Decoupling optimization method for combined electricity and heat energy system based on multi-source flexible resource coordination in severe cold weather

Abstract

This invention discloses a decoupling optimization method for a combined electric and thermal energy system based on multi-source flexible resource coordination under severe cold weather conditions. Belonging to the field of integrated energy optimization, the method includes: first, dynamically correcting the basic heating demand based on real-time ambient temperature to determine the meteorologically corrected equivalent total heat load; second, constructing an electric and thermal feasible operating domain model for extraction-condensing units based on the equivalent total heat load to determine their minimum power generation limit under severe cold conditions; third, determining the total minimum output of thermal power in conjunction with the minimum output of pure condensing units, and identifying excess power based on renewable energy output and system electrical load; finally, when excess power exists, utilizing multi-source flexible resources such as thermal storage, pumped storage, and electric boilers for heat source replacement, substituting the heating share of the extraction-condensing units, and forcibly reducing their power generation limit. This invention breaks the rigid constraint of "heat-driven power generation" in severe cold environments through heat source replacement, creating peak-shaving space for renewable energy consumption.

Description

Technical Field

[0001] This invention belongs to the field of integrated energy optimization, and in particular relates to a decoupling optimization method for a combined electric and thermal energy system based on multi-source flexible resource synergy under severe cold weather. Background Technology

[0002] With the increasing frequency of global climate anomalies, extreme cold weather poses a severe challenge to the robust operation of combined heat and power (CHP) systems. Under extremely low outdoor temperatures, building heat loss exhibits a non-linear surge, transforming urban heating load from seasonal demand to sudden peak demand with strong rigidity. Traditional dispatching schemes often rely on static or empirical heat load forecasts, making it difficult to accurately capture the deep-seated disturbances to heat demand caused by extreme low temperatures, leading to distortions in dispatching models under extreme conditions. Simultaneously, to maintain the minimum heating supply for residential use, CHP units must maintain extremely high steam extraction intensity during severe cold periods, forcibly locking their minimum technical output within a high range. This severely restricts the system's downscaling capacity, creating the paradox of "the colder it gets, the more wind power is wasted."

[0003] Existing technologies face the following technical challenges when dealing with frigid conditions: First, they lack effective identification of meteorological sensitive factors, making it difficult to accurately characterize the transient physical characteristics of "heat changing with temperature." Second, they cannot effectively decouple the rigid constraint of "heat-based power generation," resulting in a passive increase in the benchmark output of thermal power plants during frigid periods, causing the system to lose its downward adjustment capability. Third, the logic for utilizing flexible resources still focuses on smoothing short-term power fluctuations, lacking a deep collaborative strategy for heat source replacement under extreme environments, making it difficult to achieve dynamic expansion of new energy consumption space while ensuring heating security. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention provides a decoupling optimization method for a combined electric and thermal energy system based on multi-source flexible resource coordination under extremely cold weather conditions, comprising: Acquire real-time ambient temperature data containing meteorological sensitive factors, and dynamically correct the basic heating demand based on the real-time ambient temperature data to determine the meteorological-corrected equivalent total heat load. Based on the equivalent total heat load, an electrothermal feasible operating domain model of the extraction condensing unit is constructed to determine the minimum power generation limit of the extraction condensing unit under severe cold conditions. Based on the minimum power output limit of the extraction condensing unit and the minimum stable output of the pure condensing unit, the total minimum output of the thermal power unit is determined, and based on the output of new energy sources and the system electrical load, it is identified whether there is excess power. When there is excess electricity, multiple flexible resources are used to replace the heat source. The heat energy is released or converted by the multiple flexible resources to replace the heating share of the extraction condensing unit, thereby forcibly reducing the lower limit of the power generation of the extraction condensing unit and creating output space for the consumption of new energy.

[0005] Optionally, the basic heating demand is dynamically corrected based on the real-time ambient temperature data to determine the meteorologically corrected equivalent total heat load, specifically including: The equivalent total heat load after meteorological correction is determined based on the basic heating demand forecast, heat loss coefficient, the difference between the indoor heating baseline target temperature and the real-time outdoor ambient temperature, and the cold wave weather correction factor.

[0006] Optionally, the construction of an electrothermal feasible operating domain model for the extraction condensing unit to determine the minimum power generation limit of the extraction condensing unit under severe cold conditions specifically includes: The minimum power generation limit is determined based on the back pressure power generation caused by heating demand, the conversion ratio coefficient of steam extraction to power generation and heating power, the equivalent total heat load, and the unit's minimum condensing power generation.

