Pumped storage project carbon coordination management method, system, device and storage medium

Abstract

The present disclosure relates to the technical field of energy management, and particularly relates to a pumped storage project energy-carbon collaborative management method, system, device and storage medium. The method comprises the following steps: obtaining multi-source energy data and project operation data of a pumped storage project, establishing an energy-carbon correlation model, and determining a carbon emission result; based on the carbon emission result and a preset carbon evaluation index system, evaluating a low-carbon level of the pumped storage project to obtain a carbon grade evaluation result; based on the carbon grade evaluation result, an energy supply state and a project operation state, generating an energy-carbon collaborative control strategy, and adjusting energy configuration parameters and project operation parameters based on the energy-carbon collaborative control strategy; obtaining energy consumption change data and carbon emission change data after the energy-carbon collaborative control strategy is executed, updating the energy-carbon correlation model and the energy-carbon collaborative control strategy based on the energy consumption change data and the carbon emission change data, and realizing comprehensive analysis and collaborative management of energy consumption and carbon emission states in the whole process of the pumped storage project.

Description

Technical Field

[0001] This disclosure relates to the field of energy management technology, and in particular to methods, systems, equipment and storage media for energy and carbon synergy management in pumped storage projects. Background Technology

[0002] With the increasing demand for renewable energy and the low-carbon development of the power system, pumped storage projects play a crucial role in energy regulation and stable grid operation. Pumped storage projects have long construction cycles and complex construction processes. The construction phase involves extensive earthwork excavation, transportation, filling, and machinery operation. Simultaneously, the operation phase involves various energy consumption processes such as power conversion, equipment operation, and auxiliary energy use within the plant area. Each stage generates corresponding carbon emissions. Therefore, effective management of energy consumption and carbon emissions throughout the entire process of pumped storage projects is of great significance for reducing the overall carbon emission level of these projects.

[0003] Current carbon emission management methods for engineering projects typically rely on manual statistics or single-energy data collection to summarize and analyze data on fuel consumption, electricity consumption, and material transportation during construction. However, pumped storage projects involve multiple data sources, including construction machinery, power supply systems, engineering materials, and external energy supplies. These different data sources suffer from inconsistencies in data collection entities, data formats, and statistical periods, making it difficult to establish effective correlations between energy consumption data.

[0004] Meanwhile, existing carbon emission accounting methods typically calculate emissions from a single emission source. For example, they may calculate carbon emissions from equipment operation based solely on fuel consumption or indirect emissions from electricity consumption based solely on electricity usage. These methods fail to comprehensively consider the impact of various factors, such as the construction process, energy structure, and transportation of engineering materials, on carbon emissions. Consequently, the carbon emission accounting results cannot fully reflect the actual emissions of the project.

[0005] Therefore, existing technologies cannot solve the problem of comprehensive analysis and coordinated management of energy consumption and carbon emission status throughout the entire pumped storage project process. Summary of the Invention

[0006] To address the aforementioned technical issues, this disclosure provides a method, system, equipment, and storage medium for energy and carbon co-management in pumped storage projects.

[0007] This disclosure provides a method for coordinated energy and carbon management in pumped storage projects, including: Acquire multi-source energy data and engineering operation data of pumped storage projects. The multi-source energy data includes fuel energy consumption data, electrical energy consumption data, and green electricity utilization data. The engineering operation data includes construction progress data and engineering material transportation data. Based on the multi-source energy data and the engineering operation data, an energy-carbon correlation model is established, and the carbon emission results are determined through the energy-carbon correlation model. Based on the carbon emission results and the preset carbon evaluation index system, the low-carbon level of the pumped storage project is evaluated to obtain the carbon level evaluation result. Based on the carbon level assessment results, energy supply status, and engineering operation status, an energy-carbon synergistic regulation strategy is generated, and energy configuration parameters and engineering operation parameters are adjusted based on the energy-carbon synergistic regulation strategy. Obtain energy consumption change data and carbon emission change data after implementing the energy-carbon coordinated regulation strategy, and update the energy-carbon correlation model and the energy-carbon coordinated regulation strategy based on the energy consumption change data and the carbon emission change data.

[0008] Furthermore, the step of establishing an energy-carbon correlation model based on the multi-source energy data and the engineering operation data, and determining carbon emission results through the energy-carbon correlation model, includes: The energy-carbon correlation model includes a direct carbon emission model, an indirect carbon emission model, and a hidden carbon emission model. The direct carbon emission model is determined based on the energy consumption data of fuel-powered equipment, and the first carbon emission generated by direct energy consumption is determined based on the carbon emission model. The indirect carbon emission model is determined based on electricity energy consumption data and green electricity utilization data, and the second carbon emission generated by electricity energy consumption is determined based on the indirect carbon emission model. The implicit carbon emission model is determined based on engineering material transportation data, and the third carbon emission generated by engineering material transportation is determined based on the implicit carbon emission model. The first carbon emission, the second carbon emission, and the third carbon emission are combined to obtain the carbon emission results for the entire project process.

[0009] Furthermore, the process of integrating the first carbon emission, the second carbon emission, and the third carbon emission to obtain the carbon emission results for the entire engineering process includes: The weight of the first carbon emission is determined based on the energy consumption data of the fuel-powered equipment. The weight of the second carbon emission is determined based on the electrical energy consumption data and the green electricity utilization data. The weight of the third carbon emission is determined based on the engineering material transportation data. The carbon emission results for the entire project process are obtained by fusing the first carbon emission, the second carbon emission, the third carbon emission, and their corresponding weights.

[0010] Furthermore, the evaluation of the low-carbon level of the pumped storage project based on the carbon emission results and the preset carbon assessment index system, to obtain a carbon level assessment result, includes: Based on the carbon emission results, energy utilization indicators, green electricity utilization indicators, equipment decarbonization indicators, and carbon management indicators are determined in the preset carbon assessment indicator system. The comprehensive evaluation value is determined based on the preset weights of each evaluation indicator, and the carbon grade is determined based on the comprehensive evaluation value.

[0011] Furthermore, the generation of an energy-carbon synergistic regulation strategy based on the carbon level assessment results, energy supply status, and engineering operation status includes: The target emission reduction requirements are determined based on the carbon level assessment results. Adjustable energy parameters are determined based on the energy supply status; Adjustable operating parameters are determined based on the project's operating status; Based on the target emission reduction requirements, the adjustable energy parameters, and the adjustable operating parameters, the energy-carbon synergistic regulation strategy is generated. The energy-carbon coordinated regulation strategy includes adjustments to green electricity utilization, energy allocation, and engineering equipment operation.

[0012] Furthermore, updating the energy-carbon correlation model based on the energy consumption change data and the carbon emission change data includes: Obtain the energy consumption difference before and after implementing the energy-carbon synergistic regulation strategy; Obtain the carbon emission change trend before and after implementing the energy-carbon synergistic regulation strategy; The parameters of the energy-carbon correlation model are updated based on the differences in energy consumption and the trends in carbon emission changes.

