Zero-Energy Building Hydrogen Planning Under Source-Load Uncertainty
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Solution Overview
Problem
Existing studies do not adequately address how to utilize hydrogen energy devices to improve the operation efficiency and flexibility of energy supply systems in zero energy buildings, particularly in integrating electric, thermal, and hydrogen energy systems effectively.
Innovation Solution
An electric-thermal-hydrogen multi-energy device planning method is developed, which includes constructing operation constraints for electric, thermal, and hydrogen devices, establishing a robust planning model considering source-load uncertainties, and using an alternating optimization procedure based on column-and-constraint generation algorithms to optimize device planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If hydrogen energy devices are integrated into zero energy buildings, then renewable energy utilization efficiency and operation flexibility are improved, but device complexity and system configuration difficulty increase
Solution Approach 1:
The planning method segments the complex multi-energy system into distinct functional modules: photovoltaic devices for electricity generation, wind turbines for electricity generation, fuel cells for hydrogen-to-electricity conversion, electrolyzers for electricity-to-hydrogen conversion, and hydrogen storage devices for seasonal and intra-day storage. Each module has its own operational constraints and characteristics, allowing independent optimization while maintaining overall system flexibility.
Solution Approach 2:
The patent introduces a temporal dimension by implementing both seasonal hydrogen storage (across different months) and intra-day hydrogen storage (within the same day). This multi-timescale approach adds a new dimension to energy management, enabling the system to balance renewable energy supply and demand across different time horizons simultaneously, thereby improving adaptability without proportionally increasing complexity.
2Reliability
If robust planning model considering source-load uncertainties is established, then operation reliability is improved, but computational complexity and solution difficulty increase
Solution Approach 1:
The planning method performs preliminary actions by pre-establishing operational constraints for all devices before actual operation. These constraints include minimum/maximum output limits, on-off states, ramping rates, and efficiency parameters. By defining these boundaries in advance, the system can quickly assess reliability under uncertainty without performing complex real-time calculations, thus improving operational reliability while controlling computational complexity.
Solution Approach 2:
The patent implements a two-stage robust optimization approach where the first stage determines device installation capacities and the second stage optimizes operational strategies under uncertainty. This partial action approach solves the problem incrementally rather than attempting to solve all uncertainties simultaneously, reducing computational complexity while maintaining reliability. The method considers representative uncertainty scenarios rather than all possible scenarios, applying partial action to achieve sufficient reliability.
3Productivity
If seasonal and intra-day complementation of renewable energy is achieved, then renewable energy utilization efficiency is improved, but system configuration complexity and control difficulty increase
Solution Approach 1:
The patent merges seasonal hydrogen storage and intra-day hydrogen storage functions into a unified hydrogen energy system. The fuel cell, electrolyzer, and hydrogen storage devices serve dual purposes: storing excess renewable energy seasonally (e.g., summer solar energy for winter use) and balancing intra-day fluctuations (e.g., daytime excess for nighttime deficit). This merging allows the system to achieve multi-timescale complementation while using a standardized set of devices, reducing overall configuration complexity compared to implementing separate storage systems.
Solution Approach 2:
The hydrogen storage device is designed with multi-functionality, serving both seasonal storage (long-term) and intra-day storage (short-term) purposes. The same physical hydrogen storage infrastructure can be charged during seasonal excess periods and discharged during seasonal deficits, while also providing rapid response for intra-day balancing. This universality improves renewable energy utilization efficiency across different timescales without requiring separate dedicated storage systems for each function, thereby controlling system configuration complexity.
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
This method enhances the renewable energy utilization efficiency, operation economy, and flexibility of zero energy buildings by achieving seasonal and intra-day complementation of renewable energy from photovoltaics and wind turbines, thereby improving the overall operation efficiencies and benefits of zero energy buildings.
Implementation Method 1
the output electric power of the photovoltaic and wind turbine
Implementation Method 2
the output electric power of the photovoltaic and wind turbine
Implementation Method 3
constructing operation constraints of hydrogen devices including the electrolyzer, the fuel cell and the hydrogen storage device
Implementation Method 4
constructing operation constraints of hydrogen devices including the electrolyzer, the fuel cell and the hydrogen storage device
Data Source
AI summary
The present invention describes an electric-thermal-hydrogen multi-energy device planning method for zero energy buildings, including the following specific steps: firstly, constructing operation constraints of electric and thermal devices in the zero energy buildings; secondly, constructing operation constraints of hydrogen devices including the electrolyzer, the fuel cell and the hydrogen storage device; then, in view of constraints on annual zero energy of the buildings, establishing the robust electric-thermal-hydrogen multi-energy device planning model considering source-load uncertainties; and finally, solving the robust electric-thermal-hydrogen multi-energy device planning model of the zero energy buildings by adopting an alternating optimization procedure based column-and-constraint generation algorithm. By using the zero energy buildings, the planning method disclosed by the present disclosure plays important roles in aspects of promoting the development and utilization of renewable energy on the demand side, reducing energy consumption in the field of buildings, and reducing the emission of greenhouse gases.