the effectiveness judgment rules. If effective, calculate the evaluation result according to the post-evaluation rules and send the evaluation result to the upper-level power grid control system; if not effective, return the current real-time adjustment status and adjustment result data to the upper-level power grid control system.

[0057] (8) Repeat steps (2) to (7) until the control takes effect.

[0058] Among them, the verification rules in step (2) are mainly: 1. Verification of the equipment operating status. If it is currently under control, no adjustment will be made; 2. Verification of abnormal data. If the adjustment amount is obviously wrong and exceeds the capacity of the equipment, no adjustment will be made.

[0059] Step (3) performs regulation demand decomposition according to the specified strategy rules, including a proportional allocation strategy decomposition algorithm and a ranking allocation strategy decomposition algorithm. The following is a detailed introduction to the two algorithms.

[0060] The proportional allocation strategy decomposition algorithm is mainly aimed at the adjustable resources of the remote control method. It takes the adjustment capacity of the adjustable resources (the upper limit of the adjustment) as the basis, integrates other adjustment characteristics of the resources, forms a standardized comprehensive adjustment coefficient, and then allocates it proportionally according to the standardized adjustment capacity value. The key point is how to quantify the comprehensive allocation coefficient in different scenarios. Adjustable resources refer to equipment / devices that can set target adjustment power within a certain power range. The larger the comprehensive adjustment coefficient, the more suitable the resource is for participating in regulation.

[0061] The most basic allocation method is to allocate the total amount of adjustment proportionally according to the ratio of the adjustable resource to the total adjustable capacity of all resources, and generate the adjustment amount of each adjustable resource. This algorithm only considers the adjustment capacity of each adjustable resource, but the differences in other adjustment characteristics of each adjustable resource also affect the allocation effect. Therefore, in actual use, the historical adjustment performance of the resource, the importance of the load, and the impact on the user's electricity comfort after adjustment will also be taken into account to normalize the adjustment capacity. The specific allocation process of the final strategy decomposition algorithm is as follows Figure 2 As shown, it includes:

[0062] (1) Calculate the comprehensive adjustment coefficient based on the normalized evaluation coefficients of each resource dimension and the influencing factors of different allocation preferences;

[0063] (2) Calculate the allocation adjustment amount D of terminal k based on the comprehensive adjustment coefficient and the upper limit of the adjustment capacity of each adjustable resource. k ;

[0064] (3) Determine whether the adjustment amount of all resource allocations is not greater than the corresponding resource adjustment capacity. If so, generate a decomposition result; if not, proceed to the next step;

[0065] (4) Calculate the unallocated total adjustment amount and unallocated resources, and return to step (1) to allocate again.

[0066] Assume that the upper limits of the adjustment capacity of n adjustable resources are: C1, C2, ...C n , the total demand for regulation issued by the dispatcher is: P total , then the allocation adjustment amount of terminal k is:

[0067] D k =a k C k / (a1C1+a2C2+...+a n C n )*P total , if D k >C k Then D k =C k , the remaining adjustment amount is then allocated to the remaining resources in the above manner.

[0068] where a k It is the comprehensive adjustment coefficient of the adjustable resource, which represents the quantitative index of whether the adjustable resource is suitable for regulation. The higher the value, the more suitable the resource is for regulation. The calculation method is as follows:

[0069] a k =η k1 w1+η k2 w2+η k3 w3

[0070] Among them, w represents the influencing factor of different allocation preferences. Here, w1, w2, and w3 are taken as examples. w1 represents the adjustment comfort allocation factor, w2 represents the adjustment performance allocation factor, and w3 represents the resource importance allocation factor. w1+w2+w3=1. The specific allocation value is determined according to actual usage needs. The more important the preference, the larger the corresponding allocation factor.

