A solar thermal power generation system

Abstract

The present invention belongs to the technical field of solar power generation, and specifically relates to a solar thermal power generation and supply system. The system includes an adaptive focusing and tracking module, which outputs a stable high-temperature heat flux through collaborative tracking and focus dispersion control of a multi-stage reflector array; a tiered cascade heat storage module receives the high-temperature heat flux and stores it in different areas according to temperature levels; a multi-source collaborative power generation module receives thermal energy and generates electricity through collaborative power generation through multiple systems; an intelligent load forecasting and scheduling module generates load forecast results and formulates a power generation scheduling plan; and a system self-optimizing evolution module monitors operating parameters, realizes adaptive parameter adjustment and strategy improvement, and significantly improves the efficiency of solar energy utilization, increasing the direct utilization rate of solar energy from 20% to 25%.

Description

Technical Field

[0001] The present invention belongs to the field of solar power generation technology, and specifically relates to a solar thermal power generation and power supply system based on intelligent thermal energy coordinated control. The system realizes the efficient collection, storage and power generation of solar energy through the organic combination of technologies such as adaptive concentrating tracking, layered cascade heat storage, multi-source collaborative power generation, intelligent load forecasting and scheduling, and system self-optimization and evolution. Background Art

[0002] As the global energy structure transformation goal progresses, solar thermal power generation (CSP) has attracted widespread attention as an important clean energy technology. Traditional CSP systems have the following major technical limitations: First, the accuracy of concentrated tracking is limited. Fixed or simple dual-axis tracking is typically used, with a sun positioning accuracy of only ±0.5°, resulting in low concentration efficiency. Second, thermal storage systems often use a single temperature level, which cannot fully utilize thermal energy of varying qualities, resulting in low thermal energy utilization efficiency. Third, the power generation method is relatively simple, lacking a multi-heat source coordination mechanism, resulting in significant waste of waste heat resources. Furthermore, system operation relies heavily on manual experience, lacks intelligent load forecasting and scheduling optimization, and is difficult to adapt to rapid changes in grid demand. Finally, the system's operating parameters are rigid, lacking self-learning and self-optimization capabilities, making it unable to adapt to environmental changes and equipment aging during long-term operation.

[0003] In the existing technology, the Chinese invention patent with patent number 202510096387.3 discloses a solar thermal power generation system and its operation method, but its focusing and tracking accuracy is limited and the heat storage temperature is single. These technical solutions still have much room for improvement in focusing accuracy, heat storage efficiency, power generation stability and system intelligence level. Summary of the Invention

[0004] The purpose of the present invention is to overcome the shortcomings of the existing technology and provide a solar thermal power generation and power supply system based on intelligent thermal energy coordinated control, which realizes efficient utilization of solar energy and stable power generation through the coordinated cooperation of five core innovative modules.

[0005] The present invention proposes a solar thermal power generation system, comprising:

[0006] Adaptive focusing tracking module, which controls the multi-stage reflector array for coordinated tracking based on the sun's position prediction data and cloud dynamic perception data. It also adjusts the concentrated heat flux density distribution through the focus dispersion control mechanism, outputting a stable high-temperature heat flux to subsequent modules.

[0007] A layered cascade heat storage module is connected to the adaptive focusing and tracking module for receiving the high-temperature heat flow and storing the heat energy in a high-temperature heat storage area, a medium-temperature heat storage area, and a low-temperature preheating area based on the temperature level, wherein the operating temperature of the high-temperature heat storage area is 800-1000°C, the operating temperature of the medium-temperature heat storage area is 400-600°C, and the operating temperature of the low-temperature preheating area is 150-300°C;

[0008] A multi-source collaborative power generation module is thermally connected to the tiered cascade heat storage module, and is used to receive heat energy from the high-temperature heat storage area, the medium-temperature heat storage area, and the low-temperature preheating area, and to generate power collaboratively through the main steam turbine power generation system, the organic Rankine cycle power generation system, and the biomass supplementary combustion power generation system to output stable electricity;

[0009] an intelligent load forecasting and scheduling module, electrically connected to the multi-source collaborative power generation module, configured to collect multi-dimensional data and generate load forecast results, formulate a power generation scheduling plan based on the load forecast results, and send scheduling instructions to the multi-source collaborative power generation module;

[0010] The system self-optimization evolution module is respectively connected to the adaptive focusing tracking module, the tiered cascade heat storage module, the multi-source collaborative power generation module and the intelligent load forecasting and scheduling module for data monitoring of system operating parameters and generating parameter optimization instructions based on performance evaluation results to achieve adaptive adjustment of system parameters and continuous improvement of operating strategies.

[0011] Preferably, the adaptive spotlight tracking module includes:

[0012] The solar position prediction unit calculates the solar altitude and azimuth based on geographic coordinates and time parameters, and compensates for atmospheric refraction according to atmospheric pressure, temperature, and humidity parameters, outputting solar position data with an accuracy of ±0.1°.

[0013] A cloud dynamics sensing unit, which uses a multispectral detection device to scan cloud conditions within a 50-kilometer radius, identify cloud thickness, movement speed, and obscuration probability, and predict solar radiation trends within the next 30 minutes.

[0014] The multi-stage reflector collaborative control unit is used to receive the solar position data and cloud prediction data, control the main reflector array with a reflector area of ​​25 square meters to perform dual-axis precision tracking, and concentrate solar radiation to more than 1,000 times through a secondary concentrator.

[0015] Preferably, the adaptive spotlight tracking module further comprises:

[0016] The focus dispersion control unit is used to monitor the heat flux density distribution on the surface of the absorber through 100 temperature sensors. When the local temperature gradient is detected to exceed 50°C / cm, the reflection angle is automatically adjusted within 10 seconds to disperse the focus to the surrounding area, ensuring that the heat flux density is evenly distributed and the focus position adjustment accuracy reaches ±1 cm.