[0013] Furthermore, after acquiring the multi-source energy data and engineering operation data of the pumped storage project, the method further includes: The multi-source energy data and engineering operation data are preprocessed to obtain processed data; The preprocessing includes: Establish corresponding data identifiers based on the data source; Synchronize data at different time scales; Identify and correct abnormal data; Unified encoding is applied to data in different formats.

[0014] This disclosure also provides an energy-carbon synergistic management system for pumped storage projects, including: The acquisition module is used to acquire multi-source energy data and project operation data of the pumped storage project. The multi-source energy data includes fuel energy consumption data, electric energy consumption data and green electricity utilization data. The project operation data includes construction progress data and project material transportation data. A module is established to build an energy-carbon correlation model based on the multi-source energy data and the engineering operation data, and to determine the carbon emission results through the energy-carbon correlation model. The evaluation module is used to evaluate the low-carbon level of pumped storage projects based on the carbon emission results and a preset carbon evaluation index system, and obtain carbon level evaluation results. The control module is used to generate an energy-carbon coordinated control strategy based on the carbon level evaluation results, energy supply status, and engineering operation status, and to adjust energy configuration parameters and engineering operation parameters based on the energy-carbon coordinated control strategy. The update module is used to acquire energy consumption change data and carbon emission change data after the energy-carbon coordinated regulation strategy is implemented, and to update the energy-carbon correlation model and the energy-carbon coordinated regulation strategy based on the energy consumption change data and the carbon emission change data.

[0015] This disclosure also provides a computer device, including a memory and a processor, wherein the memory stores computer-readable instructions, and the processor executes the computer-readable instructions to implement the steps of the pumped storage project energy and carbon synergistic management method.

[0016] This disclosure also provides a computer-readable storage medium storing computer-readable instructions, which, when executed by a processor, implement the steps of the energy and carbon co-management method for pumped storage projects.

[0017] The technical solution provided in this disclosure has the following advantages compared with the prior art: By acquiring multi-source energy data and engineering operation data of pumped storage projects, including fuel energy consumption data, electricity consumption data, and green electricity utilization data, and construction progress data and engineering material transportation data, an energy-carbon correlation model is established based on the multi-source energy data and engineering operation data. The carbon emission results are determined through this model. Based on the carbon emission results and a pre-set carbon assessment index system, the low-carbon level of the pumped storage project is evaluated, obtaining a carbon level assessment result. Based on the carbon level assessment result, energy supply status, and engineering operation status, an energy-carbon coordinated control strategy is generated, and energy configuration parameters and engineering operation parameters are adjusted based on this strategy. Energy consumption change data and carbon emission change data after implementing the energy-carbon coordinated control strategy are acquired. Based on these data, the energy-carbon correlation model and the energy-carbon coordinated control strategy are updated, achieving comprehensive analysis and coordinated management of the energy consumption and carbon emission status throughout the entire process of the pumped storage project. Attached Figure Description

[0018] The accompanying drawings, which are incorporated in and form a part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure.

[0019] To more clearly illustrate the technical solutions in the embodiments of this disclosure or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 A schematic diagram of the energy and carbon synergy management method for pumped storage projects provided in this embodiment of the disclosure; Figure 2 This is a schematic diagram of the energy-carbon synergistic management system for pumped storage projects provided in an embodiment of this disclosure. Detailed Implementation

[0021] To better understand the above-mentioned objectives, features, and advantages of this disclosure, the solutions disclosed herein will be further described below. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other.

[0022] Numerous specific details are set forth in the following description in order to provide a full understanding of this disclosure, but this disclosure may also be implemented in other ways different from those described herein; obviously, the embodiments in the specification are only some, and not all, of the embodiments of this disclosure.

[0023] Figure 1 This is a schematic diagram of the energy and carbon synergy management method for pumped storage projects provided in an embodiment of this disclosure. Figure 1 As shown, a method for coordinated energy and carbon management in pumped storage projects includes: S1, acquire multi-source energy data and project operation data of the pumped storage project. The multi-source energy data includes fuel energy consumption data, electric energy consumption data and green electricity utilization data. The project operation data includes construction progress data and project material transportation data. Specifically, data on fuel-powered equipment energy consumption describes the energy consumption of various fuel-powered mechanical equipment during engineering construction. For example, excavating equipment, transport vehicles, loading equipment, and other auxiliary machinery used in earthmoving construction all consume fuel during operation. By obtaining information such as equipment fuel consumption, equipment operating time, and equipment operating status, the fuel energy usage can be determined.

[0024] Electricity consumption data is used to describe the electricity usage in the construction area and the plant operation area. For example, the electricity consumption generated during the operation of lighting equipment, construction auxiliary equipment, processing equipment, and plant auxiliary equipment in the construction area can all be characterized by electricity consumption data.

[0025] Green electricity utilization data describes the use of green energy in engineering projects, including data on green electricity usage, sources of green electricity, and the proportion of green electricity used. By obtaining information on green electricity utilization, the carbon emission impact of different energy sources can be distinguished.

[0026] Simultaneously, project operation data is acquired. Construction progress data describes the current construction status, such as the construction stages, completed work volume, and task execution status in different construction areas. This data helps determine the project's operational status and provides a basis for subsequent correlation analysis between energy consumption and project activities.

[0027] Engineering material transportation data describes the transportation of materials during engineering construction, including the type and quantity of materials transported, as well as related information about the transportation process. Since the transportation of engineering materials generates energy consumption, this type of data can reflect the implicit carbon emissions of the project.

[0028] By acquiring multi-source information such as energy consumption data from fuel-powered equipment, electricity consumption data, green electricity utilization data, construction progress data, and engineering material transportation data, a correlation is established between energy consumption information and the engineering operation process. Since different types of energy data can be uniformly analyzed, the problem of incomplete information caused by managing only a single energy source is avoided, thus improving the comprehensiveness of acquiring the engineering's energy consumption status.

[0029] S2, Based on the multi-source energy data and the engineering operation data, establish an energy-carbon correlation model, and determine the carbon emission results through the energy-carbon correlation model; Specifically, the energy-carbon correlation model is used to describe the mapping relationship between energy consumption processes and carbon emission processes. Based on different energy consumption types and emission sources, the energy consumption process is divided into multiple carbon emission calculation processes.

[0030] For example, during the operation of fuel-powered equipment, there is a correlation between fuel consumption and equipment operating status. Based on fuel consumption, the direct carbon emissions generated by the equipment operation can be determined. When external power is used during the construction process, the amount of power consumed and the type of power source jointly affect the carbon emission results. Indirect carbon emissions can be determined based on the power energy consumption and the use of green electricity. During the transportation of engineering materials, the transportation distance, quantity, and mode of transportation will affect the carbon emissions generated in the transportation process. Implicit carbon emissions can be determined based on engineering material transportation data.

[0031] By establishing an energy-carbon correlation model, the energy consumption process is converted into corresponding carbon emission results, enabling a quantitative relationship between energy use and carbon emission status. Because this model considers both the engineering construction process and the energy utilization process, it can more accurately reflect the carbon emission level of pumped storage projects throughout the entire process.

