Energy storage system degree electricity cost comprehensive evaluation method and system based on full life cycle dynamic modeling and cash flow discounting and application

Abstract

The application discloses a kind of based on full life cycle dynamic modeling and cash flow discounting energy storage system degree electric cost comprehensive evaluation method and system, including input technology, financial and market policy parameters;Build full life cycle dynamic cash flow sequence and electric quantity flow sequence, wherein cash flow sequence covers construction period annual investment, periodic replacement investment, operation and maintenance cost, depreciation tax rate cash flow and end-of-life salvage, and electric quantity flow sequence is dynamically corrected by efficiency attenuation model year by year net discharge capacity and deduces charging cost;Adopt benchmark discount rate to discount cash flow and electric quantity flow to benchmark time point, and obtain degree electric cost LCOE by total discharge capacity present value divided by total discharge capacity present value;By single variable and monte carlo multivariate sensitivity analysis, generate comprehensive evaluation report containing cost composition, cash flow curve and sensitivity chart.Overcome the limitation that existing method cash flow modeling is not complete, dynamic factor is missing, significantly improve the scientific nature and accuracy of energy storage project economy evaluation.

Description

Technical Field

[0001] This invention relates to the field of economic evaluation of energy storage technology and project investment decision-making, and in particular to a comprehensive evaluation method, system and application of levelized cost of energy (LCOE) of energy storage system based on dynamic modeling of the whole life cycle and discounted cash flow. It is applicable to the economic analysis and horizontal comparison of various energy storage technologies such as electrochemical energy storage, pumped hydro storage and compressed air energy storage. Background Technology

[0002] With the construction of new power systems and the increasing penetration of renewable energy, energy storage systems are playing an increasingly important role in the power system. Accurately assessing the levelized cost of electricity (LCOE) of energy storage systems is a key basis for project investment decisions, technology selection, and policy formulation. Currently, the methods for assessing the levelized cost of electricity (LCOE) of energy storage have the following limitations: The existing technology, the "Static Cost Amortization Method" (He Yingyuan, Chen Yongchong, Liu Yong, et al. Analysis of Energy Storage Cost per kilowatt-hour and Mileage Cost [J]. New Technologies of Electrical Engineering and Energy, 2019, 38(9):1-10.), uses the cost per kilowatt-hour and mileage cost methods to evaluate the economics of energy storage and establishes an analytical model based on various costs throughout the entire life cycle. However, the model does not consider the time value of money for charging the energy storage system and other costs. This method completely ignores the time value of money and does not consider the time value of money for charging the energy storage system and other costs. Its calculation results deviate significantly from reality and cannot provide a reliable basis for long-term investment, especially unsuitable for energy storage projects with long construction periods and the need for mid-term relocation.

[0003] The existing technology, "Simplified Dynamic Cost Method" (Fu Xu, Li Fuchun, Yang Xin, et al. Energy Storage Cost Analysis Based on Life Cycle Cost [J]. Distributed Energy, 2020, 5(03):34-38. DOI:10.16513 / j.2096-2185.DE.2001003.), partially introduces the concept of discount rate to calculate LCOE by discounting the initial investment and fixed annual operation and maintenance costs. However, such methods typically have significant drawbacks: 1) Incomplete models: They generally lack modeling of cash flows such as the periodic replacement cost of equipment, the operation and maintenance costs related to the operating status, and the tax savings from depreciation; 2) Crude power flow processing: They do not consider the impact of charging costs and charging and discharging efficiency on net discharge, leading to distorted assessments of energy storage scenarios that require charging from the grid or the user side; 3) Lack of sensitivity analysis framework: They cannot quantify the impact of fluctuations in key parameters (such as investment costs, electricity prices, and cycle life) on LCOE, resulting in insufficient disclosure of investment risks.

[0004] Therefore, existing technologies are insufficient for conducting scientific, accurate, and comparable full life-cycle economic assessments of energy storage projects. There is an urgent need for a systematic, modular, and comprehensive LCOE assessment method that can fully reflect the dynamic coupling relationship between "cost flow" and "energy flow". Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of existing technologies and provide a comprehensive evaluation method and system for the levelized cost of electricity (LCOE) of energy storage systems based on full lifecycle dynamic modeling and cash flow discounting. This method constructs a complete cost and energy cash flow model and incorporates factors such as time value of money, equipment replacement, tax effects, residual value, and charging costs. It achieves refined economic simulation of the entire lifecycle of energy storage systems from construction and operation to decommissioning, outputting a scientific, comparable, and decision-supporting LCOE index.

