Comprehensive energy substation supply method and device and storage medium

Abstract

The present application relates to the technical field of energy supply, and particularly relates to a comprehensive energy substation supply method and device and a storage medium, the method comprising: collecting environmental parameters, geological parameters and energy demand of underground space; constructing an environmental risk factor based on collected environmental temperature, environmental humidity, carbon dioxide concentration and methane concentration in a monitoring period, constructing a geological factor based on collected rock stratum micro-vibration frequency, water seepage rate and rock stratum displacement in the monitoring period, and determining an underground space risk index by combining the environmental factor and the geological factor; determining an energy supply coefficient based on the underground space risk index in the monitoring period, and generating an energy supply strategy by combining the energy demand in the next monitoring period; determining an update factor; and updating the energy supply strategy based on the subsonic wave harmonic proportion, lichen conductivity and the update factor collected in the monitoring period. The present application effectively improves the energy supply efficiency of the comprehensive energy substation.

Description

Technical Field

[0001] This invention relates to the field of energy supply technology, and in particular to a method, apparatus and storage medium for supplying integrated energy to a substation. Background Technology

[0002] Traditional risk management in underground spaces often relies on single environmental parameter threshold alarms and experience-based energy allocation strategies, which are difficult to adapt to complex working conditions with strong concealment and significant differences in periodic characteristics. The dynamic correlation between short-term meteorological anomalies and long-term geological creep is not fully quantified, resulting in delayed early warning of complex risks such as rock seepage and microbial corrosion. Fixed-weight energy supply models are difficult to achieve coordinated optimization of rapid switching of emergency lighting and flexible load reduction of conventional power supply, and are prone to triggering chain control failures when there are electromagnetic transients or bioelectrical parameter anomalies in cables.

[0003] Existing disturbance compensation mechanisms are mostly limited to short-term corrections of electromechanical parameters, lacking dynamic response interfaces for long-term, cross-domain disturbances such as lichen bioactivity and infrasound harmonics. Cumulative anomalies can easily lead to equipment lifespan degradation and escalation of safety hazards. This technology, through multi-factor dynamic fusion modeling and elastic energy hierarchical regulation, systematically overcomes core shortcomings such as discretized risk perception, rigid strategies, and weak disturbance adaptation, providing a revolutionary solution for intelligent operation and maintenance of underground spaces. Summary of the Invention

[0004] The purpose of this invention is to provide a method, apparatus and storage medium for supplying integrated energy to a substation, so as to solve at least one of the problems existing in the prior art.

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

[0006] A method for supplying integrated energy to a substation includes:

[0007] Environmental risk factors are constructed based on ambient temperature, humidity, carbon dioxide concentration and methane concentration collected during the monitoring period. Geological factors are constructed based on rock strata micro-vibration frequency, seepage rate and rock strata displacement collected during the monitoring period. The underground space risk index is determined by combining environmental factors and geological factors.

[0008] The energy supply coefficient is determined based on the underground space risk index of the monitoring cycle, and an energy supply strategy is generated in combination with the energy demand of the next monitoring cycle.

[0009] The electromagnetic interference intensity of the cable collected during the monitoring period is compared with the intensity discrimination factor to determine the update factor;

[0010] The energy supply strategy is updated based on the proportion of infrasound harmonics, lichen conductivity, and renewal factor collected during the monitoring period.

[0011] Furthermore, environmental parameters, geological parameters, and energy requirements of the underground space will be collected;

[0012] The first environmental risk factor y1 is constructed based on the ambient temperature HT and ambient humidity HS collected during the monitoring period. The second environmental risk factor y2 is constructed based on the carbon dioxide concentration Hr and methane concentration Hj collected during the monitoring period. An environmental factor is constructed based on the first environmental risk factor y1 and the second environmental risk factor y2. The expression of the environmental factor is Y=exp(3×y1×y2-3).