[0032] S3. Based on the carbon emission results and the preset carbon evaluation index system, evaluate the low-carbon level of the pumped storage project and obtain the carbon level evaluation result. Specifically, a pre-set carbon assessment index system is used to describe the low-carbon operation status of the project from multiple dimensions. Energy utilization index is used to evaluate the project's energy consumption efficiency and energy use; green electricity utilization index is used to evaluate the proportion of green energy used in the project and the green energy substitution situation; equipment decarbonization index is used to evaluate the energy utilization level of the project's construction equipment; and carbon management index is used to evaluate the project's carbon emission management capabilities.

[0033] During the evaluation process, the data values ​​corresponding to each evaluation indicator are determined based on the obtained carbon emission results, and the comprehensive evaluation value is calculated according to the preset weights. For example, for a project with a lower carbon emission level per unit of work volume, a higher proportion of green electricity utilization, and higher energy utilization efficiency, the corresponding comprehensive evaluation value is higher; conversely, the comprehensive evaluation value is lower.

[0034] S4. Based on the carbon level evaluation results, energy supply status and engineering operation status, generate an energy-carbon synergistic regulation strategy, and adjust energy configuration parameters and engineering operation parameters based on the energy-carbon synergistic regulation strategy. Specifically, the target emission reduction requirements for the current project are determined based on the carbon rating assessment results. For example, when the carbon rating assessment result of the project is low, it indicates that there is significant room for emission reduction in the current energy utilization or project operation methods, and in this case, it is necessary to improve the degree of energy utilization optimization.

[0035] The energy supply status describes the current availability of energy, including the supply capacity of different energy sources, energy utilization, and energy allocation. Simultaneously, the project operation status is acquired, describing the current construction activities or equipment operation, including the construction phase, equipment operating requirements, and project task arrangements. Based on the target emission reduction requirements, energy supply status, and project operation status, corresponding energy-carbon coordinated regulation strategies are generated.

[0036] Among them, energy-carbon synergistic regulation strategies include: The green electricity utilization adjustment strategy adjusts the proportion of green electricity use according to the energy supply situation, so as to increase the utilization of green energy in the process of energy consumption in engineering projects.

[0037] An energy allocation adjustment strategy involves adjusting the energy distribution method according to different energy usage patterns, so that energy supply meets project needs while reducing carbon emissions.

[0038] The operational adjustment strategy for engineering equipment involves adjusting the equipment operation mode according to the engineering operation status, so that the equipment operation process is more in line with low-carbon goals.

[0039] After generating the control strategy, the corresponding adjustment parameters are sent to the energy management system or engineering operation management system for execution. This transforms carbon emission management from data statistics to a proactive adjustment process based on the actual operating status of the project. Because the control process considers both energy conditions and project needs, it avoids the problem of impacting project operation by simply reducing energy consumption.

[0040] S5, acquire energy consumption change data and carbon emission change data after executing the energy-carbon coordinated regulation strategy, and update the energy-carbon correlation model and the energy-carbon coordinated regulation strategy based on the energy consumption change data and the carbon emission change data.

[0041] Specifically, energy consumption change data is used to reflect changes in energy use before and after the implementation of the control strategy. Carbon emission change data is used to reflect changes in the carbon emission level of the project after the implementation of the control strategy. Based on the above change data, the original energy-carbon correlation model and control strategy are updated.

[0042] First, the differences in energy consumption before and after implementing the control strategy are compared to analyze the effect of energy allocation adjustment. Second, the trends in carbon emission changes before and after implementing the control strategy are compared to analyze the emission reduction effect. Finally, the correlation parameters in the model are adjusted based on the analysis results to make the model more accurately reflect the actual operating status of the project. By collecting data on changes in energy consumption and carbon emissions after control measures are implemented, and updating model parameters and control strategies using actual operating results, the system can continuously optimize the management process according to changes in the project stages, thereby improving the adaptability and long-term application effect of energy and carbon management methods.

[0043] In some possible implementations, S2, establishing an energy-carbon correlation model based on the multi-source energy data and the engineering operation data, and determining carbon emission results through the energy-carbon correlation model, includes: the energy-carbon correlation model includes a direct carbon emission model, an indirect carbon emission model, and a latent carbon emission model; determining the direct carbon emission model based on fuel equipment energy consumption data, and determining the first carbon emission amount generated by direct energy consumption based on the carbon emission model; determining the indirect carbon emission model based on electricity energy consumption data and green electricity utilization data, and determining the second carbon emission amount generated by electricity energy consumption based on the indirect carbon emission model; determining the latent carbon emission model based on engineering material transportation data, and determining the third carbon emission amount generated by engineering material transportation based on the latent carbon emission model; and fusing the first carbon emission amount, the second carbon emission amount, and the third carbon emission amount to obtain the carbon emission results for the entire engineering process.

[0044] In this embodiment, during the construction of pumped storage projects, earthwork excavation, transportation, and filling typically require a large number of fuel-powered equipment. For example, excavating equipment, loading equipment, dump trucks, and other fuel-powered machinery at the construction site consume energy by burning fuels such as diesel during operation, and simultaneously generate corresponding carbon dioxide emissions.

[0045] Therefore, a direct carbon emission model is established based on the energy consumption data of fuel-powered equipment. This energy consumption data includes: fuel consumption, equipment operating time, equipment operating status, and equipment type information.

[0046] Specifically, fuel-powered equipment is categorized according to its type. Different types of equipment exhibit varying levels of energy consumption per unit due to their different operating methods. For example, transport vehicles are primarily related to the volume of transport tasks and the distance traveled, while excavators are mainly related to working hours and intensity. A correlation between energy consumption and carbon emissions is then established based on equipment type.

[0047] Furthermore, the corresponding energy consumption is determined based on the energy consumption data of the fuel-powered equipment, and the first carbon emission generated by direct energy consumption is calculated in conjunction with the corresponding emission parameters. The first carbon emission represents the carbon emissions generated by the direct combustion of energy by fuel-powered equipment in pumped storage projects. By establishing a direct carbon emission model, the energy consumption during the operation of construction machinery can be quantified and converted into carbon emission data.

[0048] In addition to direct emissions from fuel-fired equipment, pumped storage projects also consume significant amounts of electrical energy during construction and operation. Examples include: construction site lighting equipment, auxiliary construction equipment, processing equipment, and auxiliary operating equipment within the plant area.

[0049] Although the equipment does not directly generate combustion emissions during operation, its indirect carbon emission levels vary due to different sources of electricity. Therefore, an indirect carbon emission model is established based on electricity consumption data and green electricity utilization data. The electricity consumption data includes total electricity consumption, electricity consumption in different regions, and electricity consumption at different times. The green electricity utilization data includes the amount of green electricity used, the proportion of green electricity, and information on the sources of green electricity.

