Zero-carbon heavy truck transport capacity system scheduling method and system based on valley electricity and photovoltaic

Abstract

The invention relates to a zero-carbon heavy truck transport capacity system based on valley electricity and photovoltaic power and a scheduling method. According to the system, through cooperative work of the intelligent hydrogen production module, the zero-carbon transport capacity module and the carbon energy cooperation platform, the problems that existing hydrogen energy logistics is high in cost and the carbon footprint is not credible are solved. According to the method, the hydrogen production schedule and the vehicle path are jointly optimized, so that the hydrogen cost and the empty driving rate are remarkably reduced, and a credible zero-carbon transportation voucher is generated by utilizing a block chain technology.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of energy management and intelligent logistics, and in particular to a collaborative scheduling system and method combining green power, on-site hydrogen production and heavy truck transportation. BACKGROUND

[0002] In the prior art, the hydrogen price of hydrogen energy heavy truck logistics line is as high as 40-50 yuan / kg, the empty running rate is generally more than 15%, and the source of gray hydrogen cannot be traced reliably, which makes it difficult for the entire transportation chain to obtain third-party carbon certification, and seriously restricts the scale of zero-carbon logistics. SUMMARY

[0003] (I) Invention purpose: lock low-cost green electricity from the source, realize energy and transport capacity collaborative optimization, and generate reliable full-chain zero-carbon data.

[0004] (II) Technical solution: in order to achieve the above invention purpose, the present application adopts the following technical solution:

[0005] In a first aspect, the present application provides a zero-carbon heavy truck transport capacity scheduling method based on valley electricity and photovoltaic, characterized in that it comprises the following steps: a data input step for real-time or predictive acquisition of 24-72 hours of future step electricity price data, photovoltaic power generation prediction data, real-time storage data of hydrogen storage tanks, dynamic data of hydrogen energy heavy trucks, and transportation order data from a customer platform; a joint optimization step to minimize the total electricity cost and vehicle fleet empty running cost as the comprehensive objective function, and establish a joint optimization mathematical model of hydrogen production scheduling and vehicle path planning; a solution and decision step for solving the joint optimization mathematical model using a mathematical programming algorithm, outputting a hydrogen production operation plan within the next 24 hours, and the task sequence, driving path and planned hydrogen refueling time point of each hydrogen energy heavy truck; an execution and monitoring step for issuing the hydrogen production operation plan and vehicle scheduling plan to the intelligent hydrogen production module and zero-carbon transport capacity module for execution, and real-time monitoring of the execution, dynamic adjustment and rescheduling of the generated deviation; a certification and storage step for automatically triggering a carbon footprint accounting program after completing the transportation task, packaging the certified green electricity source data, hydrogen production energy consumption data, vehicle driving distance and hydrogen consumption data, and generating an unalterable digital zero-carbon transportation certificate using blockchain technology.

[0006] Secondly, the present invention provides a zero-carbon heavy-duty truck transportation capacity system for implementing the method described in the first aspect, characterized in that it includes: a smart hydrogen production module, deployed within a logistics park, equipped with a PEM electrolyzer, whose power input terminal is connected to the park's photovoltaic power generation system and the power grid via a smart meter, for prioritizing the scheduling of off-peak electricity and surplus photovoltaic power for hydrogen production; a zero-carbon transportation capacity module, composed of multiple hydrogen fuel cell heavy-duty trucks, each equipped with an on-board IoT terminal for real-time transmission of vehicle location, hydrogen storage capacity, and operational status data; and a carbon energy collaboration platform, communicatively connected to the smart hydrogen production module and the zero-carbon transportation capacity module, the platform comprising:

[0007] • The data acquisition unit is configured to acquire the tiered electricity price, photovoltaic power generation forecast, hydrogen storage tank capacity, vehicle dynamics, and transportation order data;

[0008] • The collaborative scheduling algorithm unit is configured to run the joint optimization mathematical model and generate hydrogen production scheduling instructions as well as vehicle routes and hydrogen refueling instructions;

[0009] • The carbon trace authentication unit is configured to generate the digital zero-carbon transport certificate based on blockchain technology.