[0007] Optionally, determining the total minimum output of the thermal power unit and identifying whether there is excess power based on the output of new energy sources and the system electrical load specifically includes: The surplus electrical load after taking into account the output of new energy sources is compared with the total minimum output of thermal power units, and the excess power is determined based on the difference between the two; wherein, the total minimum output of thermal power units is determined based on the sum of the minimum electrical output of extraction condensing units under real-time heating constraints and the minimum stable output of pure condensing units.

[0008] Optionally, the invocation of multi-source flexible resources for heat source replacement specifically includes: Determine the operating status of the extraction condensing unit. If the extraction condensing unit is operating on the EF line, which represents the heating constraint boundary, within the electrothermal feasible operating domain, then prioritize the use of the thermal storage equipment to release heat in order to replace the heating output of the extraction condensing unit. When the thermal storage device releases heat, the heat release power of the thermal storage device is determined based on the difference between the total heat load after meteorological correction and the minimum heating power required to maintain the unit's thermal cycle safety, combined with the current heat storage status of the thermal storage device.

[0009] Optionally, the step of invoking multi-source flexible resources for heat source replacement further includes: If the thermal storage equipment cannot fully absorb the excess power, the pumped storage power station will be called in to pump and store the remaining excess power. The method of calling upon multi-source flexible resources for heat source replacement also includes: If the pumped storage power station is still unable to fully absorb the excess electricity, then an electric boiler will be used to convert the excess electricity into heat energy for final heat storage or direct heating.

[0010] Optionally, when the electric boiler is invoked to convert excess electricity into heat energy, the specific steps include: The operating power of the electric boiler is determined according to the different operating states of the extraction condensing unit. If the extraction condensing unit is operating on line EF, the operating power of the electric boiler is determined according to the difference between the excess power and the heat release power of the thermal storage equipment. If the extraction condensing unit is operating at point F, which represents the boundary of pure condensing conditions, and the thermal storage equipment is not full, the excess power is directly used as the operating power of the electric boiler.

[0011] Optionally, the method further includes the steps of daily rolling calculation and long-term balance analysis: After completing the daily scheduling, the thermal storage capacity of the thermal storage equipment and the pumped storage power station are updated according to the charging and discharging power of the day. The updated state parameters are then transmitted as the initial conditions for the next day's scheduling calculations to achieve long-term energy balance analysis for the entire heating cycle or year.

[0012] On the other hand, the present invention also provides an electronic device including a memory, a processor, and a computing program stored in the memory and executable on the processor, wherein the processor implements the method when executing the computing program.

[0013] On the other hand, the present invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method.

[0014] Compared with the prior art, the present invention has the following advantages and technical effects: 1) The capacity for renewable energy consumption has been significantly enhanced. By dynamically optimizing the combination of generating units and heat source replacement, the strong electrothermal coupling relationship under severe cold conditions has been effectively decoupled, and the phenomenon of wind and solar curtailment has been greatly reduced.

[0015] 2) Both fossil fuel consumption and carbon emissions have decreased. The optimized operation mode of thermal power units has reduced standard coal consumption during the heating season, directly contributing to the achievement of carbon dioxide emission reduction targets.

[0016] 3) The model's accuracy and environmental adaptability have been comprehensively improved. The modeling technique that incorporates meteorological sensitive factors ensures high fidelity in predicting system boundaries under extreme environments, reducing scheduling risks.

[0017] 4) Enhanced support for flexible resource allocation decisions. Through quantitative analysis tools, the complementary effects of thermal storage and pumped storage under severe cold conditions were clarified, providing a scientific guidance for the long-term stable operation of the power grid. Attached Figure Description

[0018] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings: Figure 1This is a diagram showing the electrothermal coupling characteristics and dynamic evolution of the operating domain of the extraction condensing unit under extremely cold conditions, according to an embodiment of the present invention. Figure 2 This is a schematic diagram of the power balance mechanism according to an embodiment of the present invention; Figure 3 This is a flowchart illustrating the flexible resource allocation strategy of an embodiment of the present invention; Figure 4 This is a diagram illustrating the equivalent decoupled operating range of the aggregation unit under the flexible resource replacement method in this embodiment of the invention. Figure 5 This is a schematic diagram illustrating the impact of the minimum power of the extraction condensing unit on the renewable energy consumption effect according to an embodiment of the present invention; Figure 6 This is a schematic diagram illustrating the impact of the pumped storage power station capacity on the system's renewable energy utilization rate according to an embodiment of the present invention. Detailed Implementation