[0006] To achieve the above objectives, this invention provides a comprehensive evaluation method for the levelized cost of electricity (LCOE) of energy storage systems based on full lifecycle dynamic modeling and cash flow discounting, comprising the following steps: (1) Input the full life cycle assessment parameters of the energy storage system, including technical parameters, financial parameters and market policy parameters; (2) Based on the aforementioned evaluation parameters, construct dynamic cash flow sequences and dynamic electricity flow sequences for each year throughout the entire life cycle; wherein, The dynamic cash flow sequence includes at least: initial investment cash flow allocated annually according to the construction period, periodic reset investment cash flow according to the equipment reset strategy, operation and maintenance cost cash flow based on operation and maintenance rates and operating intensity, depreciation tax rate cash flow based on depreciation policy, and residual value recovery cash flow based on residual value rate at the end of the period. The dynamic power flow sequence dynamically corrects the annual net discharge through a preset efficiency decay model to obtain the annual net discharge. Based on the annual net discharge and the current year's charge and discharge efficiency, the annual charging amount is deduced, and combined with the charging price, an annual charging cost sequence is formed. (3) Using the benchmark discount rate, the cash flows of each year in the dynamic cash flow sequence and the discharge volume and charging cost of each year in the dynamic power flow sequence are discounted to the project benchmark time point to obtain the present value of total cost and the present value of total discharge volume; the present value of total cost is obtained by subtracting the present value of depreciation tax rate and the present value of residual value recovery from the sum of the present value of net investment cost, the present value of operation and maintenance cost and the present value of charging cost. (4) The levelized cost of electricity (LCOE) of the energy storage system is calculated based on the ratio of the present value of the total cost to the present value of the total discharge.

[0007] Furthermore, the depreciation tax rate cash flow is constructed in the following manner: The depreciation amount for each year is calculated based on the preset depreciation policy. The depreciation amount for each year is multiplied by the income tax rate to obtain the depreciation tax rate cash flow for the corresponding year, and this cash flow is included as an independent cash flow in the dynamic cash flow sequence for discounting. The depreciation policies include straight-line depreciation, double-declining balance depreciation, and sum-of-the-years'-digits depreciation. The system automatically switches the corresponding depreciation calculation logic based on the input parameters.

[0008] Furthermore, the efficiency decay model adopts an exponential decay model, the specific expression of which is:

[0009] in, For initial efficiency, The attenuation coefficient is... The year of operation; The annual net discharge capacity is calculated by multiplying the annual theoretical discharge capacity by the corresponding year's charge / discharge efficiency. get.

[0010] Furthermore, the annual charging cost sequence supports a time-of-use pricing mechanism, which matches the corresponding real-time electricity price or time-of-use electricity price according to the charging time period to form the charging cost, and discounts it to the present value of the charging cost year by year.

[0011] Furthermore, the method also includes: (5) Select at least one key parameter that has a significant impact on the levelized cost of electricity (LCOE), perform univariate sensitivity analysis or multivariate scenario analysis, generate analysis results including sensitivity coefficients, and output them in a visual format. The multivariate scenario analysis employs the Monte Carlo simulation method, which simultaneously perturbs multiple key parameters to generate the probability distribution of LCOE.

[0012] Furthermore, the key parameters include unit capacity cost, charging electricity price, reset cycle reflecting cycle life, operation and maintenance rate, and benchmark discount rate; The perturbation ranges for each parameter in the Monte Carlo simulation are set as follows: The unit cost is within ±20% of its benchmark value. The charging price is within ±30% of its benchmark value. The reset cycle is within ±20% of its baseline value. Operation and maintenance rates are within ±30% of their benchmark value. The benchmark discount rate is within ±0.1 of its benchmark value.

[0013] Furthermore, the visualization output includes an automatically generated comprehensive evaluation report containing a benchmark LCOE value, a cost structure pie chart, a life-cycle cash flow curve, and a sensitivity analysis chart.

