Physical-transaction coupled park carbon asset multi-dimensional value evaluation method and system, and storage medium

Abstract

The invention belongs to the field of carbon asset management and energy system decision evaluation, and particularly relates to a physics-transaction coupled park carbon asset multi-dimensional value evaluation method and system and a storage medium, and the method comprises the following steps: S1, data access and aperture unification: collecting data of four dimensions of physical operation, carbon accounting, market transaction, and user and service, performing unification processing on time granularity, measurement units, accounting and space boundaries, and completing data quality treatment; according to the method, through multi-source data fusion and physical-transaction coupling modeling, a real object option theory is utilized, the park carbon assets are converted from a fuzzy compliance cost item to an active management asset with clear value, clear strategy and controllable risk, and the risk of the park carbon assets is improved. And finally, value maximization and risk minimization of carbon assets are realized by an enterprise in a carbon neutralization background.

Description

Technical Field

[0001] This invention relates to the field of carbon asset management and energy system decision-making and evaluation technology, and in particular to a physical-trading coupled method, system and storage medium for multi-dimensional value assessment of carbon assets in industrial parks. Background Technology

[0002] Existing carbon asset assessments in industrial parks are mostly conducted using single dimensions or loosely parallel indicators. Common practices either focus on static calculations of carbon accounting standards and allowance balances, or rely solely on market prices and discounted cash flows for economic evaluation. These approaches lack a unified characterization of physical operational boundaries (uncertainty in renewable energy output, energy storage capacity / energy and lifespan, load and equipment capacity constraints, etc.) and trading mechanisms (allowances / green certificates / voluntary emission reductions, compliance and price boundaries, contract terms). The difficulty in aligning different data standards and the lack of inherent constraints between indicators lead to valuation results that are disconnected from actual feasibility, compliance, and user-side needs, easily resulting in overestimation or underestimation.

[0003] Therefore, a physical-trading coupled multidimensional valuation method, system, and storage medium for carbon assets in industrial parks are needed to address the aforementioned issues. Summary of the Invention

[0004] This invention proposes a physical-trading coupled multidimensional valuation method for industrial park carbon assets. It focuses on establishing a multi-dimensional, unified, and consistent evaluation indicator system. Within a single framework, it collaboratively characterizes four categories of indicators: "physical operation—carbon accounting—market economy—user demand," and ensures traceability and enforceability through standardized definitions and constraint linkages. Based on this, it provides an evaluation method that matches the indicator system, mapping the feasible domain formed by physical and institutional boundaries to the carbon asset state space. Combining real options concepts, it generates two types of valuation outputs: benchmark and conservative values. This effectively avoids deviations from engineering and trading constraints, improving the accuracy and decision-making applicability of industrial park carbon asset valuation.

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

[0006] A physical-trading coupled multidimensional valuation method, system, and storage medium for carbon assets in industrial parks, comprising the following steps:

[0007] Step S1, Data Access and Standardization: Collect data from four dimensions: physical operation, carbon accounting, market transactions, and users and services. Perform consistency processing on time granularity, measurement units, accounting and spatial boundaries, and complete data quality governance.

[0008] Step S2, Construction of a multi-dimensional evaluation index system: Based on the unified data in S1, establish a four-dimensional index library covering physical operation dimension, carbon accounting dimension, market economy dimension, and user and service dimension. Standardize the indicators and set weights, and define corresponding hard constraints or soft constraints and their feasible value ranges for each indicator.

[0009] Step S3, Physical-Institutional Feasible Domain Construction: Map the indicators and constraints in S2 to time-specific feasible domains, generate the state-decision-emission / emission reduction mapping interface, and verify the feasible domains;

[0010] Step S4, Value Element Decomposition and Cost Allocation: Define the cash flow composition related to carbon assets and couple equipment economics into cost calculation to form a periodic cash flow template and parameter table;

[0011] Step S5, Scenario Matrix Generation and Parameter Definition: Construct the scenario set and uncertainty set of key variables, set unified parameters for benchmark and conservative estimates, and perform robustness processing.