[0019] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0020] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0021] Example 1 This embodiment provides a decoupling optimization method for a combined electric and thermal energy system based on multi-source flexible resource coordination under extremely cold weather conditions, including: Acquire real-time ambient temperature data containing meteorological sensitive factors, and dynamically correct the basic heating demand based on the real-time ambient temperature data to determine the meteorological-corrected equivalent total heat load. Based on the equivalent total heat load, an electrothermal feasible operating domain model of the extraction condensing unit is constructed to determine the minimum power generation limit of the extraction condensing unit under severe cold conditions. Based on the minimum power output limit of the extraction condensing unit and the minimum stable output of the pure condensing unit, the total minimum output of the thermal power unit is determined, and based on the output of new energy sources and the system electrical load, it is identified whether there is excess power. When there is excess electricity, multiple flexible resources are used to replace the heat source. The heat energy is released or converted by the multiple flexible resources to replace the heating share of the extraction condensing unit, thereby forcibly reducing the lower limit of the power generation of the extraction condensing unit and creating output space for the consumption of new energy.

[0022] Specifically, it includes: like Figure 3As shown, in one specific embodiment of the present invention, the provincial-level combined electric and thermal energy system encompasses a cluster of equipment with multiple functional characteristics. For example... Figure 1 As shown, the system is first classified and logically integrated based on the working mechanism of the equipment. The power supply side includes wind and solar power, nuclear power, hydropower, and thermal power clusters. The thermal power clusters are further subdivided into extraction condensing units, forced condensing units, and optional condensing units. The core equipment on the heating side includes equivalent extraction condensing units, thermal storage devices, and high-power electric boilers.

[0023] When aggregating equipment, the principle of capacity summation and physical characteristic equivalence is followed. The core lies in establishing an operating model for extraction-condensing turbine units that can reflect the impact of severe cold conditions. To this end, this embodiment constructs a quadrilateral electrothermal feasible operating domain model based on meteorological sensitivity factors, namely… Figure 1 The AEDF model is shown in the diagram. This model is not only used to characterize the operating characteristics of the unit under normal conditions, but more importantly, by introducing a meteorological correction coefficient, it can accurately depict the dynamic compression process of the unit's electrical output range caused by the surge in heating demand due to extreme low temperatures.

[0024] In one specific embodiment of the present invention, such as Figure 1 As shown, the key points and parameters in the quadrilateral electrothermal feasible operating domain model AEDF have clear physical meanings, and are specifically set as follows: Point A represents the maximum rated power generation of the equivalent extraction condensing unit under zero heat load conditions. This parameter is a key physical indicator for measuring the maximum power supply capacity of the power system when there is no heat demand.

[0025] Point D represents the minimum technical output of the unit under zero heating conditions. This parameter reflects the basic peak-shaving depth of the thermal power unit under normal meteorological conditions.

[0026] Line segment EF reveals the lower limit of power generation that units must passively increase in order to maintain the safety of residential heating in the context of a surge in heating demand caused by extreme low temperatures. This line segment depicts the rigid squeezing process of the power system's down-shaving space under the constraint of strong thermoelectric coupling, where the "heat-driven power generation" effect exerts pressure on the power system's down-shaving capacity.

[0027] parameter This indicates the maximum heating power, which is the highest heating capacity that the equivalent unit can provide during operation.

[0028] The slope of line segment AE It is used to characterize the strength of the relationship between the extraction steam volume and the unit's power generation capacity, that is, the contribution value of each unit of extraction steam volume to the power generation.

[0029] The slope of line segment EF It is used to characterize the effect of steam extraction on the ratio of power generation to heat supply, that is, the ratio between power generation and heat supply that can be generated by each unit of steam extraction.

[0030] parameter It represents the heat output corresponding to the minimum power generation of the equivalent unit, that is, the minimum heat output that the equivalent unit can provide when outputting the minimum electrical power.

[0031] The process of calculating unit output includes: based on the real-time heat load, the minimum generating power of the unit is determined by the back-pressure generating power and the minimum condensing output. Back pressure power generation: (1) in, This represents the system's equivalent total heat load after meteorological correction during time period t; This represents the predicted basic heating demand under normal meteorological conditions for time period t. This represents the heat loss coefficient, which describes the thermal inertia and insulation properties of a building complex within a specific area. This indicates the baseline target temperature for indoor heating set to ensure the comfort of residents. This represents the real-time outdoor ambient temperature collected by the meteorological monitoring system during time period t. This is a correction factor indicating the impact of extreme cold waves on the surge in heat demand.

[0032] Minimum power generation: (2) in, This represents the generator back pressure power generated during time period t due to heating demand. This represents the coefficient that characterizes the influence of steam extraction rate on the conversion ratio between power generation and heating power. This represents the equivalent total heat load input value driven by meteorological factors in the corresponding time period t.

[0033] During periods of extreme cold, the minimum generating capacity of the unit will be passively increased due to a significant increase in heat load, resulting in a typical heat-dependent power lock-in state. This solution breaks this physical constraint through subsequent flexible resource scheduling.

