A system and method for calculating the benefits of flexibility retrofitting of a circulating fluidized bed and wind power combined system.

Abstract

This invention discloses a system and method for calculating the benefits of flexibility retrofitting a circulating fluidized bed (CFB) and wind power combined system, belonging to the field of thermal power generation technology retrofitting evaluation. The system includes a retrofitting scheme management module, which inputs one or more CFB unit flexibility retrofitting schemes and their technical parameters to be evaluated; an operation simulation module, communicatively connected to the retrofitting scheme management module, which simulates the operating status of the CFB unit within a target period after the implementation of the input retrofitting scheme and outputs operation simulation data; an economic calculation engine module, communicatively connected to the operation simulation module, which receives the operation simulation data and, in conjunction with retrofitting investment cost data, calculates one or more incremental economic indicators for evaluating the profitability of the retrofitting scheme; and an evaluation report generation module, communicatively connected to the economic calculation engine module, which generates an economic evaluation report recommending the optimal retrofitting scheme based on the economic indicators.

Description

Technical Field

[0001] This invention relates to the field of thermal power generation technology retrofit evaluation, and in particular to a system and method for calculating the benefits of flexible retrofitting of a combined circulating fluidized bed and wind power system. Background Technology

[0002] my country's energy structure is rapidly transitioning towards a clean and low-carbon model, with the installed capacity of new energy sources such as wind power and photovoltaics continuing to increase. However, the volatility and randomness of new energy output pose a severe challenge to the stable operation of the power system, urgently requiring flexible power source support. Based on my country's energy endowment, the flexible retrofitting of existing coal-fired power units to transform them into reliable peak-shaving resources has become a realistic path to ensure the consumption of new energy and grid security.

[0003] Against this backdrop, the nationally promoted "three-pronged reform" of coal-fired power plants (energy conservation and emission reduction reform, heating system reform, and flexibility reform) has become a key task for the industry. However, the reform practice faces a core challenge: enterprises struggle to make accurate decisions regarding the economic viability of reform plans. This is mainly reflected in: 1) Static evaluation methods, out of touch with market dynamics: Existing economic assessments mostly use static parameters and fixed electricity price assumptions, which cannot reflect the fluctuations and cyclical patterns of electricity prices in the electricity market (especially the spot market). Ignoring market price signals leads to calculation results that cannot accurately predict the profitability of the renovation project under real operating conditions, resulting in high investment decision-making risks.

[0004] 2) Insufficient model specificity, failing to reflect the characteristics of CFB units: Circulating fluidized bed (CFB) units possess significant potential for flexible retrofitting due to their wide fuel adaptability, strong low-load stable combustion capability, and low-cost in-furnace pollution control. However, their unique "high inertia, slow response" operating characteristics, as well as the significantly lower pollutant treatment costs compared to conventional units resulting from in-furnace desulfurization and other processes, are not accurately quantified and reflected in existing general assessment models. This leads to doubts about the accuracy and reliability of conclusions drawn from retrofitting schemes for CFB units.

[0005] Therefore, there is an urgent need to develop a method and system that can dynamically compare and select the most economical alternatives among various flexible modification schemes. Summary of the Invention

[0006] In view of the above-mentioned prior art, the present invention provides a system and method for calculating the benefits of flexible retrofitting of a circulating fluidized bed and wind power combined system, which mainly solves the technical problems existing in the background art.

[0007] To achieve the above objectives, the technical solution of this invention is implemented as follows: In a first aspect, the present invention provides a system for calculating the benefits of flexible retrofitting of a circulating fluidized bed and wind power combined system, the system comprising: The retrofit scheme management module is used to input one or more flexibility retrofit schemes for circulating fluidized bed units to be evaluated and their technical parameters. The simulation module is connected to the modification scheme management module and is used to simulate the operating status of the circulating fluidized bed unit within the target cycle after the implementation of the modification scheme based on the input, and output the operating simulation data; The economic efficiency calculation engine module is communicatively connected to the operation simulation module. It is used to receive the operation simulation data and, in conjunction with the renovation investment cost data, calculate one or more incremental economic efficiency indicators for evaluating the profitability of the renovation plan. The evaluation report generation module is connected in communication with the economic calculation engine module and is used to generate an economic evaluation report recommending the optimal renovation scheme based on the economic indicators.

[0008] Secondly, the present invention also provides a method for calculating the benefits of flexibility retrofitting of a circulating fluidized bed and wind power combined system. The method is applied to the aforementioned system and includes the following steps: Step S1: Obtain one or more flexibility retrofitting schemes for circulating fluidized bed units to be evaluated and their technical parameters; Step S2: Based on the obtained modification plan, simulate the operating status of the circulating fluidized bed unit within the target cycle after the implementation of the modification plan, and obtain operating simulation data; Step S3: Based on the simulation data and the renovation investment cost data, calculate one or more incremental economic indicators to evaluate the profitability of the renovation plan; Step S4: Based on the economic indicators, generate an economic assessment report containing recommendations for the optimal renovation scheme.

[0009] The beneficial effects of this invention are as follows: by simulating, calculating and comparing different transformation schemes, the economic benefits after implementing different transformation schemes can be observed intuitively, thereby providing the optimal scheme for circulating fluidized bed transformation. This has urgent practical significance and great application value for scientifically promoting the flexible transformation of coal-fired power plants and reducing investment risks. Attached Figure Description

[0010] Figure 1 A schematic diagram of a system structure for calculating the benefits of flexible retrofitting of a combined circulating fluidized bed and wind power system; Figure 2 A schematic diagram illustrating the steps of a method for calculating the benefits of flexible retrofitting a combined circulating fluidized bed and wind power system; Figure 3 This is a typical summer load curve of Kunming, standardized to the maximum value of 300MW. Figure 4This is a schematic diagram of a typical wind power generation scenario converted to 300MW. Figure 5 This is a diagram showing the revenue results for scenario 1 before any modifications. Figure 6 This is a diagram showing the revenue results for scenario 2 before any modifications. Figure 7 This is a screenshot of the running results for Scenario 3 before any modifications. Figure 8 This is a screenshot showing the running results of Scenario 4 before any modifications. Figure 9 This is a diagram showing the revenue results for Scenario 1 after the slope modification. Figure 10 This is a diagram showing the revenue results for Scenario 2 after the slope modification. Figure 11 This is a diagram showing the revenue results for Scenario 3 after the slope modification. Figure 12 This is a diagram showing the revenue results for scenario 4 after the slope modification. Figure 13 The diagram shows the results of the transformation of scenario 1 with minimal effort. Figure 14 The diagram shows the profit results for scenario 2 after the minimum output modification; Figure 15 The diagram shows the profit results for scenario 3 after the minimum output modification; Figure 16 The diagram shows the profit results for scenario 4 after the minimum output modification; Figure 17 The diagram shows the profit results for scenario 1 after minimum output modification and slope modification; Figure 18 The diagram shows the profit results of scenario 2 after minimum output modification and slope modification; Figure 19 The diagram shows the profit results for scenario 3 after minimum output modification and slope modification; Figure 20 The diagram shows the profit results for scenario 4 after the minimum output modification and the slope modification. Detailed Implementation

[0011] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. In the following description, the expression "some embodiments" refers to a subset of all possible embodiments; however, it should be understood that "some embodiments" can be the same subset or different subsets of all possible embodiments and can be combined with each other without conflict.