[0010] (III) Beneficial Effects: Compared with the prior art, the beneficial effects of the present invention are specifically reflected in the following three aspects:

[0011] 1. Significantly disruptive cost reduction: Through the aforementioned joint optimization scheduling, the system can guide the hydrogen production module to concentrate on producing hydrogen during off-peak electricity hours (e.g., 00:00-08:00), which are when electricity prices are lowest. Combined with photovoltaic power in the industrial park, the overall cost of hydrogen is reduced from RMB 40-50 / kg at external hydrogen refueling stations to less than RMB 20 / kg. This achieves a cost disruption to the existing hydrogen energy logistics model and removes economic obstacles for the large-scale promotion of zero-carbon logistics.

[0012] 2. Significantly improved operational efficiency: By introducing a "hydrogen safety threshold" constraint and optimizing it in conjunction with vehicle routes, the system can reduce the fleet's empty-running rate from the industry average of over 15% to below 10.5% while ensuring uninterrupted transport capacity, thus significantly improving asset utilization and operational efficiency.

[0013] 3. Trustworthy and Traceable Environmental Value: By leveraging the distributed and immutable characteristics of blockchain technology, the green data of the entire chain (green electricity -> hydrogen production -> transportation) is solidified into digital certificates with unique hash values. This solves the pain points of traditional models where carbon footprints cannot be self-verified and are difficult to obtain third-party certification, making "zero-carbon transportation" a measurable, reportable, verifiable (MRV) real asset that can be directly used for carbon market trading. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the overall architecture of the zero-carbon heavy-duty truck transportation system provided in this embodiment of the invention.

[0017] Figure 2 This is a functional block diagram of the carbon energy synergy platform provided in the embodiments of the present invention.

[0018] Figure 3 This is a flowchart of the joint optimization scheduling method provided in the embodiments of the present invention. Detailed Implementation

[0019] Example 1 (Hardware Deployment):

[0020] This embodiment provides a hardware deployment scheme for a zero-carbon heavy-duty truck transportation system based on off-peak electricity and photovoltaics. A 35MPa hydrogen production station is constructed within the logistics park, with the following core connections:

[0021] 1. The park's power grid is connected to a 380V AC cable via a box-type transformer, which is then connected to a smart meter and a rectifier cabinet, ultimately supplying power to a PEM electrolyzer with a rated power of 500kW and a rated hydrogen production capacity of 10kg / h.

[0022] 2. The hydrogen outlet pipeline of the PEM electrolyzer is connected in sequence to a fixed hydrogen storage cylinder group consisting of four 2000L carbon fiber wound hydrogen storage cylinders via a high-pressure ball valve and a cooling and purification device.

[0023] 3. The outlet of the hydrogen storage cylinder group is connected to a dual-nozzle hydrogen refueling machine with a rated pressure of 35MPa via a pressure regulating valve, for refueling hydrogen fuel cell heavy trucks.

[0024] 4. The inverter AC output terminal of the photovoltaic system in the park is connected in parallel with the grid connection point, and its power generation is also measured by the smart meter, thereby realizing complementary power supply and accurate metering of off-peak electricity and photovoltaic power.

[0025] 5. The server located in the computer room runs the aforementioned collaborative scheduling algorithm, establishes communication connections with the smart meter, the pressure sensor of the hydrogen storage cylinder group, and the vehicle's on-board telematics processor (T-Box) via Ethernet, collects electricity price, hydrogen storage amount and vehicle location data at a frequency of once every 15 minutes, and completes calculations and issues hydrogen production power instructions and vehicle route planning instructions within 30 seconds.

[0026] 6. After the transportation task is completed, the server automatically packages the green electricity source data, hydrogen production energy consumption data and vehicle driving data into a structured data package (such as JSON format), and generates a digital zero-carbon transportation certificate file (such as PDF format) with a unique hash value and immutability by calling the blockchain software development kit (SDK).

[0027] Example 2 (Algorithm Flow):

[0028] This embodiment describes in detail the operation process of the cooperative scheduling algorithm.

[0029] • Data input: The system acquires tiered electricity pricing data for the next 24 hours, photovoltaic power generation forecast data, pending transportation order data, and real-time location and remaining hydrogen data of each vehicle in the fleet.