[0014] A comprehensive evaluation system for the levelized cost of electricity (LCOE) of energy storage systems based on full lifecycle dynamic modeling and cash flow discounting includes: The basic parameter input and initialization module is used to receive and standardize the technical parameters, financial parameters, and market policy parameters required for energy storage system evaluation. The whole life cycle cash flow sequence construction and discounting module is used to construct the initial investment cash flow, periodic replacement investment cash flow, operation and maintenance cost cash flow, depreciation and tax rate cash flow and residual value recovery cash flow for each year in the whole life cycle based on input parameters, and discount all cash flows to the beginning of the first year of the construction period using the benchmark discount rate to obtain the present value of net investment cost, operation and maintenance cost, depreciation and tax rate, and residual value recovery respectively. The full lifecycle power flow present value calculation module is used to calculate the annual theoretical discharge based on system capacity, energy storage duration and number of operating days, and dynamically correct the annual discharge based on a preset efficiency decay model to obtain the annual net discharge, and discount the annual net discharge to the total present value of discharge; at the same time, it reverse-engineers the annual charging volume based on the annual net discharge and the charging and discharging efficiency of the corresponding year, and combines it with the charging price to form an annual charging cost sequence and discount it to the total present value of charging cost. The Levelized Cost of Electricity (LCOE) calculation module is used to calculate the LCOE based on the present value of each item, according to the formula: LCOE = (Net Investment Cost Present Value + Operation and Maintenance Cost Present Value - Depreciation and Tax Rate Present Value - Residual Value Recovery Present Value + Total Charging Cost Present Value) / Total Discharge Amount Present Value, which calculates the levelized cost of electricity (LCOE) for the entire life cycle of the energy storage system. The multi-dimensional sensitivity analysis and visualization output module is used to perform perturbation simulation on at least one key parameter, analyze its impact on the levelized cost of electricity (LCOE), and output a sensitivity analysis report and visualization charts. The multi-dimensional sensitivity analysis and visualization output module supports univariate sensitivity analysis and multivariate scenario analysis based on Monte Carlo simulation, and can generate probability distribution curves of LCOE as well as a comprehensive evaluation report including cost composition pie charts and life-cycle cash flow curves.

[0015] Furthermore, the efficiency decay model adopts an exponential decay model: ,in, For initial efficiency, The attenuation coefficient is... The year in which it was run.

[0016] A computer device includes a memory and a processor, the memory storing a computer program, characterized in that the processor executes the computer program to implement the steps of the method described above.

[0017] The beneficial effects of this invention are as follows: By establishing a dynamic cash flow model throughout the entire life cycle, analyzing the electricity flow and cost flow throughout the entire life cycle, constructing a standardized parameter evaluation system, and introducing a multi-dimensional sensitivity analysis method, an innovative comprehensive evaluation framework for the levelized cost of electricity (LCOE) applicable to various energy storage technologies has been constructed. This method not only significantly improves the comprehensiveness and accuracy of the economic evaluation of energy storage systems, truly reflecting the actual economic performance of different energy storage technologies throughout the entire process of initial investment, operation and maintenance costs, replacement demand, tax impact, and residual value recovery, but also possesses a high degree of standardization and engineering applicability, providing a scientific quantitative tool and decision-making basis for investment decisions, technology route comparisons, policy mechanism design, and market competitiveness analysis of energy storage projects. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the comprehensive evaluation method for the levelized cost of electricity (LCOE) of energy storage systems based on dynamic modeling and cash flow discounting throughout the entire life cycle, according to the present invention. The LCOE is defined as follows: 1---Basic parameter input and initialization module; 2---Construction and discounting module for the entire life cycle cash flow sequence; 3---Calculation module for the present value of the entire life cycle electricity flow; 4---Levelized cost of electricity (LCOE) synthesis calculation module; 5---Multi-dimensional sensitivity analysis and visualization output module. The arrows indicate the direction of implementation of the technical method.

[0019] Figure 2 Sensitivity analysis of the cost per kilowatt-hour of different energy storage technologies to charging electricity prices.

[0020] Figure 3 Sensitivity analysis of the cost per kilowatt-hour (including charging cost) of different energy storage technologies to changes in unit investment.

[0021] Figure 4 A schematic diagram illustrating the sensitivity analysis of the levelized cost of electricity (including charging cost) of different energy storage technologies to changes in energy storage duration.

[0022] Figure 5 A schematic diagram illustrating the sensitivity analysis of the levelized cost of electricity (including charging cost) of different energy storage technologies to conversion efficiency.

[0023] Figure 6 A schematic diagram illustrating the sensitivity analysis of the cost per kilowatt-hour (including charging cost) of different energy storage technologies to the discount rate. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0025] This invention relates to a comprehensive evaluation method and system for the levelized cost of electricity (LCOE) of energy storage systems based on dynamic modeling and cash flow discounting throughout the entire life cycle. The system includes a basic parameter input and initialization module 1, a full life cycle cash flow sequence construction and discounting module 2, a full life cycle electricity flow present value calculation module 3, a levelized cost of electricity (LCOE) synthesis calculation module 4, and a multi-dimensional sensitivity analysis and visualization output module 5.

[0026] The basic parameter input and initialization module includes a complete set of technical and economic parameters.