[0012] In the following description, numerous specific details are set forth in order to provide a more thorough understanding of the invention. However, it will be apparent to those skilled in the art that the invention can be practiced without one or more of these details. In other instances, certain technical features well-known in the art have not been described in order to avoid obscuring the invention.

[0013] It should be understood that the present invention can be embodied in various forms and should not be construed as being limited to the embodiments set forth herein. Rather, providing these embodiments will make the disclosure thorough and complete, and will fully convey the scope of the invention to those skilled in the art. Furthermore, the terminology used herein is intended only to describe particular embodiments and is not intended to limit the invention. When used herein, the singular forms “a,” “an,” and “the” are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the terms “compose” and / or “comprising,” when used in this specification, identify the presence of the stated features, integers, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups. When used herein, the term “and / or” includes any and all combinations of the associated listed items.

[0014] It should also be noted that when an element is referred to as being "fixed to" another element, it can be directly attached to the other element or there may be an intervening element. When an element is referred to as being "connected to" another element, it can be directly connected to the other element or there may be an intervening element. The terms "vertical," "horizontal," "inner," "outer," "left," "right," and similar expressions used herein are for illustrative purposes only and do not represent the only possible implementation.

[0015] To fully understand this invention, a detailed structure will be presented in the following description to illustrate the technical solution proposed by this invention. Optional embodiments of the invention are described in detail below; however, in addition to these detailed descriptions, the invention may have other embodiments.

[0016] Firstly, this invention provides a system for calculating the benefits of flexible retrofitting of a combined circulating fluidized bed and wind power system. Please refer to the attached document for details. Figure 1 The system includes: The retrofit scheme management module is used to input one or more flexibility retrofit schemes for circulating fluidized bed units to be evaluated and their technical parameters. The simulation module is connected to the modification scheme management module and is used to simulate the operating status of the circulating fluidized bed unit within the target cycle after the implementation of the modification scheme based on the input, and output the operating simulation data; The economic efficiency calculation engine module is communicatively connected to the operation simulation module. It is used to receive the operation simulation data and, in conjunction with the renovation investment cost data, calculate one or more incremental economic efficiency indicators for evaluating the profitability of the renovation plan. The evaluation report generation module is connected in communication with the economic calculation engine module and is used to generate an economic evaluation report recommending the optimal renovation scheme based on the economic indicators.

[0017] As a preferred embodiment of the present invention, one or more specific modification schemes to be evaluated are input into the modification scheme management module. Different modification schemes are generated by adjusting parameters. The generated modification schemes are subjected to structured analysis and parameter standardization processing to obtain a modification scheme parameter set. The modification scheme parameter set is then sent to the operation simulation module. The modification scheme parameter set includes two types of core parameters: technical performance parameters (such as the minimum stable output and maximum ramp rate of the unit after modification) and economic cost parameters (such as the total investment of the project and the annual maintenance cost increment corresponding to the scheme).

[0018] For example, different modification schemes can be generated by changing the minimum stable output or the maximum gradeability, and different modification schemes can be combined to obtain a set of modification scheme parameters.

[0019] As a preferred embodiment of the present invention, the simulation module includes: The electricity price forecasting module is used to forecast the electricity market price for the day-ahead and intraday periods. The load forecasting module is used to forecast the electricity and heat load demand for the day and within the day; The wind power forecasting module is used to predict wind power output on and off the day; The cost calculation module is used to calculate the total system cost, which includes the pollutant treatment cost of the circulating fluidized bed unit. This cost is quantified by taking into account the in-furnace desulfurization process of the unit and the corresponding desulfurizing agent consumption. The integrated dispatch module is communicatively connected to the electricity price forecast module, load forecast module, wind power forecast module, and cost calculation module, respectively. It is used to establish an optimization model based on the forecast data and cost data of each module, with the objective function of maximizing the total system revenue taking into account the capacity price of the electricity market and the renewable energy grid connection policy, and solve the objective function. Based on the solution, it generates joint dispatch instructions for circulating fluidized bed units and wind turbine units.

[0020] As a preferred embodiment of the present invention, the electricity price prediction module is equipped with a hybrid prediction algorithm based on variational mode decomposition and TimesNet to provide a high-precision electricity price prediction sequence. The specific steps for electricity price prediction using the hybrid prediction algorithm based on variational mode decomposition and TimesNet are as follows: The historical electricity price sequence is decomposed into n intrinsic mode function components and one residual component using the variational mode decomposition algorithm. Each component is input into an independent TimesNet model for training and prediction. The prediction results of each component are superimposed and reconstructed, and after being calibrated by the error correction model, the day-ahead and intraday electricity price predictions of the key inputs are output.

[0021] In this embodiment, the electricity price forecasting module employs a hybrid forecasting algorithm combining variational mode decomposition and TimesNet. Building upon the conventional open-loop process of decomposition, forecasting, and reconstruction, it introduces an error feedback correction stage, forming a complete closed-loop optimization framework. This more effectively addresses the non-stationarity, complex periodicity, and nonlinearity of the electricity market price sequence, aiming to obtain day-ahead and intraday electricity price forecast data, providing crucial and reliable data for subsequent integrated dispatching modules. The specific implementation is as follows: In the decomposition phase, the historical electricity price series is adaptively decomposed in the frequency domain using Variational Mode Decomposition (VMD). VMD adaptively decomposes the complex, non-stationary original electricity price series into a series of relatively stationary intrinsic mode functions (IMF) subsequences with different center frequencies, and separates a residual component representing the long-term trend of the series. This process separates the different components mixed in the electricity price, such as short-term random fluctuations, intraday cyclical changes, and long-term trends, effectively avoiding the mode aliasing problem of traditional methods.

[0022] In the forecasting phase, the separated IMF and residual components are input into independent TimesNet forecasting models. The TimesNet models can reparameterize the one-dimensional time series into a two-dimensional tensor structure according to its potential period (e.g., 24 hours, 168 hours), enabling them to effectively capture the changing patterns within the period and the evolutionary laws between periods, thus achieving effective prediction of the future values ​​of each component. Then, the independent forecast values ​​of all IMF and residual components are linearly superimposed to reconstruct the preliminary forecast results for the original electricity price series.

[0023] In the correction phase, this invention adds a residual correction module based on the preliminary prediction results. This module first analyzes the error sequence between the preliminary prediction and the actual value in historical data during the training phase. In practical application, the model dynamically estimates the error of the currently generated preliminary prediction value, generating a correction amount. The preliminary prediction value and the correction amount are then added to obtain the final electricity price prediction.

[0024] As a preferred embodiment of the present invention, the load forecasting module forecasts the electricity and heat load demand for the day before and during the day, specifically including: Collect historical hourly electrical and heat load data, meteorological data, and a set of parameters for the renovation plan for at least one year for the area covered by the target circulating fluidized bed unit and its associated heating network, and perform preprocessing.