[0071] η k1 , η k2 , η k3 is the normalized evaluation coefficient of each dimension of the resource, and the normalized range is [0,1], ηk1 Represents the adjustment comfort coefficient corresponding to resource k. The larger the coefficient, the smaller the impact on comfort after adjustment. η k2 Represents the adjustment performance coefficient corresponding to resource k. The larger the coefficient, the more stable the terminal adjustment. k3 Represents the importance coefficient of the load corresponding to resource k. The larger the coefficient, the lower the importance of the resource. The coefficient is reported by the terminal or calculated by the system based on basic data.

[0072] The sorting allocation strategy decomposition algorithm can select one or more attributes of resources as the sorting basis for all adjustable resources in remote adjustment and remote control mode, and allocate them in sequence according to the sorting order (allocate according to the upper limit of adjustment). The attributes used for sorting comparison can be either single attributes, such as adjustment cost, importance level, etc., or composite attributes, such as forming a composite attribute of adjustment reliability and participation frequency. If multiple attributes are selected for resource sorting, it is necessary to determine the priority of each attribute, compare the attributes with higher priority first, and then compare the attributes with the next priority if the attribute values ​​of this level are the same. Remote control mode refers to resources that can be switched on and off.

[0073] The sorting allocation strategy decomposition algorithm is relatively simple. It mainly sorts according to the specified rules and then allocates them in order from high to low. Figure 3 As shown. The following steps are included:

[0074] (1) Configure the attribute values ​​used for sorting;

[0075] (2) Sort all adjustable resources according to the sorted attribute values;

[0076] (3) Obtain the highest ranked resource among the remaining unallocated resources;

[0077] (4) allocating the adjustment amount according to the adjustment capacity of the resource with the highest ranking among the remaining unallocated resources;

[0078] (5) Repeat steps (3) to (4) until the load adjustment amount is allocated.

[0079] The key to the sorting distribution decomposition algorithm is to design the attributes used for sorting. For example, the load importance level is used as the first priority sorting attribute, and the attribute value used for sorting is configured to be 1 to 100; the composite attribute of user comfort impact and regulation frequency is used as the second priority sorting attribute, and the attribute value used for sorting is configured to be 1 to 200.

[0080] Example 2

[0081] The present invention provides an electric heating load device adapted to power grid regulation, which realizes the optimized operation and efficient management of the electric heating system by integrating innovative market trading mechanisms, dynamic power trading strategies, comprehensive safety control systems and flexible emergency control schemes. The device includes a control unit and a power detection unit, a temperature detection unit, a power regulation unit, an output interface and a remote control interface connected to the control unit;

[0082] The power detection unit is used to collect adjustable resource information and real-time adjustment status data of the adjustable terminal;

[0083] The control unit is used for: timing control; also used for: monitoring whether the adjustable terminal state is normal, if there is an abnormality, processing the abnormal terminal; after the set control time ends, judging whether the control is effective according to the validity judgment rule, and if effective, calculating the evaluation result according to the post-evaluation rule;

[0084] The temperature detection unit is used to: collect adjustment result data;

[0085] The power regulation unit is used to: determine whether the regulation demand is executed according to the load regulation amount and verification rules output by the upper-level power grid control system; determine the adjustable resources according to the decomposition strategy, and decompose the load regulation amount to obtain the electric heating load control instruction according to the load regulation amount and decomposition strategy output by the upper-level power grid control system;

[0086] Output interface: used to send the electric heating load control instruction to the target regulating device;

[0087] Remote control interface: used to receive the load regulation value output by the upper-level power grid control system, and also used to: send the evaluation result to the upper-level power grid control system, and return the current real-time regulation status data and regulation result data to the upper-level power grid control system.

[0088] The application principle of electric heating load device adapted to grid regulation is as follows Figure 4 As shown, the specific operations include:

[0089] The fusion terminal is connected to the boiler controller via Modbus RTU or Modbus TCP protocol. The choice of these two protocols can be flexibly selected according to the site conditions and equipment compatibility to ensure the stability and efficiency of communication.

[0090] Data collection: After the connection is established, the fusion terminal collects data from the boiler controller in real time, including but not limited to key parameters such as power, current, voltage and temperature, as the basis for subsequent processing and analysis.