[0012] Step S6, Real Option Evaluation Based on Feasible Region: Establish a state-dependent option tree or option lattice on the feasible region constructed in S3, and calculate the option value and optimal strategy of each node by backtracking through each period.

[0013] Step S7, Valuation Calculation and Result Integration: Calculate the benchmark value and the conservative value, summarize the optimal exercise path, contract portfolio suggestions and key boundary hits, and generate a sensitivity spectrum of indicator-valuation linkage.

[0014] Step S8, Results Release and Dual Ledger Alignment: Generate an integrated report containing valuation results, strategies, sensitivity and constraint hits, and reconcile it with the carbon accounting ledger and the transaction clearing ledger to achieve traceability and auditability.

[0015] Preferably, in step S1, the physical operation data includes renewable / conventional unit output, load curve, energy storage power / energy / SoH, network and equipment capacity, start-up, shutdown and maintenance cycle time;

[0016] The carbon accounting data includes activity data, emission factors, accounting boundaries, baselines, or intensity-based parameters.

[0017] The market transaction data includes quota / green certificate / voluntary emission reduction positions and prices, spot / forward / option contracts, compliance rules and price limits, and clearance windows;

[0018] The user and service data includes demand response elasticity, service level constraints, production stoppage and restriction costs, and default clauses.

[0019] Preferably, in step S2, the four-dimensional index library includes:

[0020] Physical operation and maintenance indicators: output boundary, energy storage power / energy / lifetime, network and equipment capacity, start-up / shutdown / maintenance cycle time;

[0021] Carbon accounting indicators: component emissions, baseline / intensity caliber, marginal emission reduction curve, accounting uncertainty;

[0022] Market economy indicators: price, position, contract elements, performance and price boundaries, risk measurement methods;

[0023] User and service metrics: resilience parameters, service level agreement (SLA), costs of production stoppages / limitations, and compensation / default mechanisms.

[0024] The formula for the indicators and standardization is as follows:

[0025]

[0026] Where W = diag(w) j ) is a joint weight matrix of "constraint tightness + valuation sensitivity".

[0027] The formulas for carbon accounting and emission reduction are as follows:

[0028]

[0029] Preferably, in step S2, the indicator weights are set based on a comprehensive criterion of "constraint tightness + valuation sensitivity", and traceability information is saved for each indicator.

[0030] Preferably, in step S3, the feasible domain includes energy balance constraints, energy storage energy and lifetime constraints, network and equipment capacity constraints, and institutional and contractual boundary constraints.

[0031] The state-decision-emission / reduction mapping interface takes as input comprehensive indicator state and feasible decision, and outputs as real-time calculation results of emission, emission reduction and cash flow factors.

[0032] The feasible region constraint formula is as follows:

[0033] Energy balance:

[0034] Energy storage:

[0035] Capacity / Network:

[0036] System / Contract: A t +G t +C t +ΔE t ≥0,

[0037] The formula for decomposing cash flow and costs is as follows:

[0038]

[0039] CycleCost t =λ s ·ECL t This refers to the equivalent cycle life cost of energy storage.

[0040] Preferably, in step S5, a multi-scenario set and its probability or uncertainty set are constructed, including wind and solar power output, energy and carbon market prices, load and policy parameters; the valuation parameter caliber is set, including the expected discount parameter for benchmark valuation and the risk measurement parameter for conservative valuation; and the key variables are robustened by setting their upper and lower bounds, correlation structures and extreme cases to support stress testing.

[0041] Preferably, in step S5, the scenario set includes a set of scenarios and probabilities or uncertainties related to wind and solar power output, price, load, and policy parameters;

[0042] The conservative valuation uses a risk measure or robust approach, including Conditional Value at Risk (CVaR), where the valuation method is as follows:

[0043] Preferably, in step S6, the rights included in the option tree or option grid include holding, expansion, trading, hedging, and substitution;

[0044] All exercise and transfer are only permitted to occur within the feasible domain defined by S3.