[0025] In this embodiment, the present invention collects historical electricity and heat load data of the target area over the past year, with a time resolution of at least hourly, from the plant-level monitoring information system (SIS) or the regional power grid / heat network dispatch center. Simultaneously, meteorological data for the same period is obtained from a meteorological service provider. The meteorological data includes temperature, relative humidity, wind speed, and weather phenomena (sunny, rainy, snowy, etc.). The collected data are then aggregated to obtain a historical time-series dataset.

[0026] After the circulating fluidized bed unit undergoes further flexibility modifications, its operating characteristics (such as thermoelectric coupling and minimum technical output) will be fundamentally altered, directly affecting its external "load characteristics." For example, adding an electric boiler may convert some electrical energy into heat energy during periods of high wind power generation, thereby changing the net load curve of the power grid.

[0027] The system obtains the parameter set of the current modification scheme to be evaluated in real time from the modification scheme management module. This parameter set is not directly used for predictive model calculations, but rather to determine which set of historical data or which prediction mode to use. A prediction scenario identifier is obtained. For example, if the scheme is "adding an electrode boiler", the system automatically associates and selects the operating data of units that have undergone similar modifications in the past as training samples, or switches to the built-in "electrothermal decoupling" prediction mode.

[0028] Simultaneously, derived features are calculated based on the parameter set of the retrofit scheme. For example, if the retrofit involves "reducing the minimum technical output to 30%", a "deep peak-shaving potential coefficient" feature is constructed; if it involves "increasing the electrothermal conversion capacity by X MW", a "transferable electrical load" feature is constructed. These are then used as contextual information for the feature vector at future moments and input into the corresponding prediction model.

[0029] For the prediction of electrical load, a gradient boosting decision tree model is used to analyze and predict load characteristics, and hourly predicted electrical load curves are obtained within the target scheduling period.

[0030] In this embodiment, the preprocessed historical feature dataset is used as input, and the corresponding historical electricity load value is used as the target label to supervise the learning of the gradient boosting decision tree model. The hyperparameters of the model are optimized through cross-validation. For the target scheduling period (day-ahead / day-intraday), the constructed future time feature vector is simultaneously input into the trained gradient boosting decision tree model, which outputs the predicted electricity load value at that time. The predicted electricity load values ​​at all times are then concatenated to form the predicted electricity load curve.

[0031] For heat load forecasting, a support vector regression model is used to analyze and predict load characteristics, and hourly predicted heat load curves are obtained within the target scheduling period.

[0032] In this embodiment, similarly, temperature-related features (such as current temperature, temperature difference, number of heating days, etc.) and historical heat load features are used as core inputs, and historical heat load values ​​are used as the target to train a support vector regression model. Feature vectors for future moments (such as the "heat storage tank influence coefficient") are then input into the trained support vector regression model. The predicted heat load value for that moment is output, and the predicted heat load values ​​for all moments are connected to form a predicted heat load curve.

[0033] As a preferred embodiment of the present invention, the wind power prediction module obtains the temporal characteristics of historical wind speed, wind direction, and historical power and the corresponding scheduling scenario mode by collecting historical power output information of wind farms, meteorological information, and parameter sets of retrofit schemes. In this embodiment, historical power output information of the wind farm is obtained through a wind farm monitoring system (such as a SCADA system). Historical meteorological information is obtained by calling the historical API from the meteorological data service provider. The obtained meteorological information is passed in the time period and geographical location (latitude and longitude coordinates of the wind farm) corresponding to the historical power output information. The system requests the historical wind speed data, historical wind direction data and historical power data of that location at the hub height layer.

[0034] The retrofit scheme management module obtains the retrofit scheme parameter set of the currently evaluated scheme in real time. This parameter set is used to define or select a specific scheduling scenario mode, resulting in a prediction context vector. For example, if the retrofit scheme is "significantly improve the unit ramp rate," the prediction model will be associated with a "high-flexibility scheduling mode," in which the system has a higher tolerance for wind power fluctuations.

[0035] The collected data is input into a long short-term memory network model for statistical analysis to obtain the predicted wind power output curve for the target period.

[0036] In this embodiment, time-series features including historical wind speed, wind direction, and historical power, along with corresponding scheduling scenario patterns, are input into the Long Short-Term Memory (LSTM) network model. Measured power for a specific future time period (e.g., the next 24 hours) is used as a supervisory signal. The network parameters are trained by minimizing prediction errors (e.g., mean squared error) through a backpropagation algorithm (e.g., the Adam optimizer). This enables the network model to not only learn the "general laws of wind energy conversion to electricity under given meteorological conditions" but also to distinguish the "expected patterns of wind power being actually scheduled or accepted by the system under different system flexibility (i.e., different retrofit schemes)." Finally, the predicted wind power output curves for each time period (e.g., every 15 minutes) within the standard period are output.

[0037] In a preferred embodiment of the present invention, the total system revenue in the integrated scheduling module is the sum of wind power sales revenue, circulating fluidized bed unit power sales revenue, and heat sales revenue, minus the total power generation cost of the system after cogeneration correction. Maximizing the total system revenue is used as the objective function of the optimization model. The specific formula is as follows:

[0038] in, The total power generation cost after adjustment for combined heat and power (CHP) For the electricity sales revenue of the circulating fluidized bed unit, For the heat sales revenue of the circulating fluidized bed unit, This refers to the revenue generated from the sale of electricity from wind turbine generators.

[0039] In this embodiment, the total power generation cost after cogeneration correction is... Including fuel consumption costs Operating and maintenance costs of circulating fluidized bed units Pollutant treatment costs Wind turbine operation and maintenance costs .Right now .

[0040] Specifically, regarding fuel consumption costs It depends mainly on the price of coal. and coal consumption during power generation Its specific mathematical expression is:

[0041] Coal consumption can be calculated using the following formula:

[0042] in, Fuel consumption, expressed in kg / h; This refers to the boiler's superheated steam evaporation rate, expressed in tons per hour (t / h). This refers to the boiler reheat steam evaporation rate, expressed in t / h. Specific enthalpy of superheated steam, expressed in kJ / kg. Specific enthalpy of feedwater at boiler unit inlet, in kJ / kg; This refers to the specific enthalpy of reheat steam outlet, expressed in kJ / kg. Specific enthalpy of reheat steam inlet, in kJ / kg; This represents the boiler thermal efficiency as a percentage. This refers to the lower heating value of the coal fed into the boiler, expressed in kJ / kg.

[0043] Substituting the lower calorific value of standard coal, the coal consumption is converted to standard coal consumption, and the unit is changed from kg / h to g / h. The specific formula is as follows:

[0044] Furthermore, comprehensive coal consumption for:

[0045] in This refers to the power generation capacity of the circulating fluidized bed unit.

[0046] According to the operating condition diagram of the circulating fluidized bed (CFB) unit:

[0047]

[0048] in, and These represent the slopes of the main steam flow-power relationship diagram and the reheat steam flow-power relationship diagram for the unit under given operating conditions. and These are the ordinates of the curve.

