New energy power consumption system and dispatching method based on multi-time scale coordination

Abstract

The present application relates to the technical field of smart grid industry, in particular to a new energy power consumption system and a dispatching method based on multi-time scale coordination. Through analyzing the correlation between the heat source and the end temperature sequence in the volume domain to determine the dynamic delay, and screening the stable working condition to identify the steady-state heat dissipation benchmark; then combining the dynamic delay and the steady-state benchmark to quantify the pipe wall heat buffer coefficient, generating a temperature down-regulation safety boundary curve, and finally executing heat source regulation according to the curve, which can improve the new energy consumption capacity of the combined heat and power unit under the premise of ensuring the safety of heating.

Description

Technical Field

[0001] This invention relates to the field of smart grid industry technology, specifically to a new energy power consumption system and scheduling method based on multi-timescale coordination. Background Technology

[0002] Under the "dual carbon" target, combined heat and power (CHP) units, as an important regulating power source in the power system, face increasingly severe pressure to absorb renewable energy. During the heating season, these units operate according to the principle of "heat-driven power generation," with their power output rigidly locked to the heating load. This results in the grid lacking sufficient downward regulation capacity during periods of high wind and solar power generation, leading to severe wind and solar curtailment. Exploiting the thermal inertia of the heating network is an effective way to improve the flexibility of the units. Long-distance heating networks have enormous heat capacity, which can significantly hysteresis and attenuate fluctuations in heat source temperature. Theoretically, utilizing this characteristic, units can reduce heating output (and thus power generation) in a short period to absorb renewable energy, while the heating quality for end users will not immediately deteriorate due to the buffering effect of the network's thermal inertia.

[0003] In theory, the thermal inertia of heating networks can unlock the regulation potential of generating units. However, practical applications face two major technical bottlenecks: First, modern heating systems generally employ variable flow regulation, resulting in a non-linear, time-varying transmission delay from heat source to the end point. Traditional models based on natural time cannot achieve physical data alignment, leading to inaccurate scheduling models. Second, the temperature at the end of the network is affected by a mixture of steady-state heat dissipation and dynamic heat storage effects from the pipe walls, making it difficult to quantify the true impact of short-term regulation on the end temperature. This forces scheduling to adopt only conservative, static strategies, resulting in the idleness of significant thermal inertia resources. Therefore, existing technologies are ill-suited to variable flow conditions and cannot accurately quantify dynamic thermal buffering capacity, thus failing to coordinate the protection of heating safety and the improvement of renewable energy consumption levels. Summary of the Invention

[0004] To address the technical challenge of existing technologies in providing adaptable and precisely quantifiable dynamic thermal buffering capabilities under variable flow conditions, thereby enabling accurate dispatching of renewable energy power, this invention aims to provide a renewable energy power consumption system and dispatching method based on multi-timescale coordination. The specific technical solution adopted is as follows: This invention proposes a new energy power consumption and dispatch method based on multi-timescale coordination, the method comprising: Obtain the heat source outlet water temperature sequence, the heating network flow sequence, and the terminal heat exchange station inlet water temperature sequence based on the volume domain; perform correlation analysis on the heat source outlet water temperature sequence and the terminal heat exchange station inlet water temperature sequence to determine the terminal heat exchange station inlet delay sequence; The steady-state operating segment is determined based on the heat source outlet water temperature sequence; a steady-state heat dissipation model under the steady-state operating segment is constructed based on the heat network flow sequence and the heat source outlet water temperature sequence to obtain the heat loss steady-state benchmark and steady-state temperature value; the pipe wall thermal buffer coefficient is obtained based on the temperature difference distribution of the steady-state temperature value and the temperature value in the inlet delay sequence of the terminal heat exchange station; and a heat source regulation allowable duration curve describing the relationship between the heat source supply water temperature reduction magnitude and duration is generated based on the heat loss steady-state benchmark and the pipe wall thermal buffer coefficient. Based on the heat source regulation allowable duration curve, a preset heat source temperature regulation operation is performed.

[0005] Furthermore, the method for obtaining the heat source outlet water temperature sequence, the heating network flow rate sequence, and the terminal heat exchange station inlet water temperature sequence based on the volume domain includes: The system collects real-time parameters of the heat source outlet water temperature, the terminal heat exchange station inlet water temperature, and the heating network flow rate. Based on the heating network flow rate parameters, it integrates and sums the data at each sampling time and all previous sampling times to obtain the cumulative water volume at each sampling time. Based on the cumulative water volume at all sampling times, it performs curve fitting to construct a cumulative water volume-sampling time curve. The system iterates through the cumulative water volume-sampling time curve with a preset volume sampling step size, and uses the sampling time corresponding to each iteration as the iteration time. It then obtains the heat source outlet water temperature, the terminal heat exchange station inlet water temperature, and the heating network flow rate parameters corresponding to the iteration time. These parameters are arranged in chronological order to establish a heat source outlet water temperature sequence, a heating network flow rate sequence, and a terminal heat exchange station inlet water temperature sequence indexed by the iteration time.

[0006] Furthermore, the method for calculating the inlet delay sequence of the terminal heat exchange station includes: By offsetting the inlet water temperature sequence of the terminal heat exchange station with each traversal time offset, the corresponding inlet reference sequence of the terminal heat exchange station is obtained. The cross-correlation function value between the heat source outlet water temperature sequence and the inlet reference sequence of the terminal heat exchange station is calculated. The inlet reference sequence of the terminal heat exchange station corresponding to the traversal time offset with the largest cross-correlation function value is taken as the inlet delay sequence of the terminal heat exchange station.

[0007] Furthermore, the method for obtaining the stable operating condition segment includes: The heat source outlet water temperature sequence is traversed through a sliding window. The water temperature difference index of the heat source outlet water temperature sequence in each sliding window is calculated. The sliding window with the water temperature difference index less than the preset stability threshold is selected as the stable operating condition segment.