[0013] Furthermore, based on the rock strata micro-vibration frequency Fv, seepage rate Fs, and rock strata displacement Fw collected during the monitoring period, a geological factor D is constructed and set as follows:

[0014] ;

[0015] In the formula, fv is the vibration frequency threshold, fs is the seepage rate threshold, and fw is the displacement threshold.

[0016] Furthermore, the environmental factor Y and the geological factor D are fused and analyzed to determine the underground space risk index KF, ​​KF=w1×Y+w2×D, where w1 is the environmental weight, w2 is the geological weight, and w1+w2=1.

[0017] Furthermore, the power supply coefficient Dq, heat supply coefficient Rq, and emergency lighting supply coefficient Yq are determined based on the underground space risk index KF of the monitoring period.

[0018] The expression for the power supply coefficient Dq is Dq=2 / (1+e -5×KF -1; the expression for the heat supply coefficient Rq is: The expression for the emergency lighting supply coefficient Yq is Yq=min(Pe / Pc,1)+KF 2 / 2, where Pc is the critical emergency lighting energy consumption threshold.

[0019] Furthermore, the power supply Gd for the next monitoring period is determined based on the power load demand Wd and the power supply coefficient Dq, where Gd = Wd × Dq; and the heat supply Gr for the next monitoring period is determined based on the heat load demand Wr and the heat supply coefficient Rq, where Gr = Wr × Rq.

[0020] The emergency lighting supply Gz for the next monitoring period is determined based on the emergency lighting energy consumption demand Pe and the emergency lighting supply coefficient Yq, where Gz = Pe × Yq.

[0021] Furthermore, the electromagnetic interference intensity Ep collected during the monitoring period is compared with the intensity discrimination factor E0. If Ep is less than or equal to E0, the update factor is set to η; otherwise, the update factor is set to {η×{1+[(Ep-E0) / (Ep+E0)]}. 1.5}}, where η is the preset update factor.

[0022] Furthermore, the lichen conductivity during the monitoring period is denoted as Lc. The energy supply strategy is updated based on the lichen conductivity Lc, the proportion of infrasound harmonics Z, and the update factor. The power supply coefficient for the next monitoring period is set as Dq1.

[0023] In another aspect of this application, an integrated energy substation supply device is provided, comprising:

[0024] The data acquisition unit is used to collect environmental parameters, geological parameters, and energy requirements of underground spaces.

[0025] The index determination unit is used to construct environmental risk factors based on ambient temperature, ambient humidity, carbon dioxide concentration and methane concentration collected during the monitoring period, construct geological factors based on rock strata micro-vibration frequency, seepage rate and rock strata displacement collected during the monitoring period, and combine environmental factors and geological factors to determine the underground space risk index.

[0026] The energy supply unit is used to determine the energy supply coefficient based on the underground space risk index of the monitoring period, and to generate an energy supply strategy in combination with the energy demand of the next monitoring period.

[0027] The weight determination unit is used to compare the electromagnetic interference intensity of the cable collected during the monitoring period with the intensity discrimination factor in order to determine the update factor;

[0028] The update unit is used to update the energy supply strategy based on the proportion of infrasound harmonics, lichen conductivity and update factor collected during the monitoring period.

[0029] In another aspect of this application, a computer-readable storage medium is provided, the computer-readable storage medium storing a computer program, wherein the computer program is used to control the electronic device in which the computer-readable storage medium is located to perform the integrated energy substation supply method during runtime.

[0030] The beneficial effects of this invention are as follows: By constructing a dynamic risk assessment model and elastic hierarchical control mechanism that integrates the environment and geology, deep synergistic control of energy supply and safety risks in underground space is achieved: the multi-physics field quantitative analysis of geological factors accurately captures the critical characteristic layers of rock stress mutation and seepage risk, supporting differentiated energy redundancy configuration; combined with the nonlinear fusion risk index of meteorological anomalies and geological instability, the dynamic coupling response of power and heat supply coefficients is driven, breaking through the hysteresis bottleneck of traditional static threshold control; further, through the two-way closed-loop correction logic of infrasound harmonics-lichen conductivity and electromagnetic interference-strategy anchor points, a dynamic absorption capacity for long-cycle environmental disturbances and biophysical coupling anomalies is formed, which significantly reduces redundant energy consumption while ensuring the stability of critical loads, forming a comprehensive technical solution with advanced early warning, dynamic adaptation and anti-disturbance fault tolerance, which can cope with the contradiction between hidden risk superposition and energy resilience demand in complex scenarios such as mines and underground energy storage. Attached Figure Description

[0031] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0032] Figure 1 This is a flowchart illustrating the integrated energy substation supply method in this embodiment.