[0049] In the above formula, and , , , All of these are constants and can be obtained by consulting the unit's technical parameters. Thus, the relationship between coal consumption and the generator terminal power of the circulating fluidized bed unit is derived.

[0050]

[0051]

[0052] Specifically, the operating and maintenance costs of the circulating fluidized bed unit The operating and maintenance costs are related to the plant's power generation. During power generation, various auxiliary machines such as primary and secondary air fans consume a certain amount of electricity to maintain normal operation.

[0053]

[0054] in, Plant power consumption rate; The remaining power generation costs for circulating fluidized bed.

[0055] Specifically, the cost of pollutant treatment Considering the costs incurred by the circulating fluidized bed unit in absorbing SO2 and NOx, namely:

[0056] When considering SO2 treatment, the high-density turbulent bed formed during the operation of the circulating fluidized bed unit enhances the contact between SO2 and the desulfurizing agent. Furthermore, the material circulation system and intense particle friction ensure that the active surface of the desulfurizing agent remains continuously exposed for reaction. Therefore, the circulating fluidized bed unit does not require an additional desulfurization device; its SO2 treatment cost primarily stems from the consumption of the desulfurizing agent, as expressed mathematically:

[0057] in, The comprehensive coal consumption for the operation of the circulating fluidized bed unit; This refers to the amount of sulfur dioxide produced per unit of coal. The calcium-to-sulfur ratio; This refers to the price of quicklime.

[0058] When considering NOx treatment, the mainstream method for circulating fluidized bed (CFB) units is currently SNCR (non-selective catalytic reduction) denitrification technology. In recent years, my country has implemented increasingly stringent emission regulations for coal-fired power plants. According to the "Action Plan for Upgrading and Retrofitting Coal-fired Power Plants for Energy Conservation and Emission Reduction (2014-2020)," the NOx emission concentration of newly built coal-fired power plants must not exceed 50 mg / m³. At this point, SNCR denitrification technology alone is insufficient to meet the emission requirements. However, by combining low-NOx combustion technology with careful design, ultra-low emissions of 50 mg / m³ can be achieved. The treatment cost at this point mainly comes from the consumption of the denitrification agent in the SNCR technology. In this invention, ammonia is selected as the denitrification agent, and the specific formula is as follows:

[0059]

[0060] in, Emissions per unit coal combustion (m³) 3 / kg); The comprehensive coal consumption (g / kWh) for the operation of the circulating fluidized bed unit; The concentration of nitrogen oxides in the standard state flue gas without ammonia injection (mg / m³) 3 ); Represents the ammonia-nitrogen molar ratio; This represents the concentration of ammonia. The price of ammonia; This represents the calorific value (kJ / kg) of the coal used.

[0061] Thus, the pollutant treatment cost of the circulating fluidized bed unit was obtained.

[0062] Specifically, the operation and maintenance cost of the wind turbine Related to power generation, that is:

[0063] in, This refers to the operation and maintenance coefficient of the wind turbine unit. This refers to the power generation capacity of the wind turbine generator; This refers to the unit's operating time.

[0064] In this embodiment, the electricity sales revenue of the circulating fluidized bed unit It is divided into two main parts: electricity price and capacity price.

[0065] The revenue from electricity price depends primarily on the grid connection price and the power generation of the generating units.

[0066] in, This indicates the predicted electricity price for circulating fluidized bed units; Indicates the generating capacity of the unit; Indicates the time of power generation.

[0067] Because the capacity price of coal-fired power plants is determined by recovering a certain percentage of the fixed costs of coal-fired power units, and the nationally unified fixed cost of coal-fired power units is 330 yuan / kW*year, the percentage of fixed costs recovered through the capacity price is as high as 50% in Yunnan Province, where coal-fired power transition and development began earlier.

[0068] Therefore, the revenue from the capacity-based electricity price depends primarily on the installed capacity of the circulating fluidized bed unit:

[0069] in, This indicates the percentage of fixed costs recovered by the capacity-based electricity price. This represents the fixed cost of a coal-fired power unit; This indicates the installed capacity of the circulating fluidized bed unit; This indicates the time it takes for electricity to be generated, measured in days.

[0070] In summary, the electricity sales revenue of the circulating fluidized bed unit was obtained. :

[0071] The heat sales revenue of the circulating fluidized bed unit It mainly depends on the amount of steam extracted for heating and the local heating unit price:

[0072] This indicates the local heating unit price; This indicates the amount of steam extracted for heating in a circulating fluidized bed unit's combined heat and power (CHP) system. This parameter is obtained from load forecasting. This indicates the unit's operating time.

[0073] The electricity sales revenue of the wind turbine This is mainly related to the on-grid tariff for wind power and the power generation of the generating units. 45% of the on-grid electricity generated by wind power projects can be compensated to the benchmark price of coal-fired power generation in Yunnan Province based on the average transaction price in the clean energy market. Therefore, this invention will include 45% of wind power in the price settlement mechanism for sustainable development of new energy.

[0074] In summary, the revenue from selling electricity from wind turbines mainly consists of two parts: the revenue from the portion of electricity sold that is included in the mechanism and receives "refunds for overpayments and subsidies for underpayments," and the revenue from selling the remaining electricity sold entirely in the market. The specific formula is as follows:

[0075] in, The proportion of wind power to be included in the price settlement mechanism for sustainable development of new energy; The local benchmark price for coal-fired power. This parameter represents the market-based on-grid tariff for wind power; it is obtained from the electricity price prediction module. The power generation capacity of the wind turbine; This refers to the time it takes for electricity to be generated.

[0076] The total operating cost of the system under the combined heat and power (CHP) condition Under combined heat and power (CHP) conditions, the standard coal consumption of the circulating fluidized bed unit is still calculated using the following formula:

[0077] Under extraction steam conditions, the heat generated by coal combustion is used to heat the main steam and reheat steam, and a portion of the main steam and reheat steam is extracted after heating as heating steam. Not all steam is used to drive the turbine. Therefore, the overall coal consumption under these conditions is:

[0078]

[0079]

[0080]

[0081]

[0082] in, It is the total operating power of the circulating fluidized bed unit, and is also used to drive the steam turbine to do work and supply heat to the outside. This refers to the generator terminal power of the unit; Electrical power converted from unit extraction steam load; This refers to the extraction steam load of the unit; is the conversion factor.

[0083] Therefore, the fuel consumption cost of the circulating fluidized bed unit is revised as follows:

[0084] The revised operating and maintenance costs of the circulating fluidized bed unit are as follows:

[0085]

[0086] The pollutant treatment cost of the circulating fluidized bed unit is revised as follows:

[0087]

[0088]

[0089] The total power generation cost of the system is then corrected to:

[0090] With the introduction of combined heat and power (CHP) operation, the power constraints of the circulating fluidized bed (CFB) unit change, and the impact of extraction steam load on generator terminal power needs to be considered. Therefore, the constraints of the CFB unit need to be modified.