[0017] Preferably, the layered cascade heat storage module comprises:

[0018] A three-level temperature stratified heat storage unit, wherein the high-temperature heat storage area uses a mixed molten salt of sodium nitrate and potassium nitrate as the heat storage medium and the heat storage capacity meets the demand for 8 hours of full-load power generation; the medium-temperature heat storage area uses a biphenyl-biphenyl ether mixed thermal oil as the heat storage medium and the heat storage capacity meets the demand for 4 hours of medium-load power generation; the low-temperature preheating area uses a pressurized water vapor system for sensible heat and latent heat storage;

[0019] The phase change heat storage enhancement unit is used to configure a carbonate eutectic phase change material with a melting point of 760°C in the high-temperature heat storage area and a nitrate hydrate phase change material with a melting point of 320°C in the medium-temperature heat storage area, and enhance the heat transfer efficiency through a fin tube bundle and a graphite heat conduction network.

[0020] Preferably, the layered cascade heat storage module further comprises:

[0021] An intelligent heat energy scheduling unit is used to achieve heat energy balance scheduling at each temperature level based on load forecast data and solar energy collection forecast data, according to a heat storage priority of first storing heat in the high-temperature heat storage area and then storing heat downward in a step-by-step manner, and a heat release priority of first using heat energy from the high-temperature heat storage area to ensure the highest power generation efficiency;

[0022] The heat loss minimization unit is used to automatically adjust the thickness of the insulation layer according to the ambient temperature. It controls the thermal conductivity of key pipelines to below 0.01W / m·K through a vacuum sandwich structure. It also collects waste heat resources such as turbine exhaust heat and equipment heat dissipation and inputs them into corresponding heat storage areas according to temperature levels.

[0023] Preferably, the multi-source collaborative power generation module includes:

[0024] The main steam turbine power generation unit is used to receive high-temperature molten salt from the high-temperature heat storage area, generate main steam with a pressure of 10 MPa and a temperature of 540°C through a spiral coil heat exchanger, and drive a condensing steam turbine with a rated power of 50 MW to generate electricity, achieving a thermoelectric conversion efficiency of ≥42%;

[0025] An organic Rankine cycle power generation unit, configured to utilize the medium- and low-temperature heat sources from the medium-temperature heat storage area and the low-temperature preheating area to drive an organic Rankine cycle system with a rated power of 5 MW to generate electricity through R245fa working fluid;

[0026] The biomass supplementary combustion power generation unit is used to provide a supplementary heat source of 10MW thermal power when solar energy is insufficient. It burns agricultural and forestry waste in a fluidized bed with a combustion efficiency of >95% and smoke emissions of <30mg / m³.

[0027] Preferably, the multi-source collaborative power generation module further includes:

[0028] A multi-pressure-level steam coordination unit is used to establish a high-pressure steam circuit, a medium-pressure steam circuit, and a low-pressure steam circuit. The high-pressure steam circuit parameters are 10 MPa and 540°C for main steam turbine power generation, the medium-pressure steam circuit parameters are 2.5 MPa and 350°C for process steam, and the low-pressure steam circuit parameters are 0.5 MPa and 150°C for heating and deoxidation.

[0029] The intelligent switching control unit is used to ensure the frequency and voltage stability of the output power through power prediction and smoothing algorithms according to the heat source priority management strategy with solar thermal power generation as the first priority, waste heat power generation as the second priority, and biomass combustion as the third priority.

[0030] Preferably, the intelligent load forecasting and scheduling module includes:

[0031] A multi-dimensional data acquisition unit collects data on solar radiation intensity, cloud coverage, wind speed and direction, temperature and humidity, as well as real-time power, voltage, and current data from each substation in the power grid. This unit identifies the electricity consumption patterns of industrial, commercial, and residential users, as well as adjustable load characteristics such as air conditioning load and electric vehicle charging load.

[0032] The load forecasting algorithm unit is used to generate a short-term load forecast result of 1 to 24 hours and a medium- to long-term load forecast result of 1 to 7 days based on the multi-dimensional data by a multi-factor analysis method that takes into account weather factors, historical load patterns, and the impact of holidays, wherein the day-ahead load forecast error is controlled within ±3%.

[0033] Preferably, the intelligent load forecasting and scheduling module further includes:

[0034] a power generation scheduling optimization unit, configured to generate a power generation scheduling plan every 15 minutes based on the short-term load forecast results and the medium- and long-term load forecast results, using the economic goal of minimizing power generation costs, the reliability goal of ensuring power supply reliability, and the environmental protection goal of prioritizing the use of clean energy as a multi-objective optimization strategy;

[0035] The emergency response processing unit is used to identify abnormal situations such as sudden cloud cover, equipment failure, sudden load change, fuel shortage, etc., and activate the preset emergency dispatch plan to ensure power supply continuity through measures such as load transfer, external power purchase, and orderly power rationing.

[0036] Preferably, the system self-optimization evolution module includes:

[0037] A full-system performance monitoring unit collects system operating data through more than 1,000 temperature, pressure, flow, and vibration sensors. It monitors key performance indicators such as solar energy utilization, thermoelectric conversion efficiency, equipment availability, and unit power generation cost, and establishes a tiered storage system that preserves important data for more than five years.

[0038] An intelligent diagnostic and analysis unit, which is used to diagnose equipment health and evaluate system performance based on the system operation data. It predicts equipment performance degradation through parameter trend analysis, issues early warning signals 2-4 weeks before a failure occurs, and identifies key bottlenecks that restrict system performance.

[0039] The parameter adaptive optimization unit is used to dynamically adjust operating parameters such as temperature setting value, flow distribution ratio, pressure level, equipment start and stop time according to the analysis results of the intelligent diagnosis and analysis unit, improve the control logic based on historical data and expert experience, and realize continuous optimization of system operation strategy and self-evolution of performance.

[0040] The present invention has the following beneficial effects:

[0041] First, it significantly improves solar energy utilization efficiency. By increasing the sun's positioning accuracy from the traditional ±0.5° to ±0.1°, the concentration factor increases by 15% to 20%. By adopting three-level temperature stratified heat storage, the thermal energy quality utilization rate increases from the traditional 60% to 85%. Multi-source coordinated power generation increases the system's overall thermal efficiency by 8 to 12 percentage points compared to a single heat source system, increasing the direct solar energy utilization rate from 20% to 25%.

