Carbon emission reduction accounting method and monitoring system based on electric and hybrid power ships

Abstract

The invention discloses a carbon emission reduction accounting method and monitoring system based on electric and hybrid power ships, and belongs to the technical field of carbon emission reduction accounting, and the carbon emission reduction accounting method comprises the steps of datum line emission calculation, project emission calculation and carbon emission calculation. Wherein the datum line emission factor needs to be obtained through calculation according to the fuel consumption rate, the fuel net heat value and the fuel emission factor under the datum line scene, and the fuel consumption rate is obtained through calculation by constructing a dynamic datum model. In order to overcome the calculation deviation of a traditional reference line model, the engine efficiency, the fuel characteristics, the environmental interference and the dynamic change of the transportation task load are comprehensively considered, so that the dynamic reference model of the fuel consumption rate is established, the reference line prediction precision is effectively improved, and the prediction accuracy is improved. And a more accurate carbon emission reduction management basis is provided for the development of electric and hybrid power ship projects.

Description

Technical Field

[0001] The present invention belongs to the technical field of carbon emission reduction accounting, and specifically relates to a carbon emission reduction accounting method and a monitoring system based on electric and hybrid power ships. Background Art

[0002] Under the severe challenge of global climate change, the global shipping industry's demand for carbon emission reduction is accelerating. Electric and hybrid ships are ships that use electricity to partially or completely replace traditional fuel for power generation. As a new type of green transportation, compared with traditional diesel-powered ships, electric and hybrid ships have the advantages of energy saving, low emissions, low pollution, cleanliness, low noise, and diversified available energy, which is an important way to achieve energy conservation and emission reduction in ships.

[0003] Voluntary greenhouse gas emission reduction trading is an important way to fully utilize market mechanisms to promote greenhouse gas emission reduction. It has positive significance for cultivating carbon emission reduction market awareness, exploring and testing carbon emission trading procedures and norms. The premise of voluntary greenhouse gas emission reduction trading is to accurately determine the emission reduction amount of each industry. For electric and hybrid ship projects, it is urgent to establish a scientific carbon emission reduction quantification model.

[0004] However, for the baseline emission scenario, the fuel consumption rate is currently mainly obtained through sampling measurements or recommended values. However, this calculation method is mainly transplanted from the field of road transportation and has serious defects in water transport adaptability. It ignores the nonlinear effects of ship cargo distribution, speed changes, and hydrological conditions on energy consumption, resulting in a calculation deviation of the baseline fuel consumption rate exceeding ±15%, which seriously affects the quantification accuracy of carbon emission reduction. Summary of the invention

[0005] Purpose of the invention: In view of the above-mentioned deficiencies, the present invention provides a carbon emission reduction accounting method and monitoring system based on electric and hybrid power ships, establishes a dynamic benchmark model of fuel consumption rate based on the characteristics of ship transportation, and provides a more accurate carbon emission reduction management basis for the development of electric and hybrid power ship projects.

[0006] Technical solution: To achieve the above objectives, the present invention provides a carbon emission reduction accounting method and monitoring system based on electric and hybrid ships, comprising the following steps: 1) Calculate the baseline emissions of the target ship based on the baseline emission factor and passenger and cargo turnover; 2) Calculate the project emissions of the target ship based on the grid emission factor, fuel emission factor and passenger and cargo turnover; 3) Calculate the carbon emission reduction of the target ship based on the baseline emissions and the project emissions; The baseline emission factor is calculated based on the fuel consumption rate, net calorific value of the fuel, and fuel emission factor under the baseline scenario. The fuel consumption rate is calculated through the following dynamic baseline model:

[0007] In the formula, is the fuel consumption rate under the baseline scenario; is the instantaneous value of the main engine power in the i-th voyage segment, and n is the total number of voyage segments; is the thermal efficiency of the main engine; is the lower calorific value of the fuel; is the environmental correction factor; is the cargo volume in the j-th voyage, and m is the total number of voyages; is the transportation distance in the j-th voyage.

[0008] Furthermore, the main engine power is calculated according to the following formula:

[0009] In the formula, is the total resistance, is the thrust deduction coefficient, is the hull efficiency, is the relative rotative efficiency.