[0008] Furthermore, the method for obtaining the steady-state reference for heat loss and the steady-state temperature value includes: For the stable operating condition segment, a steady-state heat dissipation model is constructed. The steady-state heat dissipation model uses the ambient temperature as a reference and multiplies the difference between the heat source outlet water temperature and the ambient temperature by an exponential decay factor. The exponential term of the exponential decay factor is directly proportional to the pipe heat decay coefficient and inversely proportional to the heat network flow rate. The steady-state temperature value is obtained by forward calculation of the steady-state heat dissipation model based on the heat source outlet water temperature sequence and the heat network circulation flow rate sequence. The pipe heat decay coefficient is obtained by backfitting the steady-state heat dissipation model based on the heat source outlet water temperature sequence and the heat network circulation flow rate sequence, and the pipe heat decay coefficient is used as the steady-state benchmark for heat loss.

[0009] Furthermore, the method for obtaining the pipe wall thermal buffer coefficient includes: Based on the difference between the steady-state temperature value and the temperature value in the inlet delay sequence of the terminal heat exchange station, the corresponding pipe wall heat absorption and release temperature difference sequence is determined. Based on the pipe wall heat absorption and release temperature difference sequence, the heat network flow sequence, and the preset volume sampling step size, the pipe wall heat storage state index is determined. The pipe wall heat storage state index is normalized and mapped to obtain the pipe wall thermal buffer coefficient.

[0010] Furthermore, the method for obtaining the allowable duration curve of heat source regulation includes: A temperature decay prediction model is constructed, and the maximum temperature difference transmitted to the terminal heat exchange station in the temperature decay prediction model is set as a preset safety threshold. Inverse calculation is performed to obtain the allowable duration curve of heat source regulation, which describes the relationship between the temperature reduction magnitude and duration of the heat source water supply.

[0011] Furthermore, the method for constructing the temperature decay prediction model includes: Using the temperature reduction of the heat source supply water as a benchmark; an exponential decay factor is constructed based on the heat loss steady-state benchmark, the exponential term of which is proportional to the heat loss steady-state benchmark; an axial dispersion correction term for the water body is constructed, which is positively correlated with the duration; an equivalent thermal inertia gain correction term is constructed, which is negatively correlated with the pipe wall thermal buffer coefficient; and a temperature decay prediction model is constructed based on the temperature reduction of the heat source supply water, the exponential decay factor, the axial dispersion correction term for the water body, and the equivalent thermal inertia gain correction term to calculate the maximum temperature difference conducted to the terminal heat exchange station.

[0012] Furthermore, the preset heat source temperature adjustment operation includes: The system receives active power adjustment instructions from the power grid and converts them into a heat source water supply temperature reduction demand value based on the preset unit thermoelectric coupling coefficient. It then queries the heat source adjustment allowable duration curve based on the predicted duration of new energy fluctuations provided by the prediction system to obtain the corresponding maximum allowable reduction range. Finally, it performs the corresponding temperature reduction operation by comparing the heat source water supply temperature reduction demand value with the maximum allowable reduction range.

[0013] The present invention also proposes a new energy power consumption system based on multi-timescale coordination, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the new energy power consumption scheduling method based on multi-timescale coordination.

[0014] The present invention has the following beneficial effects: This invention determines the inlet delay sequence of the terminal heat exchange station by acquiring the volume domain sequence, accurately locking the constant transmission volume of the pipeline network, and transforming the nonlinear time delay problem under variable flow into a linear spatial displacement problem; it obtains the heat loss benchmark by constructing a steady-state heat dissipation model, realizing the decoupling of steady-state and dynamic thermal characteristics; it obtains the pipe wall thermal buffer coefficient by analyzing the temperature difference distribution, transforming uncontrollable thermal inertia into a quantifiable adjustment resource; it generates a heat source regulation allowable duration curve based on the steady-state benchmark and buffer coefficient, transforming complex physical constraints into a visualized safe scheduling boundary; finally, it executes temperature regulation operations based on this curve, enabling cogeneration units to safely reduce temperature according to clear physical boundaries while ensuring heating safety, effectively improving the grid's ability to absorb fluctuating new energy sources. Attached Figure Description

[0015] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a flowchart illustrating a new energy power consumption and dispatch method based on multi-timescale coordination, as provided in one embodiment of the present invention. Detailed Implementation

[0017] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a new energy power consumption system and dispatching method based on multi-timescale coordination proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0019] The following description, in conjunction with the accompanying drawings, details a specific scheme for a new energy power consumption and dispatch method based on multi-timescale coordination provided by the present invention.

[0020] Please see Figure 1 The diagram illustrates a flowchart of a new energy power consumption and dispatch method based on multi-time-scale coordination, according to an embodiment of the present invention. The method includes: S101: Obtain the heat source outlet water temperature sequence, the heating network flow sequence, and the terminal heat exchange station inlet water temperature sequence based on the volume domain; perform correlation analysis on the heat source outlet water temperature sequence and the terminal heat exchange station inlet water temperature sequence to determine the terminal heat exchange station inlet delay sequence.

[0021] Because centralized heating networks generally employ variable flow regulation strategies, the circulating flow rate of the heating network fluctuates in real time with the heating load demand, resulting in a nonlinear, time-varying lag time for the water element emitted from the heat source to reach the terminal heat exchange station. If analysis is performed directly based on the natural time axis, the heat source outlet data and the terminal inlet data cannot physically correspond to the same water body, leading to temporal misalignment in subsequent thermal inertia identification. To eliminate the nonlinear interference caused by flow velocity fluctuations, this invention constructs a volume-domain-based (indexed by traversal time) sequence of heat source outlet water temperature, heating network flow rate, and terminal heat exchange station inlet water temperature to characterize the water transport location. To achieve physical alignment between the heat source and terminal heat exchange station data, correlation analysis is performed on the heat source outlet water temperature sequence and the terminal heat exchange station inlet water temperature sequence to determine the terminal heat exchange station inlet delay sequence, which characterizes the measured temperature sequence when the same water element arrives at the heat exchange station inlet after being transported through the pipeline.