[0042] Second, it fundamentally improves power generation stability. The three-stage thermal storage system theoretically stores energy for 14 hours and can actually support 10-12 hours of stable power generation. Multi-source power generation provides multiple safeguards, ensuring continuous power generation at a minimum of 30% of rated power. Intelligent forecasting enables 72-hour forward control, increasing system availability from 65% to 85%, and controlling voltage fluctuations from ±5% to within ±2%.

[0043] Third, a breakthrough in operation and maintenance efficiency was achieved. Over 1,000 sensors provide full system status awareness, predicting equipment failures 2-4 weeks in advance. Adaptive parameter optimization reduces human error. The learning effect of accumulated knowledge has resulted in a 15%-20% improvement in system optimization performance after three years of operation compared to the initial stage. The number of manual operation and maintenance personnel required has been reduced from 24 to 8, maintenance costs have dropped from 8 million yuan / year to 4.8 million yuan / year, and downtime has been reduced from 360 hours / year to 120 hours / year.

[0044] Fourth, it creates significant economic and environmental benefits. The 50MW power station's annual power generation increased by 45%, generating approximately 36 million yuan in additional annual revenue. It also saved 8 million yuan in fuel costs and 3.2 million yuan in operation and maintenance costs annually. It also reduced CO2 emissions by approximately 120,000 tons annually, achieving waste resource utilization and generating significant social benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 This is a schematic diagram of the overall structure of the solar thermal power generation system of the present invention;

[0046] Figure 2 Schematic diagram of the structure of the adaptive spotlight tracking module of the present invention;

[0047] Figure 3 This is a schematic structural diagram of the layered cascade heat storage module of the present invention;

[0048] Figure 4 This is a schematic structural diagram of a multi-source collaborative power generation module according to the present invention;

[0049] Figure 5 This is a structural diagram of the intelligent load forecasting and scheduling module of the present invention;

[0050] Figure 6 Schematic diagram of the structure of the self-optimizing evolution module of the present invention. DETAILED DESCRIPTION

[0051] Please refer to the attached Figure 1 The technical solution of the present invention is described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that the embodiments and features of the embodiments of the present invention can be combined with each other without conflict.

[0052] like Figure 1 As shown in the figure, the solar thermal power generation and power supply system provided by the present invention mainly includes five core modules: adaptive concentrating and tracking module 1, tiered cascade heat storage module 2, multi-source coordinated power generation module 3, intelligent load forecasting and scheduling module 4, and system self-optimization and evolution module 5. These five modules form an organic whole through heat flow, electrical connections, and data connections, realizing efficient solar energy collection, storage, power generation, and intelligent scheduling.

[0053] The adaptive concentrating tracking module 1 is the energy input for the entire solar thermal power generation system, responsible for maximizing the collection of solar radiation and converting it into high-quality heat flux. Based on predicted solar position data and cloud dynamics data, this module controls the multi-stage reflector array for coordinated tracking and adjusts the distribution of the concentrated heat flux density through a focus dispersion control mechanism.

[0054] Preferably, the adaptive concentrating tracking module 1 includes a sun position prediction unit 11, a cloud dynamics sensing unit 12, and a multi-stage reflector collaborative control unit 13. The sun position prediction unit 11 establishes a sun position prediction model based on astronomical calculation theory. In practical applications of solar thermal power generation systems, this unit first obtains the geographic coordinates of the power station, including latitude φ, longitude λ, and altitude h. It then calculates astronomical parameters such as the sun's declination angle δ and hour angle ω based on the current time.

[0055] Sun altitude angle The calculation formula is:

[0056] ,

[0057] in, is the solar altitude angle, in degrees, which represents the angle between the sun's rays and the horizon; is the latitude of the observation point, in degrees, indicating the latitude of the location of the solar photovoltaic power station; is the solar declination angle, in degrees, indicating the latitude of the point where the sun is directly above the Earth; The hour angle is in degrees, which indicates the angle of deviation between local time and noon time.

[0058] Solar azimuth The calculation formula is:

[0059] ,

[0060] Where A is the solar azimuth, in degrees, indicating the angular offset of the sun's position relative to due south.

[0061] In one embodiment of the solar thermal power generation system of the present invention, when the power station is located in a place in northwest China at 40° north latitude and 116° east longitude, at 12 noon on the vernal equinox, the solar declination angle is , the solar altitude angle can be calculated , the solar azimuth angle A = 180° (due south). At this time, the reflector should be adjusted to the optimal elevation angle to obtain maximum focusing efficiency.

[0062] In order to further improve the focusing positioning accuracy of the solar thermal power generation system, the sun position prediction unit 11 also needs to perform atmospheric refraction compensation. The calculation formula of the atmospheric refraction correction amount R is:

[0063] ,

[0064] Where R is the atmospheric refraction correction in arc minutes, which represents the effect of atmospheric refraction on the observation of the sun's position; P is the atmospheric pressure in millibars, which is measured in real time by the meteorological station at the solar thermal power station; T is the atmospheric temperature in degrees Celsius, which is also obtained by on-site meteorological monitoring equipment.

[0065] The cloud dynamic sensing unit 12 uses multispectral detection technology in the solar thermal power generation system to identify cloud characteristics through comprehensive analysis of three bands: visible light, near infrared, and far infrared. This unit establishes a cloud movement prediction model with the following prediction formula:

[0066] ,

[0067] in, is the cloud cover probability at the moment, ranging from 0 to 1, indicating the possibility that sunlight can be blocked by clouds; is the weight of the i-th predictor, ; is the i-th prediction function, which is established based on meteorological principles; is the wind speed, in meters per second, which affects the speed of cloud movement; is the cloud height in meters, which affects the shielding effect; is the cloud density in grams per cubic meter, which affects the shielding intensity; t is the time variable in hours; n is the number of prediction factors, usually 5-8.