[0091] The climbing constraint remains unchanged:

[0092]

[0093] Thermal output constraint:

[0094] Constraints of Cogeneration:

[0095]

[0096] in, and These are the minimum and maximum power generation of the circulating fluidized bed unit under pure condensation conditions, respectively. This is the reduction factor for the amount of electricity generated per unit of heat supplied during combined heat and power generation. This is the elasticity coefficient between electrical power and thermal power in combined heat and power generation; It is a constant.

[0097] As a preferred embodiment of the present invention, the integrated scheduling module employs a dual-time-scale architecture to simulate and solve the objective function of the optimization model, specifically including: In the current simulation phase, the model is optimized based on the next day's forecast data, with a 24-hour cycle, to generate a preliminary joint operation plan for the circulating fluidized bed unit and the wind turbine unit. The intraday rolling simulation phase is used to perform rolling optimization simulations on the preliminary joint operation plan based on updated ultra-short-term data, and generate the final scheduling instructions.

[0098] In this embodiment, solving the objective function yields the output plans for the circulating fluidized bed generators and wind turbines for each time period of the day; these plans serve as the final joint scheduling instructions, directly guiding the real-time operation control of the two types of generators.

[0099] As a preferred embodiment of the present invention, the incremental economic indicators calculated by the economic calculation engine module include: total power generation revenue, electricity sales revenue of circulating fluidized bed unit, capacity electricity price revenue, heat sales revenue of circulating fluidized bed unit, net wind power generation revenue, and total wind curtailment.

[0100] In this embodiment, the economic efficiency calculation engine module transforms simulation data into intuitive investment decision-making data. This module communicates closely with the simulation module, receiving detailed simulation results including electricity sales revenue, heat sales revenue, and various operating costs, and integrating investment cost data for the renovation schemes from the front end. Its core function is to dynamically calculate and output a series of incremental economic indicators for evaluating the profitability of renovation schemes, thereby achieving precise quantification and horizontal comparison of the financial benefits of different renovation schemes.

[0101] Finally, the assessment report generation module, as the final output of the entire economic feasibility calculation system, receives all key data from the economic feasibility calculation engine and detailed revenue and cost structure data provided by the simulation module. It systematically integrates, visualizes, and professionally interprets the calculation results from the economic feasibility calculation engine module, ultimately generating a comprehensive and clear economic feasibility assessment report, providing direct evidence for investment decisions.

[0102] Secondly, the present invention also provides a method for calculating the benefits of flexibility retrofitting of a circulating fluidized bed and wind power combined system. The method is applied to the aforementioned system and includes the following steps: Step S1: Obtain one or more flexibility retrofitting schemes for circulating fluidized bed units to be evaluated and their technical parameters; Step S2: Based on the obtained modification plan, simulate the operating status of the circulating fluidized bed unit within the target cycle after the implementation of the modification plan, and obtain operating simulation data; Step S3: Based on the simulation data and the renovation investment cost data, calculate one or more incremental economic indicators to evaluate the profitability of the renovation plan; Step S4: Based on the economic indicators, generate an economic assessment report containing recommendations for the optimal renovation scheme.

[0103] To verify the effectiveness of the system and method in this invention, wind power and load curves from a certain region in Yunnan Province were used as input data to test the effectiveness of the proposed collaborative method.

[0104] A case study analysis is conducted on the integrated dispatch module. The objective function is to maximize net power generation revenue, which includes the revenue from electricity sales by the circulating fluidized bed generators. Heat sales revenue of circulating fluidized bed units and the revenue from selling electricity from wind turbine units Net revenue from power generation is expressed as revenue from power generation minus the cost of power generation. The model also includes ramp-up constraints for circulating fluidized bed units, combined heat and power constraints, power constraints for wind turbine units, and power balance constraints.

[0105] The system in this example consists of a 300MW subcritical circulating fluidized bed turbine and a 300MW wind farm. The system is considered as a coordinated integrated energy system, responding to grid dispatch. The circulating fluidized bed turbine is also assumed to supply heat to the outside world at a long-term extraction steam load of 140t / h. The model's input parameters include the electrical load and the maximum generateable power of the wind farm during the corresponding time period, which is limited by the wind speed at the wind farm location.

[0106] Regarding electricity pricing, this example adopts Yunnan Province's policy on time-of-use pricing, which divides peak, normal, and off-peak periods based on electricity load. The time-of-use pricing scheme adopts a 20% increase on the benchmark price during peak periods, the benchmark price during normal periods, and a 20% decrease on the benchmark price during off-peak periods.

[0107] Regarding electrical load, see Figure 3 Referring to the typical summer load curve of Kunming City and considering the volatility and intermittency of wind power generation, in order to ensure the stability of power supply and the safety of system operation, the load curve is converted into a new load curve with a maximum load of 300MW by scaling the maximum value, which is used as the input parameter of the system. The time resolution of the data is 10 minutes.

[0108] For the maximum power output of wind power generation, please refer to [link / reference]. Figure 4Four typical wind power scenarios were used as wind power constraints for this example. Furthermore, the wind power curve was calculated using the ratio of the rated power in the original dataset to the 300MW rated power in the example, and served as another input parameter for the system. The time resolution of the data was 10 minutes.

[0109] Example 1: Benefit model of wind and fire synergy operation without modification.

[0110] Scenario 1: Low-power stable output scenario.

[0111] like Figure 5 As shown, when wind power is operating at low power and with stable output, the net revenue from power generation is 1,823,584.29 yuan. Of this, the revenue from electricity sales by the first CFB unit is -52,256.57 yuan, and the revenue from electricity sales by the second CFB unit is 328,260.68 yuan. The revenue from capacity pricing for the two CFB units is 271,232.88 yuan, the revenue from heat sales is 1,196,160 yuan, and the revenue from wind power sales is 80,187.31 yuan. In this scenario, wind power output is generally low, and the two CFB units primarily meet the electricity load. During coordinated operation, to maximize economic efficiency, the two CFB units adopt a strategy of one unit generating as much power as possible while the other fills the load gap. Therefore, one CFB unit experiences a negative revenue from electricity sales, while the other CFB unit generates a higher revenue.

[0112] Scenario 2: High power fluctuation scenario like Figure 6 As shown, when wind power experiences high power output with significant fluctuations, the net revenue from power generation is 2,811,453.87 yuan. Of this, the revenue from electricity sales from the first CFB unit is 306,523.83 yuan, and the revenue from electricity sales from the second CFB unit is -388,158.45 yuan. The revenue from capacity electricity price for the two CFB units is 271,232.88 yuan, the revenue from heat sales is 1,196,160 yuan, and the revenue from wind power sales is 1,425,695.62 yuan. In this scenario, the power generation of the CFB units is relatively small and mainly concentrated during periods of low electricity prices, thus further reducing the revenue from electricity sales. Simultaneously, the CFB units are limited by minimum output and ramp-up rate during peak shaving. Therefore, when high wind power generation forces the circulating fluidized bed units to operate at minimum load, the system cannot accommodate more wind power, resulting in significant wind curtailment. Furthermore, when wind power decreases to a point where the circulating fluidized bed (CFB) turbine no longer operates at its lowest output, the ramp-up rate of the CFB may not be able to match the wind speed fluctuations due to large wind speed variations, which could lead to wind curtailment due to untimely adjustments. The total wind curtailment in Scenario 2 is 77.5 MWh.