[0027] (1) Technical parameters include the system's rated capacity (Unit: MWh), Construction Period (Unit: Year), Investment Ratio by Year during Construction Period ( , ,.., Design service life (Unit: year) Charge-discharge cycle efficiency (over time) The change can be represented as an efficiency decay curve. ,in For initial efficiency, (attenuation coefficient), power generation duration (Unit: hours / day), number of operating days per year ; (2) Financial parameters include unit capacity cost (Unit: Yuan / kWh), Operation and Maintenance Rate (Percentage of total investment), equipment replacement ratio Reset cycle (Unit: Year), Fixed Asset Depreciation Rate residual value rate Income tax rate .

[0028] (3) Market and policy parameters include feed-in tariffs (Unit: Yuan / kWh), Charging Electricity Price (Unit: Yuan / kWh), Benchmark Discount Rate r This provides a foundation for the construction and discounting of subsequent full life-cycle cash flows.

[0029] The full life cycle cash flow sequence construction and discounting module constructs and discounts the core cash flow based on the basic parameter input and initialization module.

[0030] (1) Investment cash flow 1) Initial total investment:

[0031] 2) Investment in installments over the construction period: For the construction period Year, the Year( Investment amount Can be allocated according to preset ratio (satisfy )calculate: .

[0032] 3) Reset investment cash flow: during the operating life Every year, every interval A reset is triggered once a year. The reset occurred in the year ( ,and ), reset investment amount .

[0033] (2) Operating expenditure cash flow Annual maintenance cost: Annual maintenance costs ,in In order to be with the first Adjustment factors related to annual operating intensity (such as discharge volume), under the baseline condition .

[0034] (3) Cash flow from depreciation and taxes 1) Annual depreciation expense, using the straight-line depreciation method, annual depreciation amount ,in The depreciation period (usually) ).

[0035] 2) Annual depreciation tax, No. Annual depreciation tax cash flow .

[0036] (4) Residual value cash flow at the end of the period Recovery of residual value at the end of the period: occurs in the period Year-end residual cash flow .

[0037] (5) Cash flow discounting, with the beginning of the first year of the construction period as the base date ( ), discount all of the above cash flows.

[0038] 1) Present value of net investment cost: (j=1,.., , ,and ) 2) Present value of operation and maintenance costs:

[0039] 3) Present value of depreciation and taxes:

[0040] 4) Residual value recovery present value:

[0041] The full lifecycle power flow present value calculation module.

[0042] (1) Calculation of present value of discharge quantity 1) Annual theoretical discharge:

[0043] 2) Annual net discharge, considering capacity decay.

[0044] 3) Total present value of discharge:

[0045] (2) Calculation of present value of charging quantity 1) Annual charging capacity:

[0046] 2) Annual charging cost:

[0047] 3) Total present value of charging costs

[0048] The Levelized Cost of Electricity (LCOE) synthesis calculation module integrates calculations at the present value level.

[0049] (1) Present value of total cost

[0050] (2) Levelized Cost of Electricity (LCOE)

[0051]

[0052] The multi-dimensional sensitivity analysis and visualization output module performs perturbation analysis on key parameters, setting parameters... The baseline value is The disturbance range is .

[0053] (1) Univariate sensitivity analysis, calculation of parameters The response curves are obtained by taking LCOE values ​​at different values ​​within the disturbance range.

[0054] Sensitivity coefficient:

[0055] (2) Multivariate sensitivity analysis: Through multivariate Monte Carlo simulation, the probability distribution of LCOE can be obtained. The analysis results are visualized as a line graph (showing the impact of individual parameter changes on LCOE) and a radar chart (showing the combined effect of multiple parameters), and a comprehensive report including a pie chart of cost composition, full-cycle cash flow curve and sensitivity conclusions is generated.

[0056] Preferably, in one embodiment of the present invention, the charge-discharge cycle efficiency is characterized by an exponential decay model, specifically expressed as:

[0057] in, For initial efficiency, The attenuation coefficient is... For the running year (t=1,2,…, Attenuation coefficient The range of values ​​is / year corresponds to different types of energy storage technologies.

[0058] Preferably, the depreciation policy supports multiple methods, including straight-line depreciation, double-declining balance depreciation, and sum-of-the-years'-digits depreciation. The system automatically switches the calculation logic based on the input depreciation method parameters.