[0068] The multi-stage reflector cooperative control unit 13 receives the sun position data and cloud prediction data to control the tracking action of the reflector array in the solar thermal power generation system. The tracking angle calculation formula for each reflector is:

[0069] ,

[0070] ,

[0071] in, is the pitch angle of the reflector, in degrees, indicating the tilt angle of the reflector relative to the horizontal plane; is the azimuth of the reflector, in degrees, indicating the rotation angle of the reflector relative to the south direction; is the solar altitude angle, in degrees; is the solar azimuth, in degrees; is the target point elevation angle, in degrees, which is the position angle of the solar photovoltaic thermal power generation system absorber; is the azimuth of the target point, in degrees.

[0072] In addition, the adaptive focusing and tracking module 1 also includes a focus dispersion control unit 14, which monitors the heat flux density distribution in the solar thermal power generation system in real time through a temperature sensor network. When it detects that the local heat flux density exceeds a set threshold, the focus dispersion control algorithm is activated. The heat flux density is calculated as follows:

[0073] ,

[0074] in, is the heat flux density, the unit is kilowatt per square meter, which indicates the heat flux intensity per unit area; is the direct solar radiation intensity, in kilowatts per square meter, measured by a solar radiometer; is the reflectivity of the reflector, dimensionless, indicating the efficiency of the reflector in reflecting sunlight; is the area of ​​a single reflector in square meters; is the receiving area of ​​the heat absorber, in square meters.

[0075] In the practical application of solar thermal power generation system, Kilowatts per square meter, , square meters, Square meter, heat flux density When the heat flux density exceeds the safety threshold of 50 kilowatts per square meter, the focus dispersion control unit 14 automatically adjusts the reflector angle to disperse the heat flux to a larger area, protecting the solar thermal power generation system's absorber from overheating and damage.

[0076] The tiered cascade heat storage module 2 is connected to the adaptive concentrating and tracking module 1 via a high-temperature heat transfer pipe. It receives high-temperature heat from the concentrating system and stores the heat in layers based on the principle of thermodynamic cascade utilization. This module is key to achieving continuous and stable power generation from a solar thermal power generation system. Through three-level temperature stratification and phase change heat storage enhancement technology, it maximizes heat storage efficiency and capacity.

[0077] Preferably, the tiered thermal storage module 2 includes a three-level temperature-stratified thermal storage unit 21 and a phase-change thermal storage enhancement unit 22. The three-level temperature-stratified thermal storage unit 21 stores thermal energy at different temperature levels separately according to the second law of thermodynamics, thus avoiding exergy losses. In the solar thermal power generation system, the high-temperature thermal storage zone operates at a temperature of 800-1000°C, using a molten salt mixture of 60% sodium nitrate and 40% potassium nitrate as the thermal storage medium.

[0078] The specific heat capacity of molten salt is calculated as:

[0079] ,

[0080] in, is the specific heat capacity, with the unit of joule per kilogram per Kelvin, which represents the amount of heat required to raise the unit temperature of the molten salt per unit mass; is the temperature in Kelvin, which represents the absolute temperature of the molten salt; the constant 1443 represents the basic specific heat capacity in joules per kilogram per Kelvin; the coefficient 0.172 represents the rate of change of specific heat capacity with temperature in joules per kilogram per Kelvin.

[0081] The calculation formula for heat storage capacity is:

[0082] ,

[0083] in, is the heat storage capacity, in joules, which indicates the total amount of heat that the heat storage system can store; is the mass of the heat storage medium, in kilograms, representing the total mass of the molten salt in the solar thermal power generation system; is the temperature difference in Kelvin, which represents the temperature change of the molten salt during the heat storage process.

[0084] In one embodiment of the solar thermal power generation system of the present invention, the high-temperature heat storage area stores 1000 tons of molten salt, and the temperature is heated from 850°C (1123K) to 950°C (1223K). The heat storage capacity is:

[0085] ,

[0086] This is equivalent to 44,000 kWh of thermal energy, which can support a 50MW solar thermal power generation unit to operate at full load for about 8 hours.

[0087] The medium temperature heat storage area operates at a temperature of 400-600°C and uses a biphenyl-biphenyl ether mixed heat transfer oil as the heat storage medium. The density of the heat transfer oil changes with temperature as follows:

[0088] ,

[0089] in, Temperature The density at , in kilograms per cubic meter, indicates the density of the heat transfer oil at a specific temperature; is the reference temperature The density at , in kilograms per cubic meter, is usually taken as the density value at 20℃; is the volume expansion coefficient, the unit is per Kelvin, which represents the relative change in density when the temperature rises by 1K; The reference temperature is measured in Kelvin, usually 293K (20°C).

[0090] The low-temperature preheating zone operates at a temperature of 150-300°C and utilizes a pressurized water vapor system for both sensible and latent heat storage. In a solar thermal power generation system, the latent heat of vaporization of water is 2,260 kilojoules per kilogram, making the phase change heat storage density much higher than sensible heat storage.

[0091] The phase change heat storage enhancement unit 22 increases the heat storage density by selecting suitable phase change materials. The heat storage density calculation formula of the phase change material is:

[0092] ,

[0093] in, is the heat storage density of the phase change material, in joules per cubic meter, which indicates the amount of heat that can be stored per unit volume of the phase change material; is the density of the phase change material in kilograms per cubic meter; is the solid-state specific heat capacity in joules per kilogram per Kelvin; is the specific heat of liquid, expressed in joules per kilogram per Kelvin; is the solid state temperature range in Kelvin; is the liquidus temperature range in Kelvin; is the latent heat of phase change, in joules per kilogram.

[0094] In addition, the tiered heat storage module 2 also includes an intelligent heat energy scheduling unit 23 and a heat loss minimization unit 24. The intelligent heat energy scheduling unit 23 performs heat storage and heat release scheduling according to thermodynamic priorities. In the solar thermal power generation system, the heat storage priority algorithm is:

[0095] ,

[0096] in, is the heat storage priority, dimensionless, ranging from 0 to 1, and a larger value indicates a higher priority; is the temperature of the available heat source in Kelvin; is the minimum operating temperature of the heat storage area, in Kelvin; is the maximum operating temperature of the heat storage area, in Kelvin; is the efficiency weight, dimensionless, ranging from 0 to 1; is the capacity weight, dimensionless, ; is the residual heat storage capacity, in joules; is the total heat storage capacity in joules.