[0091] Data processing: The built-in supporting APP performs preliminary processing on the collected data, including data cleaning and format conversion, to facilitate further analysis and display of the data.

[0092] The fusion terminal uploads the processed data to the main station system, including key information such as power, current, voltage and temperature, so that the remote monitoring system can obtain the operating status of the boiler in real time, discover and deal with potential problems in time, and improve the reliability and stability of the system.

[0093] The relay module and the loop circuit modification are used to collect the loop switch status, and the precise control of the loop status is achieved by modifying the original loop circuit. The application of the relay module improves the safety and reliability of the system.

[0094] Zero-line control utilizes the zero-line control loop status to simplify the control logic, reduce the complexity of the system, and improve the reliability and safety of control.

[0095] The application of temperature sensors, temperature sensors and temperature sensing lines are used together to accurately collect the boiler outlet and return water temperatures, which are used to monitor the operating status and heating effect of the boiler. The collected temperature data is transmitted to the fusion terminal through the 485 line to realize remote monitoring and analysis of temperature data.

[0096] Power distribution monitoring, the terminal monitoring unit is mainly used for power distribution monitoring, including electrical parameter monitoring, fault monitoring, etc. These monitoring functions ensure the stable operation and safety of the system.

[0097] Current and voltage monitoring: The conventional current and voltage monitoring functions ensure that the electric heating system operates within a safe current and voltage range. That is, monitor whether the adjustable terminal status is normal. If there is an abnormality, the abnormal terminal will be processed.

[0098] Example 3

[0099] The present invention provides a centralized electric heating aggregation control system (i.e., a flexible load control system), including an electric heating load control device adapted to power grid control, and the electric heating load control device adapted to power grid control is connected between the upper-level power grid control system and the electric heating load. The master station platform side can configure the IP and port of the device side to communicate with the device side, encrypt the transmission module, and collect the electric meter configuration. In order to protect the security of the data, the power detection module will encrypt the detected data when transmitting it to the main server to prevent the data from being illegally obtained or tampered with. The use of encryption to transmit data not only ensures the security of the data, but also realizes the rapid transmission of data, and improves the response speed of the system.

[0100] The present invention has significant beneficial effects compared with the prior art through technical innovations such as timely power detection of the electric boiler circuit, multi-point temperature analysis, data communication transmission, real-time data detection, reasonable distribution of heating power, cooperation with user big data analysis module and improvement of user experience. Timely power detection ensures the stability and adequacy of power supply by real-time monitoring of the power situation of the electric boiler circuit, and avoids heating interruption caused by power problems. Multi-point temperature analysis uses the temperature acquisition module to measure and analyze multiple points, which can more accurately understand the temperature distribution of the heating system and provide a basis for subsequent adjustment. Data communication transmission: The collected data is sent to the platform side through data communication technology, which realizes remote monitoring and management of data and improves the intelligence level of the system. Real-time data detection enables users to more conveniently select and adjust heating power through real-time detection of electric boiler data, which improves the user's convenience. Reasonable distribution of heating power can reasonably distribute heating power according to real-time data detection and user needs, avoids energy waste and improves energy utilization efficiency.

[0101] Data acquisition is the process of obtaining raw data from the boiler controller, while data processing involves operations such as cleaning, conversion, integration, analysis and encryption of raw data to make it suitable for transmission, analysis and final decision support. These two processes are crucial steps in intelligent control systems and ensure the quality and availability of data. Real-time acquisition, after the fusion terminal establishes a connection with the boiler controller, it starts to collect data in real time. These data include key parameters such as power, current, voltage, and temperature. According to the set time interval, the fusion terminal periodically reads data from the boiler controller to ensure that the latest operating information is obtained. The collected data may include analog quantities (such as temperature and pressure), digital quantities (such as equipment status), cumulative quantities (such as energy consumption), etc. The collected data is first temporarily stored in the memory of the fusion terminal or boiler controller, waiting for further processing. The collected data is preliminarily processed, including removing outliers, correcting errors, filling missing values, etc., to maintain the accuracy and integrity of the data and convert the data into a unified format for subsequent analysis and display, such as converting voltage and current into standard units. If there are multiple boilers or multiple sensors in the system, it may be necessary to integrate data from different sources to form a consistent data set. Analyze the data trends over time to identify patterns and regularities, such as peak hours of energy consumption, temperature fluctuation ranges, etc. Detect anomalies in the data by setting thresholds or using algorithms, such as a sudden increase in current that may indicate a device failure. To protect data security, especially during data transmission, data may need to be encrypted. Package the processed data and prepare for transmission over the network to the main station system or cloud platform for further analysis and storage.