[0022] Furthermore, in a specific implementation of this invention, the system iterates through the corresponding values ​​in the heat source outlet water temperature sequence, the heating network flow rate sequence, and the terminal heat exchange station inlet delay sequence at each traversal time, and constructs a common source water temperature alignment sequence; each element in this sequence includes the temperature value in the heat source outlet water temperature sequence, the flow rate value in the heating network flow rate sequence, and the delayed temperature value in the terminal heat exchange station inlet delay sequence at the corresponding traversal time.

[0023] Preferably, in some possible implementations of the embodiments of the present invention, the method for obtaining the heat source outlet water temperature sequence, the heating network flow rate sequence, and the terminal heat exchange station inlet water temperature sequence based on the volume domain includes: The monitoring and data acquisition system (SCADA) at the primary heat source station and the terminal sentinel heat exchange station collects real-time heat source outlet water temperature parameters, terminal heat exchange station inlet water temperature parameters, and heat network flow parameters at preset time sampling intervals. To transform discrete time data into a volume domain sequence characterizing the location of water transport, this embodiment integrates and sums the heat network flow parameters at each sampling time and all previous sampling times to obtain the cumulative water volume at each sampling time. Based on the cumulative water volume at all sampling times, a curve fitting method using least squares is used to construct a cumulative water volume-sampling time curve. This curve characterizes the sampling time corresponding to each cumulative water volume. The system utilizes a "piston flow" mechanism based on water transport. The invention employs the first-order approximation assumption of "Flow," which considers that water elements primarily undergo translational motion within the pipe. In this embodiment, the cumulative water volume-sampling time curve is traversed using a preset volume sampling step size. The sampling time corresponding to each traversal is taken as the traversal time. The heat source outlet water temperature parameters corresponding to these traversal times are obtained and arranged chronologically to establish a heat source outlet water temperature sequence indexed by the traversal times. Similarly, the inlet water temperature parameters of the terminal heat exchange stations corresponding to the traversal times are obtained to construct an inlet water temperature sequence for the terminal heat exchange stations. Finally, the heat network flow rate parameters corresponding to the traversal times are obtained to construct a heat network flow rate sequence. In these sequences, any two adjacent data points represent water elements with a constant volume, and their physical interval is no longer affected by changes in flow velocity.

[0024] It should be noted that, in one specific implementation of this invention, the system generates a sequence every 24 hours. Since the centralized heating network is a large inertial system, the dominant time constants for heat transfer in the pipes and the heat storage and release processes on the pipe walls are typically on the order of several minutes to tens of minutes or even hours. A 60-second sampling interval is sufficient to capture the changing trends of these major dynamic processes; therefore, the preset time sampling interval is set to 60 seconds; the preset volume sampling step size is set to 10. That is, every 10 The volume is used as the corresponding time for traversal, thereby enabling data analysis. It can be automatically adjusted according to the pipe flow rate in the actual scenario.

[0025] Preferably, in some possible implementations of the embodiments of the present invention, the method for calculating the inlet delay sequence of the terminal heat exchange station includes: Since the diameter and length of the main pipeline network are fixed physical facilities, the volume of water that the pipeline between the initial heat source station and the terminal heat exchange station can hold is a constant that does not change with operating conditions. Therefore, in order to achieve physical alignment of the data between the heat source and the terminal heat exchange station, it is necessary to determine the pipeline transmission volume constant between them. In this embodiment of the invention, the inlet water temperature sequence of the terminal heat exchange station is offset by an offset at each traversal time point to obtain the corresponding inlet reference sequence of the terminal heat exchange station. The cross-correlation function value between the heat source outlet water temperature sequence and the terminal heat exchange station inlet reference sequence is calculated. This cross-correlation function value is used to characterize the similarity between the measured waveform of the heat source outlet water temperature sequence and the terminal heat exchange station inlet reference sequence after shifting the heat source outlet water temperature sequence backward by a certain traversal time point offset. When the cross-correlation function value reaches its maximum value, it means that the two waveforms are most similar. At this time, the shifted traversal time offset physically corresponds to the pipeline transmission volume constant between the heat source and the terminal heat exchange station. Therefore, this invention takes the traversal time offset corresponding to the maximum cross-correlation function value as the pipeline transmission volume constant that the pipeline between the first heat source station and the terminal heat exchange station can accommodate, and takes the terminal heat exchange station inlet reference sequence corresponding to the traversal time offset as the terminal heat exchange station inlet delay sequence.

[0026] As an example, in one specific implementation of this invention, the traversal time offset is... Corresponding cross-correlation function value The calculation formula can be expressed as: in, This represents each iteration time; This represents the upper limit of the traversal time. Indicates the first The temperature values ​​corresponding to the heat source outlet water temperature sequence at each traversal time point; Indicates in Iterate through the inlet water temperature sequence of the terminal heat exchange station at each time step to find the corresponding temperature values. The offset of the traversal time is a non-negative integer, representing the volume of the pipeline between the heat source outlet and the terminal heat exchange station. This formula treats two temperature values ​​as two multidimensional vectors, and the sum of their products is the dot product of the multidimensional vectors. The larger the dot product, the closer the directions of the two multidimensional vectors are, that is, the higher the similarity between the two sequences.

[0027] It should be noted that, in one specific implementation of this invention, the upper limit of traversal time is set to the total number of traversal times in the 24 hours prior to the current time.

[0028] Furthermore, in one specific implementation of this invention, although a simple peak alignment method can be used for rough estimation, it is necessary to consider the measurement noise and waveform distortion caused by water dispersion in the actual operating signal, and the fact that the heating temperature is usually maintained at a relatively high base value (e.g., 90°C). This causes severe interference in the DC component. Before calculating the inlet delay sequence of the terminal heat exchange station, it is necessary to perform mean-reduction processing on the heat source outlet water temperature sequence and the terminal heat exchange station inlet water temperature sequence, and then calculate the terminal heat exchange station inlet delay sequence based on the mean-reduction heat source outlet water temperature sequence and the terminal heat exchange station inlet water temperature sequence.