[0050] Specifically, when calculating indirect carbon emissions, the first step is to distinguish between the green energy portion and the non-green energy portion of the electricity used in the project. For the green energy portion, the carbon emission level during its energy production process is relatively low, thus its corresponding carbon emission impact is small. For the non-green energy portion, calculations need to be based on the carbon emission parameters generated by the corresponding energy source. By combining electricity consumption with the utilization of green energy, more accurate results on the indirect carbon emissions of electrical energy can be obtained.

[0051] Furthermore, a second carbon emission is determined based on an indirect carbon emission model. This second carbon emission represents the indirect carbon emissions generated during the use of electrical energy in the project.

[0052] The construction of pumped storage hydroelectric projects requires the use of large quantities of engineering materials, such as cement, steel, sand, and other construction materials. The transportation of these materials from the production site to the project site generates transportation energy consumption and corresponding carbon emissions. Since these emissions do not originate directly from the operation of equipment at the project site but are generated through the engineering material supply chain process, they constitute implicit carbon emissions. An implicit carbon emission model is established based on engineering material transportation data. This data includes material type, transportation volume, transportation distance, and transportation mode.

[0053] Specifically, the correlation between transportation energy consumption and carbon emissions is established based on different material transportation processes. For example, for materials with large transportation volumes, the impact of transportation frequency and distance on carbon emissions needs to be considered; for materials with long transportation distances, the energy consumption generated by long-distance transportation needs to be considered. Through engineering material transportation data, the third carbon emission corresponding to the material transportation stage in the engineering construction process can be determined. The third carbon emission represents the implicit carbon emissions generated during the engineering material transportation process. After obtaining the direct carbon emissions, indirect carbon emissions, and implicit carbon emissions respectively, the three types of carbon emission results are comprehensively processed.

[0054] Specifically, the first category of carbon emissions corresponds to emissions from fuel-powered equipment; the second category corresponds to emissions from electrical energy consumption; and the third category corresponds to emissions from the transportation of engineering materials. By integrating these three categories of carbon emissions, the overall carbon emission results for the pumped storage project can be obtained. These results simultaneously reflect the energy usage of construction equipment, the project's electrical energy structure, and the energy consumption during material transportation. They cover the main sources of carbon emissions during the project's construction.

[0055] In one alternative implementation, the direct carbon emission model, indirect carbon emission model, and implicit carbon emission model can be dynamically selected according to the engineering stage. For example, during the construction phase, direct emissions from the operation of fuel-powered equipment account for the majority, so the focus is on acquiring energy consumption data for fuel-powered equipment; during the construction electricity consumption phase, the indirect carbon emission calculation results are adjusted based on the utilization of green electricity; and during the material transportation phase, implicit carbon emissions are calculated based on the transportation of engineering materials. By selecting the corresponding calculation model according to different engineering stages, the carbon emission calculation process can be made more consistent with the actual operating characteristics of pumped storage projects.

[0056] The direct carbon emission model determines the emissions generated by equipment operation based on the energy consumption data of fuel-powered equipment, avoiding the problem of unquantifiable energy consumption of construction machinery. The indirect carbon emission model combines electricity energy consumption data and green electricity utilization data, so that the differences in electricity sources can be reflected in the carbon emission calculation process, avoiding the problem of result deviation caused by using the same method to calculate electricity with different energy attributes. The implicit carbon emission model further considers the transportation process of engineering materials, so that the emissions generated in the engineering construction supply chain can be included in the calculation scope, improving the completeness of carbon emission statistics throughout the entire process.

[0057] By integrating the first, second, and third carbon emissions, a comprehensive carbon emission result covering construction equipment, energy supply, and engineering transportation can be generated. This enables engineering managers to obtain more comprehensive information on carbon emission status, providing a data foundation for subsequent carbon level assessment and coordinated energy and carbon regulation.

[0058] In some possible implementations, the fusion of the first carbon emissions, the second carbon emissions, and the third carbon emissions to obtain the carbon emission result for the entire project process includes: determining the weight of the first carbon emissions based on the fuel energy consumption data; determining the weight of the second carbon emissions based on the electricity energy consumption data and the green electricity utilization data; determining the weight of the third carbon emissions based on the project material transportation data; and fusing the first carbon emissions, the second carbon emissions, the third carbon emissions, and their corresponding weights to obtain the carbon emission result for the entire project process.

[0059] Specifically, the proportion of fuel-powered equipment energy consumption in the overall energy consumption is determined based on the energy consumption characteristics of different types of equipment, and the corresponding weight for the first carbon emission is determined based on this proportion. When the project is in the stage of concentrated operation of fuel-powered equipment such as earthwork excavation and transportation, the corresponding weight for the first carbon emission is increased so that the carbon emission results throughout the process can reflect the main impact of fuel-powered equipment operation; when the usage of fuel-powered equipment decreases, the corresponding weight is reduced according to the actual changes in energy consumption, thereby improving the degree of matching between the carbon emission calculation results and the project operation status.

[0060] When determining the weight of the second carbon emission level, the weight is determined based on the amount of non-green electricity used, the proportion of green electricity, and changes in electricity consumption. This ensures that changes in the electricity energy structure are reflected in the overall carbon emission calculation. Simultaneously, the weight of the third carbon emission level is determined based on engineering material transportation data. By analyzing information such as material transportation volume, distance, and mode of transportation, the impact of transportation on overall carbon emissions is determined. When the project is in the stage of concentrated material transportation, the weight of the third carbon emission level is increased; when transportation demand decreases, the weight is decreased. This ensures that carbon emission data from different sources participate in the comprehensive calculation according to their actual impact, avoiding the problem that fixed-proportion calculation methods cannot adapt to changes in the project stage. The final overall carbon emission result can simultaneously reflect the carbon emission impact of fuel-powered equipment energy consumption, electricity energy structure, and material transportation processes.

[0061] In some possible implementations, S3, the evaluation of the low-carbon level of the pumped storage project based on the carbon emission results and the preset carbon evaluation index system to obtain a carbon level evaluation result includes: determining energy utilization indicators, green electricity utilization indicators, equipment decarbonization indicators, and carbon management indicators in the preset carbon evaluation index system based on the carbon emission results; determining a comprehensive evaluation value according to the preset weights of each evaluation indicator; and determining the carbon level according to the comprehensive evaluation value.

[0062] Specifically, energy utilization indicators are used to evaluate the efficiency of energy consumption in the project, reflecting the rationality of energy use by analyzing the energy consumption and carbon emissions corresponding to a unit of project volume; green electricity utilization indicators are used to evaluate the application of green energy in the project, determining the level of green energy substitution by analyzing the relationship between green electricity usage and total energy consumption; equipment decarbonization indicators are used to evaluate the energy utilization of construction equipment, judging the low-carbon level of equipment operation through equipment energy consumption data; and carbon management indicators are used to evaluate the carbon emission management capability of the project, reflecting the level of carbon management through carbon data collection, statistics, and management.