[0034] To address the nonlinear coupling relationship between heating demand and outdoor temperature under severe cold conditions, the heat load of each region is summarized, and a temperature supplement is introduced.

[0035] The calculation logic for the aggregated equivalent total heat load is as follows.

[0036] (3) in, This indicates the minimum power generation capacity that the extraction condensing unit must maintain under extremely cold conditions. This indicates the minimum condensing power required by the unit to ensure the cooling of the low-pressure cylinder and the safety of the thermodynamic cycle.

[0037] The minimum adjustable capacity requirement is typically calculated based on daily generation load and reserve demand. Specifically, minimum adjustable capacity refers to the minimum generation capacity that generating units can adjust to meet the most basic needs of the power system, ensuring grid stability during load changes or system anomalies. (4) To meet the minimum adjustable capacity requirement on day d Under the premise of ensuring that the number of pure condensing units to be started at different times of the day is dynamically determined, it is necessary to ensure that the system can meet the load requirements. and backup The requirements are met while also taking into account economic efficiency and unit start-up and shutdown constraints. The main idea is similar to the minimum adjustable capacity calculation, but it introduces unit constraints such as the minimum stable output, start-up and shutdown costs, and minimum start-up and shutdown time of the pure condensing unit itself.

[0038] The system dynamically determines the operating capacity of pure condensing units based on daily power generation load and spinning reserve requirements. : (5) in, This refers to the capacity of pure condensing units in the system that need to remain running at all times. Their function is to ensure the stability of the power grid during peak hours and to provide baseload for the power system. This indicates the capacity of the extraction condensing unit. It refers to the power output capacity that a unit with thermoelectric coupling capability can provide. This indicates the reliability of wind and solar power generation. As renewable energy sources, the amount of electricity generated by wind and solar power has a certain degree of uncertainty. This indicates the installed capacity of hydropower and nuclear power. As relatively stable power sources, the installed capacity of hydropower and nuclear power is crucial for the stable operation of the power system. This indicates the adjustable power output rate of hydropower and nuclear power plants. It means that these types of units can adjust their power generation output during operation.

[0039] The power balancing process treats renewable energy output as a negative load and adds it in. By comparing the difference between the sum of the minimum output of all thermal power plants in the entire grid and the remaining load, it identifies whether there is excess power. Under severe cold conditions, the minimum output of thermal power plants is locked at high levels due to heating demand, significantly increasing the risk of power curtailment and necessitating intervention through flexible resources. For example... Figure 2 As shown.

[0040] The output of new energy sources is typically unstable and fluctuating; therefore, they are superimposed as loads to represent the load fluctuations that need to be considered in the system. They can be treated as the power supply portion of the grid and superimposed on traditional loads. The minimum output of thermal power units is calculated, which is usually determined by the technical limitations of the units. After calculating the remaining load, it needs to be compared with the minimum output of the thermal power units to identify whether there is excess power. (6) Under the background of severe cold weather, this scheme first conducts a power balance analysis under the condition of no flexible resources, aiming to identify the peak-shaving bottleneck caused by the rigid demand for residential heating. The total minimum technical output of thermal power units is jointly determined by the operating status of extraction condensing units and pure condensing units, as shown in equation (7).

[0041] Minimum output calculation for thermal power units: (7) in, This represents the total minimum output of thermal power units within the system during time period t; This represents the minimum electrical output of the extraction condensing unit under real-time heating constraints. This indicates the minimum stable output of a pure condensing unit.

[0042] The system's current excess power and required adjustable output capacity: (8) (9) in, This represents the excess electricity during time period t; Indicates adjustable output demand; This indicates the remaining electrical load after taking into account the output of new energy sources.

[0043] Heat release and heat storage power of thermal storage equipment: Its core function is to replace the heat supply share of thermal power units through heat release, thereby forcibly lowering the lower limit of power generation under the constraint of heat-based power generation. If the unit is operating at the boundary of the operating domain, the power of the thermal energy released by the thermal storage equipment is determined by formula (10).

[0044] (10) in, This represents the heat release power of the thermal storage device during time period t; This represents the total heat load after meteorological correction; This indicates the minimum heating power at which the unit can maintain a safe thermodynamic cycle. This indicates the current heat storage status of the thermal storage device.

[0045] If the system still has the capacity to absorb heat, then the excess electricity is converted into heat energy by the charging power of the thermal storage device through Equation 11.

[0046] (11) Indicates the charging power; : Indicates the maximum capacity limit of the thermal storage device.

[0047] In extremely cold conditions, electric boilers directly supplement residential heating needs through electricity-to-heat conversion, further decoupling the bond between heat and power. If the unit operates at a high operating point, the operating power of the electric boiler is determined according to Equations 12 and 13.