[0029] It should be noted that the mean removal process is a well-known technique in the art, and the specific process will not be described in detail here.

[0030] S102: Determine a stable operating condition segment based on the heat source outlet water temperature sequence; construct a steady-state heat dissipation model under the stable operating condition segment based on the heat network flow sequence and the heat source outlet water temperature sequence, and obtain the heat loss steady-state benchmark and steady-state temperature value; obtain the pipe wall thermal buffer coefficient based on the temperature difference distribution of the steady-state temperature value and the temperature value in the inlet delay sequence of the terminal heat exchange station; generate a heat source regulation allowable duration curve describing the relationship between the heat source supply water temperature reduction magnitude and duration based on the heat loss steady-state benchmark and the pipe wall thermal buffer coefficient.

[0031] Since the terminal temperature of a centralized heating network is affected not only by the static heat dissipation of the insulation layer but also by the significant interference of the unsteady-state heat charge and release behavior of the pipe wall metal, directly using data mixed with dynamic noise for identification will lead to distorted results. Therefore, this invention analyzes the heat dissipation of water in a centralized heating network from both static and dynamic perspectives by analyzing the steady-state benchmark of heat loss and the pipe wall thermal buffer coefficient. Considering that the combined heat dissipation capacity of the pipe insulation layer and soil is a parameter that changes slowly with the seasons (timescale: days), while the heat storage of the pipe wall is a process that fluctuates rapidly with operating conditions (timescale: minutes / hours), it is not possible to identify the steady-state benchmark of heat loss at any given time. Therefore, this invention determines stable operating condition segments based on the water temperature sequence at the heat source outlet. Under these stable operating condition segments, the water temperature changes extremely slowly, the temperature difference between the pipe wall metal and the water is approximately constant, the heat absorption and release effect of the pipe wall is negligible, and the dynamic transfer model naturally degenerates into a steady-state heat loss model. At this point, the steady-state parameters and dynamic parameters can be physically decoupled using the data from the stable segments, thereby accurately identifying the steady-state benchmark of heat loss. Based on the aforementioned heat network flow sequence and heat source outlet water temperature sequence, a steady-state heat dissipation model is constructed under stable operating conditions to obtain the steady-state benchmark and steady-state temperature value for heat loss. Furthermore, when the water temperature changes rapidly, the massive metal mass of the pipe wall undergoes sensible heat exchange with the water. This non-steady-state "heat charging and discharging" behavior causes the measured terminal temperature trajectory to lag significantly behind the predicted value of the steady-state model. To analyze this dynamic temperature change characteristic, this invention obtains the pipe wall thermal buffer coefficient based on the temperature difference distribution between the steady-state temperature value and the temperature value in the terminal heat exchange station inlet delay sequence. This coefficient measures the pipe wall's ability to buffer the water temperature. Since scheduling commands are executed in the future time domain, and future flow fluctuations will alter the transmission time, and the steady-state benchmark determines the basic temperature drop for normal water transmission, while the thermal buffer coefficient quantifies the pipe wall's ability to delay the temperature drop due to heat dissipation, this invention, combining fluid dynamics dispersion mechanisms and reverse-engineering, can generate a heat source regulation allowable duration curve describing the relationship between the magnitude and duration of the heat source supply water temperature reduction, serving as a benchmark for subsequent control command generation.

[0032] Preferably, in some possible implementations of the embodiments of the present invention, the method for obtaining the steady-state operating condition segment includes: The heat source outlet water temperature sequence is traversed through a sliding window. The water temperature difference index of the heat source outlet water temperature sequence in each sliding window is calculated. The sliding window with the water temperature difference index less than the preset stability threshold is selected as the stable operating condition segment.

[0033] It should be noted that, in one specific implementation of this invention, the rate of change of the temperature of the heat source outlet water temperature sequence with respect to the water volume in each sliding window is selected as the water temperature difference index.

[0034] In this embodiment of the invention, the sliding window size is set to 3 hours to ensure that the entire process of fluid flowing from the heat source to the terminal heat exchange station is covered; the sliding step size is set to the time interval between two traversal moments; and a preset stability threshold is set. It can be adjusted automatically according to the specific real-time scenario.

[0035] Preferably, in some possible implementations of the embodiments of the present invention, the method for obtaining the heat loss steady-state reference and steady-state temperature value includes: For the stable operating condition segment, a steady-state heat dissipation model is constructed. The steady-state heat dissipation model uses the ambient temperature as a reference and multiplies the difference between the heat source outlet water temperature and the ambient temperature by an exponential decay factor. The exponential term of the exponential decay factor is directly proportional to the pipeline heat decay coefficient and inversely proportional to the heat network flow rate. The steady-state temperature value is obtained by forward calculation of the steady-state heat dissipation model based on the heat source outlet water temperature sequence and the heat network circulation flow rate sequence. Based on the heat source outlet water temperature sequence and the heat network circulation flow rate sequence, with the objective of minimizing the sum of squared residuals between the temperature value at each traversal time point in the terminal heat exchange station inlet water temperature sequence and the steady-state temperature value, the pipeline heat decay coefficient is obtained by iterative backfitting of the steady-state heat dissipation model using the nonlinear least squares method. The pipeline heat decay coefficient is used as the steady-state benchmark for heat loss.

[0036] It should be noted that the calculation of residuals is a technique well known to those skilled in the art, and its calculation process will not be described in detail here; in other implementations of the embodiments of the present invention, other data fitting methods such as Fourier series fitting algorithms may also be used, and will not be limited or described in detail here.

