A full life cycle cost assessment method for energy storage technology applicable to multi-dimensional scenarios

Abstract

The present invention relates to the field of energy storage assessment technology, and in particular to a method for assessing the full life cycle cost of energy storage technology applicable to multi-dimensional scenarios, including the following steps: determining the full life cycle of a new power system that needs to be calculated based on energy storage technology; determining the optimal power sales curve based on the predicted value and actual value of the power generation of wind turbines; evaluating the full life cycle benefits of the wind-solar hybrid energy storage system to be tested according to the optimal power sales curve; determining the system boundary for carbon footprint accounting of the new power system based on the full life cycle; collecting activity level data and emission factor data within the full life cycle based on the system boundary; calculating the carbon footprint of the new power system within the life cycle based on the activity level data and emission factor data, and increasing the proportion of renewable energy based on the carbon footprint. The present invention can effectively reduce the number of switching times of energy storage charging and discharging, thereby extending the service life of the hybrid energy storage system.

Description

Technical Field

[0001] The present invention relates to the field of energy storage evaluation technology, and in particular to a full life cycle cost evaluation method for energy storage technology applicable to multi-dimensional scenarios. Background Art

[0002] As the global energy crisis intensifies, wind energy, as one of the most common renewable energy sources, has gradually been developed and applied. However, wind energy resources have the characteristics of randomness, uncontrollability and low prediction accuracy, and its power generation is uncontrollable. The power system requires a stable and controllable power supply, but it is difficult for wind power plants to directly connect to the power system for power generation. Therefore, the uncertainty of wind power output limits the widespread application of wind power generation.

[0003] In recent years, the cost of energy storage systems has gradually decreased, and new energy storage devices such as flywheel energy storage systems have come into people's view. The construction of energy storage systems supporting wind power generation has become an effective way to smooth the output power curve of wind power generation. This application will bring greater economic benefits and technical convenience to the power system. The energy storage system can store electricity during the low electricity price period and release electricity during the peak electricity price period. The combination of energy storage systems with wind power generation can smooth the fluctuations in wind power output power.

[0004] However, the existing technology can only provide a joint dispatching solution for wind power and energy storage hybrid system, ignoring the restrictions on the charging and discharging switching of battery energy storage, which will cause serious life loss for energy storage and seriously affect the service life of battery energy storage system. In addition, the existing technology does not evaluate the full life cycle benefits brought by the energy storage system from a long-term perspective. Summary of the invention

[0005] In view of the above problems or problems existing in the prior art, the present invention is proposed.

[0006] Therefore, the purpose of the present invention is to provide a full life cycle cost assessment method for energy storage technology applicable to multi-dimensional scenarios.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions: a method for evaluating the full life cycle cost of energy storage technology applicable to multi-dimensional scenarios, comprising the following steps:

[0008] Determine the full life cycle of new power systems that need to be accounted for based on energy storage technology;

[0009] Determine the optimal electricity sales curve based on the predicted value and actual value of wind turbine power generation;

[0010] According to the optimal electricity sales curve, determine the life loss of the wind-solar hybrid energy storage system to be tested, and evaluate the full life cycle benefits of the wind-solar hybrid energy storage system to be tested;

[0011] Determine the system boundary of carbon footprint accounting of the new power system based on the full life cycle;

[0012] Collect activity level data and emission factor data over the entire life cycle based on the system boundaries;

[0013] Based on the activity level data and emission factor data, the carbon footprint of the new power system during its life cycle is calculated, and based on the carbon footprint, the proportion of renewable energy is increased to achieve emission reduction and carbon reduction.

[0014] As a preferred scheme of the full life cycle cost assessment method of energy storage technology applicable to multi-dimensional scenarios of the present invention, the full life cycle includes the equipment production stage, equipment installation stage, operation and maintenance stage and decommissioning and recovery stage in the new power system.

[0015] As a preferred solution of the full life cycle cost assessment method of energy storage technology applicable to multi-dimensional scenarios of the present invention, wherein: the system boundary is the recycling and disposal of equipment in the new power system within the full life cycle.

[0016] As a preferred solution of the energy storage technology full life cycle cost evaluation method applicable to multi-dimensional scenarios of the present invention, wherein: the general characteristic model of multiple types of energy storage, the economic characteristic model of multiple types of energy storage, the technical characteristic model of multiple types of energy storage and the source-grid-load model are integrated to construct a planning-operation double-layer optimization configuration model, which specifically includes:

[0017] A planning-operation two-layer optimization configuration model is constructed with the investment cost model as the upper-level target, planning restriction constraints as the upper-level constraints, operation and maintenance cost model and loss cost model as the lower-level targets, and multi-type energy storage general characteristic model, energy conversion constraints, charge range constraints and source-grid-load model as the lower-level constraints.