[0048] (12) (13) This indicates the electricity consumed by the electric boiler; This indicates the heat it converts into the heating network; This indicates the efficiency of electro-thermal conversion.

[0049] Through this multi-energy supplementation mechanism, the system can reduce the rigid power output of thermal power units from a high level during severe cold periods, creating a window of opportunity for the absorption of new energy sources.

[0050] When there is excess power, flexibility resources are deployed in the following order: Thermal storage equipment should be given priority in consumption. Different operating modes of thermal storage equipment have different priorities, depending on their operation.

[0051] If the extraction condensing unit operates on the EF line, the thermal storage equipment will preferentially release heat, dissipating the stored thermal energy. The heat release capacity of the thermal storage equipment is: (14) If operating on the FD line, the thermal storage device will be charged first, converting excess electricity into thermal energy for storage. The charging power of the thermal storage device is: (15) Pumped storage power stations can store energy when there is excess power in the power grid by raising the water level to store electrical energy, which is then released when the grid load is high. Pumped storage power stations are the second-priority to be used for pumping out excess power. (16) Electric boilers are used as a last resort, typically as a last line of defense, to convert excess electricity into thermal energy storage when other equipment cannot fully absorb it.

[0052] If the extraction condensing unit is operating on the EF line: (17) If operating at point F and the thermal storage device is not full, the electric boiler will convert excess electricity into thermal energy storage: (18) The process of daily rolling calculation and long-term balance analysis includes: The first step is to transfer daytime status parameters. These data will be used as initial conditions for the next day to ensure that the thermal storage equipment and pumped storage power station can continue to operate normally on the new day and adjust according to the new load demand.

[0053] Thermal storage equipment can store a large amount of heat. (20) This represents the amount of heat stored at the beginning of day d+1. This represents the state at the beginning of day d.

[0054] Pumped storage power station storage capacity: (twenty one) Indicates the battery status for the next day; Indicates the power generation capacity of water release. This indicates power generation efficiency.

[0055] The annual-scale equilibrium calculation process includes: In a specific embodiment of the present invention, in order to achieve long-term equilibrium analysis on an annual scale, daily rolling calculations are performed according to the following steps: First, initialization is carried out at the beginning of the year. Based on historical operating data or system planning schemes, the initial heat storage capacity of the thermal storage equipment and the initial reservoir capacity of the pumped storage power station are set.

[0056] Subsequently, the daily cyclical calculation begins. For each day d, based on the current day's power demand, equipment operating status, and status parameters transmitted from the previous day, the following sub-steps are executed: The first step is to make decisions regarding equipment aggregation and unit combination. This involves selecting appropriate flexible resources for scheduling based on the day's power load and equipment status. Specifically: for thermal storage equipment, the decision is made regarding whether to charge or release heat based on the day's power surplus or heat load demand; for pumped-storage hydroelectric power stations, it is determined whether to pump water for energy storage to absorb electricity or release water to generate electricity to supplement the power shortage; simultaneously, if the system experiences excess power, it is also necessary to decide whether to utilize other flexible equipment such as electric boilers to absorb it.

[0057] The second step is to update the heat storage status of the thermal storage equipment and the energy storage status of the pumped storage power station after the daily scheduling operation is completed.

[0058] The third step is to transmit the updated state parameters of the thermal storage equipment and pumped storage power station as the initial conditions for the next day (i.e., day d+1), and continue the scheduling calculation for the next day.

[0059] After completing the daily cyclical calculations throughout the year, annual statistics are performed. Specifically, based on the data recorded daily throughout the year, the annual renewable energy curtailment rate is calculated. This curtailment rate is determined by the ratio of the total amount of curtailed power that cannot be absorbed throughout the year to the total theoretical generating power of renewable energy.

[0060] (twenty two) in, This indicates the annual rate of curtailment of renewable energy. This indicates the amount of abandoned power that ultimately cannot be absorbed; This represents the total theoretical power generation capacity of new energy sources.

[0061] This long-term analysis process can quantitatively assess the system robustness and low-carbon emission reduction benefits of this solution in the face of persistent extreme cold weather.

[0062] Example 2 This embodiment provides a decoupling optimization method for a combined electric and thermal energy system based on multi-source flexible resource coordination under extremely cold weather conditions, including: The meteorological-sensitive combined power and heat dispatching model proposed in this invention has significant accuracy advantages when dealing with complex operating conditions in northern winters. Comparative analysis reveals that the traditional EnergyPLAN model, due to neglecting the rigid constraints of thermoelectric coupling under severe cold conditions, exhibits a large deviation between its predicted power curtailment rate and actual operating data.