[0037] As an example, in a specific implementation of this invention, the steady-state heat dissipation model can be represented as: in, express Steady-state temperature values ​​at each traversal time point; This indicates the ambient temperature of the deeply buried pipeline environment; express The temperature values ​​corresponding to the heat source outlet water temperature sequence at each traversal time point; As the steady-state reference for heat loss; Let be the fluid thermophysical constant, and for water take . ; To prevent the elimination of zero factors, in this embodiment of the invention, it is set as follows: ; express The flow rate values ​​corresponding to the circulating flow rate sequence of the heating network at each traversal time point are in units of ; The flow regime correction index is used to characterize the effect of flow rate changes on the heat transfer coefficient. Represents the total temperature difference of a fluid relative to its ambient temperature when it leaves the heat source; exponential term. Combined with heat loss steady-state benchmark The larger the volume, the faster the heat dissipation; and the flow rate of the water body. The larger the temperature difference, the more heat it carries, and the less heat it dissipates. Since the initial temperature difference decays exponentially due to heat dissipation during the pipeline transport process, an exponential decay factor is constructed by multiplying the total temperature difference of the fluid relative to the environment when it leaves the heat source by the exponential term. This factor is used to characterize the degree of influence of the dynamic change of heat dissipation capacity on the temperature difference. Using the ambient temperature as a reference, the temperature difference value decaying exponentially is used as a correction value to comprehensively determine the steady-state temperature value at each traversal time.

[0038] It should be noted that the heat loss steady-state reference Units and denominator terms With the same units, its primary function is to characterize the overall heat dissipation capacity of the pipeline insulation layer and the soil, and then to eliminate the influence of dimensions on calculations.

[0039] It should be noted that, in one specific implementation of this invention, the ambient temperature of the deeply buried pipeline environment is selected. This is the arithmetic mean of the measured inlet temperatures of the terminal heat exchange stations over the past 24 hours; based on the Nusselt number correlation. Derivation shows that the heat transfer coefficient is proportional to the 0.8th power of the flow rate, and the attenuation index involves the reciprocal of the thermal resistance; therefore, in engineering, it is taken as... Therefore, in this embodiment of the invention, the flow correction index is taken as 0.2.

[0040] Preferably, in some possible implementations of the embodiments of the present invention, the method for obtaining the pipe wall thermal buffer coefficient includes: Since the steady-state temperature represents the expected terminal temperature of each water element (identified by the traversal time in this embodiment) under ideal conditions assuming no dynamic heat absorption or release from the pipe wall (i.e., pure steady state), solely due to heat dissipation from the pipe to the environment, and the temperature value in the terminal heat exchange station inlet delay sequence represents the actual temperature of the same water element reaching the terminal heat exchange station inlet, this invention determines the corresponding pipe wall heat absorption / release temperature difference sequence by subtracting the temperature value in the terminal heat exchange station inlet delay sequence from the steady-state temperature value. This sequence directly reflects the heat exchange state of the pipe wall: if an element in the sequence is positive, it indicates that the pipe wall temperature is higher than the fluid temperature, releasing heat and delaying fluid cooling; if an element in the sequence is negative, it indicates that the pipe wall temperature is lower than the fluid temperature, absorbing heat and accelerating fluid cooling. Based on the pipe wall heat absorption / release temperature difference sequence, the heat network flow sequence, and the preset sampling step size, a pipe wall heat storage state index is determined; the pipe wall heat storage state index is then normalized to obtain the pipe wall thermal buffer coefficient.

[0041] It should be noted that, in one specific implementation of this invention, in order to quantify the unsteady temperature difference caused by the heat absorption and release of the pipe wall metal, the system selects a cumulative volume window covering the most recent complete transmission cycle, i.e., sets the window length to the pipe network transmission volume constant; and sets the preset volume sampling step size to 10. For each traversal time within the window, the corresponding pipe wall heat absorption and release temperature difference sequence is determined by subtracting the temperature value from the steady-state temperature value in the inlet delay sequence of the terminal heat exchange station.

[0042] As an example, in a specific implementation of this invention, the pipe wall heat storage state index The calculation formula can be expressed as: in, This represents each iteration time; This represents the upper limit of the traversal time. express The temperature difference values ​​in the heat absorption and release temperature difference sequence of the tube wall at each traversal time point, in units of ; express The flow values ​​in the heat network flow sequence at each traversal time point are in units of ; Indicates the first The time interval between the traversal time and the previous traversal time (the time interval corresponding to the first traversal time is the time interval between it and the start time of the heating network flow sequence), in hours. Pipe wall heat storage status index. This quantifies the additional thermal energy accumulated by the pipe wall relative to the steady-state baseline at the current moment (unit: (Used for balance dimensions). Due to the actual heat exchanged between the pipe wall and the fluid (i.e., the pipe wall heat storage state index). The flow rate is directly proportional not only to the temperature difference but also to the volume of fluid flowing through it; therefore, this formula incorporates the flow rate value. As a weighting factor, the temperature difference value in the heat absorption and release temperature difference sequence of the pipe wall is... With a preset volume sampling step size Integrating in the volume domain with units of 1, we obtain a pipe wall heat storage state index to characterize the additional thermal energy accumulated by the pipe wall relative to a steady-state baseline. .

[0043] As an example, in a specific implementation of this invention, the pipe wall thermal buffer coefficient... The calculation formula can be expressed as: in, This indicates the maximum permissible correction range, representing the maximum suppression ratio of the pipe wall heat capacity on the rate of temperature drop; This represents the sensitivity coefficient, used to adjust the slope of the mapping function; This indicates the heat storage status of the pipe wall. Since the heat capacity of the pipe wall metal is finite, its buffering capacity inevitably has a physical upper limit, meaning that regardless of... The effect of the pipe wall in suppressing fluid temperature drop cannot be increased indefinitely (at a certain size, including when the pipe wall is reheated). Therefore, this invention introduces a hyperbolic tangent function. Under the guarantee Tiny changes will cause While maintaining a steady change, Strictly limited to a certain range, and used The function is linearly scaled to the sensitive region of the hyperbolic tangent function; at the same time, considering that the heat capacity of the pipe wall metal is finite, a dynamic safety margin is set according to the pipeline design specifications. Limiting the pipe wall thermal buffer coefficient to Within safe limits.