[0059] Preferably, the sensitivity analysis module employs a multivariate Monte Carlo simulation method, and the perturbation ranges for each parameter are set as follows: Cost per unit capacity:

[0060] Electricity price for charging:

[0061] Cycle life (affects reset cycle):

[0062] Operation and maintenance rates:

[0063] Benchmark discount rate:

[0064] like Figure 1-2As shown, the comprehensive evaluation method for the levelized cost of electricity (LCOE) of energy storage systems based on full lifecycle dynamic modeling and cash flow discounting of this invention includes: a basic parameter input and initialization module 1; a full lifecycle cash flow sequence construction and discounting module 2; a full lifecycle electricity flow present value calculation module 3; a levelized cost of electricity (LCOE) synthesis calculation module 4; and a multi-dimensional sensitivity analysis and visualization output module 5. This invention constructs a complete levelized cost of electricity (LCOE) evaluation system for energy storage systems based on the Python technology stack. The basic parameter input and initialization module uses a Pandas dictionary to input parameters. The full lifecycle cash flow sequence construction and discounting module uses the NumPy module to perform array processing of cash flow sequences and net present value calculation. It simulates the full lifecycle cash flow, including investment, operation and maintenance, depreciation, and residual value recovery, year by year through a loop control structure, and strictly performs time value discounting according to the discount formula. The multi-dimensional sensitivity analysis and visualization output module uses the Matplotlib module for visualization, automatically generating cost composition pie charts, sensitivity analysis radar charts, and multi-technology comparison curves; the Pandas module manages multi-scenario parameter combinations and result data, while the Open PyXL module outputs a standardized Excel evaluation report. The system has an embedded parameter verification mechanism to ensure the rationality of the input, and realizes multivariate probability analysis through Monte Carlo simulation. Its modular architecture supports fully automated processing from parameter input and dynamic calculation to visualization output, providing a scientific, efficient and verifiable calculation tool for the economic evaluation of energy storage projects.

[0065] The following description, in conjunction with the accompanying drawings, further illustrates pumped hydro storage, electrochemical energy storage, and compressed air energy storage, which employ the technical solutions of this invention: The evaluation boundary conditions adopted in this invention are as follows: the benchmark discount rate is set at 6%, and the calculation operation period is 50 years. The technical solutions cover three mainstream technical routes: constant-speed pumped storage, new energy storage (4-hour system), and compressed air energy storage, with installed capacities of 1 million kW, 400,000 kW, and 500,000 kW, respectively, and utilization hours of 6 hours, 4 hours, and 5 hours, respectively. The initial static investment is RMB 5,500 / kW, RMB 4,000 / kW, and RMB 7,000 / kW, respectively. The equipment operating life is 25 years, 10 years, and 30 years, respectively, and the annual operation and maintenance cost rates are set at 2.40%, 1.50%, and 2.50%, respectively. Regarding replacement, pumped storage is replaced in the 25th year of operation at 25% of the initial investment over two years (0.5, 0.5); new energy storage is replaced annually at a rate of 56% in the 10th, 20th, 30th, and 40th years; and compressed air energy storage is replaced annually at a rate of 40% in the 30th year. The depreciation period for pumped-storage power stations is 25 years, while the depreciation period for electrochemical energy storage and compressed air energy storage is uniformly 20 years. The residual value rates for pumped-storage, electrochemical energy storage, and compressed air energy storage are 0%, 3%, and 5%, respectively. The corporate income tax rate is uniformly 25%. For scenarios requiring external power purchase, the benchmark charging price (excluding tax) is set at 0.288 yuan / kWh. The investment during the construction period of the three types of energy storage is amortized into cash flows according to the following annual proportions: pumped-storage has a construction period of 7 years, with an annual investment proportion of [0.12, 0.18, 0.2, 0.24, 0.16, 0.07, 0.02]; new energy storage has a construction period of 2 years, with an annual investment proportion of [0.5, 0.5]; and compressed air energy storage has a construction period of 3 years, with an annual investment proportion of [0.3, 0.4, 0.3]. The above boundary conditions constitute the core parameter system for evaluating the levelized cost of electricity (LCOE) of various energy storage technologies throughout their entire life cycle.

[0066] like Figure 1-2 As shown, based on the aforementioned full lifecycle dynamic modeling and cash flow discounting method, a comprehensive assessment of the levelized cost of electricity (LCOE) for three energy storage technologies—pumped hydro storage, compressed air storage, and electrochemical storage—was conducted. Based on typical engineering parameters and unified financial boundary conditions for each technology, a complete cash flow model was constructed, encompassing initial investment, periodic replacement, operation and maintenance costs, depreciation and tax rates, residual value recovery, and external charging costs. Through present value discounting and energy flow coupling calculations, the levelized cost of electricity (LCOE) was obtained for both scenarios, considering and not considering charging costs.