[0063] Table 1 As shown in Table 1, the curtailment rate calculated by the model of this invention is 4.5%, which is much closer to the actual data of 6.2% than the 0.45% of the traditional model. This proves that the dynamic heat load correction and operation domain reconstruction technology introduced in this scheme can more realistically restore the squeezing effect of heat-determined power generation on the system under severe cold conditions, and provide the dispatching department with more valuable boundary warnings.

[0064] This solution ensures stable system operation during the transition from extreme low temperatures to conventional heating by meticulously characterizing the unit parameters at different heating stages.

[0065] Table 2 Based on the data analysis in Table 2, during the peak heating season when severe cold weather is concentrated, all operating indicators of the units remain at high levels. This invention, by dynamically adjusting operating parameters at different times, enables thermal power units to precisely respond to the surge in heat load caused by extreme weather, thus ensuring a physical balance between heating and power generation under extreme conditions.

[0066] By introducing pumped storage power stations and heat source replacement strategies, the system can effectively reduce its reliance on pure condensing units during severe cold periods.

[0067] Table 3 As shown in Table 3, with the increase in the scale of flexible resource allocation in this scheme, the operating capacity and annual power generation of the selected condensing units show a significant downward trend. When the pumped storage capacity reaches 8400 MW, the annual power generation of the selected units can be reduced to zero. This fully demonstrates that the present invention utilizes flexible resources to perform heat substitution tasks during severe cold periods, successfully freeing up a large amount of thermal power generation space, thereby solving the technical problem of excessive wind curtailment in cold weather.

[0068] Based on the experimental data above, the beneficial effects of this embodiment are mainly reflected in the following four dimensions: 1) The capacity for renewable energy consumption has been significantly enhanced. By dynamically optimizing the combination of generating units and heat source replacement, the strong electrothermal coupling relationship under severe cold conditions has been effectively decoupled, and the phenomenon of wind and solar curtailment has been greatly reduced.

[0069] 2) Both fossil fuel consumption and carbon emissions have decreased. The optimized operation mode of thermal power units has reduced standard coal consumption during the heating season, directly contributing to the achievement of carbon dioxide emission reduction targets.

[0070] 3) The model's accuracy and environmental adaptability have been comprehensively improved. The modeling technique that incorporates meteorological sensitive factors ensures high fidelity in predicting system boundaries under extreme environments, reducing scheduling risks.

[0071] 4) Enhanced support for flexible resource allocation decisions. Through quantitative analysis tools, the complementary effects of thermal storage and pumped storage under severe cold conditions were clarified, providing a scientific guidance for the long-term stable operation of the power grid.

[0072] Example 3 This embodiment provides a decoupling optimization method for a combined electric and thermal energy system based on multi-source flexible resource coordination under extremely cold weather conditions, including: Step 1: System component classification and aggregation, and meteorological sensitive parameters; In implementing this plan, the thermal power units are first finely classified and aggregated. The extraction condensing unit cluster serves as the core of the heating supply, and its operating domain is dynamically reconfigured according to equations 1 to 3. During the middle of the heating season, its maximum heating power is set at 7095 MW, corresponding to a back-pressure power generation of 4714 MW. The mandatory pure condensing units are responsible for supporting the grid base load, with an operating capacity set at 4100 MW, and a minimum output rate limited to 50%, i.e., a minimum power output of 2050 MW. The optional pure condensing units are dynamically adjusted between 0 and 6650 MW based on peak load.

[0073] In response to the severe cold environment, this plan sets the building heat loss coefficient at 0.85 and the indoor reference temperature at 20 degrees Celsius. During extreme cold weather, the cold wave intensity factor (Lambda) fluctuates between 1.2 and 1.5. Regarding flexibility resources, the thermal storage device is configured with a capacity of 1820 MWh, with a maximum heat release power of 240 MW, effectively offsetting the risk of thermoelectric lock-up. The pumped-storage power station is configured with an installed capacity of 1200 MW, and the electric boiler is configured with an installed capacity of 120 MW with a conversion efficiency of 98%, thus establishing a physical defense system against extreme load shocks.

[0074] Step 2: Daily-cycle meteorological-driven equilibrium analysis process; The system enters the daily balance calculation phase, acquiring real-time temperature data through the meteorological monitoring module. If the daily temperature drops below -20 degrees Celsius, the equivalent total heat load calculated by the system using Equation 1 will increase by approximately 30% compared to the normal temperature heating season. At this time, the minimum generating capacity of the extraction condensing unit will be passively increased from the conventional 2822 MW to over 4000 MW, severely compressing the peak-shaving window.

