Power shift system to store and distribute energy with direct compressor drive
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Solution Overview
Problem
The imbalance between renewable energy supply and demand leads to significant waste and reliance on non-renewable sources, as existing energy storage technologies suffer from inefficiencies and high costs, making it challenging to efficiently store and distribute energy on a micro-grid scale.
Innovation Solution
A machine-learning energy management system that harnesses renewable energy during low-demand periods, converts it into compressed air, and stores it for peak demand using an isothermal process, minimizing thermal and mechanical inefficiencies, and directly drives a coolant compressor to enhance system efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing energy storage technologies are used to store renewable energy, then energy can be stored for later use, but the systems suffer from high costs, inefficiencies, and high infrastructure requirements
Solution Approach 1:
The patent extracts the core energy storage function from complex existing systems (batteries, pumped hydro, traditional CAES) and implements it using a simplified compressed air storage system with above-ground tanks, eliminating the need for complex infrastructure while maintaining storage reliability
Solution Approach 2:
The patent replaces traditional mechanical energy storage mechanisms (moving parts in batteries, water movement in pumped hydro, mechanical compressors in traditional CAES) with a static compressed air storage system that uses pressure vessels and control valves, reducing mechanical complexity while maintaining functionality
2Productivity
If renewable energy is produced during low-demand periods, then green energy generation increases, but the energy must be curtailed due to supply-demand imbalance
Solution Approach 1:
The patent implements preliminary action by storing compressed air during low-demand periods when renewable energy is abundant, preparing energy storage in advance of peak demand periods, thereby preventing curtailment and enabling later energy discharge when needed
Solution Approach 2:
The patent changes the temporal parameter of energy availability by storing energy when supply exceeds demand and releasing it when demand exceeds supply, transforming the mismatched intermittent renewable energy into a reliable on-demand power source that eliminates curtailment losses
3Quantity of substance
If traditional CAES systems are used for energy storage, then large-scale energy storage is achieved, but thermal inefficiencies and mechanical losses occur during compression and expansion
Solution Approach 1:
The patent converts the harmful thermal energy generated during compression into a beneficial resource by capturing and storing it for later use during expansion, transforming what was previously wasted heat into a useful input that improves overall system efficiency and reduces energy losses
Solution Approach 2:
The patent merges the compression and expansion processes into a integrated system where the thermal energy from compression is directly utilized in expansion, combining previously separate thermal management functions into a unified efficient process that minimizes mechanical losses
4Reliability
If peak energy demand is met using non-renewable sources, then reliable power supply is ensured, but greenhouse gas emissions increase
Solution Approach 1:
The patent introduces compressed air storage as an intermediary between intermittent renewable energy generation and steady peak demand, enabling renewable energy to reliably meet peak demand without requiring fossil fuel backup, thereby eliminating greenhouse gas emissions while maintaining power supply reliability
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 solution provides reliable, efficient, and cost-effective energy storage and distribution, reducing curtailment of renewable energy and minimizing environmental impact, while enabling grid resiliency and independence on a micro-grid scale.
Implementation Method 1
a compressor mechanically coupled to the wind turbine to convey rotational energy directly from the wind turbine to the compressor
Implementation Method 2
a wind turbine having a rotor, a nacelle, and a tower
Implementation Method 3
The compressor mechanically coupled to the wind turbine conveys rotational energy directly from the wind turbine to the compressor, which compresses air into storage tanks
Implementation Method 4
converts it into compressed air, and stores it for peak demand using an isothermal process, minimizing thermal and mechanical inefficiencies
Data Source
AI summary
Disclosed is a machine learning energy management system that regulates incoming energy sources into compressed air storage operations and energy generation. Compressed air is directed into a thermoregulation system that cycles storage tanks according to physical qualities. A boost impulse creates energy to initiate the electrical energy generation. The compressed air operations and energy generation leverage the heating and cooling of an external HVAC system to improve performance and conservation of the heating and cooling for an external building, wherein compressed air is used to drive a coolant compressor. The system combines real-time data, historical performance data, algorithm control, variable air pressure for demand-based generation, tank-to-tank thermal cycling, building air heat exchanger, and boost pulsation to achieve optimized system efficiency and responsiveness.