[0063] After determining the evaluation indicators, corresponding weights are assigned to each indicator based on their impact on the project's low-carbon level. The evaluation results of each indicator are then integrated with their corresponding weights to obtain a comprehensive evaluation value. The weights of each evaluation indicator can be set according to the actual operational characteristics of the project, ensuring that the evaluation results reflect the energy consumption structure and operational characteristics of the pumped storage project. A higher comprehensive evaluation value corresponds to higher energy utilization efficiency, a higher proportion of green electricity use, a higher level of equipment low-carbonization, and stronger carbon management capabilities; conversely, a lower comprehensive evaluation value corresponds to lower values. By converting carbon emission results into graded evaluation results, project managers can more intuitively understand the current low-carbon status and take corresponding optimization measures based on the evaluation results.

[0064] In some possible implementations, S4, generating an energy-carbon coordinated regulation strategy based on the carbon level assessment results, energy supply status, and engineering operation status includes: determining target emission reduction requirements based on the carbon level assessment results; determining adjustable energy parameters based on the energy supply status; determining adjustable operating parameters based on the engineering operation status; and generating the energy-carbon coordinated regulation strategy based on the target emission reduction requirements, the adjustable energy parameters, and the adjustable operating parameters; wherein the energy-carbon coordinated regulation strategy includes adjustments to green electricity utilization, energy allocation, and engineering equipment operation.

[0065] Specifically, the low-carbon operation level of the project is determined based on the current carbon level assessment results, and the difference between the current carbon emission status and the target low-carbon requirements is analyzed. When the carbon level assessment results are lower than the preset target, the corresponding emission reduction demand is determined, and this emission reduction demand is used as the target constraint for generating the control strategy. This enables the subsequent control process to be optimized for actual carbon emission issues, rather than simply adjusting based on energy consumption.

[0066] Furthermore, the energy supply status includes information such as the supply of different energy sources, the utilization of green electricity, and the energy allocation status. Based on the currently available energy types and energy supply capacity, adjustable energy allocation parameters are determined, such as the proportion of green electricity utilization and the distribution relationship between different energy sources. When the green electricity supply capacity is high, the proportion of green energy utilization is increased; when the green energy supply is insufficient, the energy allocation method is adjusted according to the project's operational needs to ensure the stability of the project's operation.

[0067] Simultaneously, adjustable operating parameters are determined based on the project's operational status. This status includes information such as construction progress, equipment operating status, and project task arrangements. Based on current project operational needs, adjustable equipment operating parameters are determined, such as equipment operating time, equipment work schedules, and equipment energy usage methods. By linking the project's operational status with the energy adjustment process, the problem of impacting project progress due to simply reducing energy consumption can be avoided.

[0068] In some possible implementations, S5, updating the energy-carbon correlation model based on the energy consumption change data and the carbon emission change data includes: obtaining the energy consumption difference before and after implementing the energy-carbon coordinated regulation strategy; obtaining the carbon emission change trend before and after implementing the energy-carbon coordinated regulation strategy; and updating the energy-carbon correlation model parameters according to the energy consumption difference and the carbon emission change trend.

[0069] Specifically, energy consumption change data includes information on changes in energy consumption of fuel-fired equipment, changes in electricity consumption, and changes in green electricity utilization. By comparing energy consumption before and after adjustments, the impact of different energy configurations and engineering operation adjustments on energy use can be determined. For example, by analyzing changes in the electricity consumption structure after increasing the proportion of green electricity utilization, the impact of green energy substitution on overall energy consumption and carbon emission levels can be determined; similarly, by analyzing changes in equipment energy consumption after adjusting the operation mode of construction equipment, the optimization effect of equipment operation can be determined.

[0070] Furthermore, the study obtains the carbon emission change trends before and after implementing the energy-carbon coordinated regulation strategy, and analyzes the actual emission reduction effect of the regulation strategy based on the changes in carbon emissions. By analyzing the change trends of different types of carbon emissions, the degree of impact of different regulation measures on various emission sources can be determined. For example, if indirect carbon emissions decrease after energy configuration adjustment, it indicates that the energy structure optimization measures are effective; if direct carbon emissions decrease after equipment operation adjustment, it indicates that the equipment operation optimization measures have achieved the expected results.

[0071] Based on the discrepancies between actual energy consumption data and model calculations, adjustments were made to the energy consumption correlation parameters, carbon emission calculation parameters, and relationships between different emission sources in the model. This updated model aims to more accurately describe the actual operating status of the project. Simultaneously, the subsequent energy and carbon synergistic control strategy was optimized based on the model update results, enabling the control strategy to be dynamically adjusted as the project progresses.

[0072] In some possible implementations, S1, after acquiring the multi-source energy data and engineering operation data of the pumped storage project, further includes: preprocessing the multi-source energy data and engineering operation data to obtain processed data; The preprocessing includes: establishing corresponding data identifiers based on the data source; synchronizing data at different time scales; identifying and correcting abnormal data; and uniformly encoding data in different formats.

[0073] Specifically, pumped storage projects involve multiple data collection objects, such as construction machinery, electricity metering equipment, green electricity trading platforms, and material management systems. Data from different sources has different data attributes and application scenarios. Therefore, generating corresponding data identification information based on the data collection source and associating these identifications with corresponding energy data or project operation data can quickly identify the data source and data type. For example, data identification can distinguish between data collected from fuel oil equipment, electricity collection data, and project management data, ensuring that different types of data can be analyzed according to their respective processing methods.

[0074] Furthermore, time synchronization processing is performed on data from different time scales. Because different devices and systems have different data acquisition cycles—for example, some energy metering devices collect data at fixed time intervals, while project progress data may be updated daily or monthly—direct data fusion may result in inaccurate correlation between energy consumption data and project operation status. Therefore, based on a preset time benchmark, time mapping is performed on data from different acquisition cycles, enabling correlation analysis of various data at a unified time scale and improving the matching degree between data.

[0075] Simultaneously, based on historical operational data, data variation ranges, and equipment operating status, the system determines whether data anomalies exist. When anomalies are detected, corrections are made based on the trend of data changes in adjacent time periods or preset correction rules, reducing the impact of anomalies on carbon emission calculation and evaluation results. Furthermore, data in different formats undergoes unified encoding processing, converting data from different platforms and devices into a unified data format, providing a standardized data foundation for energy-carbon correlation model calculations, carbon level assessments, and the generation of control strategies.

[0076] Through the above data preprocessing process, multi-source heterogeneous data with different sources, formats, and time scales are transformed into standardized data that can be correlated and computed, thereby improving data utilization efficiency.

[0077] In some possible implementations, a multi-source data acquisition module serves as the system's data entry point, connecting downwards to various hardware terminals and external system interfaces, and upwards to perform data cleaning, format normalization, and standardized storage. For mobile construction machinery, on-site data collection is achieved using vehicle-mounted edge terminals; for fixed power consumption nodes, wired data collection is used via smart meters; and for external systems, standardized API interfaces are used for connection, uniformly outputting standardized datasets that meet greenhouse gas emission accounting requirements.