[0075] When excess power is detected, the system initiates a dispatch strategy centered on heat source replacement. The thermal storage equipment prioritizes releasing 240 MW of thermal power, directly replacing an equivalent amount of steam extraction from the extraction condensing units, thus forcibly lowering the unit's power generation floor from 4000 MW to 3700 MW. If the system still faces the risk of power curtailment, the electric boiler will activate a 120 MW power-to-heat conversion to compensate, further decoupling the heat-power binding relationship. This multi-dimensional data linkage ensures that, while guaranteeing basic residential heating, the system can absorb approximately 450 MWh of additional wind power per hour, achieving a counter-trend expansion of the curtailment space. Figure 4 As shown.

[0076] Step 3: Statistical analysis and robustness assessment of annual-scale equilibrium results; After completing a 365-day long-term simulation, the system summarized annual operating indicators using Equation 19. Experimental data showed that before adopting this scheme, the system's annual wind and solar curtailment rate was as high as 16.2% due to the severe cold conditions in northern China. After introducing meteorological sensitivity correction and flexible resource collaborative scheduling, the annual curtailment rate was successfully reduced to 4.5%, and the utilization level of new energy sources increased by 11.7%.

[0077] Regarding fossil fuel conservation, the annual power generation of the condensing unit decreased from 8.22 TWh to 4.89 TWh during the severe cold period, thanks to the efficient heat substitution performed by the electric boilers and thermal storage equipment. This represents a 41% reduction. This directly corresponds to a decrease in standard coal consumption and a significant drop in carbon dioxide emissions. By transferring the daily thermal storage surplus and energy storage status across days, the system ensured the maintenance of dynamic energy balance even during a two-week-long continuous cold wave, demonstrating the economic viability and technical robustness of the solution from a multi-dimensional data perspective.

[0078] Example 4 This embodiment provides a decoupling optimization method for a combined electric and thermal energy system based on multi-source flexible resource coordination under extremely cold weather conditions, including: This embodiment aims to verify the accuracy of the weather-sensitive correction model in reproducing the operating status of the energy system under extreme conditions. The entire operating data of a provincial power grid in northern China for the year 2020 was selected as the benchmark. In this region, renewable energy accounted for 46% of the installed capacity, and the region experienced a week-long period of extreme cold weather during the winter, with the lowest outdoor temperature dropping to minus 25 degrees Celsius.

[0079] In the verification process of this embodiment, the scheduling optimization model proposed in this invention is compared and analyzed with the internationally accepted traditional energy balance model. Traditional models often use averaging or static processing methods when dealing with heating loads, ignoring the nonlinear surge in building heat loss as the temperature drops. However, the model of this invention introduces environmental temperature variables and cold wave intensity factors through Equation 1, which can dynamically correct the equivalent total heat load.

[0080] Comparative data shows that the model of this invention reduces the error in identifying the risk of power curtailment during severe cold periods by approximately 4% compared to traditional models. The core reason for this improved accuracy lies in the fact that this scheme accurately characterizes the rigid lock-in characteristic of power generation based on heat demand, meaning that under extreme low temperatures, thermal power units cannot create peak-shaving space to ensure basic residential heating needs. Experimental results fully demonstrate the necessity and effectiveness of introducing meteorological sensitive factors in improving the accuracy of power-heat combined energy system scheduling.

[0081] Example 5 This embodiment provides a decoupling optimization method for a combined electric and thermal energy system based on multi-source flexible resource coordination under extremely cold weather conditions, including: This embodiment focuses on analyzing the collaborative compensation capability of flexible resources in response to extreme weather loads. Two comparative scenarios were set up in the experiment. Scenario A only configured a 1820 MWh thermal storage device. Scenario B adopted multiple resource coordination modes recommended in this invention, including a 240 MW thermal storage device, a 1200 MW pumped storage power station, and a low-pressure cylinder cut-off retrofit unit.

[0082] In simulating a thermoelectric lockout caused by an extreme cold wave, Scenario A, due to its single regulation method, rapidly depletes its thermal storage capacity when the heating load reaches its peak, forcing the system into a rigid heat-driven power generation mode, resulting in a wind curtailment rate as high as 16%. Scenario B, through a multi-energy compensation mechanism, demonstrates stronger decoupling capabilities. According to the data records in Tables 3 and 4, the power curtailment rate in Scenario B was successfully reduced to 8%.

[0083] like Figure 5 and Figure 6 As shown in the figure, experimental data further demonstrates that in scenario B, for every 1200 MW increase in pumped storage power station capacity, the system's renewable energy utilization rate can increase by an average of 2.6%. This embodiment demonstrates that the resource allocation logic described in this invention not only ensures energy supply security in extreme environments but also completely breaks the energy shackles that restrict the consumption of clean energy at the physical level.