[0010] Furthermore, the total resistance is calculated according to the following formula:

[0011] In the formula, is the frictional resistance, is the wave-making resistance, is the air resistance, and they are calculated according to the following formulas respectively:

[0012]

[0013]

[0014] In the formula, is the water density, is the frictional resistance coefficient, is the wetted surface area of the hull, and V is the ship speed; is the cargo distribution correction factor, L is the ship length, B is the ship width, T is the designed draft, and Cb is the block coefficient; is the cross-sectional area in the horizontal direction, is the wind speed, and θ is the wind direction.

[0015] Furthermore, the load distribution correction factor is calculated according to the following formula:

[0016] In the formula, is the load in the front cargo hold; is the load in the rear cargo hold; is the total load in the cargo hold; , that is, the wave-making resistance increase factor caused by full load in the front; , that is, the vortex resistance increase factor caused by full load in the rear.

[0017] Furthermore, the environmental correction factor is calculated according to the following formula:

[0018] In the formula, Hw is the wave height, L is the ship length, Vc is the water flow velocity, V is the ship speed, and θ is the wind direction.

[0019] Furthermore, the lower calorific value of the fuel is calculated according to the following formula:

[0020] In the formula, is the mass percentage of the kth hydrocarbon component; is the standard calorific value of the kth hydrocarbon component; is the sulfur content correction term.

[0021] Furthermore, the grid emission factor is calculated through the following model: 2.1. Construct a real-time calculation engine for the carbon emission factor of the regional power grid:

[0022] In the formula, = 1 to 5 respectively represent coal-fired power, gas-fired power, hydropower, nuclear power, and renewable energy; represents the output of the th type of power source at time t; represents the total output of all types of power sources at time t; Indicates the class power life cycle emission factor; 2.2. Construct a dynamic mapping algorithm for emission factors based on ship trajectories:

[0023] In the formula, represents the longitude and latitude coordinates of the ship at time t; represents the on-board battery charge during time period t; represents the on-board battery charge during the total time period T.

[0024] In addition, the present invention also provides a carbon emission reduction monitoring system for electric and hybrid ships, including an on-board monitoring terminal, a cloud computing platform, and a verification terminal. The on-board monitoring terminal is used to collect real-time ship operation data for the cloud computing platform to calculate the carbon emission reduction amount based on the above carbon emission reduction accounting method, and then upload the collected data and calculation results to the verification terminal.

[0025] Further, the on-board monitoring terminal includes a main control unit, a sensor unit, and a communication unit. The main control unit realizes data collection through the sensor unit and then realizes communication transmission with the cloud computing platform through the communication unit.

[0026] Further, the cloud computing platform realizes data upload through a blockchain evidence storage module.

[0027] Beneficial effects: The present invention comprehensively considers the dynamic changes of engine efficiency, fuel characteristics, environmental interference, and transportation task volume, thereby establishing a dynamic benchmark model for fuel consumption rate, effectively improving the prediction accuracy of the baseline, and providing a more accurate carbon emission reduction management basis for the development of electric and hybrid ship projects. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 is the schematic diagram of the dynamic benchmark model in the embodiment of the present invention; Figure 2 is the architecture diagram of the carbon emission reduction monitoring system in the embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0029] In order to make the objectives, features, and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments.

[0030] For the electric and hybrid ship project, the baseline scenario is the emissions generated by the ship using fossil fuels in the absence of project activities. The project scenario is the emissions generated by the electric / hybrid ship using electricity and fossil fuel electricity under project activities. Then, the project emission reduction is calculated based on the baseline emissions and project emissions. However, the existing accounting system technology has the following defects: 1) Baseline inaccuracy: The traditional baseline model ignores the non-linear effects of ship cargo distribution and hydrological conditions on energy consumption, resulting in a calculation deviation of the baseline fuel consumption rate exceeding ±15%; 2) Emission factor distortion: The existing system cannot reflect key factors such as fuel calorific value fluctuations and grid dynamic changes, causing overestimation or underestimation of emission reductions; 3) Monitoring data inaccuracy: Discrete monitoring equipment has problems such as data fragmentation and insufficient accuracy, making it difficult to meet the requirements of the carbon market for data traceability.