[0033] Figure 2 This is a flowchart illustrating the method for constructing the underground space risk index in this embodiment.

[0034] Figure 3 This is a flowchart illustrating the energy supply strategy generation method in this embodiment.

[0035] Figure 4 This is a schematic diagram of the integrated energy substation supply device in this embodiment.

[0036] Figure 5 This is a schematic diagram of the electronic device in this embodiment. Detailed Implementation

[0037] To more clearly illustrate the present invention, the following description, in conjunction with preferred embodiments and accompanying drawings, further explains the invention. Similar components in the drawings are indicated by the same reference numerals. Those skilled in the art should understand that the specific description below is illustrative rather than restrictive and should not be construed as limiting the scope of protection of the present invention.

[0038] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of this application described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0039] Specifically, this embodiment is applied to the coordinated supply control of an underground integrated energy substation. Targeting enclosed and complex geological conditions, a spatial risk index is constructed based on multi-dimensional environmental anomaly parameters and dynamic rock displacement data. Combined with cable electromagnetic interference intensity, a multi-energy coupled supply coefficient model is established. Simultaneously, a dynamic compensation mechanism is constructed by integrating the infrasound environmental induction effect and the bioelectric response characteristics of lichens. Through a three-level closed-loop control system of "risk perception - strategy generation - biofeedback," elastic matching of power, heat, and emergency lighting is achieved under complex operating conditions such as extreme micro-meteorological conditions and electromagnetic harmonic disturbances. This precisely achieves the operational goals of dynamically following load demand, intelligently dissipating supply redundancy, and minimizing multi-energy losses, significantly improving the disaster prevention and emergency response capabilities and multi-energy conversion efficiency of the underground energy station.

[0040] Please see Figure 1 As shown, it is a flowchart illustrating the integrated energy substation supply method of this embodiment, including:

[0041] Step S101: Collect environmental parameters, geological parameters, and energy requirements of the underground space. The environmental parameters include ambient temperature, ambient humidity, carbon dioxide concentration, and methane concentration. The geological parameters include rock stratum micro-vibration frequency, seepage rate, and rock stratum displacement. The energy requirements include electricity load requirements, heat load requirements, and emergency lighting energy consumption requirements.

[0042] For example, in this embodiment, the ambient temperature can be monitored by fixing an embedded temperature sensor (such as a PT100 or thermocouple) in a key area; the ambient humidity can be collected in real time using a capacitive humidity sensor or a resistive humidity sensor; the carbon dioxide concentration can be collected using a non-dispersive infrared (NDIR) gas sensor; the methane concentration can be monitored using a catalytic combustion sensor or a laser methane detector; the rock strata micro-vibration frequency can be collected by deploying a micro-vibration monitoring system using a piezoelectric accelerometer or a fiber optic vibration sensor; the seepage rate can be measured by installing an ultrasonic flow meter or an osmotic pressure sensor in the drainage pipe; the rock strata displacement can be measured using a laser displacement sensor or an inclinometer; and the energy demand parameters can be collected using a smart meter. This embodiment does not specifically limit the above data collection methods, and those skilled in the art can freely set them according to their needs.

[0043] Step S102: Construct environmental risk factors based on ambient temperature, ambient humidity, carbon dioxide concentration and methane concentration collected during the monitoring period; construct geological factors based on rock strata micro-vibration frequency, seepage rate and rock strata displacement collected during the monitoring period; and determine the underground space risk index by combining environmental factors and geological factors.