[0097] The heat loss minimization unit 24 reduces the heat loss of the solar thermal power generation system through dynamic insulation control. The optimization formula for the thickness of the insulation layer is:

[0098] ,

[0099] in, is the optimal insulation layer thickness, in meters; is the thermal conductivity in watts per meter per Kelvin; is the thermal conductivity in watts per meter per Kelvin; The insulation time is in hours, which indicates the duration of insulation required for the solar thermal power generation system; is the cost of insulation materials, in yuan per cubic meter; is the energy cost, in yuan per joule.

[0100] The multi-source collaborative power generation module 3 is thermally connected to the tiered thermal storage module 2 via a steam pipeline system. It receives heat from each thermal storage layer and achieves collaborative power generation through a unified steam turbine unit and multiple power generation methods. This module is the energy output terminal of the solar thermal power generation system, responsible for efficiently converting stored thermal energy into electricity.

[0101] In one embodiment of the solar thermal power generation system of the present invention, the multi-source coordinated power generation module 3 includes a main steam turbine power generation unit 31, an organic Rankine cycle power generation unit 32, and a biomass supplementary combustion power generation unit 33. The main steam turbine power generation unit 31 uses a condensing steam turbine with a rated power of 50 MW and main steam parameters of 10 MPa and 540°C. The formula for calculating the thermal efficiency of the steam turbine is:

[0102] ,

[0103] in, is the thermal efficiency of the steam turbine, dimensionless, which indicates the efficiency of the steam turbine in converting thermal energy into mechanical energy; is the cold end temperature in Kelvin, which represents the exhaust temperature of the steam turbine in the solar thermal power generation system; is the hot end temperature in Kelvin, which represents the turbine inlet steam temperature.

[0104] The heat transfer calculation formula for the steam generator is:

[0105] ,

[0106] in, is the heat transfer capacity, in watts, which represents the heat transfer power of the steam generator in the solar thermal power generation system; is the total heat transfer coefficient, expressed in watts per square meter per Kelvin, and represents the overall heat transfer capacity of the heat transfer equipment; is the heat transfer area in square meters, which represents the effective heat exchange area of ​​the steam generator; is the logarithmic mean temperature difference in Kelvin.

[0107] The calculation formula for the logarithmic mean temperature difference is:

[0108] ,

[0109] in, is the temperature difference at the hot end of the heat exchanger, in Kelvin, which represents the difference between the hot fluid inlet temperature and the cold fluid inlet temperature; is the temperature difference at the cold end of the heat exchanger, in Kelvin, which represents the difference between the hot fluid outlet temperature and the cold fluid outlet temperature; is the natural logarithm function.

[0110] The organic Rankine cycle power generation unit 32 uses the medium and low temperature heat source of the solar thermal power generation system to generate electricity. The working fluid is R245fa, which has a boiling point of 15.14°C and is suitable for medium and low temperature waste heat recovery. The formula for calculating the efficiency of the ORC system is:

[0111] ,

[0112] in, is the ORC system efficiency, dimensionless, representing the thermoelectric conversion efficiency of the organic Rankine cycle system; is the net output work in watts; is the input heat in watts; The unit of steam turbine power is watt, which indicates the mechanical work generated by the organic working medium pushing the steam turbine. is the working fluid pump work, the unit is watt, which represents the mechanical work consumed by the circulating working fluid pump; The heat absorbed by the evaporator, measured in watts.

[0113] The biomass supplementary combustion power generation unit 33 provides a supplementary heat source when the solar energy of the solar thermal power generation system is insufficient. The calculation formula of the biomass combustion calorific value is:

[0114] ,

[0115] in, The calorific value of biomass combustion is in joules, which represents the heat released by the complete combustion of biomass fuel; is the biomass mass in kilograms; The lower calorific value of biomass is expressed in joules per kilogram, indicating the calorific value per unit mass of biomass fuel. Combustion efficiency is dimensionless and represents the ratio of the actual heat released by the combustion of biomass fuel to the theoretical combustion heat.

[0116] In addition, the multi-source collaborative power generation module 3 also includes a multi-pressure level steam coordination unit 34 and an intelligent switching control unit 35. The multi-pressure level steam coordination unit 34 establishes a high, medium, and low pressure steam system to achieve cascade utilization of steam in the solar thermal power generation system. The optimization algorithm for steam distribution is:

[0117] ,

[0118] in, is the high-pressure steam production in kilograms per hour; is the medium-pressure steam production in kilograms per hour; is the low-pressure steam production in kilograms per hour; is the distribution matrix coefficient, dimensionless, representing the The demand for Distribution ratio of stage steam; is the steam demand of the steam turbine, in kilograms per hour; is the process steam demand in kilograms per hour; is the heating steam demand, in dry grams per hour. The above matrix is ​​a 3×3 matrix, which represents the distribution relationship between the three steam pressure levels and the three steam demands.

[0119] The intelligent switching control unit 35 performs switching control according to the heat source priority management strategy. In the solar thermal power generation system, the decision matrix of the switching logic is:

[0120] ,

[0121] in, is the selected power generation mode, with values ​​of 1, 2, or 3, representing solar power mode, waste heat mode, and biomass mode, respectively; Indicates the variable that maximizes the objective function The value of is the solar power available in megawatts; is the waste heat available power in megawatts; is the power available from biomass, in megawatts; is the cleanliness weight, dimensionless, ranging from 0 to 1; is the efficiency weight, dimensionless, ranging from 0 to 1; is the reliability weight, dimensionless, ranging from 0 to 1, and 1.

[0122] The intelligent load forecasting and scheduling module 4 is electrically connected to the multi-source collaborative power generation module 3 to collect grid and load data, generate accurate load forecasts, and formulate optimal power generation scheduling plans. This module is the core of the intelligent operation of the solar thermal power generation system. Through multi-dimensional data integration and advanced forecasting algorithms, it ensures supply and demand balance and economic operation.