[0113] Scenario 3: Medium power dual-peak scenario (morning and evening).

[0114] like Figure 7As shown, when wind power operates in a mid-power, dual-peak scenario (morning and evening), the net revenue from power generation is 1,904,714.23 yuan, of which the revenue from electricity sales by the first CFB unit is 262,783.79 yuan, and the revenue from electricity sales by the second CFB unit is -39,295.85 yuan. The capacity price revenue from the two CFB units is 271,232.88 yuan, the heat sales revenue is 1,196,160 yuan, and the wind power sales revenue is 213,833.41 yuan. During periods of relatively stable power, the output of the circulating fluidized bed (CFB) units varies with the wind farm's fluctuations, filling the gap between the electricity load and wind power output. The two CFB units maintain a coordinated power generation strategy of one generating more power while the other supplements. However, during the evening peak hours, the ramp rate of the CFB units cannot match the fluctuations in wind power, resulting in a certain degree of wind curtailment when wind speed fluctuates rapidly. At this time, the daily wind curtailment is 0.7 MWh.

[0115] Scenario 4: High power with high fluctuations transitioning to low power with stable output.

[0116] like Figure 8 As shown, when wind power transitions from a high-power, high-fluctuation phase to a low-power, stable output scenario, the net revenue from power generation is 1,975,262.14 yuan. Of this, the revenue from electricity sales by the first CFB unit is 286,460.41 yuan, and the revenue from electricity sales by the second CFB unit is -66,325.35 yuan. The capacity price revenue from both CFB units is 271,232.88 yuan, the heat sales revenue is 1,196,160 yuan, and the wind power sales revenue is 287,734.21 yuan. During periods of high wind power fluctuation, both CFB units respond simultaneously to changes in wind power. At this time, the ramp-up rate of the two CFB units is sufficient to match the wind power fluctuations, thus the wind power is fully absorbed in this scenario. Furthermore, both CFB units maintain their original power generation strategy.

[0117] As can be seen, in this embodiment, the operating results of each scenario are used as the representative of its cluster, and the annual revenue from the minimum output modification is calculated by weighted summation. The results show that the total net revenue of the system in annual operation is 738,848,712.5 yuan, of which the revenue from electricity sales from the two circulating fluidized bed units is 71,535,828.51 yuan, the revenue from capacity electricity price is 99,000,499.08 yuan, the revenue from heat sales is 436,598,899.1 yuan, and the revenue from wind power electricity sales is 110,243,909.49 yuan.

[0118] Example 2: Benefit model of wind and fire coordinated operation considering slope modification.

[0119] The ramp rate for 50% load and above was changed from 1.2% of rated load / minute to 4% of rated load / minute; the ramp rate for 30-50% load was changed from 0.8% of rated load / minute to 2% of rated load / minute. The models were then solved for four typical wind power generation scenarios.

[0120] Scenario 1: Low-power stable output scenario.

[0121] Table 1 Comparison of operational benefits before and after the slope modification in Scenario 1

[0122] Through analysis Figure 9 A comparison of the operational results and the parameters in Table 1 reveals that when wind power is operating at a low and stable output, the benefit of ramp-up modifications is minimal, amounting to only 56.05 yuan. This is because the power output and fluctuations of wind power generation are relatively small at this time, and the ramp-up rate before modification is already sufficient to meet peak-shaving requirements.

[0123] Scenario 2: High power fluctuation scenario.

[0124] Table 2 Comparison of operational benefits before and after the slope modification in Scenario 2

[0125] Through analysis Figure 10 A comparison of the operational results and the parameters in Table 2 reveals that when wind power experiences significant high-power fluctuations, the net revenue from power generation increased by 4720.45 yuan after the ramp-up modification, and the wind power absorption capacity increased by 10.1 MWh. The increase in revenue primarily stemmed from the increase in wind power generation and the decrease in power generation from the circulating fluidized bed (CFB) turbines. Furthermore, the economic benefits of the coordinated operation of the two CFB units also increased with the ramp-up rate. It is worth noting that since the decrease in CFB turbine power generation mainly occurred during off-peak and normal periods, the increase in revenue was more substantial than the decrease in cost.

[0126] Scenario 3: Medium power dual-peak scenario (morning and evening).

[0127] Table 3 Comparison of operational benefits before and after the slope modification in Scenario 3

[0128] Through analysis Figure 11 A comparison of the operational results and the parameters in Table 3 reveals that when wind power operates in a mid-power, dual-peak scenario (morning and evening), the net revenue from power generation increased by 1953.82 yuan after the ramp-up modification, and wind power became fully absorbed. The reduction in total power generation cost comes partly from the increased wind power absorption, and the remainder from the optimization results of the coordinated operation of the two CFB units.

[0129] Scenario 4: High power with high fluctuations transitioning to low power with stable output.

[0130] Table 4 Comparison of operational benefits before and after the slope modification in Scenario 4

[0131] Through analysis Figure 12 A comparison of the operational results and the parameters in Table 4 reveals that when wind power transitions from a high-power, high-fluctuation to a low-power, stable output scenario, the net revenue from power generation after the ramp-up modification increased by 348.52 yuan. The reduction in total power generation cost also stems from the improved collaborative operation of the two CFB units. In this scenario, since the ramp-up rate was already capable of matching the fluctuations in wind power before the modification, the benefits of the ramp-up modification were relatively small.

[0132] As can be seen, in the example of the wind-thermal co-operation benefit model considering ramp-up rate modification, the operating results of each scenario are used as the representative of their respective clusters, and the annual benefit of minimum output modification is calculated by weighted summation. The results show that after ramp-up modification, the annual net power generation benefit of the integrated system consisting of circulating fluidized bed (CFB) turbines and wind farms increased by RMB 506,846.75, while the wind power absorption capacity increased by 617.55 MWh. This data indicates that ramp-up rate modification of CFB turbines can bring certain economic and environmental benefits. In this example, because the maximum generating capacity of the two CFB units is relatively large, the inability to absorb wind power only occurs during extreme fluctuations, in which case the benefit of ramp-up modification is relatively small.

[0133] Example 3: Benefit model of wind and fire co-operation considering minimum output modification.

[0134] Consider modifying the circulating fluidized bed unit to achieve minimum output, reducing the minimum power from 30% of rated load to 20% of rated load. Then, solve the model for four typical wind power generation scenarios.

[0135] Scenario 1: Low-power stable output scenario.

[0136] Table 5 Comparison of operational benefits before and after the minimum output modification in Scenario 1

[0137] Through analysis Figure 13 A comparison of the operational results and the parameters in Table 5 reveals that when wind power is at a stable low-power output, the total power generation revenue increases by 136.2 yuan. Since the power output of wind power generation in Scenario 1 is generally low, even without modification, the circulating fluidized bed unit does not reach its minimum output throughout the day; therefore, the revenue from minimum output modification is also relatively small.

[0138] Scenario 2: High power fluctuation scenario.