[0084] Table 4 On the other hand, this embodiment also provides an electronic device, including a memory, a processor, and a computing program stored in the memory and executable on the processor, wherein the processor implements the method when executing the computing program.

[0085] On the other hand, this embodiment also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method.

[0086] The above are merely preferred embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A decoupling optimization method for a combined electric and thermal energy system based on multi-source flexible resource synergy under severe cold weather, characterized in that, include: Acquire real-time ambient temperature data containing meteorological sensitive factors, and dynamically correct the basic heating demand based on the real-time ambient temperature data to determine the meteorological-corrected equivalent total heat load. Based on the equivalent total heat load, an electrothermal feasible operating domain model of the extraction condensing unit is constructed to determine the minimum power generation limit of the extraction condensing unit under severe cold conditions. Based on the minimum power output limit of the extraction condensing unit and the minimum stable output of the pure condensing unit, the total minimum output of the thermal power unit is determined, and based on the output of new energy sources and the system electrical load, it is identified whether there is excess power. When there is excess electricity, multiple flexible resources are used to replace the heat source. The heat energy is released or converted by the multiple flexible resources to replace the heating share of the extraction condensing unit, thereby forcibly reducing the lower limit of the power generation of the extraction condensing unit and creating output space for the consumption of new energy.

2. The method according to claim 1, characterized in that, Based on the real-time ambient temperature data, the basic heating demand is dynamically adjusted to determine the meteorologically corrected equivalent total heat load, specifically including: The equivalent total heat load after meteorological correction is determined based on the basic heating demand forecast, heat loss coefficient, the difference between the indoor heating baseline target temperature and the real-time outdoor ambient temperature, and the cold wave weather correction factor.

3. The method according to claim 1, characterized in that, The construction of an electrothermal feasible operating domain model for the extraction condensing unit, to determine the minimum power generation limit of the extraction condensing unit under severe cold conditions, specifically includes: The minimum power generation limit is determined based on the back pressure power generation caused by heating demand, the conversion ratio coefficient of steam extraction to power generation and heating power, the equivalent total heat load, and the unit's minimum condensing power generation.

4. The method according to claim 1, characterized in that, The determination of the total minimum output of thermal power units, and the identification of whether there is excess power based on the output of new energy sources and the system electrical load, specifically includes: The surplus electrical load after taking into account the output of new energy sources is compared with the total minimum output of thermal power units, and the excess power is determined based on the difference between the two; wherein, the total minimum output of thermal power units is determined based on the sum of the minimum electrical output of extraction condensing units under real-time heating constraints and the minimum stable output of pure condensing units.

5. The method according to claim 1, characterized in that, The process of utilizing multi-source flexible resources for heat source replacement specifically includes: Determine the operating status of the extraction condensing unit. If the extraction condensing unit is operating on the EF line, which represents the heating constraint boundary, within the electrothermal feasible operating domain, then prioritize the use of the thermal storage equipment to release heat in order to replace the heating output of the extraction condensing unit. When the thermal storage device releases heat, the heat release power of the thermal storage device is determined based on the difference between the total heat load after meteorological correction and the minimum heating power required to maintain the unit's thermal cycle safety, combined with the current heat storage status of the thermal storage device.

6. The method according to claim 1, characterized in that, The method of calling upon multi-source flexible resources for heat source replacement also includes: If the thermal storage equipment cannot fully absorb the excess power, the pumped storage power station will be called in to pump and store the remaining excess power. The method of calling upon multi-source flexible resources for heat source replacement also includes: If the pumped storage power station is still unable to fully absorb the excess electricity, then an electric boiler will be used to convert the excess electricity into heat energy for final heat storage or direct heating.

7. The method according to claim 6, characterized in that, The process of calling upon an electric boiler to convert excess electricity into heat energy specifically includes: The operating power of the electric boiler is determined according to the different operating states of the extraction condensing unit. If the extraction condensing unit is operating on line EF, the operating power of the electric boiler is determined according to the difference between the excess power and the heat release power of the thermal storage equipment. If the extraction condensing unit is operating at point F, which represents the boundary of pure condensing conditions, and the thermal storage equipment is not full, the excess power is directly used as the operating power of the electric boiler.

8. The method according to claim 1, characterized in that, The method also includes steps of daily rolling calculation and long-term balance analysis: After completing the daily scheduling, the thermal storage capacity of the thermal storage equipment and the pumped storage power station are updated according to the charging and discharging power of the day. The updated state parameters are then transmitted as the initial conditions for the next day's scheduling calculations to achieve long-term energy balance analysis for the entire heating cycle or year.

9. An electronic device comprising a memory, a processor, and a computing program stored in the memory and executable on the processor, characterized in that, When the processor executes the computing program, it implements the method of any one of claims 1-8.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1-8.

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