[0044] Specifically, a joint analysis framework for environment and geology is established, and the dynamic adaptability of risk characterization is improved through the nonlinear coupling of multidimensional parameters. This effectively identifies hidden environmental anomalies and potential instability trends in rock strata, and strengthens the forward-looking nature and comprehensive judgment capabilities of risk warning.

[0045] Please see Figure 2 As shown, the method for constructing the underground space risk index includes:

[0046] Step S201: Construct environmental factors based on environmental parameters collected during the monitoring period.

[0047] Specifically, in step S201, a first environmental risk factor is constructed based on the ambient temperature HT and ambient humidity HS collected during the monitoring period. The expression for the first environmental risk factor is y1=k1×max(HT-ht,0) / ht0+k2×max(HS-hs,0); where y1 is the first environmental risk factor, ht is the temperature threshold, ht0 is the temperature offset factor, hs is the humidity threshold, k1 is the temperature weight, k2 is the humidity weight, and k1+k2=1.

[0048] A second environmental risk factor is constructed based on the carbon dioxide concentration Hr and methane concentration Hj collected during the monitoring period. The expression for the second environmental risk factor is y2=k3×ln(Hr / hr+1)+k4×Hc / hc; where y2 is the second environmental risk factor, k3 is the methane weight, k4 is the carbon dioxide weight, k3+k4=1, hr is the methane threshold, and hc is the carbon dioxide threshold.

[0049] An environmental factor is constructed based on the first environmental risk factor y1 and the second environmental risk factor y2. The expression for the environmental factor is Y=exp(3×y1×y2-3).

[0050] For example, in this embodiment, the temperature threshold can be set to 30°C, the humidity threshold can be set to 0.7, the temperature offset factor can be set to 10°C, the humidity weight can be set to 0.6, the temperature weight can be set to 0.4, the methane concentration can be set to 10%, the carbon dioxide threshold can be set to 5000ppm, the methane weight can be set to 0.7, and the carbon dioxide weight can be set to 0.3. In this embodiment, the values ​​of the above data are not specifically limited, and those skilled in the art can set them freely according to their needs.

[0051] Specifically, based on the graded weighting calculation of ambient temperature, humidity and gas concentration, the cumulative effect of environmental anomalies is quantified, breaking through the limitations of a single threshold criterion and enhancing the sensitivity to microclimate anomalies and harmful gas risks in enclosed spaces.

[0052] Please continue reading. Figure 2 As shown, the method for constructing the underground space risk index includes:

[0053] Step S202: Construct geological factors based on the geological parameters collected during the monitoring period.

[0054] Specifically, in step S203, a geological factor D is constructed based on the rock strata micro-vibration frequency Fv, seepage rate Fs, and rock strata displacement Fw collected during the monitoring period, and is set as follows: ;

[0055] In the formula, fv is the vibration frequency threshold, fs is the seepage rate threshold, and fw is the displacement threshold.

[0056] For example, in this embodiment, the vibration frequency threshold can be set to 50Hz, the seepage rate can be set to 30L / min, and the displacement threshold can be set to 30mm. In this embodiment, the values ​​of the above data are not specifically limited, and those skilled in the art can set them freely according to their needs.

[0057] Specifically, geological factors are constructed as a quantitative representation of the dynamic response of rock strata, establishing a mapping relationship between rock strata stability and energy supply capacity, and providing key input parameters for cross-domain risk coupling analysis of environment and geology. Through the processing of multi-physics geological parameters, the critical characteristics of rock strata stress mutation and seepage risk are intuitively reflected, supporting the accurate matching of energy redundancy and security requirements in subsequent supply strategies, and avoiding supply strategy lags caused by insufficient quantification of geological anomalies.

[0058] Please continue reading. Figure 2As shown, the method for constructing the underground space risk index includes:

[0059] Step S203 involves fusing environmental factors with geological factors to determine the risk index of underground space.

[0060] Specifically, step S203 involves fusing environmental factor Y with geological factor D to determine the underground space risk index KF, ​​where KF = w1 × Y + w2 × D, w1 is the environmental weight, w2 is the geological weight, and w1 + w2 = 1.