[0030] • Decision output: The algorithm outputs two types of instructions: First, the start-up and shutdown status of the electrolyzer and the hydrogen production power instructions for each time period in the next 24 hours; Second, the planned task sequence, designated hydrogen refueling stations and estimated arrival time for each hydrogen-powered heavy truck.

[0031] • Optimization Solution: The core of the algorithm is to establish a mathematical optimization model with the objective of minimizing the sum of total electricity costs and fleet empty-run costs. This model is solved using a mathematical programming solver (e.g., Gurobi), where the empty-run cost can be converted to RMB 1.8 per kilometer according to industry standards. The model's constraints include hydrogen supply and demand balance constraints, final delivery time constraints for all transportation orders, and a constraint that the vehicle's hydrogen load must not fall below a preset safety threshold.

[0032] • Closed-loop control: The system monitors the execution process in real time. When the deviation between the actual hydrogen consumption and the hydrogen production of the vehicle exceeds 5%, it will automatically trigger the model to be resolved and push the updated scheduling plan to the relevant execution units.

[0033] • Technical Results: Through the scheduling of this algorithm, the system can concentrate on producing sufficient hydrogen during off-peak electricity hours from 00:00 to 08:00, ensuring that the overall hydrogen cost does not exceed 20 yuan / kg, and reducing the fleet's empty-running rate from the industry average of 18% to below 10.5%. The carbon footprint data across the entire chain is uploaded to the blockchain in real time after the task is completed, ensuring its authenticity and reliability.

Claims

1. A zero-carbon heavy-duty truck capacity scheduling method based on off-peak electricity and photovoltaic power, characterized in that, Includes the following steps: a) Obtain tiered electricity pricing data, photovoltaic power generation forecast data, transportation order queues, real-time vehicle status, and hydrogen storage tank capacity for the next 24 to 72 hours; b) Establish a joint optimization model for hydrogen production scheduling and vehicle routing with the objective function of minimizing "total electricity cost + fleet empty running cost"; c) Solve the model and output the "Hydrogen Production Operation Plan" and "Vehicle Dispatch and Hydrogen Refueling Plan"; d) The plan will be distributed to the smart hydrogen production module and the zero-carbon transportation module to monitor the execution process in real time and make dynamic adjustments to any deviations; e) Upon completion of the task, the data on green electricity sources, hydrogen production energy consumption, and vehicle driving and hydrogen consumption will be automatically packaged and uploaded to the blockchain to generate a digital zero-carbon transportation certificate.

2. The method according to claim 1, characterized in that: The hydrogen production scheduling model prioritizes starting the PEM electrolyzer during the period with the lowest electricity price, centrally producing and storing the hydrogen needed during the day.

3. The method according to claim 1, characterized in that: The vehicle route planning incorporates a "hydrogen safety threshold" constraint. When the predicted hydrogen level is below the threshold, the next task destination is automatically planned to be the nearest hydrogen refueling station.

4. The method according to claim 1, characterized in that: The joint optimization model is solved using mixed integer linear programming or genetic algorithms.

5. The method according to claim 1, characterized in that: The digital zero-carbon transport certificate is generated based on blockchain technology, has a unique hash value, and can be used for carbon trading.

6. A zero-carbon heavy-duty truck transportation system implementing the method of any one of claims 1 to 5, characterized in that, include: - A smart hydrogen production module, deployed within a logistics park, includes a PEM electrolyzer, a hydrogen storage tank, and a smart meter, which is connected to the power grid and a photovoltaic system; - Zero-carbon transportation module, including hydrogen fuel cell heavy trucks, each equipped with an on-board IoT terminal for transmitting location, hydrogen quantity, and operating status; - The carbon energy collaboration platform includes a data acquisition unit, a collaborative scheduling algorithm unit, and a blockchain carbon trace authentication unit; The cooperative scheduling algorithm unit is used to execute the joint optimization method described in claim 1.

7. The system according to claim 6, characterized in that: The data acquisition unit is communicatively connected to the power grid, photovoltaic system, vehicle terminal, and hydrogen storage tank sensors to obtain real-time data on electricity price, photovoltaic power, hydrogen quantity, orders, and vehicles.

8. The system according to claim 6, characterized in that: The blockchain carbon trace authentication unit is used to package green electricity, hydrogen production, and transportation data into blocks to generate an immutable zero-carbon transportation certificate.

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