[0045] A physical-trading coupled multidimensional value assessment system for industrial park carbon assets, characterized by comprising:

[0046] A data and caliber unification module is used to perform step S1 as described in claim 1;

[0047] An indicator system construction module is used to perform step S2 as described in claim 1;

[0048] The feasible domain construction module is used to perform step S3 as described in claim 1;

[0049] A value element and option evaluation module is used to perform steps S4 and S6 as described in claim 1;

[0050] The scenario and valuation module is used to perform steps S5 and S7 as described in claim 1;

[0051] The results publishing and ledger alignment module is used to perform step S8 as described in claim 1.

[0052] A storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described method.

[0053] Compared with the prior art, the beneficial effects of the present invention are:

[0054] 1. Integrated Construction and Alignment of Multidimensional Assessment Indicator System: Under the same data caliber, the relevant information of carbon assets in the park is systematically divided into four categories of indicators: physical operation dimension, carbon accounting dimension, market economy dimension, and user and service dimension. A master-slave relationship and constraint mapping are established, clarifying the hard or soft constraint attributes and feasible value range of each indicator. Through unified scaling, weight setting, and traceability recording, the inherent constraint correlation and traceable auditability between indicators are realized, forming a structured indicator library that can directly drive the generation of feasible domains, scenario analysis, and valuation linkage, solving the problems of inconsistent data caliber, fragmented indicators, and disconnect from actual feasibility in existing assessments.

[0055] 2. Real Option Valuation Method Based on Feasible Region Mapping: Within a time-varying feasible region defined by multidimensional indicators and constraints, a state-dependent real option valuation framework is constructed. Holding, expansion, trading, hedging, and substitution strategies are considered as exercise options, with institutional and contractual boundaries serving as exercise constraints. Benchmark and conservative valuations are performed using a scenario matrix, outputting the optimal strategy path and value sensitivity. This method avoids overestimation or underestimation detached from engineering and performance conditions, ensuring the valuation results are accurate while maintaining feasibility and compliance. Attached Figure Description

[0056] Figure 1 This is a flowchart of a physical-trading coupled multidimensional value assessment method for carbon assets in industrial parks, as proposed in this invention. Detailed Implementation

[0057] The technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0058] Reference Figure 1 A multi-dimensional valuation method for carbon assets in industrial parks that combines physical and trading elements includes the following steps:

[0059] Step S1: Data Access and Standardization

[0060] This step forms the data foundation for all subsequent analyses. In practice:

[0061] Data Acquisition: Data is collected from heterogeneous data sources within the park, including its energy management system, carbon accounting platform, electricity trading platform, and user service management system, and is categorized into four main types:

[0062] Physical operation data: Specifically, this includes real-time and historical output data of renewable units such as photovoltaic and wind power, and conventional units such as gas turbines; electricity, heat, and cooling load curves within the park; charging and discharging power, available energy, and health status of energy storage systems such as batteries; capacity limits of networks such as power grids and gas pipelines, as well as key equipment; and the number of start-ups and shutdowns, duration, and maintenance plans of major equipment.

[0063] Carbon accounting data includes activity data such as fuel consumption and purchased electricity; emission factors for various energy sources; accounting boundaries at the organizational and facility levels; and historical data or intensity targets used to calculate baseline emissions.

[0064] Market transaction data includes: the quantity and market price of carbon allowances, green certificates, and nationally certified voluntary emission reductions; details of spot, forward, and option contracts; government-mandated compliance rules, price ceilings / floors; and the time window for allowance clearance.

[0065] User and service data: Specifically, this includes the price elasticity of user participation in demand response; binding clauses in service level agreements signed with key users; direct and indirect economic losses caused by production stoppages or restrictions; and breach of contract compensation clauses in various contracts.