[0061] For example, in this embodiment, the environmental weight can be set to 0.4 or 0.6; this embodiment does not specifically limit the setting of each weight, and those skilled in the art can set it freely according to their needs.

[0062] Specifically, by integrating nonlinear weighting of environmental and geological factors, a unified risk assessment benchmark is formed across the entire region. This ensures that the risk index simultaneously includes the combined effects of short-term meteorological anomalies and long-term geological instability. The integrated risk index generated in this step directly guides the dynamic adjustment range of the subsequent energy supply coefficient, providing a quantitative basis for the exponential response relationship of the power / heat supply coefficient and the superimposed compensation of emergency lighting, thus avoiding energy distribution imbalances caused by single-dimensional risk assessment.

[0063] Please continue reading. Figure 2 As shown, the integrated energy substation supply method includes,

[0064] Step S103: Determine the energy supply coefficient based on the underground space risk index of the monitoring period, and generate an energy supply strategy in combination with the energy demand of the next monitoring period.

[0065] Please see Figure 3 As shown, the energy supply strategy generation method includes:

[0066] Step S301: Determine the energy supply coefficient based on the underground space risk index of the monitoring period.

[0067] Specifically, step S301 determines the power supply coefficient Dq, heat supply coefficient Rq, and emergency lighting supply coefficient Yq based on the underground space risk index KF of the monitoring period;

[0068] The expression for the power supply coefficient Dq is Dq=2 / (1+e -5×KF -1; the expression for the heat supply coefficient Rq is: The expression for the emergency lighting supply coefficient Yq is Yq=min(Pe / Pc,1)+KF 2 / 2, Pe is the emergency lighting energy consumption requirement, and Pc is the critical emergency lighting energy consumption threshold.

[0069] Specifically, by constructing a multidimensional energy supply coefficient, discrete risk levels are transformed into continuous control commands for the energy system. The differentiated coefficient design in this step directly provides a mathematical benchmark for the dynamic adjustment of subsequent electricity and heat supply. At the same time, through the critical threshold superposition mechanism of the emergency lighting supply coefficient, the basic capacity of critical loads is prioritized to be locked when a risk is triggered, avoiding delays in emergency response or increased redundant energy consumption caused by a uniform global supply.

[0070] Specifically, the critical emergency lighting energy consumption threshold is the lower limit of electrical power required to maintain the minimum safe lighting level in underground spaces during sudden power outages or main power system failures, and can be obtained through user interaction.

[0071] Please continue reading. Figure 3 As shown, the energy supply strategy generation method further includes:

[0072] Step S302: Generate an energy supply strategy by combining the energy supply coefficient and the energy demand for the next monitoring period.

[0073] Specifically, in step S302, the power supply Gd for the next monitoring period is determined based on the power load demand Wd and the power supply coefficient Dq for the next monitoring period, where Gd = Wd × Dq.

[0074] The heat supply Gr for the next monitoring period is determined based on the heat load demand Wr and the heat supply coefficient Rq, where Gr = Wr × Rq.

[0075] The emergency lighting supply Gz for the next monitoring period is determined based on the emergency lighting energy consumption demand Pe and the emergency lighting supply coefficient Yq, where Gz = Pe × Yq.

[0076] Specifically, based on the real-time matching of demand forecasts and supply coefficients, a flexible and adjustable energy allocation strategy is generated to ensure the flexible expansion and contraction of supply capacity under different risk levels and to coordinate the efficient coupling operation of multiple energy subsystems.

[0077] Please continue reading. Figure 1 As shown, the integrated energy substation supply method further includes:

[0078] Step S104: Compare the electromagnetic interference intensity of the cable collected during the monitoring period with the intensity discrimination factor to determine the update factor.

[0079] Specifically, in step S104, the electromagnetic interference intensity Ep of the cable collected during the monitoring period is compared with the intensity discrimination factor E0. If Ep is less than or equal to E0, the update factor is set to η; otherwise, the update factor is set to {η×{1+[(Ep-E0) / (Ep+E0)]}. 1.5}}, where η is the preset update factor.