[0067] According to the calculation model proposed in this invention, the levelized cost of electricity (LCOE) of energy storage systems can be quantified as follows: Pumped hydro storage technology has an LCOE of 0.237 yuan / kWh without considering charging costs, which rises to 0.621 yuan / kWh after considering charging costs; compressed air storage has LCOEs of 0.667 yuan / kWh and 1.147 yuan / kWh, respectively; and electrochemical storage has LCOEs of 0.403 yuan / kWh and 0.763 yuan / kWh, respectively. The results show that external charging costs have a significant impact on the overall economic efficiency of energy storage systems, especially in operating scenarios where electricity needs to be purchased from the grid, where charging costs can account for 30% to 60% of the total cost. Pumped hydro storage has a clear cost advantage without considering charging costs, while electrochemical storage still exhibits good economic competitiveness after considering system efficiency and cycle characteristics.

[0068] Based on the full lifecycle dynamic modeling and cash flow discounting method proposed in this invention, a systematic sensitivity analysis was conducted on the key parameters affecting the levelized cost of electricity (LCOE) of energy storage systems. The corresponding results are as follows: Figures 2 to 6 As shown.

[0069] Sensitivity analysis of charging electricity price ( Figure 1-3 The data shows that as the charging electricity price increased from 0 yuan / kWh to 0.5 yuan / kWh, the LCOE of all three types of energy storage technologies showed a linear increase. Pumped hydro storage saw its LCOE rise from 0.237 yuan / kWh to 0.85 yuan / kWh, an increase of 258.6%, indicating its economics are highly sensitive to electricity price changes. Compressed air storage increased from 0.667 yuan / kWh to 1.51 yuan / kWh, an increase of 126.4%. Electrochemical storage rose from 0.403 yuan / kWh to 1.028 yuan / kWh, an increase of 155.1%, with its higher energy conversion efficiency mitigating the impact of rising electricity prices to some extent.

[0070] Sensitivity analysis of unit investment cost ( Figure 1-4 The results show that as the unit investment multiple increases from 0.6 to 1.4, the LCOE of all three energy storage technologies exhibits near-linear growth, but their sensitivity differs. Pumped hydro storage's LCOE increased from RMB 0.69 / kWh to RMB 1.06 / kWh, an increase of approximately 53.6%, with relatively smooth cost transmission. Compressed air storage increased from RMB 0.88 / kWh to RMB 1.40 / kWh, an increase of approximately 59.1%, with a significantly faster growth rate, especially after the investment multiple exceeds 1.0, reflecting the high initial cost proportion of this technology. Electrochemical storage increased from RMB 0.60 / kWh to RMB 0.98 / kWh, an increase of approximately 63.3%. Although it has the lowest absolute cost, it is the most sensitive to investment changes, which is related to its shorter equipment lifespan and higher reset frequency. Overall, the economics of electrochemical and compressed air storage are more susceptible to fluctuations in initial investment, while pumped hydro storage shows stronger cost robustness.

[0071] Energy storage duration sensitivity analysis Figure 1-5 The study reveals that different energy storage technologies exhibit varying economic viability across different duration scenarios. In short-duration scenarios (1-2 hours), electrochemical energy storage demonstrates the best performance with an LCOE of approximately 0.35-0.45 yuan / kWh; pumped hydro storage, due to its higher fixed costs, has an LCOE of 0.55-0.65 yuan / kWh. In medium-duration scenarios (2-4 hours), pumped hydro storage's LCOE drops to 0.40-0.50 yuan / kWh, demonstrating economies of scale; electrochemical energy storage costs increase linearly with duration to 0.50-0.65 yuan / kWh. In long-duration scenarios (4-5 hours), pumped hydro storage's LCOE remains stable at 0.35-0.40 yuan / kWh, showing a clear advantage; although compressed air storage's LCOE decreases from 1.2 yuan / kWh to 0.9 yuan / kWh, it is still higher than other technologies.

[0072] Conversion efficiency sensitivity analysis Figure 1-6 The results show that increasing efficiency from 50% to 90% can significantly reduce the LCOE of various energy storage technologies. Electrochemical energy storage saw its LCOE decrease from 0.98 yuan / kWh to 0.73 yuan / kWh, a reduction of 25.5%, showing the most significant impact from efficiency improvements; pumped hydro storage decreased from 1.08 yuan / kWh to 0.82 yuan / kWh, a reduction of 24.1%; and compressed air storage decreased from 1.20 yuan / kWh to 0.99 yuan / kWh, a reduction of 17.5%.