[0066] Standardization and Governance: Standardize all the above data to the same time granularity (e.g., 15 minutes, 1 hour) and ensure consistency in units of measurement. Clearly define the system boundaries between carbon accounting and physical operations to ensure they are aligned. Clean the data, fill in missing values, and remove outliers to ensure data quality meets modeling requirements.

[0067] Step S2: Construction of a multi-dimensional evaluation index system

[0068] Based on the unified data of S1, a structured indicator evaluation system is constructed.

[0069] Establish a four-dimensional indicator library:

[0070] Physical operation and maintenance indicators: such as the unit's maximum / minimum technical output, energy storage rated power and capacity, equipment remaining life, network transmission limits, minimum start-up and shutdown time, etc.

[0071] Carbon accounting indicators include: range 1, 2, and 3 emissions, baseline emission intensity, marginal emission reduction cost curve, and the range of uncertainty in the accounting results.

[0072] Market economy indicators include: price volatility of various assets, VaR of open positions, strike price and expiration date of contracts, and market-regulated price limits.

[0073] User and service maintenance indicators include: load price elasticity coefficient, minimum service guarantee level agreed upon in the SLA, unit downtime cost, and formula for calculating penalty for breach of contract.

[0074] Setting Constraints and Weights: Define the constraint nature ("hard constraints," such as physical capacity limits, which cannot be violated; and "soft constraints," such as optimization objectives, which can have some relaxation) and their feasible numerical range for each indicator. The setting of indicator weights adopts a comprehensive criterion: on the one hand, considering the "constraint tightness," i.e., the frequency and severity of the constraint being triggered in historical operations; on the other hand, considering the "valuation sensitivity," i.e., the degree of impact of small changes in the indicator on the final valuation result. Simultaneously, record the data source and calculation logic for each indicator to ensure traceability.

[0075] The formula for the indicators and standardization is as follows:

[0076]

[0077] Where W = diag(w) j ) is a joint weight matrix of "constraint tightness + valuation sensitivity".

[0078] The formulas for carbon accounting and emission reduction are as follows:

[0079]

[0080] Step S3: Construction of the Physical-Institutional Feasibility Domain

[0081] This step is crucial for transforming static indicators into dynamic operating boundaries.

[0082] Mapping to Feasible Region: The various indicators and constraints in S2 are transformed into a mathematically feasible region according to a time series (e.g., 96 time points / day). This feasible region defines the set of all possible operating states of the park at any given time. Typical constraints include:

[0083] Energy balance constraints (power generation + power purchase + power discharge = load + power sales + charging).

[0084] Constraints on energy conservation, charging and discharging power, and lifetime decay models for energy storage systems.

[0085] Upper limits on power grid flow and equipment capacity.

[0086] Institutional boundaries are constrained by market rules and contractual terms.

[0087] Construct a mapping interface: Develop a computing interface whose inputs are the current system state (such as load, wind and solar power output) and alternative decisions (such as unit start-up and shutdown, energy storage charging and discharging, market transactions), and whose outputs are the carbon emissions / emission reductions generated under the decision, as well as the corresponding cash flow changes (such as fuel costs, electricity revenue, carbon trading expenditures).

[0088] The feasible region constraint formula is as follows:

[0089] Energy balance:

[0090] Energy storage:

[0091] Capacity / Network:

[0092] System / Contract: A t +G t +C t +ΔE t ≥0,

[0093] The formula for decomposing cash flow and costs is as follows:

[0094]

[0095] CycleCost t =λ s ·ECL t Cost of equivalent cycle life for energy storage.

[0096] Step S4: Value element decomposition and cost aggregation

[0097] This step aims to accurately quantify the cash flows associated with carbon assets.

[0098] Define the composition of cash flow: comprehensively identify cash inflows and outflows, including:

[0099] Revenue from the sale of carbon allowances, green certificates, CCERs, etc.