[0044] Specifically, when When the temperature is high, it indicates that the pipe wall is in a state of thermal saturation, providing additional thermal buffering capacity; when... When, it indicates that the pipe wall has no additional buffering capacity; when When this occurs, it indicates that the pipe wall is in a state of thermal deficit, which will accelerate the cooling of the fluid.

[0045] It should be noted that, in one specific implementation of this invention, the maximum permissible correction range is... According to the dynamic safety margin setting in the pipeline design specification, the value range is [0.15, 0.3], and in this embodiment of the invention, it is taken as 0.20; sensitivity coefficient In the embodiments of the present invention, take This is used to eliminate the influence of dimensions; the specific calibration method is: statistically analyze the historical operation data of the pipeline network. Maximum absolute value ,make (This causes the Tanh function to enter the saturation region), thus allowing the solution to be obtained from the inverse problem. .

[0046] Preferably, in some possible implementations of the embodiments of the present invention, the method for obtaining the allowable duration curve of heat source adjustment includes: A temperature decay prediction model is constructed, which characterizes the relationship between the maximum temperature difference conducted from water to the terminal heat exchange station and the arbitrary assumed adjustment range and duration of the heat source water supply temperature. To ensure heating safety, this embodiment of the invention sets the maximum temperature difference conducted to the terminal heat exchange station as a preset safety threshold and performs inverse calculation on the temperature decay prediction model to obtain the allowable duration curve of heat source regulation describing the relationship between the adjustment range and duration of the heat source water supply temperature.

[0047] It should be noted that, in one specific implementation of this invention, the preset security threshold is set to... Within a preset time range (1 to 60 minutes in this embodiment of the invention), the adjustment range of the heat source water supply temperature corresponding to each duration is calculated iteratively. All calculation results are then subjected to linear regression analysis to obtain the heat source regulation allowable duration curve describing the relationship between the adjustment range of the heat source water supply temperature and the duration. Linear regression analysis is a technique well-known to those skilled in the art, and its process will not be elaborated upon here.

[0048] Preferably, in some possible implementations of the embodiments of the present invention, the method for constructing the temperature decay prediction model includes: Using the temperature reduction of the heat source supply water as a benchmark; an exponential decay factor is constructed based on the heat loss steady-state benchmark, the exponential term of which is proportional to the heat loss steady-state benchmark; an axial dispersion correction term for the water body is constructed, which is positively correlated with the duration; an equivalent thermal inertia gain correction term is constructed, which is negatively correlated with the pipe wall thermal buffer coefficient; and a temperature decay prediction model is constructed based on the temperature reduction of the heat source supply water, the exponential decay factor, the axial dispersion correction term for the water body, and the equivalent thermal inertia gain correction term to calculate the maximum temperature difference conducted to the terminal heat exchange station.

[0049] As an example, in a specific implementation of this invention, the temperature decay prediction model can be expressed as: in, This indicates the maximum temperature difference that is conducted to the terminal heat exchange station; Indicates the degree of temperature reduction of the heat source water supply; This represents the steady-state reference for heat loss. This represents the fluid's thermophysical constant; for water, take... ; This represents the baseline for predicted transport flow rate, in units of... ; To prevent the elimination of zero factors, in this embodiment of the invention, it is set as follows: ; This is the flow correction exponent, which takes the same value as in the above steady-state heat dissipation model; and Empirical constants related to pipe diameter (e.g.) This can be obtained through step response testing and fitting; Indicates duration; This represents the pipe wall heat buffer coefficient. (Exponential term) Combined with heat loss steady-state benchmark The larger the volume, the faster the heat dissipation; and the flow rate of the water body. The larger the temperature difference, the more heat it carries, and the less heat it dissipates. Since the initial temperature difference (i.e., the temperature reduction of the heat source water supply) decays exponentially due to heat dissipation during the pipeline transportation process, the exponential decay factor constructed by multiplying the temperature reduction of the heat source water supply by one of the aforementioned exponential terms is used to characterize the degree of influence of the dynamic change of heat dissipation capacity on the temperature reduction of the heat source water supply. This represents the axial dispersion correction term for water, used to characterize the temperature fluctuation caused by the mixing and diffusion of water in the pipe. The longer the duration of this phenomenon, the greater the temperature fluctuation. The equivalent thermal inertia gain correction term is used to characterize the effect of the pipe wall thermal buffer coefficient on the suppression or acceleration of water temperature drop. This formula integrates the above three temperature influence mechanisms to predict the maximum temperature difference when conducted to the terminal heat exchange station based on the magnitude and duration of the temperature reduction of the heat source supply water.

[0050] In one specific implementation of this invention, the weighted average of the current flow rate and the minimum flow rate recorded in the past hour is taken as the benchmark for predicting the transport flow rate. To cover the risk of increased transmission latency due to potential future traffic reduction; set , It can be obtained through step response testing and fitting.

[0051] S103: Execute a preset heat source temperature adjustment operation based on the heat source adjustment allowable duration curve.

[0052] Because the output of new energy sources such as wind power and photovoltaics fluctuates rapidly on a minute-by-minute basis, the traditional "heat-driven power generation" model is limited by static heating parameters and cannot keep up with such fluctuations. However, the heat source regulation allowance curve provided in step S102 takes into account the dynamic safety boundary of the physical system, constraining the unit's regulation needs within the physical range that the network's thermal inertia can withstand. It can directly call and execute the corresponding preset heat source temperature regulation operation, eliminating decision-making delays and uncertainties.

[0053] Preferably, in some possible implementations of the embodiments of the present invention, the preset heat source temperature adjustment operation includes: The system receives active power adjustment instructions from the power grid and converts them into a heat source water supply temperature reduction demand value based on the preset unit thermoelectric coupling coefficient. It then queries the heat source adjustment allowable duration curve based on the predicted duration of new energy fluctuations provided by the prediction system to obtain the corresponding maximum allowable reduction range. Finally, it performs the corresponding temperature reduction operation by comparing the heat source water supply temperature reduction demand value with the maximum allowable reduction range.

