Hydrogen Production Planning for Multi-Source Demand Forecasting
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current hydrogen production systems face challenges in efficiently managing and predicting the demand for different types of hydrogen (green, grey, and blue) produced from renewable and non-renewable energy sources, leading to inefficiencies in operation and resource allocation.
Innovation Solution
A planning apparatus that includes a prediction unit and a control unit, which utilize machine learning models to predict demand, electricity prices, and certificate prices, generating operation and transportation plans to optimize hydrogen production and distribution based on real-time data and historical trends.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If hydrogen production systems manage multiple types of hydrogen (green, grey, blue) without advanced prediction, then production can proceed, but demand prediction accuracy and resource allocation efficiency deteriorate
Solution Approach 1:
The patent segments hydrogen production into multiple types (green, grey, blue) based on different energy sources and production methods. The prediction system is divided into separate prediction models for each hydrogen type, allowing accurate demand forecasting for each category while managing complexity through modular architecture. Each prediction model processes specific data relevant to its hydrogen type.
Solution Approach 2:
The system performs preliminary demand prediction and operation plan generation before actual hydrogen production and distribution. By predicting future demand for different hydrogen types and pre-generating operation plans, the system enables proactive resource allocation and production scheduling, improving accuracy while streamlining subsequent execution.
2Productivity
If traditional operation management is used for hydrogen production, then operational simplicity is maintained, but productivity and resource allocation efficiency deteriorate
Solution Approach 1:
The patent implements feedback mechanisms where prediction results inform operation plan generation, and actual production data feeds back into refining future predictions. The control system continuously adjusts hydrogen production and distribution based on predicted demand, electricity prices, and certificate prices, improving productivity through data-driven decision-making while managing complexity through automated feedback loops.
Solution Approach 2:
The system dynamically changes operational parameters (production rates, distribution schedules, energy source selection) based on predicted demand and market conditions. By adjusting these parameters optimally for different hydrogen types and market scenarios, the system maximizes productivity and resource allocation efficiency while using software-based parameter management to control system complexity.
3Loss of energy
If hydrogen production optimizes for cost without considering environmental factors, then operational costs decrease, but environmental sustainability deteriorates
Solution Approach 1:
The patent applies different production methods and energy sources locally according to specific needs and conditions. Green hydrogen production using renewable energy is selected when environmental sustainability is prioritized, while grey or blue hydrogen may be used when cost optimization is the primary goal. This local quality approach allows the system to balance operational costs with environmental impact on a case-by-case basis.
Solution Approach 2:
The system dynamically adjusts the mix of hydrogen types produced and the energy sources used based on real-time and predicted conditions. When renewable energy availability and certificate prices favor green hydrogen, the system increases green hydrogen production to reduce environmental impact. When economic conditions change, the system can dynamically shift to other hydrogen types, maintaining flexibility to balance cost and sustainability.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system enables efficient generation, storage, and distribution of hydrogen by accurately predicting demand and optimizing production plans, reducing waste and operational costs while ensuring environmental sustainability.
Implementation Method 1
a hydrogen production apparatus for generating hydrogen by electrolysis of water is known
Data Source
AI summary
Provided is an apparatus for generating a operation plan of a hydrogen production system comprising a hydrogen production apparatus, comprising: a demand predicting unit for generating a predicted demand amount for each of a plurality of types of hydrogen with a different environmental load of production over a target period of the operation plan; and an operation planning unit for generating the operation plan, which is for generating a plurality of types of hydrogen with a different environmental load of production by the hydrogen production apparatus, based on a predicted hydrogen demand amount of each of the plurality of types of hydrogen.