[0100] The cost of purchasing the aforementioned assets.

[0101] The profit from the difference between buying and selling electricity in the electricity market.

[0102] Penalties / penalties paid for violating SLAs or market rules.

[0103] Compensation received for providing services such as demand response.

[0104] Economic efficiency of coupled equipment: In cost calculation, not only direct costs are considered, but also the economic impact of the dynamic characteristics of the equipment are taken into account. For example, for energy storage assets, each charge-discharge cycle is converted into an equivalent cycle cost, and the investment recovery pressure caused by the depreciation of lifespan is taken into account; for the production side, the profit loss caused by production stoppages and restrictions is included in the cost.

[0105] Step S5: Scenario Matrix Generation and Parameter Specification

[0106] To address future uncertainties, we conduct multi-scenario analysis.

[0107] Constructing a scenario set: Based on historical data and expert judgment, generate future scenarios for key uncertain variables, such as fluctuations in wind and solar power output, trends in carbon and electricity prices, load changes, and policy adjustments (such as changes in quota allocation methods). Each scenario can be assigned a probability of occurrence or described using an uncertain set (such as a range).

[0108] Set valuation parameters: Set benchmark valuation parameters such as the risk-free rate used to discount cash flows. For conservative valuations, use risk-adjusted parameters or risk measurement tools such as conditional value at risk to reflect potential losses under adverse scenarios.

[0109] The valuation method is as follows:

[0110] Step S6: Real Options Evaluation Based on Feasible Region

[0111] This is the core of value assessment: identifying and quantifying the value brought by management flexibility.

[0112] Establish the option structure: Construct an option tree or option grid along the time axis on the feasible region constructed by S3. Each node represents a specific system state (such as energy storage capacity, quota position, contract position).

[0113] Defining Rights and Backtracking Calculation: At each node, the park possesses multiple "rights" (real options), such as: continuing to hold assets, expanding energy storage, trading quotas, hedging using market contracts, and replacing traditional electricity with green electricity. By backtracking calculations from the end of the valuation period to the beginning, the optimal decision for each node (which right to exercise) and the option value of that node under that decision are dynamically planned. Crucially, all decisions must be within the physically-institutionally feasible domain defined by S3 to ensure the strategy's executability.

[0114] Step S7: Valuation Calculation and Result Integration

[0115] Calculate the final value: By taking into account all scenarios and paths, calculate the value range of carbon assets under baseline and conservative parameters.

[0116] Generate decision support information: The output is not only the valuation figure, but also the optimal exercise path to realize that value (i.e. a series of operation strategies), the recommended contract combination, and the analysis of which key constraints are triggered during the optimization process (boundary hit situation).

[0117] Sensitivity analysis: Generate sensitivity spectrum to visually demonstrate the impact of changes in different assessment indicators (such as carbon price and wind and solar forecast accuracy) on the final valuation.

[0118] Step S8: Results Publication and Dual Ledger Alignment

[0119] Ensure the valuation process is transparent, traceable, and auditable.

[0120] Generate an integrated report: The report includes the final valuation, recommendation strategy, sensitivity analysis results, and details of constraint hits.

[0121] Perform dual-ledger alignment: Reconcile the trading and emissions data in the valuation model with the official carbon accounting ledger (for compliance) and the trading clearing ledger (for financial settlement). Any discrepancies need to be documented and explained to achieve closed-loop management from financial valuation to physical and financial facts.

[0122] A physical-trading coupled multi-dimensional valuation system for industrial park carbon assets, which can be deployed on a server or cloud computing platform, includes the following logical modules that work together to execute the methods described above:

[0123] Data and Standard Unification Module: Responsible for connecting to the data source and executing step S1.

[0124] Indicator system construction module: responsible for managing the indicator library, constraints and weights, and executing step S2.