[0054] Specifically, the system receives active power regulation commands (in MW) issued by the power grid dispatch center in real time. If the command requires the generating unit to reduce its output to absorb renewable energy (i.e., the active power regulation command is less than 0), the system uses the unit's factory performance curve or real-time thermal test data to determine the unit's thermoelectric coupling coefficient (in MW / ). This converts power regulation demand into a demand value for lowering water supply temperature.

[0055] It should be noted that, in a specific implementation of this invention, considering that the change in power generation is approximately proportional to the change in water supply temperature that causes the change, and that the proportionality constant is the thermoelectric coupling coefficient of the unit, the absolute value of the active power adjustment command is used as the numerator and the thermoelectric coupling coefficient of the unit is used as the denominator to obtain the water supply temperature reduction demand value.

[0056] The system reads the renewable energy fluctuation prediction duration provided by the ultra-short-term renewable energy power prediction system (e.g., predicting that high wind power output will last for 15 minutes in the future). In the heat source regulation allowable duration curve generated in step S102, it finds the heat source water supply temperature reduction range corresponding to the renewable energy fluctuation prediction duration.

[0057] The following logic should be used to compare the reduced demand value for water supply temperature with the allowable reduction value for the water supply temperature from the heat source: If the demand value for lowering the water supply temperature is less than or equal to the allowable range for lowering the heat source water supply temperature, it indicates that the adjustment is within the safe overdraft range of the pipeline network. The dispatching system sets the lower water supply temperature to the demand value for lowering the water supply temperature, instructs the generating units to quickly reduce their load, and utilizes the thermal inertia of the pipeline network to completely absorb the fluctuations in renewable energy.

[0058] If the demand for lowering the water supply temperature exceeds the allowable range for lowering the heat source water supply temperature, it indicates that the demand exceeds the current safe capacity of the pipeline network. The dispatching system will perform a limiting operation, lowering the water supply temperature only by the allowable range for lowering the heat source water supply temperature, prioritizing ensuring that the temperature at the heating terminal does not fall below the safe threshold, and reducing or balancing the remaining power regulation demand through other units.

[0059] Furthermore, the aforementioned heat source temperature regulation operation essentially pre-draws the thermal potential energy stored in the pipe wall metal. If this pre-drawing continues for a long period without compensation, the pipe wall's thermal buffer coefficient will decrease, weakening the system's ability to regulate subsequent fluctuations. Therefore, a heat repayment plan needs to be developed during periods of stable new energy fluctuations.

[0060] Specifically, after each preset scheduling cycle (set to 15 minutes in this embodiment) following the end of the overdraft operation, the pipe wall thermal buffer coefficient output in step S102 is monitored. A hysteresis recharge threshold is set (set to 1.0 in this embodiment). If the pipe wall thermal buffer coefficient is less than or equal to the hysteresis recharge threshold, it indicates that the pipe wall thermal potential energy has been exhausted or has entered a deficit state, and the system automatically triggers the pipe wall heat recharge operation.

[0061] Using renewable energy power forecast data, the system searches for wind power off-peak or stable periods within the next 1 to 4 hours. During this period, the unit's water supply temperature setpoint is positively offset, making it higher than the baseline value required for the current heating load (in this embodiment, this is referred to as upward adjustment). To prevent thermal stress damage, the heating rate is limited to the range permitted by pipeline safety regulations (in this embodiment of the invention, the heating rate should be less than...). ).

[0062] During the recharging process, the change in the pipe wall thermal buffer coefficient is continuously monitored. If the recharging operation lasts for a preset time threshold (set to 1 hour in this embodiment), or the pipe wall thermal buffer coefficient rises to a preset overcharge threshold (set to 1.05 in this embodiment), it indicates that the pipe wall metal has re-accumulated sufficient thermal potential energy. The system exits the recharging mode and returns to normal heating status, preparing to cope with the next round of new energy consumption tasks. Through the above closed-loop mechanism, this system achieves long-term sustainable maintenance of the new energy consumption capacity.

[0063] In summary, this invention determines the inlet delay sequence of the terminal heat exchange station by obtaining the volume domain sequence, accurately locking the constant transmission volume of the pipeline network, and transforming the nonlinear time delay problem under variable flow into a linear spatial displacement problem; it obtains the heat loss benchmark by constructing a steady-state heat dissipation model, realizing the decoupling of steady-state and dynamic thermal characteristics; it obtains the pipe wall thermal buffer coefficient by analyzing the temperature difference distribution, transforming uncontrollable thermal inertia into a quantifiable adjustment resource; it generates a heat source regulation allowable duration curve based on the steady-state benchmark and buffer coefficient, transforming complex physical constraints into a visualized safe scheduling boundary; and finally, it executes temperature regulation operations based on this curve, enabling cogeneration units to safely reduce temperature according to clear physical boundaries while ensuring heating safety, effectively improving the grid's ability to absorb fluctuating new energy sources.

[0064] Based on the same inventive concept, the present invention also proposes a new energy power consumption system based on multi-timescale coordination, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the new energy power consumption scheduling method based on multi-timescale coordination.

[0065] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0066] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A new energy power consumption and dispatch method based on multi-timescale coordination, characterized in that, The method includes: Obtain the heat source outlet water temperature sequence, the heating network flow sequence, and the terminal heat exchange station inlet water temperature sequence based on the volume domain; perform correlation analysis on the heat source outlet water temperature sequence and the terminal heat exchange station inlet water temperature sequence to determine the terminal heat exchange station inlet delay sequence; The steady-state operating segment is determined based on the heat source outlet water temperature sequence; a steady-state heat dissipation model under the steady-state operating segment is constructed based on the heat network flow sequence and the heat source outlet water temperature sequence to obtain the heat loss steady-state benchmark and steady-state temperature value; the pipe wall thermal buffer coefficient is obtained based on the temperature difference distribution of the steady-state temperature value and the temperature value in the inlet delay sequence of the terminal heat exchange station; and a heat source regulation allowable duration curve describing the relationship between the heat source supply water temperature reduction magnitude and duration is generated based on the heat loss steady-state benchmark and the pipe wall thermal buffer coefficient. Based on the heat source regulation allowable duration curve, a preset heat source temperature regulation operation is performed.