[0139] Table 6 Comparison of operational benefits before and after the minimum output modification in Scenario 2

[0140] Through analysis Figure 14 A comparison of the operational results and the parameters in Table 6 reveals that when wind power experiences significant high-power fluctuations, the net revenue from power generation increased by RMB 48,381.45 after the minimum output modification, and the wind power absorption capacity increased by 63 MWh. Similar to scenario 2 in the cost calculation model, this scenario involves higher wind power output. Before the modification, the circulating fluidized bed unit operates at minimum output for a significant period. By modifying the minimum output, the power output of the circulating fluidized bed unit can be further reduced, thereby absorbing more wind power and significantly increasing the revenue from power generation.

[0141] Scenario 3: Medium power dual-peak scenario (morning and evening).

[0142] Table 7 Comparison of operational benefits before and after the minimum output modification in Scenario 3

[0143] Through analysis Figure 15 A comparison of the operational results and parameters in Table 7 reveals that when wind power operates in a mid-power, dual-peak scenario, the net revenue from power generation increased by 4548.19 yuan after the minimum output modification, but the wind power consumption did not increase. The revenue model incorporates combined heat and power (CHP), and the minimum power output of the circulating fluidized bed generator had already been reduced to some extent before the modification. However, in the mid-power, dual-peak scenario, wind power generation is at a mid-power level, and the circulating fluidized bed had not reached the new minimum power output before the modification, thus failing to promote wind power consumption. The increase in revenue at this time mainly comes from the reduction in power output of CFB unit 2 during the low-power period of thermal power, which allows CFB unit 1 to maintain higher power operation.

[0144] Scenario 4: High power with high fluctuations transitioning to low power with stable output.

[0145] Table 8 Comparison of operational benefits before and after the minimum output modification in Scenario 4

[0146] Through analysis Figure 16 A comparison of the operational results and the parameters in Table 8 reveals that when wind power transitions from a high-power, high-fluidity output scenario to a low-power, stable output scenario, the net revenue from power generation increased by 7513.15 yuan after the minimum output modification. In this scenario, the initial wind power output is high, and the circulating fluidized bed (CFB) unit operates at a lower load. Therefore, after the minimum output modification, CFB unit 1 can operate at a lower power, resulting in significant revenue during this period. However, when the wind power output decreases, the power generation of the CFB unit is higher than the minimum output before the modification, so there is no revenue from the minimum output modification during these periods.

[0147] As can be seen, the operational results of each scenario are used as representatives of their respective clusters, and the annual benefits of minimum output retrofitting are calculated through weighted summation. The results show that after minimum output retrofitting, the annual net power generation revenue of the integrated system consisting of the circulating fluidized bed turbine and the wind farm increased by RMB 3,675,296.42, while the wind power consumption increased by 3,378.86 MWh. This data indicates that minimum output retrofitting of the circulating fluidized bed turbine can bring certain economic and environmental benefits.

[0148] Example 4: A wind-fire coordinated operation benefit model considering simultaneous minimum output modification and slope modification.

[0149] Based on the preceding analysis, both minimum output modification and ramp rate modification can increase the net power generation revenue of the energy system composed of circulating fluidized bed (CFB) turbines and wind turbines, and can also improve wind power absorption. Therefore, it is feasible to simultaneously modify the CFB turbine for both minimum output and ramp rate. In this example, we solve four typical wind power generation scenarios to verify the synergistic effect of simultaneous modifications.

[0150] Scenario 1: Low-power stable output scenario.

[0151] Table 9 Comparison of operational benefits before and after minimum output modification and ramp modification in Scenario 1

[0152] Through analysis Figure 17 Comparing the operational results with the parameters in Table 9, it was found that when the wind power was in a low-power stable output state, the total power generation revenue increased by 145.25 yuan when both minimum output modification and ramp-up modification were performed simultaneously. Based on the analysis results from Scenario 1 where minimum output modification and ramp-up modification were performed separately, the results of this example were predictable. This is because the minimum output and ramp-up rate before modification were already sufficient to meet the needs of small-range fluctuations in wind power in this scenario; therefore, the revenue from modification at this time was very limited.

[0153] Scenario 2: High power fluctuation scenario.

[0154] Table 10 Comparison of operational benefits before and after minimum output modification and ramp modification in Scenario 2

[0155] Through analysis Figure 18A comparison of the operational results and the parameters in Table 10 reveals that when wind power experiences significant high-power fluctuations, the net revenue from power generation increased by 54,652.23 yuan after simultaneously implementing minimum output and ramp-up modifications, which is 1,550.33 yuan higher than the combined revenue from implementing only minimum output and ramp-up modifications. Wind power absorption increased by 77.5 MWh, achieving complete absorption of wind power. This is 4.4 MWh higher than the combined increase in wind power absorption achieved by implementing only minimum output and ramp-up modifications.

[0156] Scenario 3: Medium power dual-peak scenario (morning and evening).

[0157] Table 11 Comparison of operational benefits before and after minimum output modification and ramp modification in Scenario 3

[0158] Through analysis Figure 19 A comparison of the operational results and parameters in Table 11 reveals that when wind power operates in a mid-power, dual-peak scenario (morning and evening), the net revenue from power generation increased by 8020.77 yuan after simultaneously implementing minimum output and ramp-up modifications, which is 1518.76 yuan higher than the combined revenue from implementing minimum output and ramp-up modifications alone. Wind power absorption increased by 0.67 MWh, achieving complete absorption of wind power. It is worth noting that wind power absorption did not increase when ramp-up and minimum output modifications were implemented separately, but it was completely absorbed when both modifications were implemented simultaneously. Therefore, the synergistic effect of the two modifications yields significant economic benefits.

[0159] Scenario 4: High power with high fluctuations transitioning to low power with stable output.

[0160] Table 12 Comparison of operational benefits before and after minimum output modification and ramp modification in Scenario 4

[0161] Through analysis Figure 20 Comparing the operational results with the parameters in Table 12, it was found that when wind power transitions from a high-power, high-fluctuation to a low-power, stable output scenario, the net revenue from power generation increased by 7823.43 yuan after simultaneously implementing minimum output modification and ramp-up modification. This result is similar to that of scenario 4 in the cost model, indicating that in this scenario, minimum output modification and ramp-up rate modification take effect at different times. Therefore, the decrease in minimum output has a relatively small impact on ramp-up rate modification, and the increase in ramp-up rate also has a relatively small impact on minimum output modification. The revenue from simultaneous modification and the sum of the revenue from separate modifications are very close.

[0162] As can be seen, in the cost model example of wind-thermal co-operation considering both minimum output modification and ramp-up modification, the operating results of each scenario are used as the representative of their respective clusters, and the annual revenue from minimum output modification is calculated through weighted summation. The results show that after minimum output modification, the annual net revenue of the integrated system consisting of circulating fluidized bed (CFB) turbines and wind farms increased by RMB 4,428,579.07, which is RMB 246,435.90 more than the revenue from each modification separately. Simultaneously, wind power consumption increased by 4232.39 MWh, which is 311.84 MWh higher than the total wind power consumption from each modification separately. This data indicates that the economic and environmental benefits of simultaneously performing minimum output modification and ramp-up modification on CFB turbines are the greatest, exceeding the total revenue from each modification separately. Therefore, when considering unit modifications, power companies can prioritize simultaneously performing minimum output modification and ramp-up modification on CFB units to maximize economic and environmental benefits. When promoting peak-shaving retrofits for coal-fired power units, government departments should simultaneously focus on the ramp-up and minimum-output retrofits of CFB units, promoting their coordinated development to facilitate the implementation of the next generation of coal-fired power units.