[0123] In one embodiment of the solar thermal power generation system of the present invention, the intelligent load forecasting and scheduling module 4 includes a multi-dimensional data acquisition unit 41 and a load forecasting algorithm unit 42. Multi-dimensional data acquisition unit 41 establishes a comprehensive monitoring network to collect meteorological data, power grid data, and user behavior data. Data is collected once per minute to ensure the real-time and accuracy of the solar thermal power generation system's scheduling data.

[0124] The load forecasting algorithm unit 42 adopts a multi-factor time series forecasting model, and the forecasting formula is:

[0125] ,

[0126] in, for The load forecast value at the moment, in megawatts, represents the power that the solar thermal power generation system needs to provide at a certain moment in the future; For the The weight of each predictor, dimensionless, For the A prediction function based on statistical and machine learning methods; is the weather temperature in degrees Celsius; is the historical load data in megawatts; Calendar information, including days of the week, holidays, etc. It is an economic activity indicator, indicating the level of regional economic activity; is the number of predictors, usually ranging from 8 to 12; is a time variable in hours.

[0127] The function of temperature's effect on load is:

[0128] ,

[0129] in, is the temperature impact function, in megawatts, which represents the impact of temperature changes on the power supply load of the solar photovoltaic power generation system; is the low temperature sensitivity coefficient, in megawatts per degree Celsius, which indicates the sensitivity of the load to temperature changes below the reference temperature; is the high temperature sensitivity coefficient, in megawatts per degree Celsius, which indicates the sensitivity of the load to temperature changes above the reference temperature; is the actual temperature in degrees Celsius; It is the reference temperature in degrees Celsius, usually 18°C, which indicates the critical temperature at which the load is insensitive to temperature changes.

[0130] The periodic modeling formula for historical load is:

[0131] ,

[0132] in, is the periodic load component at the moment, in megawatts, which represents the periodic variation of the load of the solar photovoltaic power generation system; is the amplitude, in megawatts, which indicates the magnitude of the periodic change in load; The unit is hours, usually 24 hours (daily cycle) or 168 hours (weekly cycle); is the phase, in radians, which represents the initial phase of the periodic function; is the DC component in megawatts, indicating the base level of load; is pi, approximately equal to 3.14159.

[0133] In addition, the intelligent load forecasting and scheduling module 4 also includes a power generation scheduling optimization unit 43 and an emergency response processing unit 44. The power generation scheduling optimization unit 43 adopts a multi-objective optimization algorithm. In the solar thermal power generation system, the objective function is:

[0134] ,

[0135] Constraints include:

[0136] Power balance constraints: ;

[0137] Capacity constraints: ;

[0138] Climbing constraints: ;

[0139] in, is the total cost function, in yuan, which represents the total cost of operating the solar thermal power generation system; For the The fuel cost of each unit, in yuan per megawatt-hour; For the The startup cost of each unit, in yuan; For the Environmental cost of each unit, in yuan per megawatt-hour; For the Unit output, in megawatts; The start / stop status of the unit, the value is 0 or 1, 0 means shutdown, 1 means startup; For the Pollutant emissions of each unit, in kilograms per megawatt-hour; is the load demand in megawatts; For the The minimum output of the unit, in megawatts; For the The maximum output of the unit, in megawatts; For the The ramp rate of the unit, in megawatts per minute; is the total number of generator sets.

[0140] The emergency response processing unit 44 establishes an abnormal situation identification and processing mechanism. In the solar thermal power generation system, the abnormality detection algorithm adopts statistical control theory, and the control limit calculation formula is:

[0141] UCL = μ + 3σ,

[0142] LCL = μ - 3σ,

[0143] Among them, UCL is the upper control limit, the unit is the same as the monitoring parameter, and it represents the upper limit of the normal operating parameter; LCL is the lower control limit, the unit is the same as the monitoring parameter, and it represents the lower limit of the normal operating parameter; μ is the mean, the unit is the same as the monitoring parameter, and it represents the average value of the monitoring parameter when the solar thermal power generation system is operating normally; σ is the standard deviation, the unit is the same as the monitoring parameter, and it represents the degree of dispersion of the monitoring parameter; the coefficient of 3 represents the principle of 3 times the standard deviation, corresponding to a confidence level of 99.7%.

[0144] When the monitoring parameters exceed the control limit, the emergency response process is initiated. The optimization algorithm for load transfer is:

[0145] ,

[0146] Constraints: , ,

[0147] in, From the demand point To the supply point The transfer cost is in yuan per megawatt; From the demand point To the supply point The amount of transfer in megawatts; For demand points The demand, in megawatts, represents the demand for the first The power demand of each load point; For supply point The supply capacity, in megawatts, represents the The power supply capacity of each power generation unit; is the number of demand points; is the number of supply points.

[0148] The System Self-Optimization and Evolution Module 5, connected to the data of the four aforementioned modules, monitors the operating status of the entire solar thermal power generation system and generates optimization instructions based on performance evaluation results, enabling continuous improvement and self-evolution of the system. This module represents the highest level of intelligent solar thermal power generation, continuously improving system performance through big data analysis and machine learning technologies.

[0149] In one embodiment of the solar thermal power generation system of the present invention, the system self-optimization evolution module 5 includes a full system performance monitoring unit 51, an intelligent diagnosis and analysis unit 52, and a parameter adaptive optimization unit 53. The full system performance monitoring unit 51 establishes a KPI monitoring system, and the calculation formula of the key performance indicator is:

[0150] Solar energy utilization rate:

[0151] ,

[0152] Thermoelectric conversion efficiency:

[0153] ,

[0154] Overall system efficiency:

[0155] ,

[0156] in, The solar energy utilization rate is expressed in percentage, indicating the proportion of solar energy actually collected by the solar thermal power generation system to the available solar energy. The collected heat is expressed in joules, which indicates the amount of solar heat actually collected by the concentrating system. is the available solar energy, measured in joules, which represents the total energy provided by solar radiation; Thermoelectric conversion efficiency, expressed in percentage, indicates the efficiency of converting thermal energy into electrical energy; is the power generation power, in watts; is the input heat in watts; The overall efficiency of the system is expressed in percentage, indicating the overall energy conversion efficiency of the solar thermal power generation system; is the net power generation, in watts, which represents the net power output of the system; is the solar radiation intensity in watts per square meter; is the total area of ​​the reflector in square meters.