[0018] As a preferred solution of the full life cycle cost evaluation method of energy storage technology applicable to multi-dimensional scenarios of the present invention, wherein: the optimal power sales curve is determined based on the predicted value and the actual value of the power generation of the wind turbine generator set, including:

[0019] Based on the predicted value of wind turbine power generation, the constructed day-ahead declaration model is solved to obtain the optimal declaration curve;

[0020] Based on the real value of wind turbine power generation, the constructed intraday dispatch model is solved, and the optimal power sales curve is obtained according to the optimal declaration curve.

[0021] As a preferred solution of the full life cycle cost evaluation method of energy storage technology applicable to multi-dimensional scenarios of the present invention, wherein: the life loss of the wind-solar hybrid energy storage system to be tested is determined according to the optimal electricity sales curve, and the full life cycle benefits of the wind-solar hybrid energy storage system to be tested are evaluated, including:

[0022] Using a linear function, according to the optimal electricity sales curve, the life loss of the wind-solar hybrid energy storage system to be tested is determined;

[0023] Re-extracting a wind power generation sequence randomly from the historical wind power generation data of the wind turbine generator set in the wind-solar hybrid energy storage system to be tested, until the life of the wind-solar hybrid energy storage system to be tested reaches a preset life lower limit, and then stopping the extraction;

[0024] The electricity sales revenue obtained in each round is added up as the full life cycle benefit of the wind-solar hybrid energy storage system to be tested.

[0025] As a preferred solution of the full life cycle cost assessment method of energy storage technology applicable to multi-dimensional scenarios of the present invention, the wind-solar hybrid energy storage system to be tested includes an energy storage system and a wind turbine generator set, and the energy storage system includes a battery energy storage system and a flywheel energy storage system.

[0026] The beneficial effects of the present invention are:

[0027] The present invention proposes a full life cycle cost assessment method for energy storage technology applicable to multi-dimensional scenarios, which can comprehensively evaluate the benefits brought by the energy storage system from a long-term perspective.

[0028] The present invention utilizes a large amount of real historical wind power generation data of wind turbines and adopts a data-driven method to effectively simulate the randomness of wind power generation, making the evaluation result closer to the actual situation.

[0029] The method proposed in the present invention can also effectively reduce the number of switching times of energy storage charging and discharging, thereby extending the service life of the hybrid energy storage system, thereby achieving greater economic benefits.

[0030] In summary, the present invention can be widely used in the field of energy storage assessment. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0032] Figure 1 A flow chart of a method for evaluating the full life cycle cost of energy storage technology applicable to multi-dimensional scenarios provided by the present invention. DETAILED DESCRIPTION

[0033] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0034] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0035] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0036] Example 1, reference Figure 1 , which is the first embodiment of the present invention, provides a method for evaluating the full life cycle cost of energy storage technology applicable to multi-dimensional scenarios, comprising the following steps:

[0037] Determine the full life cycle of new power systems that need to be accounted for based on energy storage technology;

[0038] The whole life cycle includes the equipment production stage, equipment installation stage, operation and maintenance stage and decommissioning and recycling stage in the new power system;

[0039] The general characteristic model of multiple types of energy storage, the economic characteristic model of multiple types of energy storage, the technical characteristic model of multiple types of energy storage and the source-grid-load model are integrated to construct a planning-operation two-layer optimization configuration model, which specifically includes:

[0040] A planning-operation two-layer optimization configuration model is constructed with the investment cost model as the upper-level target, planning restriction constraints as the upper-level constraints, operation and maintenance cost model and loss cost model as the lower-level targets, and multi-type energy storage general characteristic model, energy conversion constraints, charge range constraints and source-grid-load model as the lower-level constraints.

[0041] The system boundary is the recycling and disposal of equipment in the new power system during the entire life cycle.

[0042] Determine the optimal electricity sales curve based on the predicted value and actual value of wind turbine power generation;

[0043] According to the optimal electricity sales curve, determine the life loss of the wind-solar hybrid energy storage system to be tested, and evaluate the full life cycle benefits of the wind-solar hybrid energy storage system to be tested;

[0044] The step of determining the optimal electricity sales curve based on the predicted value and the actual value of the power generation of the wind turbine generator set includes:

[0045] Based on the predicted value of wind turbine power generation, the constructed day-ahead declaration model is solved to obtain the optimal declaration curve;

[0046] Based on the real value of wind turbine power generation, the constructed intraday dispatch model is solved, and the optimal power sales curve is obtained according to the optimal declaration curve;

[0047] The method of determining the life loss of the wind-solar hybrid energy storage system to be tested based on the optimal electricity sales curve and evaluating the full life cycle benefits of the wind-solar hybrid energy storage system to be tested includes:

[0048] Using a linear function, according to the optimal electricity sales curve, the life loss of the wind-solar hybrid energy storage system to be tested is determined;

[0049] Re-extracting a wind power generation sequence randomly from the historical wind power generation data of the wind turbine generator set in the wind-solar hybrid energy storage system to be tested, until the life of the wind-solar hybrid energy storage system to be tested reaches a preset life lower limit, and then stopping the extraction;

[0050] The wind-solar hybrid energy storage system to be tested includes an energy storage system and a wind turbine generator set, and the energy storage system includes a battery energy storage system and a flywheel energy storage system.