[0078] Carbon Interconnection Accounting Module: As the core computing unit of the system, it has a built-in hierarchical accounting model and dynamic coupling algorithm. It receives standardized data from the acquisition module and automatically completes real-time carbon emission accounting for the first, second, and third ranges. It outputs detailed carbon emission data and summary data by region, process, and equipment. The accounting results are synchronously pushed to the carbon level evaluation module and the collaborative control module.

[0079] The intelligent carbon rating evaluation module has a built-in evaluation index library and combined weighting algorithm for pumped storage power stations. It calls on the carbon emission data from the accounting module and the engineering progress and technology application data from the acquisition module to automatically complete the index scoring, weight calculation, total score calculation and rating determination, and output the evaluation report and emission reduction potential analysis results.

[0080] Green electricity-energy consumption-carbon emission coordinated control module: As the system decision output unit, it receives real-time carbon emission data from the accounting module and emission reduction targets from the evaluation module. Combined with electricity market prices and construction schedule plans, it generates control strategies through optimization algorithms and sends them down to the construction scheduling system, energy storage system and electricity load management system for execution.

[0081] Visualization and early warning output module: As the system interaction entry point, it is deployed on the large screen of the plant command center, the PC management backend and the mobile mini-program, integrating data dashboard, report generation, threshold early warning and work order dispatch functions; when indicators such as carbon emission intensity and green electricity ratio deviate from the set threshold, it automatically triggers graded early warning and pushes it to the corresponding management personnel.

[0082] Multi-source heterogeneous data acquisition technology is adapted to the characteristics of dispersed earthwork construction scenarios, multiple mobile devices, and heterogeneous data sources in pumped storage power stations, and achieves full coverage acquisition of energy and carbon data in all dimensions.

[0083] A dynamic coupling accounting model for energy and carbon interconnection in pumped storage projects is developed, and a hierarchical accounting model is constructed for direct emissions (fuel-fired machinery), indirect emissions (purchased non-green electricity), and other emissions (building material production and transportation, etc.).

[0084] The stratified carbon emission accounting formula covers the first scope (direct emissions), the second scope (indirect electricity emissions), and the third scope (implicit emissions from building material transportation). The accounting formulas for each part are as follows: The first scope covers direct carbon emissions from fuel-powered machinery. This applies to all fuel-powered construction machinery, categorized by equipment type. The total direct emissions are calculated using the following formula: ; in: The direct CO2 emissions (t) from fuel-powered machinery during the statistical period are denoted as i; i represents the i-th type of construction machinery. When the workbench is for the i-th type of machine (h), the data is acquired in real time by the acquisition module. The fuel consumption per unit hour (L / h) of the i-th type of machinery is dynamically corrected based on the factory-set quota and measured fuel consumption data. Carbon dioxide emissions per unit combustion of diesel fuel (kg / L). is the molecular weight conversion factor between carbon and carbon dioxide.

[0085] The second scope includes indirect carbon emissions from purchased electricity, which are calculated separately for green and non-green electricity. The formula for calculating the total indirect emissions is as follows: ; in: The indirect CO2 emissions (t) of purchased electricity during the statistical period; The total construction electricity consumption (kWh) during the statistical period is collected by smart meters; The amount of green electricity consumed during the statistical period (kWh); The average carbon emission factor (tCO2 / kWh) for the Northwest regional power grid is based on the annual value released by the Ministry of Ecology and Environment. It is a carbon emission factor for green electricity.

[0086] The third area concerns the carbon emissions inherent in the transportation of building materials. For emissions from the transportation of bulk building materials, the calculation formula is as follows: ; in: The CO2 emissions (t) from building material transportation during the statistical period; j represents the j-th type of building material (cement, steel, sand, gravel, etc.). Let be the transport volume (t) of the j-th type of building materials; Let be the average transportation distance (km) for the j-th type of building materials; The carbon emission factor per unit turnover of the corresponding transport vehicle type (tCO2 / (t km).

[0087] The carbon rating system for pumped storage power stations is constructed, establishing multi-dimensional evaluation indicators for energy carbon emissions, low-carbon technology applications, equipment decarbonization, green electricity utilization, and carbon management and operation. These indicators include core parameters such as the proportion of green electricity, carbon emission intensity per unit of earthwork, fuel substitution rate, and emission reduction. The system is divided into four evaluation levels: zero carbon, near-zero carbon, low carbon, and those requiring improvement. The system is embedded to achieve automatic scoring and level determination. It can dynamically adapt to regional wind and solar resources and green electricity policies, and output carbon assessment reports and emission reduction potential lists.

[0088] Weight determination: A combined weighting method using the Analytic Hierarchy Process (AHP) and entropy weighting is adopted. Subjective weights are combined with the experience of industry experts, while objective weights are calculated based on actual project measurement data. The final index weights are obtained by weighting and integrating the two methods to avoid the bias of single weighting.

[0089] Scoring Calculation: A 100-point system is used. The score for each indicator is calculated as the ratio of the actual value to the target value. If the actual value exceeds the target value, the full score is given. The total score is the weighted sum of the scores of each indicator multiplied by their corresponding weights.

[0090] Grading: A four-level evaluation standard is set: 90 points and above is "zero carbon construction site / park", 80-89 points is "near zero carbon construction site / park", 70-79 points is "low carbon construction site / park", and below 70 points is "needs improvement".

[0091] Dynamic Adaptation: The system has a built-in database of regional policies and wind and solar resource parameters, which can dynamically adjust the weight of indicators and scoring benchmarks according to local low-carbon policies and green electricity trading rules, and output formal carbon assessment reports and multi-dimensional emission reduction potential lists.

[0092] Intelligent coordinated regulation strategy for green electricity, energy consumption, and carbon emissions: The green electricity procurement optimization strategy constructs a multi-objective optimization model for green electricity procurement, targeting the electricity demand during the construction period, to achieve a balance between maximizing the proportion of green electricity and the economic efficiency of electricity purchase: Optimization algorithm: Mixed Integer Linear Programming (MILP).

[0093] The objective function aims to maximize the proportion of green electricity over the entire lifecycle and minimize the total electricity purchase cost, achieving a multi-objective trade-off through weighting coefficients.

[0094] Objective 1: Introduce a weighting factor for the proportion of green electricity. : ; Objective 2, Total Electricity Purchase Cost : ; in: The amount of green electricity purchased during period t. The price of green electricity during time period t. The amount of non-green electricity procured by the power grid during time period t. The price of non-green electricity during time period t.

[0095] Constraints include: monthly / daily electricity demand constraints, upper limit constraints for green electricity trading in the electricity market, power supply reliability constraints, and green electricity traceability compliance constraints.

[0096] Construction sequence and machinery operation optimization strategies, linking earthwork construction plans with wind and solar power output patterns, maximize the local consumption of green electricity and minimize fuel consumption by optimizing operation sequences, thereby minimizing daily carbon emissions. Objective function: ; Regulation logic: Obtain the output forecast curves of distributed photovoltaic and surrounding wind and solar power plants for the next day to identify periods of surplus green electricity; High-energy-consuming construction procedures will be prioritized during peak green energy output periods to reduce the proportion of non-green energy consumption. Optimize the scheduling and operation routes of fuel-powered machinery to reduce idle time and reduce fuel consumption per unit of earthwork; plan routes for transportation to shorten one-way transportation distances.