[0163] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. The scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A system for calculating the benefits of flexible retrofitting of a circulating fluidized bed and wind power combined system, characterized in that, The system includes: The retrofit scheme management module is used to input one or more flexibility retrofit schemes for circulating fluidized bed units to be evaluated and their technical parameters. The simulation module is connected to the modification scheme management module and is used to simulate the operating status of the circulating fluidized bed unit within the target cycle after the implementation of the modification scheme based on the input, and output the operating simulation data; The economic efficiency calculation engine module is communicatively connected to the operation simulation module. It is used to receive the operation simulation data and, in conjunction with the renovation investment cost data, calculate one or more incremental economic efficiency indicators for evaluating the profitability of the renovation plan. The evaluation report generation module is connected in communication with the economic calculation engine module and is used to generate an economic evaluation report recommending the optimal renovation scheme based on the economic indicators.

2. The system for calculating the benefits of flexible retrofitting of a circulating fluidized bed and wind power combined system according to claim 1, characterized in that, The transformation scheme management module is configured as follows: Input one or more specific modification schemes to be evaluated, and adjust the parameters to generate different modification schemes. Perform structured analysis and parameter standardization on the generated modification schemes to obtain a modification scheme parameter set, and send the modification scheme parameter set to the operation simulation module. The modification scheme parameter set includes two types of core parameters: technical performance parameters and economic cost parameters.

3. The system for calculating the benefits of flexibility retrofitting a circulating fluidized bed and wind power combined system according to claim 1, characterized in that, The simulation module includes: The electricity price forecasting module is used to forecast the electricity market price for the day-ahead and intraday periods. The load forecasting module is used to forecast the electricity and heat load demand for the day and within the day; The wind power forecasting module is used to predict wind power output on and off the day; The cost calculation module is used to calculate the total system cost, which includes the pollutant treatment cost of the circulating fluidized bed unit. This cost is quantified by taking into account the in-furnace desulfurization process of the unit and the corresponding desulfurizing agent consumption. The integrated dispatch module is communicatively connected to the electricity price forecast module, load forecast module, wind power forecast module, and cost calculation module, respectively. It is used to establish an optimization model based on the forecast data and cost data of each module, with the objective function of maximizing the total system revenue taking into account the capacity price of the electricity market and the renewable energy grid connection policy, and solve the objective function. Based on the solution, it generates joint dispatch instructions for circulating fluidized bed units and wind turbine units.

4. The system for calculating the benefits of flexibility retrofitting a circulating fluidized bed and wind power combined system according to claim 2, characterized in that, The electricity price prediction module includes a hybrid prediction algorithm based on variational mode decomposition and TimesNet to provide high-precision electricity price prediction sequences. The prediction process is as follows: The historical electricity price sequence is decomposed into n intrinsic mode function components and one residual component using the variational mode decomposition algorithm. Each component is input into an independent TimesNet model for training and prediction. The prediction results of each component are superimposed and reconstructed, and after being calibrated by the error correction model, the day-ahead and intraday electricity price predictions of the key inputs are output.

5. The system for calculating the benefits of flexible retrofitting of a circulating fluidized bed and wind power combined system according to claim 3, characterized in that, The load forecasting module forecasts the electricity and heat load demand for the day and within the day, specifically including: Collect historical hourly electrical and heat load data, meteorological data, and a set of parameters for the renovation plan for at least one year for the area covered by the target circulating fluidized bed unit and its associated heating network, and perform preprocessing. For the prediction of electrical load, a gradient boosting decision tree model is used to analyze and predict load characteristics, and hourly predicted electrical load curves are obtained within the target scheduling period. For heat load forecasting, a support vector regression model is used to analyze and predict load characteristics, and hourly predicted heat load curves are obtained within the target scheduling period.

6. The system for calculating the benefits of flexibility retrofitting a circulating fluidized bed and wind power combined system according to claim 4, characterized in that, The wind power prediction module is configured as follows: Collect historical power output information, meteorological information, and retrofit plan parameter sets from wind farms to obtain the temporal characteristics of historical wind speed, wind direction, and historical power, as well as the corresponding dispatch scenario modes. The collected data is input into a long short-term memory network to obtain the predicted wind power output curve for the target period.

7. The system for calculating the benefits of flexible retrofitting of a circulating fluidized bed and wind power combined system according to claim 2, characterized in that, The total system revenue in the integrated scheduling module is the sum of wind power sales revenue, circulating fluidized bed unit power sales revenue, and heat sales revenue, minus the total power generation cost after cogeneration correction. Maximizing the total system revenue is used as the objective function of the optimization model. The specific formula is as follows: in, The total power generation cost after adjustment for combined heat and power (CHP) For the electricity sales revenue of the circulating fluidized bed unit, For the heat sales revenue of the circulating fluidized bed unit, This refers to the revenue generated from the sale of electricity from wind turbine generators.

8. The system for calculating the benefits of flexibility retrofitting a circulating fluidized bed and wind power combined system according to claim 3, characterized in that, The integrated scheduling module employs a dual-time-scale architecture to simulate and solve the objective function of the optimization model, specifically including: In the current simulation phase, the model is optimized based on the next day's forecast data, with a 24-hour cycle, to generate a preliminary joint operation plan for the circulating fluidized bed unit and the wind turbine unit. The intraday rolling simulation phase is used to perform rolling optimization simulations on the preliminary joint operation plan based on updated ultra-short-term data, and generate the final scheduling instructions.

9. The system for calculating the benefits of flexible retrofitting of a circulating fluidized bed and wind power combined system according to claim 1, characterized in that, The incremental economic indicators calculated by the economic calculation engine module include: total power generation revenue, electricity sales revenue of circulating fluidized bed units, capacity electricity price revenue, heat sales revenue of circulating fluidized bed units, net wind power generation revenue, and total wind curtailment.

10. A method for calculating the benefits of flexibility retrofitting a circulating fluidized bed and wind power combined system, wherein the method is applied to the system described in any one of claims 1-9, characterized in that, The method includes the following steps: Step S1: Obtain one or more flexibility retrofitting schemes for circulating fluidized bed units to be evaluated and their technical parameters; Step S2: Based on the obtained modification plan, simulate the operating status of the circulating fluidized bed unit within the target cycle after the implementation of the modification plan, and obtain operating simulation data; Step S3: Based on the simulation data and the renovation investment cost data, calculate one or more incremental economic indicators to evaluate the profitability of the renovation plan; Step S4: Based on the economic indicators, generate an economic assessment report containing recommendations for the optimal renovation scheme.

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