[0080] For example, in this embodiment, the intensity discrimination factor can be set to 5 volts per meter, and the preset update factor can be set to 0.5; this embodiment does not specifically limit the setting of the above data, and those skilled in the art can set it freely according to their needs.

[0081] Specifically, by dynamically identifying and compensating for the electromagnetic interference intensity of cables, the continuous disturbance of power frequency harmonics to the supply strategy can be effectively suppressed, the system's anti-interference ability against sudden changes in the electromagnetic environment can be enhanced, and the stability and robustness of the control logic can be maintained.

[0082] Please continue reading. Figure 1 As shown, the integrated energy substation supply method further includes:

[0083] Step S105: Based on the infrasound harmonic ratio, lichen conductivity, and renewal factor collected during the monitoring period, update the energy supply strategy. The infrasound harmonic ratio is the ratio of frequency band [0.1Hz, 3Hz] energy to full-band sound energy. The lichen conductivity is a comprehensive parameter characterizing the electrical response of lichen obtained by measuring the current difference under dark and light conditions when a constant voltage is applied to the surface of the lichen biofilm, combined with the lichen water content.

[0084] Specifically, in step S105, the conductivity of the lichen during the monitoring period is denoted as Lc, and the expression for Lc is Lc=V / |A1-A2|×[1+0.05×(SL-0.65)]; where V is the applied DC voltage, A1 is the steady-state loop current when the lichen is in contact with the electrode in the absence of light, A2 is the loop current after the lichen is excited at 1000 lux, and SL is the water content of the lichen;

[0085] Based on the lichen conductivity Lc, the proportion of infrasound harmonics Z, and the renewal factor, the energy supply strategy is updated, and the power supply coefficient for the next monitoring cycle is set to Dq1, where Dq1 = Dq × {1 - α × renewal factor × [ln(1 + 10Z) / ln11 × Lc / L0]}, where L0 is the preset conductivity and α is the preset adjustment factor.

[0086] Specifically, a bio-physical feedback mechanism consisting of infrasound harmonics and lichen electrical response is introduced, combined with a self-renewing dynamic correction factor, to achieve real-time compensation of the supply strategy for hidden environmental disturbances (such as ground pressure fluctuations and microbial activity), thereby improving the system's adaptability to nonlinear and long-period environmental induced effects.

[0087] For example, in this embodiment, the preset conductivity can be set to 0.3 S / m, and the preset adjustment factor can be set to 0.4. This embodiment does not specifically limit the setting of the above data, and those skilled in the art can set it freely according to their needs.

[0088] For example, in this embodiment, the electromagnetic interference intensity of the cable can be measured using an electromagnetic field tester or a spectrum analyzer to collect power frequency interference data. The proportion of infrasound harmonics can be calculated using a broadband acoustic sensor (0.1Hz–200Hz range) in conjunction with Fourier transform analysis. The applied DC voltage can be applied to the bidirectional electrodes on the surface of the lichen biofilm using a 12V DC power supply. The steady-state loop current of the lichen in contact with the electrodes when there is no light and the loop current of the lichen after excitation at 1000 lux can be collected using a high-precision ammeter. The lichen moisture content can be measured using an infrared moisture meter or a capacitive humidity sensor. In this embodiment, the method of collecting the above data is not specifically limited, and those skilled in the art can freely set it according to their needs.

[0089] For example, in this embodiment, the monitoring period can be set to 5 seconds; this embodiment does not specifically limit the setting of the monitoring period, and those skilled in the art can set it freely according to their needs.

[0090] Please see Figure 4 As shown, the integrated energy substation supply device includes:

[0091] The data acquisition unit is used to collect environmental parameters, geological parameters, and energy requirements of underground spaces.