[0073] Discount rate sensitivity analysis Figure 6 The results show that pumped hydro storage is most sensitive to changes in the discount rate; when the discount rate increases from 4% to 8%, its LCOE increases by more than 30%. Electrochemical storage's LCOE changes by about 15-20%, showing relatively lower sensitivity. Compressed air storage falls in between, with an increase of about 25%. Under a low discount rate (4%), pumped hydro storage's LCOE can be 15-20% lower than that of electrochemical storage; however, under a high discount rate (8%), the economic gap between the two narrows significantly.

[0074] The calculations and sensitivity analyses presented in the above embodiments demonstrate that the cost per kilowatt-hour obtained using the method of this invention not only includes factors such as replacement cost and charging cost that are ignored by traditional methods, but also reveals deeper patterns, such as the extreme sensitivity of pumped storage to charging electricity prices, through sensitivity analysis. Conclusions that can only be derived through a complete dynamic cost model provide quantitative evidence for investment decisions and risk management that traditional static or simplified models cannot offer, thus verifying the comprehensiveness and practicality of the method of this invention.

[0075] By adopting the above-disclosed technical solution of this invention, the following beneficial effects are obtained: The evaluation method proposed in this invention is systematic, comprehensive, and computationally rigorous, clearly revealing the cost structure and key influencing factors of different energy storage technologies. In the context of new power system construction and the marketization of energy storage, this method can provide scientific, quantitative, and comparable decision-making basis for energy storage project investment decisions, technology route comparisons, pricing mechanism design, and policy formulation, possessing significant practical application value and promising prospects for widespread adoption.

[0076]

[0077] 1. The system introduces a dynamic cash flow modeling and precise discounting method for the entire life cycle, which integrates all cost elements such as initial investment, periodic replacement cost, dynamic operation and maintenance expenditure, depreciation tax rate effect and residual value recovery at the end of the period. It also combines the time value of money for precise discounting, which overcomes the shortcomings of incomplete cash flow modeling in existing models and constructs a complete cost model that conforms to financial evaluation standards, significantly improving the scientificity and rigor of energy storage cost per kilowatt-hour calculation.

[0078] 2. While accurately calculating the present value of discharge, the external charging cost is included as an important variable in the cost per kilowatt-hour model, and the energy output is dynamically corrected through the efficiency decay model. This truly reflects the net energy value and comprehensive cost of the energy storage system during its operating cycle, making the evaluation results closer to actual application scenarios.

[0079] 3. A multidimensional sensitivity analysis method is proposed. By defining a unified interface for technical and economic parameters and an evaluation process, the comparability of evaluation results for different projects is ensured, providing a unified benchmark for horizontal comparison. At the same time, systematic sensitivity analysis can quickly identify key sensitive factors affecting the economics of projects, quantify investment risks, and provide an effective tool for project optimization design and risk management.

[0080] This evaluation system provides the energy storage industry with scientific, transparent, and comparable economic evaluation standards, which helps promote the market development and large-scale application of energy storage technology, and provides key technical support for the planning and configuration of energy storage and the innovation of business models in the construction of new power systems.

[0081] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A comprehensive evaluation method for the levelized cost of electricity (LCOE) of an energy storage system based on full lifecycle dynamic modeling and cash flow discounting, characterized in that, Includes the following steps: (1) Input the full life cycle assessment parameters of the energy storage system, including technical parameters, financial parameters and market policy parameters; (2) Based on the aforementioned evaluation parameters, construct dynamic cash flow sequences and dynamic electricity flow sequences for each year throughout the entire life cycle; wherein, The dynamic cash flow sequence includes at least: initial investment cash flow allocated annually according to the construction period, periodic reset investment cash flow according to the equipment reset strategy, operation and maintenance cost cash flow based on operation and maintenance rates and operating intensity, depreciation tax rate cash flow based on depreciation policy, and residual value recovery cash flow based on residual value rate at the end of the period. The dynamic power flow sequence dynamically corrects the annual net discharge through a preset efficiency decay model to obtain the annual net discharge. Based on the annual net discharge and the current year's charge and discharge efficiency, the annual charging amount is deduced, and combined with the charging price, an annual charging cost sequence is formed. (3) Using the benchmark discount rate, the cash flows of each year in the dynamic cash flow sequence and the discharge volume and charging cost of each year in the dynamic power flow sequence are discounted to the project benchmark time point to obtain the present value of total cost and the present value of total discharge volume; the present value of total cost is obtained by subtracting the present value of depreciation tax rate and the present value of residual value recovery from the sum of the present value of net investment cost, the present value of operation and maintenance cost and the present value of charging cost. (4) The levelized cost of electricity (LCOE) of the energy storage system is calculated based on the ratio of the present value of the total cost to the present value of the total discharge.