[0157] The intelligent diagnosis and analysis unit 52 uses trend analysis and anomaly detection algorithms. In a solar thermal power generation system, the equipment health index is calculated as follows:

[0158] ,

[0159] in, The health index is dimensionless and ranges from 0 to 1. The closer the value is to 1, the better the health of the device. is the weight of the i-th parameter, dimensionless, ; is the value of the ith parameter during normal operation, and the unit is determined by the parameter type; is the current i-th parameter value, and its unit is same; is the number of monitoring parameters.

[0160] Fault prediction uses exponential smoothing method, and the prediction formula is:

[0161] ,

[0162] ,

[0163] in, for The smoothed value at the moment, in the same unit as the monitoring parameter, represents the parameter value after smoothing; is the smoothing coefficient, dimensionless, ranging from 0 to 1, usually from 0.1 to 0.3; for The observed value at the moment, the unit is the same as the monitoring parameter; for The smoothed value at the moment, in units of same; The remaining service life is expressed in hours or days, indicating the expected time until the solar thermal power generation system equipment fails; is the fault threshold, and its unit is the same as the monitoring parameter; is the degradation slope, with the unit of monitored parameter per time unit.

[0164] The parameter adaptive optimization unit 53 uses a genetic algorithm to optimize the parameters. In the solar thermal power generation system, the fitness function of the genetic algorithm is:

[0165] ,

[0166] in, is the fitness value, dimensionless, ranging from 0 to 1, and the larger the value, the better the individual fitness; is the weight of the i-th target, dimensionless, ; is the target value of the i-th target, and the unit is determined by the target type; For the The actual value of the target, in units of same; To optimize the number of targets.

[0167] The selection operation adopts the roulette method, and the selection probability is:

[0168] ,

[0169] in, For individuals The probability of being selected is dimensionless and ranges from 0 to 1; For individuals The fitness value of is the population size, which represents the total number of individuals in the genetic algorithm. The crossover operation uses a single-point crossover, and the crossover position is randomly selected. The mutation probability of the mutation operation is:

[0170] ,

[0171] in, is the mutation probability, dimensionless, ranging from 0 to 1; is the basic mutation probability, dimensionless, usually ranging from 0.01 to 0.1; is the current algebra, dimensionless; is the maximum algebra, dimensionless; It is a natural constant, approximately equal to 2.71828.

[0172] Through the coordinated collaboration of these five core modules, the solar thermal power generation and power supply system of the present invention achieves intelligent control of the entire process, from solar energy collection to power output. During system operation, the adaptive concentrating and tracking module 1 converts solar radiation into high-temperature heat flux, the tiered thermal storage module 2 stores thermal energy in layers, the multi-source collaborative power generation module 3 converts thermal energy into electrical energy, the intelligent load forecasting and scheduling module 4 optimizes power generation plans, and the system self-optimizing evolution module 5 continuously improves system performance, forming a complete closed-loop control system.

[0173] Actual operating data show that the solar energy utilization rate of the solar thermal power generation system of the present invention reaches more than 25%, the system availability rate exceeds 85%, and the power generation cost is reduced by more than 20% compared with the traditional solar thermal power generation system, which fully verifies the practicality of the technical solution.

[0174] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A solar thermal power generation system, characterized in that: include: The adaptive focusing and tracking module is used to control the multi-stage reflector array for coordinated tracking based on the sun position prediction data and cloud dynamic perception data, and adjust the distribution of the concentrated heat flux density through the focus dispersion control mechanism to output a stable high-temperature heat flux to the subsequent modules; the stratified cascade heat storage module is connected to the adaptive focusing and tracking module heat flux, and is used to receive the high-temperature heat flux and store the heat energy in the high-temperature heat storage area, the medium-temperature heat storage area and the low-temperature preheating area based on the temperature level, wherein the operating temperature of the high-temperature heat storage area is 800-1000°C, the operating temperature of the medium-temperature heat storage area is 400-600°C, and the operating temperature of the low-temperature preheating area is 150-300°C; the multi-source collaborative power generation module is connected to the stratified cascade heat storage module heat energy, and is used to receive the heat energy from the high-temperature storage area. The heat energy of the hot zone, the medium-temperature heat storage zone and the low-temperature preheating zone is used to collaboratively generate electricity through the main steam turbine power generation system, the organic Rankine cycle power generation system and the biomass supplementary combustion power generation system to output stable electricity; an intelligent load forecasting and scheduling module is electrically connected to the multi-source collaborative power generation module, and is used to collect multi-dimensional data and generate load forecast results, formulate a power generation scheduling plan based on the load forecast results, and send scheduling instructions to the multi-source collaborative power generation module; a system self-optimization and evolution module is respectively connected to the adaptive focusing and tracking module, the tiered cascade heat storage module, the multi-source collaborative power generation module and the intelligent load forecasting and scheduling module for monitoring system operating parameters, generating parameter optimization instructions based on performance evaluation results, and realizing adaptive adjustment of system parameters and continuous improvement of operating strategies; The adaptive focusing and tracking module includes: a sun position prediction unit, which is used to calculate the sun's altitude and azimuth based on geographic coordinates and time parameters, and to compensate for atmospheric refraction according to atmospheric pressure, temperature, and humidity parameters, outputting sun position data with an accuracy of ±0.1°; a cloud dynamic perception unit, which is used to scan the cloud state within a radius of 50 kilometers using a multi-spectral detection device, identify cloud thickness, movement speed, and obscuration probability, and predict the trend of solar radiation changes within the next 30 minutes; a multi-stage reflector collaborative control unit, which is used to receive the sun position data and cloud prediction data, control the main reflector array with a reflector area of ​​25 square meters to perform dual-axis precision tracking, and concentrate solar radiation to more than 1,000 times through a secondary concentrator; The adaptive focusing and tracking module also includes: a focus dispersion control unit, which is used to monitor the heat flux density distribution on the surface of the absorber through 100 temperature sensors. When the local temperature gradient is detected to exceed 50°C / cm, the reflection angle is automatically adjusted within 10 seconds to disperse the focus to the surrounding area, ensuring that the heat flux density is evenly distributed and the focus position adjustment accuracy reaches ±1 cm.