[0092] The index determination unit is used to construct environmental risk factors based on ambient temperature, ambient humidity, carbon dioxide concentration and methane concentration collected during the monitoring period, construct geological factors based on rock strata micro-vibration frequency, seepage rate and rock strata displacement collected during the monitoring period, and combine environmental factors and geological factors to determine the underground space risk index.

[0093] The energy supply unit is used to determine the energy supply coefficient based on the underground space risk index of the monitoring period, and to generate an energy supply strategy in combination with the energy demand of the next monitoring period.

[0094] The weight determination unit is used to compare the electromagnetic interference intensity of the cable collected during the monitoring period with the intensity discrimination factor in order to determine the update factor;

[0095] The update unit is used to update the energy supply strategy based on the proportion of infrasound harmonics, lichen conductivity and update factor collected during the monitoring period.

[0096] This application also provides an electronic device for executing the integrated energy substation supply method. For example... Figure 5As shown, the electronic device includes: a processor unit 501, a memory unit 502, a communication interface unit 503, and a bus architecture unit 504. The processor unit includes at least one processor unit, which is composed of one or more of a central processing unit (CPU), a graphics processing unit (GPU), and a programmable gate array (FPGA). The processor unit is configured to perform data operations and generate operation control signals by executing a code instruction set. The memory unit includes a composite structure of non-volatile storage medium and erasable dynamic storage medium. The non-volatile storage medium preferably adopts a flash memory chip or a solid-state drive structure for storing program code and historical databases. The erasable dynamic storage medium adopts a random access chip array to provide runtime data caching and intermediate variable temporary storage functions. The communication interface unit integrates a dual-mode communication link between a first communication module and a second communication module. The first communication module implements local sensor network interconnection based on a wired data transmission link, and its physical layer protocol is adapted to the Ethernet standard and RS-485 industrial bus specification. The second communication module establishes a wide-area remote service connection based on a wireless communication link, and its protocol stack is compatible with the LoRa spread spectrum communication protocol, the fifth-generation mobile communication technology specification, and satellite communication standards. The bus architecture unit realizes data interaction and clock synchronization control between core components based on the high-speed bus specification, and its topology uses PCI. The Express interconnect protocol or AXI on-chip bus standard is a bus architecture unit that can operatively connect processor units, memory units and communication interface units to a high-speed data path and provides a phase-aligned clock synchronization signal transmission mechanism.

[0097] This embodiment also provides a computer-readable storage medium, which physically stores computer-executable instructions. When the instructions are transmitted to the processing unit via the integrated circuit substrate, they are encapsulated and processed through the data channel of the bus system and then solidified into the non-volatile storage area of ​​the storage module. The executable instructions are configured to implement the complete technical solution of the integrated energy substation supply method when executed by the processor.

[0098] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the implementation of the present invention. For those skilled in the art, other variations or modifications can be made based on the above description. It is impossible to exhaustively list all the implementation methods here. All obvious variations or modifications derived from the technical solutions of the present invention are still within the protection scope of the present invention.

Claims

1. A method for supplying integrated energy to a substation, characterized in that, include: Environmental risk factors are constructed based on ambient temperature, humidity, carbon dioxide concentration and methane concentration collected during the monitoring period. Geological factors are constructed based on rock strata micro-vibration frequency, seepage rate and rock strata displacement collected during the monitoring period. The underground space risk index is determined by combining environmental factors and geological factors. The energy supply coefficient is determined based on the underground space risk index of the monitoring period, and an energy supply strategy is generated by combining the energy demand of the next monitoring period. The energy supply coefficient includes the electricity supply coefficient Dq, the heat supply coefficient Rq, and the emergency lighting supply coefficient Yq. The generation process of the energy supply strategy is as follows: the electricity supply Gd for the next monitoring period is determined based on the electricity load demand Wd and the electricity supply coefficient Dq, where Gd = Wd × Dq; the heat supply Gr for the next monitoring period is determined based on the heat load demand Wr and the heat supply coefficient Rq, where Gr = Wr × Rq; and the emergency lighting supply Gz for the next monitoring period is determined based on the emergency lighting energy consumption demand Pe and the emergency lighting supply coefficient Yq, where Gz = Pe × Yq. The electromagnetic interference intensity of the cable collected during the monitoring period is compared with the intensity discrimination factor to determine the update factor; Based on the infrasound harmonic ratio, lichen conductivity and renewal factor collected during the monitoring period, an energy supply strategy is updated. The electromagnetic interference intensity Ep collected during the monitoring period is compared with the intensity discrimination factor E0. If Ep is less than or equal to E0, the update factor is set to η; otherwise, the update factor is set to {η×{1+[(Ep-E0) / (Ep+E0)]}. 1.5 }}, where η is a preset update factor, the intensity discrimination factor is 5 volts per meter, and the preset update factor is 0.5; The lichen conductivity during the monitoring period is denoted as Lc. The energy supply strategy is updated based on the lichen conductivity Lc, the infrasound harmonic ratio Z, and the update factor. The power supply coefficient for the next monitoring period is set as Dq1, where Dq1 = Dq × {1 - α × update factor × [ln(1 + 10Z) / ln11 × Lc / L0]}, where L0 is the preset conductivity and α is the preset adjustment factor.