[0125] The feasible region construction module is responsible for mathematical modeling, generating time-varying feasible regions and mapping interfaces, and executing step S3.

[0126] Value Elements and Option Evaluation Module: Responsible for cash flow modeling and real option calculation, executing steps S4 and S6.

[0127] Scenario and Valuation Module: Responsible for managing scenario sets, performing valuation calculations and result integration, and executing steps S5 and S7.

[0128] The Results Publishing and Ledger Alignment Module is responsible for report generation and verification with external ledger systems, executing step S8.

[0129] A non-volatile computer-readable storage medium (such as an SSD, server hard drive array, or cloud storage) stores a computer program (such as software code or an executable file). When the program is loaded and executed by a processor (such as a server CPU), it can control the computer system to fully implement the above-described method flow.

[0130] For the same industrial park, valuations were performed using both traditional methods and the method of this invention, and the results are shown in the table below:

[0131]

[0132]

[0133] Value sensitivity spectrum (Example of output S7 of this invention)

[0134] By perturbing the key parameters by ±20%, their impact on the final valuation is obtained, as shown in the following figure (simulation):

[0135] +---------------------------+

[0136] Sensitivity analysis (impact on benchmark value)

[0137] +------------+--------------+

[0138] |Indicator|Amplitude of Impact|

[0139] +------------+--------------+

[0140] |Quota Price|+ / -40%|←Most Sensitive Factor

[0141] |PV Output|+ / -15%|

[0142] |Energy storage capacity|+ / -10%|

[0143] Initial Quota | + / - 8% |

[0144] +------------+--------------+

[0145] This result clearly shows that quota price is the biggest driver of value, proving the necessity of focusing on the market dimension.

[0146] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A method for multidimensional valuation of carbon assets in industrial parks through physical-trading coupling, characterized in that, Includes the following steps: Step S1, Data Access and Standardization: Collect data from four dimensions: physical operation, carbon accounting, market transactions, and users and services. Perform consistency processing on time granularity, measurement units, accounting and spatial boundaries, and complete data quality governance. Step S2, Construction of a multi-dimensional evaluation index system: Based on the unified data in S1, establish a four-dimensional index library covering physical operation dimension, carbon accounting dimension, market economy dimension, and user and service dimension. Standardize the indicators and set weights, and define corresponding hard constraints or soft constraints and their feasible value ranges for each indicator. Step S3, Physical-Institutional Feasible Domain Construction: Map the indicators and constraints in S2 to time-specific feasible domains, generate the state-decision-emission / emission reduction mapping interface, and verify the feasible domains; Step S4, Value Element Decomposition and Cost Allocation: Define the cash flow composition related to carbon assets and couple equipment economics into cost calculation to form a periodic cash flow template and parameter table; Step S5, Scenario Matrix Generation and Parameter Definition: Construct the scenario set and uncertainty set of key variables, set unified parameters for benchmark and conservative estimates, and perform robustness processing. Step S6, Real Option Evaluation Based on Feasible Region: Establish a state-dependent option tree or option lattice on the feasible region constructed in S3, and calculate the option value and optimal strategy of each node by backtracking through each period. Step S7, Valuation Calculation and Result Integration: Calculate the benchmark value and the conservative value, summarize the optimal exercise path, contract portfolio suggestions and key boundary hits, and generate the sensitivity spectrum of indicator-valuation linkage. Step S8, Results Release and Dual Ledger Alignment: Generate an integrated report containing valuation results, strategies, sensitivity and constraint hits, and reconcile it with the carbon accounting ledger and the transaction clearing ledger to achieve traceability and auditability.

2. The method for multi-dimensional valuation of carbon assets in industrial parks through physical-trading coupling as described in claim 1, characterized in that, In step S1, the physical operation data includes renewable / conventional unit output, load curve, energy storage power / energy / SoH, network and equipment capacity, start-up, shutdown and maintenance cycle time; The carbon accounting data includes activity data, emission factors, accounting boundaries, baselines, or intensity-based parameters. The market transaction data includes quota / green certificate / voluntary emission reduction positions and prices, spot / forward / option contracts, compliance rules and price limits, and clearance windows; The user and service data includes demand response elasticity, service level constraints, production stoppage and restriction costs, and default clauses.