[0031] Based on this, this embodiment provides a carbon emission reduction accounting method for electric and hybrid ships, including the following steps: 1. Baseline emission calculation; The baseline emissions need to be calculated based on the baseline emission factor and the passenger and cargo turnover volume. The baseline emission factor is calculated based on the fuel consumption rate, net calorific value of the fuel, and fuel emission factor under the baseline scenario. To improve the prediction accuracy of the baseline model, the following dynamic baseline model (as Figure 1 shown) is used to calculate the fuel consumption rate: 1.1. Multi-dimensional data collection: a. Ship parameters: ship length L, ship width B, design draft T, block coefficient Cb; b. Operating parameters: real-time cargo volume W (±0.5% accuracy), speed V (0.1 knot resolution), main engine power P (kW); c. Environmental parameters: water flow velocity Vc, wind direction θ, wave height Hw.

[0032] 1.2. Establish a correction coefficient model for the resistance of the cargo distribution:

[0033] In the formula, is the cargo distribution correction coefficient; is the cargo volume in the front cargo hold (tons); is the cargo volume in the rear cargo hold (tons); is the total cargo volume in the cargo hold (tons); , that is, the wave-making resistance increase coefficient caused by full load in the front; , i.e., the coefficient of increased vortex resistance caused by full load at the rear

[0034] 1.3. Establish the relationship between the main engine power and the ship speed based on ship hydrodynamics:

[0035] Wherein, is the instantaneous value of the main engine power, is the total resistance, is the thrust deduction coefficient, representing the proportion of the propeller thrust reduced due to the hull influence, usually 0.1 - 0.3; is the hull efficiency, reflecting the interaction efficiency between the hull and the propeller, which can be increased to 1.0 - 1.3 after optimization; is the relative rotational efficiency, representing the ratio of the propeller efficiency in the actual hull flow field to the ideal open water efficiency, approximately 0.95 - 1.05, affected by the uniformity of the wake flow field at the stern. Among them, the total resistance Rt can be calculated according to the following formula:

[0036] Specific component calculation: Frictional resistance (ITTC - 1957 formula):

[0037] Wherein, is the water density, is the frictional resistance coefficient, determined by the Reynolds number Re and the surface roughness, is the wetted surface area of the hull, i.e., the total area of the hull in contact with water; Wave - making resistance (improved Townsin formula):

[0038] Air resistance:

[0039] Wherein, is the lateral cross - sectional area, is the wind speed, and θ is the wind direction.

[0040] 1.4. Construct a dynamic benchmark model for the fuel consumption rate:

[0041] Wherein, is the fuel consumption rate under the baseline scenario; is the instantaneous value of the main engine power (kW) in the i - th voyage segment, and n is the total number of voyage segments (which can be divided according to the working modes of the ship engine, such as full speed, cruising, idle speed, etc.); is the main engine thermal efficiency (0.45 for diesel engines and 0.52 for LNG); is the lower calorific value of the fuel (real-time detected value, unit: MJ / kg); is the environmental correction coefficient, which is used to quantify the impact of the external environment on fuel consumption; is the cargo volume (tons) of the j-th voyage, and m is the total number of voyages; is the transportation distance (nautical miles) of the j-th voyage.

[0042] Furthermore, the environmental correction coefficient can be calculated according to the following formula:

[0043] Under calm sea conditions ≈ 1.0, and it can reach 1.2 - 1.5 under severe sea conditions.

[0044] Furthermore, the quality of marine fuel fluctuates significantly. The actual measurement shows that the difference in the lower calorific value of diesel in different batches reaches 1.8 MJ / kg. In order to further improve the calculation accuracy of the fuel consumption rate, laser spectroscopy analysis can be used to online measure the fuel components, and thus the real-time detection of the fuel calorific value can be carried out. The specific calculation formula is as follows:

[0045] In the formula, is the mass percentage of the k-th hydrocarbon component; is the standard calorific value (MJ / kg) of the k-th hydrocarbon component; is the sulfur content correction term.