2. The integrated energy substation supply method according to claim 1, characterized in that, Collect environmental parameters, geological parameters, and energy requirements of underground spaces; The first environmental risk factor y1 is constructed based on the ambient temperature HT and ambient humidity HS collected during the monitoring period. The second environmental risk factor y2 is constructed based on the carbon dioxide concentration Hr and methane concentration Hj collected during the monitoring period. An environmental factor is constructed based on the first environmental risk factor y1 and the second environmental risk factor y2. The expression of the environmental factor is Y=exp(3×y1×y2-3).

3. The integrated energy substation supply method according to claim 2, characterized in that, Geological factor D is constructed based on the rock strata micro-vibration frequency Fv, seepage rate Fs, and rock strata displacement Fw collected during the monitoring period, and is defined as follows: ； In the formula, fv is the vibration frequency threshold, fs is the seepage rate threshold, and fw is the displacement threshold.

4. The integrated energy substation supply method according to claim 3, characterized in that, The environmental factor Y and the geological factor D are integrated for analysis to determine the underground space risk index KF, ​​KF=w1×Y+w2×D, where w1 is the environmental weight, w2 is the geological weight, and w1+w2=1.

5. The integrated energy substation supply method according to claim 4, characterized in that, The underground space risk index KF based on the monitoring period determines the power supply coefficient Dq, heat supply coefficient Rq, and emergency lighting supply coefficient Yq. The expression for the power supply coefficient Dq is Dq=2 / (1+e -5×KF -1; the expression for the heat supply coefficient Rq is: The expression for the emergency lighting supply coefficient Yq is Yq=min(Pe / Pc,1)+KF 2 / 2, where Pc is the critical emergency lighting energy consumption threshold.

6. A comprehensive energy substation supply device, applied to the comprehensive energy substation supply method as described in any one of claims 1-5, characterized in that, include: The data acquisition unit is used to collect environmental parameters, geological parameters, and energy requirements of underground spaces. The index determination unit is used to construct environmental risk factors based on ambient temperature, ambient humidity, carbon dioxide concentration and methane concentration collected during the monitoring period, construct geological factors based on rock strata micro-vibration frequency, seepage rate and rock strata displacement collected during the monitoring period, and combine environmental factors and geological factors to determine the underground space risk index. The energy supply unit is used to determine the energy supply coefficient based on the underground space risk index of the monitoring period, and to generate an energy supply strategy in combination with the energy demand of the next monitoring period. The weight determination unit is used to compare the electromagnetic interference intensity of the cable collected during the monitoring period with the intensity discrimination factor in order to determine the update factor; The update unit is used to update the energy supply strategy based on the proportion of infrasound harmonics, lichen conductivity and update factor collected during the monitoring period.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, wherein the computer program is used to control the electronic device on which the computer-readable storage medium is located to perform the integrated energy substation supply method according to any one of claims 1-5 during runtime.

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