[0102] In the centralized electric heating aggregation control system, transformers (current transformers CT and voltage transformers VT) are used to monitor current and voltage. Transformers can proportionally reduce high current and high voltage values ​​so that monitoring equipment can safely measure data. The terminal monitoring unit collects current and voltage data from the transformer and transmits the data to the energy controller through the RS-485 serial communication standard (RS-485 is a differential signal transmission method that supports long-distance, multi-node networks and is suitable for industrial environments). The switch status information of the circuit is collected by modifying the line of the original circuit. It is usually necessary to connect a relay to the circuit to detect and control the opening and closing state of the circuit. The zero line (neutral line) is used to control the state of the circuit, and the live line (phase line) is used to collect the actual current state. The live line circuit state is sent to the fusion terminal via RS-485 communication and Modbus protocol. Modbus is a communication protocol used to connect industrial equipment and is widely used in RS-485 networks. The temperature control line probe is connected to the temperature sensor to collect temperature data and send this data to the fusion terminal. The fusion terminal collects all the above data (power data, circuit status, temperature, etc.) and processes them. The data is transmitted through the APN (Virtual Private Network) private network to ensure the security of data transmission. Through the network firewall, the data is securely sent to the secure access area and then transmitted to the main station platform.

Claims

1. An electric heating load control method adapted to power grid regulation, characterized in that: The following steps are involved: (1) Collecting adjustable resource information; (2) Determine whether the regulation demand is executed according to the load regulation amount and verification rules output by the upper-level power grid control system; if so, proceed to the next step; (3) Determine the adjustable resources according to the decomposition strategy, and decompose the load regulation amount to obtain the electric heating load control instruction according to the load regulation amount output by the upper-level power grid control system and the decomposition strategy; (4) sending the electric heating load control instruction to the target regulating device; (5) Collecting real-time adjustment status data of the adjustable terminal and collecting adjustment result data; (6) Monitor whether the adjustable terminal status is normal. If there is an abnormality, handle the abnormal terminal; (7) After the set control time ends, determine whether the control is effective according to the effectiveness judgment rules. If effective, calculate the evaluation result according to the post-evaluation rules and send the evaluation result to the upper-level power grid control system; if not effective, return the current real-time regulation status data and regulation result data to the upper-level power grid control system. (8) Repeat steps (2) to (7) until the control takes effect.

2. The electric heating load control method adapted to power grid regulation according to claim 1 is characterized in that: The decomposition strategy includes a proportional allocation type strategy decomposition algorithm and a sorting allocation type strategy decomposition algorithm.

3. The electric heating load control method adapted to power grid regulation according to claim 1 is characterized in that: The proportional sharing strategy decomposition algorithm includes the following steps: (1) Calculate the comprehensive adjustment coefficient based on the normalized evaluation coefficients of each resource dimension and the influencing factors of different allocation preferences; (2) Calculate the allocation adjustment amount of each terminal based on the comprehensive adjustment coefficient and the upper limit of the adjustment capacity of each adjustable resource; (3) Determine whether the adjustment amount of all resource allocations is not greater than the corresponding resource adjustment capacity. If so, generate a decomposition result; if not, proceed to the next step; (4) Calculate the unallocated total adjustment amount and unallocated resources, and return to step (1) to allocate again until the load adjustment amount is allocated.