[0046] 2. Project emission calculation; The project emissions need to be calculated based on the grid emission factor, fuel emission factor, and passenger and cargo turnover volume. In order to improve the prediction accuracy of the project model, the grid emission factor is obtained in real time from the spatial and temporal dimensions respectively: 2.1. Build a real-time calculation engine for the regional power grid carbon emission factor:

[0047] In the formula, = 1 - 5 respectively represent coal power, gas power, hydropower, nuclear power, and renewable energy; represents the output (MW) of the -th type of power source at time t; Denote the total output of various power sources at time t (MW); Denote the emission factor of the life cycle of the

[0048] 2.2. Develop a dynamic mapping algorithm for emission factors based on ship trajectories:

[0049] In the formula, Denote the longitude and latitude coordinates of the ship at time t; Denote the charging amount of the on-board battery during the time period t (kWh); Denote the total charging amount of the on-board battery within the total time period T (kWh).

[0050] 3. Project emission reduction quantity accounting; Based on the baseline emissions and project emissions, the carbon emission reduction quantity of the target ship can be calculated.

[0051] See Figure 2 , this embodiment also provides a carbon emission reduction monitoring system based on electric and hybrid ships, specifically including: On-board monitoring terminal, used to collect ship operation data in real time; Cloud computing platform, deploying a baseline model and an emission factor calculation engine, thereby calculating the carbon emission reduction quantity based on the above carbon emission reduction accounting method, and uploading the collected data and calculation results to the verification terminal; Verification terminal, with data visualization and anomaly detection functions; Among them, the on-board terminal and the cloud platform are connected through a 5G / satellite dual-channel connection to achieve a data delay ≤ 150 ms.

[0052] Furthermore, the on-board monitoring terminal includes a main control unit, a sensor unit, and a communication unit. Among them, the main control unit realizes data collection through the sensor unit, and then realizes 5G / satellite dual-channel data transmission with the cloud computing platform through the communication unit.

[0053] Specifically, the sensor unit includes: Microstrain load sensor array, used to realize load distribution measurement, with a measurement error ; Coriolis mass flowmeter, used to realize fuel metering, with a metering accuracy 0.25%; Multi-frequency GNSS module, used to realize Beidou satellite positioning, with a positioning accuracy 0.5 m, and further realize ship speed detection and track recording.

[0054] Furthermore, the cloud computing platform realizes data upload through the blockchain evidence storage module. A data fingerprint containing the timestamp, cargo volume, ship speed, and energy consumption is generated every 10 seconds and encrypted in slices through the threshold signature algorithm and then written into the consortium blockchain.

[0055] Embodiment: Three typical ship types are selected on the main line of the Yangtze River for 12 months of field testing. The test objects are as follows:

[0056] Accuracy improvement data after adopting the above optimization system: 1. Baseline calculation error: Traditional method: The maximum error is 21.4% (in the light-load condition of bulk carriers); This method: The error range is ±4.7% (confidence level 95%); 2. Real-time emission factor: The update delay of the grid factor is shortened from 8 hours to 15 minutes; The detection response time of the fuel calorific value < 30 seconds; 3. Data credibility: The abnormal detection rate of blockchain evidence storage is 100%; The data integrity rate is 99.8% (compared with 82.3% of the traditional method).

[0057] In summary, based on the establishment of a scientific carbon emission reduction quantification model, and integrating industry pain points and technical status, the present invention further achieves breakthroughs in the following dimensions: 1. Dynamic baseline modeling: Develop a machine learning model that integrates cargo distribution, hydrological conditions, and ship type parameters to improve the prediction accuracy of the baseline; 2. High-resolution emission factor: Construct a regional power grid carbon emission factor map updated at the minute level to accurately reflect the dynamic changes of the power grid; 3. All-factor monitoring terminal: Develop an on-board integrated intelligent monitoring device to achieve millisecond-level synchronous acquisition of cargo volume - energy consumption - position data; 4. Blockchain evidence storage: Establish a data traceability mechanism based on a distributed ledger to prevent the tampering of monitoring data.

[0058] The present invention precisely aims at the above technical gaps and overcomes the long-existing problems of accuracy loss and insufficient credibility in the field of ship carbon accounting through an innovative method architecture and hardware system design.