3. The method for multi-dimensional valuation of carbon assets in industrial parks through physical-trading coupling as described in claim 1, characterized in that, In step S2, the four-dimensional indicator library includes: Physical operation and maintenance indicators: output boundary, energy storage power / energy / lifetime, network and equipment capacity, start-up / shutdown / maintenance cycle time; Carbon accounting indicators: component emissions, baseline / intensity caliber, marginal emission reduction curve, accounting uncertainty; Market economy indicators: price, position, contract elements, performance and price boundaries, risk measurement methods; User and service metrics: resilience parameters, service level agreement (SLA), costs of production stoppages / limitations, and compensation / default mechanisms. The formula for the indicators and standardization is as follows: Where W = diag(w) j ) is a joint weight matrix of "constraint tightness + valuation sensitivity". The formulas for carbon accounting and emission reduction are as follows:

4. The method for multidimensional valuation of industrial park carbon assets through physical-trading coupling as described in claim 1, characterized in that, In step S2, the indicator weights are set based on a comprehensive criterion of "constraint tightness + valuation sensitivity", and traceability information is saved for each indicator.

5. The method for multi-dimensional valuation of industrial park carbon assets through physical-trading coupling as described in claim 1, characterized in that, In step S3, the feasible domain includes energy balance constraints, energy storage energy and lifetime constraints, network and equipment capacity constraints, and institutional and contractual boundary constraints. The input to the state-decision-emission / reduction mapping interface is the comprehensive indicator state and feasible decision, and the output is the real-time calculation results of emission, emission reduction and cash flow factors. The feasible region constraint formula is as follows: Energy balance: Energy storage: SoH s ≥ SoH Capacity / Network: System / Contract: A t +G t +C t +ΔE t ≥0, The formula for decomposing cash flow and costs is as follows: CycleCost t =λ s ·ECL t Cost of equivalent cycle life for energy storage.

6. The method for multi-dimensional valuation of carbon assets in industrial parks through physical-trading coupling as described in claim 1, characterized in that, In S5, a multi-scenario set and its probability or uncertainty set are constructed, including wind and solar power output, energy and carbon market prices, load and policy parameters; the valuation parameter caliber is set, including the expected discount parameter for benchmark valuation and the risk measurement parameter for conservative valuation; and the key variables are robustened by setting their upper and lower bounds, correlation structure and extreme cases to support stress testing.

7. The method for multidimensional valuation of carbon assets in industrial parks through physical-trading coupling as described in claim 1, characterized in that, In step S5, the scenario set includes a set of scenarios and probabilities or uncertainties related to wind and solar power output, prices, loads, and policy parameters. The conservative valuation uses a risk measure or robust approach, including Conditional Value at Risk (CVaR), where the valuation method is as follows:

8. The method for multidimensional valuation of carbon assets in industrial parks through physical-trading coupling as described in claim 1, characterized in that, In step S6, the rights contained in the option tree or option grid include holding, expansion, trading, hedging, and substitution. All exercise and transfer are only permitted to occur within the feasible domain defined by S3.

9. A physical-trading coupled multidimensional value assessment system for industrial park carbon assets, characterized in that, include: A data and caliber unification module is used to perform step S1 as described in claim 1; An indicator system construction module is used to perform step S2 as described in claim 1; The feasible domain construction module is used to perform step S3 as described in claim 1; A value element and option evaluation module is used to perform steps S4 and S6 as described in claim 1; The scenario and valuation module is used to perform steps S5 and S7 as described in claim 1; The results publishing and ledger alignment module is used to perform step S8 as described in claim 1.

10. A storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1 to 8.

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