2. The solar thermal power generation system according to claim 1, characterized in that: The tiered cascade heat storage module includes: a three-level temperature tiered heat storage unit, wherein the high-temperature heat storage area uses a mixed molten salt of sodium nitrate and potassium nitrate as the heat storage medium and the heat storage capacity meets the demand for 8 hours of full-load power generation; the medium-temperature heat storage area uses a biphenyl-biphenyl ether mixed heat transfer oil as the heat storage medium and the heat storage capacity meets the demand for 4 hours of medium-load power generation; the low-temperature preheating area uses a pressurized water vapor system for sensible heat and latent heat storage; a phase change heat storage enhancement unit, which is used to configure a carbonate eutectic phase change material with a melting point of 760°C in the high-temperature heat storage area and a nitrate hydrate phase change material with a melting point of 320°C in the medium-temperature heat storage area, and enhance heat transfer efficiency through a fin tube bundle and a graphite heat conduction network.

3. The solar thermal power generation system according to claim 2, characterized in that: The tiered cascade heat storage module also includes: an intelligent heat energy scheduling unit for achieving heat energy balance scheduling at each temperature level based on load forecast data and solar energy collection forecast data, according to a heat storage priority of prioritizing heat storage in the high-temperature heat storage area and storing it downward step by step, and a heat release priority of prioritizing the use of heat energy in the high-temperature heat storage area to ensure the highest power generation efficiency; a heat loss minimization unit for automatically adjusting the thickness of the insulation layer according to the ambient temperature, controlling the thermal conductivity of key pipelines to below 0.01 W / m·K through a vacuum sandwich structure, and collecting waste heat resources such as turbine exhaust heat and equipment heat dissipation, and inputting them into corresponding heat storage areas according to temperature levels.

4. The solar thermal power generation system according to claim 1, characterized in that: The multi-source collaborative power generation module includes: a main steam turbine power generation unit, which is used to receive high-temperature molten salt from the high-temperature heat storage area, generate main steam with a pressure of 10MPa and a temperature of 540°C through a spiral coil heat exchanger, and drive a condensing steam turbine with a rated power of 50MW to generate electricity, achieving a thermoelectric conversion efficiency of ≥42%; an organic Rankine cycle power generation unit, which is used to utilize the medium and low temperature heat sources from the medium-temperature heat storage area and the low-temperature preheating area to drive an organic Rankine cycle system with a rated power of 5MW to generate electricity through R245fa working fluid; and a biomass supplementary combustion power generation unit, which is used to provide a supplementary heat source of 10MW thermal power when solar energy is insufficient, and burn agricultural and forestry waste through a fluidized bed, with a combustion efficiency of >95% and smoke emissions of <30mg / m³.

5. The solar thermal power generation system according to claim 4, characterized in that: The multi-source collaborative power generation module also includes: a multi-pressure level steam coordination unit, which is used to establish a high-pressure steam circuit, a medium-pressure steam circuit and a low-pressure steam circuit, wherein the high-pressure steam circuit parameters are 10MPa and 540°C for main steam turbine power generation, the medium-pressure steam circuit parameters are 2.5MPa and 350°C for process steam, and the low-pressure steam circuit parameters are 0.5MPa and 150°C for heating and deoxidation; an intelligent switching control unit, which is used to ensure the frequency and voltage stability of the output power through power prediction and smoothing algorithms in accordance with the heat source priority management strategy of solar thermal power generation as the first priority, waste heat power generation as the second priority, and biomass supplementary combustion as the third priority.

6. The solar thermal power generation system according to claim 1, characterized in that: The intelligent load forecasting and scheduling module includes: a multi-dimensional data acquisition unit for collecting solar radiation intensity, cloud coverage, wind speed and direction, temperature and humidity data, as well as real-time power, voltage, and current data of each substation in the power grid, to identify the electricity consumption patterns of industrial users, commercial users, and residential users, as well as adjustable load characteristics such as air conditioning load and electric vehicle charging load; a load forecasting algorithm unit for generating short-term load forecast results of 1 to 24 hours and medium- and long-term load forecast results of 1 to 7 days based on the multi-dimensional data through a multi-factor analysis method that considers weather factors, historical load patterns, and the impact of holidays, wherein the day-ahead load forecast error is controlled within ±3%.

7. The solar thermal power generation system according to claim 6, characterized in that: The intelligent load forecasting and scheduling module also includes: a power generation scheduling optimization unit, which is used to generate a power generation scheduling plan every 15 minutes based on the short-term load forecast results and the medium- and long-term load forecast results, with the economic goal of minimizing power generation costs, the reliability goal of ensuring power supply reliability, and the environmental protection goal of prioritizing the use of clean energy as a multi-objective optimization strategy; an emergency response processing unit, which is used to identify abnormal situations such as sudden cloud cover, equipment failure, sudden load changes, fuel shortages, etc., and initiate a preset emergency scheduling plan to ensure power supply continuity through measures such as load transfer, external power purchase, and orderly power rationing.

8. The solar thermal power generation system according to claim 1, characterized in that: The system self-optimization and evolution module includes: a full-system performance monitoring unit, which is used to collect system operation data through more than 1,000 temperature, pressure, flow, and vibration sensors, monitor key performance indicators such as solar energy utilization rate, thermoelectric conversion efficiency, equipment availability, unit power generation cost, and establish a hierarchical storage system covering the preservation of important data for more than 5 years; an intelligent diagnosis and analysis unit, which is used to diagnose equipment health status and evaluate system performance based on the system operation data, predict equipment performance degradation through parameter change trend analysis, issue early warning signals 2-4 weeks before a failure occurs, and identify key bottlenecks that restrict system performance; a parameter adaptive optimization unit, which is used to dynamically adjust operating parameters such as temperature setting values, flow distribution ratios, pressure levels, equipment start and stop times according to the analysis results of the intelligent diagnosis and analysis unit, improve control logic based on historical data and expert experience, and achieve continuous optimization of system operation strategies and self-evolution of performance.

Images