2. The method according to claim 1, characterized in that, The depreciation tax rate cash flow is constructed in the following way: The depreciation amount for each year is calculated based on the preset depreciation policy. The depreciation amount for each year is multiplied by the income tax rate to obtain the depreciation tax rate cash flow for the corresponding year, and this cash flow is included as an independent cash flow in the dynamic cash flow sequence for discounting. The depreciation policies include straight-line depreciation, double-declining balance depreciation, and sum-of-the-years'-digits depreciation. The system automatically switches the corresponding depreciation calculation logic based on the input parameters.

3. The method according to claim 1, characterized in that, The efficiency decay model adopts an exponential decay model, and the specific expression is as follows: in, For initial efficiency, The attenuation coefficient is... The year of operation; The annual net discharge capacity is calculated by multiplying the annual theoretical discharge capacity by the corresponding year's charge / discharge efficiency. get.

4. The method according to claim 1, characterized in that, The annual charging cost sequence supports a time-of-use pricing mechanism, which matches the corresponding real-time electricity price or time-of-use electricity price according to the charging time period to form the charging cost, and discounts it to the present value of the charging cost year by year.

5. The method according to claim 1, characterized in that, The method further includes: (5) Select at least one key parameter that has a significant impact on the levelized cost of electricity (LCOE), perform univariate sensitivity analysis or multivariate scenario analysis, generate analysis results including sensitivity coefficients, and output them in a visual format. The multivariate scenario analysis employs the Monte Carlo simulation method, which simultaneously perturbs multiple key parameters to generate the probability distribution of LCOE.

6. The method according to claim 5, characterized in that, The key parameters include unit capacity cost, charging electricity price, reset cycle reflecting cycle life, operation and maintenance rate, and benchmark discount rate; The perturbation ranges for each parameter in the Monte Carlo simulation are set as follows: The unit cost is within ±20% of its benchmark value. The charging price is within ±30% of its benchmark value. The reset cycle is within ±20% of its baseline value. Operation and maintenance rates are within ±30% of their benchmark value. The benchmark discount rate is within ±0.1 of its benchmark value.

7. The method according to claim 5, characterized in that, The visualization output includes an automatically generated comprehensive evaluation report containing a baseline LCOE value, a cost structure pie chart, a life-cycle cash flow curve, and sensitivity analysis charts.

8. A comprehensive evaluation system for the levelized cost of electricity (LCOE) of an energy storage system based on full lifecycle dynamic modeling and cash flow discounting, characterized in that, include: The basic parameter input and initialization module is used to receive and standardize the technical parameters, financial parameters, and market policy parameters required for energy storage system evaluation. The whole life cycle cash flow sequence construction and discounting module is used to construct the initial investment cash flow, periodic replacement investment cash flow, operation and maintenance cost cash flow, depreciation and tax rate cash flow and residual value recovery cash flow for each year in the whole life cycle based on input parameters, and discount all cash flows to the beginning of the first year of the construction period using the benchmark discount rate to obtain the present value of net investment cost, operation and maintenance cost, depreciation and tax rate, and residual value recovery respectively. The full lifecycle power flow present value calculation module is used to calculate the annual theoretical discharge based on system capacity, energy storage duration and number of operating days, and dynamically correct the annual discharge based on a preset efficiency decay model to obtain the annual net discharge, and discount the annual net discharge to the total present value of discharge; at the same time, it reverse-engineers the annual charging volume based on the annual net discharge and the charging and discharging efficiency of the corresponding year, and combines it with the charging price to form an annual charging cost sequence and discount it to the total present value of charging cost. The Levelized Cost of Electricity (LCOE) calculation module is used to calculate the LCOE based on the present value of each item, according to the formula: LCOE = (Net Investment Cost Present Value + Operation and Maintenance Cost Present Value - Depreciation and Tax Rate Present Value - Residual Value Recovery Present Value + Total Charging Cost Present Value) / Total Discharge Amount Present Value, which calculates the levelized cost of electricity (LCOE) for the entire life cycle of the energy storage system. The multi-dimensional sensitivity analysis and visualization output module is used to perform perturbation simulation on at least one key parameter, analyze its impact on the levelized cost of electricity (LCOE), and output a sensitivity analysis report and visualization charts. The multi-dimensional sensitivity analysis and visualization output module supports univariate sensitivity analysis and multivariate scenario analysis based on Monte Carlo simulation, and can generate probability distribution curves of LCOE as well as a comprehensive evaluation report including cost composition pie charts and life-cycle cash flow curves.

9. The system according to claim 8, characterized in that, The efficiency decay model adopts an exponential decay model: ,in, For initial efficiency, The attenuation coefficient is... The year in which it was run.

10. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 7.

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