[0059] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should all be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A carbon emission reduction accounting method based on electric and hybrid ships, characterized in that: The following steps are involved: 1) Calculate the baseline emissions of the target ship based on the baseline emission factor and passenger and cargo turnover; 2) Calculate the project emissions of the target ship based on the grid emission factor, fuel emission factor and passenger and cargo turnover; 3) Calculate the carbon emission reduction of the target ship based on the baseline emissions and the project emissions; The baseline emission factor is calculated based on the fuel consumption rate, fuel net calorific value and fuel emission factor under the baseline scenario. The fuel consumption rate is calculated using the following dynamic baseline model: In the formula, is the fuel consumption rate under the baseline scenario; is the instantaneous value of the main engine power of the i-th flight segment, and n is the total number of flight segments; is the host thermal efficiency; It is the lower heating value of fuel; is the environmental correction factor; is the cargo volume of the jth voyage, and m is the total number of voyages; is the transportation distance of the jth voyage.

2. The carbon emission reduction accounting method according to claim 1, characterized in that: The host power Calculated using the following formula: In the formula, is the total resistance, is the thrust derating factor, For hull efficiency, is the relative rotation efficiency.

3. The carbon emission reduction accounting method according to claim 2, characterized in that: The total resistance Calculated using the following formula: In the formula, is the friction resistance, To create resistance, is the air resistance, calculated according to the following formulas: In the formula, is the water density, is the friction coefficient, is the wet surface area of ​​the hull, V is the speed; is the cargo distribution correction factor, L is the ship length, B is the ship width, T is the design draft, and Cb is the square coefficient; is the transverse cross-sectional area, is the wind speed and θ is the wind direction.

4. The carbon emission reduction accounting method according to claim 3, characterized in that: The cargo distribution correction factor Calculated using the following formula: In the formula, For the cargo capacity of the front cargo hold; For the cargo capacity of the rear cargo hold; is the total cargo capacity of the cargo hold; , that is, the coefficient of wave-making resistance increases due to full front loading; , that is, the full load at the rear causes the vortex drag to increase.

5. The carbon emission reduction accounting method according to claim 1, characterized in that: The environmental correction factor Calculated using the following formula: Where Hw is the wave height, L is the ship length, Vc is the water velocity, V is the ship speed, and θ is the wind direction.

6. The carbon emission reduction accounting method according to claim 1, characterized in that: The lower heating value of the fuel Calculated using the following formula: In the formula, is the mass percentage of the kth hydrocarbon component; is the standard calorific value of the kth hydrocarbon component; is the sulfur content correction term.

7. The carbon emission reduction accounting method according to claim 1, characterized in that: The grid emission factor is calculated using the following model: 2.

1. Build a real-time calculation engine for regional power grid carbon emission factors: In the formula, =1~5 They represent coal power, gas power, hydropower, nuclear power, and renewable energy respectively; Indicates the time t Class power output; Indicates the total output of various power sources at time t; Indicates Life cycle emission factors for power sources; 2.

2. Constructing a dynamic mapping algorithm of emission factors based on ship trajectories: In the formula, Indicates the longitude and latitude coordinates of the ship at time t; Indicates the charge level of the onboard battery during period t; Indicates the charge capacity of the onboard battery within the total period T.

8. A carbon emission reduction monitoring system based on electric and hybrid ships, characterized in that: It includes a shipboard monitoring terminal, a cloud computing platform and a verification terminal, wherein the shipboard monitoring terminal is used to collect ship operation data in real time, so that the cloud computing platform can calculate the carbon emission reduction based on the carbon emission reduction accounting method described in any one of claims 1 to 7, thereby uploading the collected data and calculation results to the verification terminal.

9. The carbon emission reduction monitoring system according to claim 8, characterized in that: The shipborne monitoring terminal includes a main control unit, a sensor unit and a communication unit, wherein the main control unit realizes data collection through the sensor unit, and then realizes communication transmission with the cloud computing platform through the communication unit.

10. The carbon emission reduction monitoring system according to claim 8, characterized in that: The cloud computing platform realizes data uploading through the blockchain evidence storage module.

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