[0097] The implementation method involves generating an optimized construction scheduling plan for the next day every day, tracking the execution effect in real time, and dynamically adjusting the optimization parameters.

[0098] A two-stage energy and carbon control strategy for construction and operation, combined with the energy storage regulation characteristics of pumped storage power stations, achieves integrated energy and carbon management throughout the entire lifecycle: During the construction period, a construction microgrid will be built based on the distributed photovoltaic system and supporting energy storage system in the factory area to prioritize the consumption of self-generated green electricity; excess green electricity will be stored in the energy storage system and released during peak electricity consumption periods to reduce the proportion of purchased non-green electricity.

[0099] During the operation period, the pumped storage unit pumping power generation operation plan is coordinated with the characteristics of the plant's own electricity load to optimize the pumping time of the pumped storage unit. Priority is given to pumping and storing water during periods of surplus green electricity, and generating electricity for the plant's own use during peak electricity consumption periods, so as to maximize the proportion of green electricity in the plant's own electricity consumption.

[0100] Outputs and applications, including: It can automatically generate daily, weekly, and monthly carbon emission reports, quarterly carbon level assessment reports, and special emission reduction optimization plans; it supports large-screen visualization in the command center, with core indicators including real-time total carbon emissions, green electricity ratio, carbon emission intensity per unit of earthwork, and carbon emission ranking of each work area.

[0101] A three-tiered early warning mechanism is set up. A yellow warning is triggered when the hourly carbon emission intensity exceeds the threshold by 10%, an orange warning is triggered when it exceeds 20%, and a red warning is triggered when it affects the overall emission reduction target. The warning information is automatically pushed to the corresponding responsible person.

[0102] Figure 2 This is a schematic diagram of the energy-carbon synergistic management system for pumped storage projects provided in an embodiment of this disclosure. Figure 2 As shown, this disclosure also provides an energy-carbon co-management system for pumped storage projects, including: an acquisition module 201, used to acquire multi-source energy data and project operation data of the pumped storage project, wherein the multi-source energy data includes fuel energy consumption data, electrical energy consumption data, and green electricity utilization data, and the project operation data includes construction progress data and project material transportation data; an establishment module 202, used to establish an energy-carbon correlation model based on the multi-source energy data and the project operation data, and determine the carbon emission results through the energy-carbon correlation model; and an evaluation module 203, used to evaluate the carbon emission results. The system includes a preset carbon assessment index system to evaluate the low-carbon level of pumped storage projects and obtain carbon level assessment results; a control module 204 is used to generate an energy-carbon coordinated control strategy based on the carbon level assessment results, energy supply status, and project operation status, and adjust energy configuration parameters and project operation parameters based on the energy-carbon coordinated control strategy; an update module 205 is used to acquire energy consumption change data and carbon emission change data after implementing the energy-carbon coordinated control strategy, and update the energy-carbon correlation model and the energy-carbon coordinated control strategy based on the energy consumption change data and the carbon emission change data.

[0103] In some possible implementations, module 202 includes: the energy-carbon correlation model includes a direct carbon emission model, an indirect carbon emission model, and a latent carbon emission model; a first submodule for determining the direct carbon emission model based on fuel energy consumption data and determining the first carbon emission amount generated by direct energy consumption based on the carbon emission model; a second submodule for determining the indirect carbon emission model based on electricity energy consumption data and green electricity utilization data and determining the second carbon emission amount generated by electricity energy consumption based on the indirect carbon emission model; a third submodule for determining the latent carbon emission model based on engineering material transportation data and determining the third carbon emission amount generated by engineering material transportation based on the latent carbon emission model; and a fourth submodule for fusing the first, second, and third carbon emissions to obtain the carbon emission results for the entire engineering process.

[0104] In some possible implementations, the fourth sub-module is specifically used for: determining the weight of the first carbon emission based on the fuel energy consumption data; determining the weight of the second carbon emission based on the electricity energy consumption data and the green electricity utilization data; determining the weight of the third carbon emission based on the engineering material transportation data; and fusing the first carbon emission, the second carbon emission, the third carbon emission, and the corresponding weights to obtain the carbon emission result for the entire engineering process.

[0105] In some possible implementations, the evaluation module 203 is specifically used to: determine the energy utilization index, green electricity utilization index, equipment decarbonization index, and carbon management index in the preset carbon evaluation index system based on the carbon emission results; determine the comprehensive evaluation value according to the preset weight of each evaluation index; and determine the carbon level according to the comprehensive evaluation value.

[0106] In some possible implementations, the control module 204 is specifically used to: determine the target emission reduction demand based on the carbon level assessment results; determine adjustable energy parameters based on the energy supply status; determine adjustable operating parameters based on the engineering operation status; and generate the energy-carbon coordinated control strategy based on the target emission reduction demand, the adjustable energy parameters, and the adjustable operating parameters; wherein the energy-carbon coordinated control strategy includes adjustments to green electricity utilization, energy configuration, and engineering equipment operation.

[0107] In some possible implementations, the update module 205 is specifically used to: obtain the energy consumption difference before and after implementing the energy-carbon synergistic regulation strategy; obtain the carbon emission change trend before and after implementing the energy-carbon synergistic regulation strategy; and update the energy-carbon correlation model parameters based on the energy consumption difference and the carbon emission change trend.

[0108] In some possible implementations, a processing module (not shown in the figure) is also included, specifically for: preprocessing the multi-source energy data and engineering operation data to obtain processed data; The preprocessing includes: establishing corresponding data identifiers based on the data source; synchronizing data at different time scales; identifying and correcting abnormal data; and uniformly encoding data in different formats.

[0109] This disclosure also provides a computer device, including a memory and a processor, wherein the memory stores computer-readable instructions, and the processor executes the computer-readable instructions to implement the steps of the pumped storage project energy and carbon synergistic management method.

[0110] The computer device includes a memory, a processor, and a network interface that are interconnected via a system bus. It should be noted that not all of the shown components are required; more or fewer components may be implemented instead. Those skilled in the art will understand that the computer device described herein is a device capable of automatically performing numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes, but is not limited to, microprocessors, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0111] The computer device can be a desktop computer, laptop, handheld computer, or cloud server, etc. The computer device can interact with the user via a keyboard, mouse, remote control, touchpad, or voice control.

[0112] The memory includes at least one type of readable storage medium, including flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, disk, optical disk, etc. In some embodiments, the memory may be an internal storage unit of the computer device, such as the hard disk or memory of the computer device. In other embodiments, the memory may also be an external storage device of the computer device, such as a plug-in hard disk, smart media card (SMC), secure digital card (SD), flash card, etc. Of course, the memory may include both internal storage units and external storage devices of the computer device. In this embodiment, the memory is typically used to store the operating system and various application software installed on the computer device, such as program code for real-time data processing methods. Furthermore, the memory can also be used to temporarily store various types of data that have been output or will be output.