[0051] The electricity sales revenue obtained in each round is added up as the full life cycle benefit of the wind-solar hybrid energy storage system to be tested.

[0052] Determine the system boundary of carbon footprint accounting of the new power system based on the full life cycle;

[0053] Collect activity level data and emission factor data over the entire life cycle based on the system boundaries;

[0054] Based on the activity level data and emission factor data, the carbon footprint of the new power system during its life cycle is calculated, and based on the carbon footprint, the proportion of renewable energy is increased to achieve emission reduction and carbon reduction.

[0055] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for evaluating the full life cycle cost of energy storage technology applicable to multi-dimensional scenarios, characterized in that: The steps include: Determine the full life cycle of new power systems that need to be accounted for based on energy storage technology; Determine the optimal electricity sales curve based on the predicted value and actual value of wind turbine power generation; According to the optimal electricity sales curve, determine the life loss of the wind-solar hybrid energy storage system to be tested, and evaluate the full life cycle benefits of the wind-solar hybrid energy storage system to be tested; Determine the system boundary of carbon footprint accounting of the new power system based on the full life cycle; Collect activity level data and emission factor data over the entire life cycle based on the system boundaries; Based on the activity level data and emission factor data, the carbon footprint of the new power system during its life cycle is calculated, and based on the carbon footprint, the proportion of renewable energy is increased to achieve emission reduction and carbon reduction.

2. The method for evaluating the full life cycle cost of energy storage technology applicable to multi-dimensional scenarios according to claim 1, characterized in that: The full life cycle includes the equipment production stage, equipment installation stage, operation and maintenance stage, and decommissioning and recycling stage in the new power system.

3. The method for evaluating the full life cycle cost of energy storage technology applicable to multi-dimensional scenarios as claimed in claim 2, characterized in that: The system boundary is the recycling and disposal of equipment in the new power system during the entire life cycle.

4. The method for evaluating the full life cycle cost of energy storage technology applicable to multi-dimensional scenarios as claimed in claim 3, characterized in that: The integration of the general characteristic model of multiple types of energy storage, the economic characteristic model of multiple types of energy storage, the technical characteristic model of multiple types of energy storage and the source-grid-load model to construct a planning-operation two-layer optimization configuration model specifically includes: A planning-operation two-layer optimization configuration model is constructed with the investment cost model as the upper-level target, planning restriction constraints as the upper-level constraints, operation and maintenance cost model and loss cost model as the lower-level targets, and multi-type energy storage general characteristic model, energy conversion constraints, charge range constraints and source-grid-load model as the lower-level constraints.

5. The method for evaluating the full life cycle cost of energy storage technology applicable to multi-dimensional scenarios as claimed in claim 4, characterized in that: The step of determining the optimal electricity sales curve based on the predicted value and the actual value of the power generation of the wind turbine generator set includes: Based on the predicted value of wind turbine power generation, the constructed day-ahead declaration model is solved to obtain the optimal declaration curve; Based on the real value of wind turbine power generation, the constructed intraday dispatch model is solved, and the optimal power sales curve is obtained according to the optimal declaration curve.

6. The method for evaluating the full life cycle cost of energy storage technology applicable to multi-dimensional scenarios as claimed in claim 5, characterized in that: The method of determining the life loss of the wind-solar hybrid energy storage system to be tested based on the optimal electricity sales curve and evaluating the full life cycle benefits of the wind-solar hybrid energy storage system to be tested includes: Using a linear function, according to the optimal electricity sales curve, the life loss of the wind-solar hybrid energy storage system to be tested is determined; Re-extracting a wind power generation sequence randomly from the historical wind power generation data of the wind turbine generator set in the wind-solar hybrid energy storage system to be tested, until the life of the wind-solar hybrid energy storage system to be tested reaches a preset life lower limit, and then stopping the extraction; The electricity sales revenue obtained in each round is added up as the full life cycle benefit of the wind-solar hybrid energy storage system to be tested.

7. The method for evaluating the full life cycle cost of energy storage technology applicable to multi-dimensional scenarios according to claim 6, characterized in that: The wind-solar hybrid energy storage system to be tested includes an energy storage system and a wind turbine generator set, and the energy storage system includes a battery energy storage system and a flywheel energy storage system.

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