4. The electric heating load control method adapted to power grid regulation according to claim 1 is characterized in that: According to the normalized evaluation coefficients of each dimension of resources and the influencing factors of different allocation preferences, the comprehensive adjustment coefficient is calculated as follows: a k =the k1 w1+n k2 w2+n k3 w3 where a k is the comprehensive adjustment coefficient of terminal k, w represents the influencing factor of different allocation preferences, w1 represents the adjustment comfort allocation factor, w2 represents the adjustment performance allocation factor, and w3 represents the resource importance allocation factor; w1+w2+w3=1; η k1 , η k2 , η k3 is the normalized evaluation coefficient of each dimension of the resource, and the normalized range is [0,1], η k1 represents the adjustment comfort coefficient corresponding to terminal k; η k2 represents the regulation performance coefficient corresponding to terminal k; η k3 Represents the importance coefficient of the load corresponding to resource k; According to the comprehensive adjustment coefficient and the upper limit of the adjustment capacity of each adjustable resource, the allocation adjustment amount of each terminal is calculated as follows: D k =a k C k / (a1C1+a2C2+...+a n C n )*P total Where C1, C2, ...C n are the upper limits of the adjustment capabilities of n adjustable resources, a1~a n is the comprehensive adjustment coefficient of n adjustable resources, P total is the total demand for regulation issued by the dispatcher, a k is the comprehensive adjustment coefficient of terminal k, C k is the upper limit of the regulation capability of terminal k, D k is the allocation adjustment amount of terminal k.

5. The electric heating load control method adapted to power grid regulation according to claim 1 is characterized in that: The sorting distribution strategy decomposition algorithm comprises the following steps: (1) Configure the attribute values ​​used for sorting; (2) Sort all adjustable resources according to the sorted attribute values; (3) Obtain the highest ranked resource among the remaining unallocated resources; (4) allocating the adjustment amount according to the adjustment capacity of the resource with the highest ranking among the remaining unallocated resources; (5) Repeat steps (3) to (4) until the load adjustment amount is allocated.

6. The electric heating load control method adapted to power grid regulation according to claim 5 is characterized in that: The attributes designed for sorting in the sorting distribution decomposition algorithm include: taking the load importance level as the first priority sorting attribute, and the composite attribute of user comfort impact and regulation frequency as the second priority sorting attribute.

7. An electric heating load control device adapted to power grid regulation, characterized in that: It includes a control unit and a power detection unit, a temperature detection unit, a power regulation unit, an output interface and a remote control interface connected to the control unit; The power detection unit is used to collect adjustable resource information and real-time adjustment status data of the adjustable terminal; The control unit is used for: timing control; and is also used for: monitoring whether the state of the adjustable terminal is normal, and if there is an abnormality, processing the abnormal terminal; after the set control time ends, judging whether the control is effective according to the validity judgment rule, and if effective, calculating the evaluation result according to the post-evaluation rule; The temperature detection unit is used to: collect adjustment result data; The power regulation unit is used to: determine whether the regulation demand is executed according to the load regulation amount and verification rules output by the upper-level power grid control system; determine the adjustable resources according to the decomposition strategy, and decompose the load regulation amount to obtain the electric heating load control instruction according to the load regulation amount and decomposition strategy output by the upper-level power grid control system; The output interface is used to send the electric heating load control instruction to the target regulating device; The remote control interface is used to receive the load regulation value output by the upper-level power grid control system, and is also used to send the evaluation result to the upper-level power grid control system, and return the current real-time regulation status data and regulation result data to the upper-level power grid control system.

8. The electric heating load control method adapted to power grid regulation according to claim 1 is characterized in that: The real-time adjustment status data of the adjustable terminal includes: the current power of the electric heating load, the current energy consumption, and the estimated power consumption trend.

9. The electric heating load control method adapted to power grid regulation according to claim 1 is characterized in that: The adjustment result data includes: ambient temperature and user set temperature.

10. A centralized electric heating control system, characterized in that: It comprises the electric heating load control device adapted to grid regulation as described in any one of claims 7 to 9, wherein the electric heating load control device adapted to grid regulation is connected between the upper-level grid control system and the electric heating load.

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