2. The new energy power consumption and dispatch method based on multi-timescale coordination according to claim 1, characterized in that, The method for obtaining the heat source outlet water temperature sequence, the heating network flow rate sequence, and the terminal heat exchange station inlet water temperature sequence based on the volume domain includes: The system collects real-time parameters of the heat source outlet water temperature, the terminal heat exchange station inlet water temperature, and the heating network flow rate. Based on the heating network flow rate parameters, it integrates and sums the data at each sampling time and all previous sampling times to obtain the cumulative water volume at each sampling time. Based on the cumulative water volume at all sampling times, it performs curve fitting to construct a cumulative water volume-sampling time curve. The system iterates through the cumulative water volume-sampling time curve with a preset volume sampling step size, and uses the sampling time corresponding to each iteration as the iteration time. It then obtains the heat source outlet water temperature, the terminal heat exchange station inlet water temperature, and the heating network flow rate parameters corresponding to the iteration time. These parameters are arranged in chronological order to establish a heat source outlet water temperature sequence, a heating network flow rate sequence, and a terminal heat exchange station inlet water temperature sequence indexed by the iteration time.

3. The new energy power consumption and dispatch method based on multi-timescale coordination according to claim 2, characterized in that, The calculation method for the inlet delay sequence of the terminal heat exchange station includes: By offsetting the inlet water temperature sequence of the terminal heat exchange station with each traversal time offset, the corresponding inlet reference sequence of the terminal heat exchange station is obtained. The cross-correlation function value between the heat source outlet water temperature sequence and the inlet reference sequence of the terminal heat exchange station is calculated. The inlet reference sequence of the terminal heat exchange station corresponding to the traversal time offset with the largest cross-correlation function value is taken as the inlet delay sequence of the terminal heat exchange station.

4. The new energy power consumption and dispatch method based on multi-timescale coordination according to claim 1, characterized in that, The method for obtaining the steady-state operating condition segment includes: The heat source outlet water temperature sequence is traversed through a sliding window. The water temperature difference index of the heat source outlet water temperature sequence in each sliding window is calculated. The sliding window with the water temperature difference index less than the preset stability threshold is selected as the stable operating condition segment.

5. The new energy power consumption and dispatch method based on multi-timescale coordination according to claim 1, characterized in that, The methods for obtaining the steady-state reference for heat loss and the steady-state temperature value include: For the stable operating condition segment, a steady-state heat dissipation model is constructed. The steady-state heat dissipation model uses the ambient temperature as a reference and multiplies the difference between the heat source outlet water temperature and the ambient temperature by an exponential decay factor. The exponential term of the exponential decay factor is directly proportional to the pipe heat decay coefficient and inversely proportional to the heat network flow rate. The steady-state temperature value is obtained by forward calculation of the steady-state heat dissipation model based on the heat source outlet water temperature sequence and the heat network circulation flow rate sequence. The pipe heat decay coefficient is obtained by backfitting the steady-state heat dissipation model based on the heat source outlet water temperature sequence and the heat network circulation flow rate sequence, and the pipe heat decay coefficient is used as the steady-state benchmark for heat loss.

6. The new energy power consumption and dispatch method based on multi-timescale coordination according to claim 1, characterized in that, The method for obtaining the pipe wall thermal buffer coefficient includes: Based on the difference between the steady-state temperature value and the temperature value in the inlet delay sequence of the terminal heat exchange station, the corresponding pipe wall heat absorption and release temperature difference sequence is determined. Based on the pipe wall heat absorption and release temperature difference sequence, the heat network flow sequence, and the preset volume sampling step size, the pipe wall heat storage state index is determined. The pipe wall heat storage state index is normalized and mapped to obtain the pipe wall thermal buffer coefficient.

7. The new energy power consumption and dispatch method based on multi-timescale coordination according to claim 1, characterized in that, The method for obtaining the allowable duration curve of heat source regulation includes: A temperature decay prediction model is constructed, and the maximum temperature difference transmitted to the terminal heat exchange station in the temperature decay prediction model is set as a preset safety threshold. Inverse calculation is performed to obtain the allowable duration curve of heat source regulation, which describes the relationship between the temperature reduction magnitude and duration of the heat source water supply.

8. A new energy power consumption and dispatch method based on multi-timescale coordination according to claim 7, characterized in that, The method for constructing the temperature decay prediction model includes: Using the temperature reduction of the heat source supply water as a benchmark; an exponential decay factor is constructed based on the heat loss steady-state benchmark, the exponential term of which is proportional to the heat loss steady-state benchmark; an axial dispersion correction term for the water body is constructed, which is positively correlated with the duration; an equivalent thermal inertia gain correction term is constructed, which is negatively correlated with the pipe wall thermal buffer coefficient; and a temperature decay prediction model is constructed based on the temperature reduction of the heat source supply water, the exponential decay factor, the axial dispersion correction term for the water body, and the equivalent thermal inertia gain correction term to calculate the maximum temperature difference conducted to the terminal heat exchange station.

9. The new energy power consumption and dispatch method based on multi-timescale coordination according to claim 1, characterized in that, The preset heat source temperature adjustment operation includes: The system receives active power adjustment instructions from the power grid and converts them into a heat source water supply temperature reduction demand value based on the preset unit thermoelectric coupling coefficient. It then queries the heat source adjustment allowable duration curve based on the predicted duration of new energy fluctuations provided by the prediction system to obtain the corresponding maximum allowable reduction range. Finally, it performs the corresponding temperature reduction operation by comparing the heat source water supply temperature reduction demand value with the maximum allowable reduction range.

10. A new energy power consumption system based on multi-timescale coordination, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the new energy power consumption and dispatch method based on multi-timescale coordination as described in any one of claims 1 to 9.

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