[0113] In some embodiments, the processor may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chip. The processor is typically used to control the overall operation of the computer device. In this embodiment, the processor is used to run program code stored in the memory or process data, for example, to run the program code of the method.

[0114] The network interface may include a wireless network interface or a wired network interface, which is typically used to establish communication connections between the computer device and other electronic devices.

[0115] This disclosure also provides a computer-readable storage medium storing computer-readable instructions, which, when executed by a processor, implement the steps of a pumped storage engineering energy and carbon co-management method.

[0116] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0117] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0118] The above description is merely a specific embodiment of this disclosure, enabling those skilled in the art to understand or implement it. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this disclosure. Therefore, this disclosure is not to be limited to the embodiments described herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for coordinated energy and carbon management in pumped storage projects, characterized in that, include: Acquire multi-source energy data and engineering operation data of pumped storage projects. The multi-source energy data includes fuel energy consumption data, electrical energy consumption data, and green electricity utilization data. The engineering operation data includes construction progress data and engineering material transportation data. Based on the multi-source energy data and the engineering operation data, an energy-carbon correlation model is established, and the carbon emission results are determined through the energy-carbon correlation model. Based on the carbon emission results and the preset carbon evaluation index system, the low-carbon level of the pumped storage project is evaluated to obtain the carbon level evaluation result. Based on the carbon level assessment results, energy supply status, and engineering operation status, an energy-carbon synergistic regulation strategy is generated, and energy configuration parameters and engineering operation parameters are adjusted based on the energy-carbon synergistic regulation strategy. Obtain energy consumption change data and carbon emission change data after implementing the energy-carbon coordinated regulation strategy, and update the energy-carbon correlation model and the energy-carbon coordinated regulation strategy based on the energy consumption change data and the carbon emission change data.

2. The energy and carbon synergy management method for pumped storage projects according to claim 1, characterized in that, The step of establishing an energy-carbon correlation model based on the multi-source energy data and the engineering operation data, and determining carbon emission results through the energy-carbon correlation model, includes: The energy-carbon correlation model includes a direct carbon emission model, an indirect carbon emission model, and a hidden carbon emission model. The direct carbon emission model is determined based on the energy consumption data of fuel-powered equipment, and the first carbon emission generated by direct energy consumption is determined based on the carbon emission model. The indirect carbon emission model is determined based on electricity energy consumption data and green electricity utilization data, and the second carbon emission generated by electricity energy consumption is determined based on the indirect carbon emission model. The implicit carbon emission model is determined based on engineering material transportation data, and the third carbon emission generated by engineering material transportation is determined based on the implicit carbon emission model. The first carbon emission, the second carbon emission, and the third carbon emission are combined to obtain the carbon emission results for the entire project process.

3. The energy and carbon synergy management method for pumped storage projects according to claim 2, characterized in that, The process of integrating the first carbon emission, the second carbon emission, and the third carbon emission to obtain the carbon emission results for the entire project includes: The weight of the first carbon emission is determined based on the energy consumption data of the fuel-powered equipment. The weight of the second carbon emission is determined based on the electrical energy consumption data and the green electricity utilization data. The weight of the third carbon emission is determined based on the engineering material transportation data. The carbon emission results for the entire project process are obtained by fusing the first carbon emission, the second carbon emission, the third carbon emission, and their corresponding weights.

4. The energy and carbon synergy management method for pumped storage projects according to claim 1, characterized in that, The evaluation of the low-carbon level of pumped storage projects based on the carbon emission results and a preset carbon assessment index system, to obtain carbon level assessment results, includes: Based on the carbon emission results, energy utilization indicators, green electricity utilization indicators, equipment decarbonization indicators, and carbon management indicators are determined in the preset carbon assessment indicator system. The comprehensive evaluation value is determined based on the preset weights of each evaluation indicator, and the carbon grade is determined based on the comprehensive evaluation value.

5. The energy and carbon synergistic management method for pumped storage projects according to claim 1, characterized in that, The generation of an energy-carbon synergistic regulation strategy based on the carbon level assessment results, energy supply status, and engineering operation status includes: The target emission reduction requirements are determined based on the carbon level assessment results. Adjustable energy parameters are determined based on the energy supply status; Adjustable operating parameters are determined based on the project's operating status; Based on the target emission reduction requirements, the adjustable energy parameters, and the adjustable operating parameters, the energy-carbon synergistic regulation strategy is generated. The energy-carbon coordinated regulation strategy includes adjustments to green electricity utilization, energy allocation, and engineering equipment operation.

6. The energy and carbon synergy management method for pumped storage projects according to claim 1, characterized in that, Updating the energy-carbon correlation model based on the energy consumption change data and the carbon emission change data includes: Obtain the energy consumption difference before and after implementing the energy-carbon synergistic regulation strategy; Obtain the carbon emission change trend before and after implementing the energy-carbon synergistic regulation strategy; The parameters of the energy-carbon correlation model are updated based on the differences in energy consumption and the trends in carbon emission changes.

7. The method for coordinated energy and carbon management of pumped storage projects according to any one of claims 1 to 6, characterized in that, After acquiring the multi-source energy data and engineering operation data of the pumped storage project, the following is also included: The multi-source energy data and engineering operation data are preprocessed to obtain processed data; The preprocessing includes: Establish corresponding data identifiers based on the data source; Synchronize data at different time scales; Identify and correct abnormal data; Unified encoding is applied to data in different formats.

8. A pumped storage power plant energy and carbon co-management system, characterized in that, include: The acquisition module is used to acquire multi-source energy data and project operation data of the pumped storage project. The multi-source energy data includes fuel energy consumption data, electric energy consumption data and green electricity utilization data. The project operation data includes construction progress data and project material transportation data. A module is established to build an energy-carbon correlation model based on the multi-source energy data and the engineering operation data, and to determine the carbon emission results through the energy-carbon correlation model. The evaluation module is used to evaluate the low-carbon level of pumped storage projects based on the carbon emission results and a preset carbon evaluation index system, and obtain carbon level evaluation results. The control module is used to generate an energy-carbon coordinated control strategy based on the carbon level evaluation results, energy supply status, and engineering operation status, and to adjust energy configuration parameters and engineering operation parameters based on the energy-carbon coordinated control strategy. The update module is used to acquire energy consumption change data and carbon emission change data after the energy-carbon coordinated regulation strategy is implemented, and to update the energy-carbon correlation model and the energy-carbon coordinated regulation strategy based on the energy consumption change data and the carbon emission change data.

9. A computer device, characterized in that, The system includes a memory and a processor, wherein the memory stores computer-readable instructions, and the processor executes the computer-readable instructions to implement the steps of the pumped storage engineering energy and carbon synergistic management method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-readable instructions, which, when executed by a processor, implement the steps of the pumped storage engineering energy and carbon synergistic management method as described in any one of claims 1 to 7.

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