System, method and computer program product for energy allocation
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Solution Overview
Problem
The increasing cost of energy resources and the underutilization of renewable energy sources, such as waste vegetable oil and solar/wind energy, necessitate the development of systems that can efficiently conserve and allocate energy resources, particularly in food processing facilities.
Innovation Solution
A system that filters waste vegetable oil to power a generator, producing both AC and DC power, which is then blended with photovoltaic or wind energy to sustain continuous AC power operation, both on and off the grid, while utilizing a predictive algorithm for real-time energy management and selling excess power back to the utility grid, and incorporates a multi-speed condenser and fan system to minimize energy consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If waste vegetable oil is filtered and used to power a generator, then energy conservation and reduced reliance on non-renewable energy sources is achieved, but the system complexity and initial investment cost increases
Solution Approach 1:
The system converts waste vegetable oil, which would otherwise be discarded or require expensive disposal, into a valuable energy source. The filtration system transforms this waste material into usable fuel for the generator, simultaneously achieving waste management and energy production goals while reducing reliance on non-renewable energy sources
Solution Approach 2:
The generator system serves multiple functions: it generates electrical power from waste vegetable oil, provides backup power during outages, and can be integrated with existing HVAC systems. The system can operate in multiple modes (generator-only, hybrid with solar, or grid-connected), making it adaptable to various energy needs and scenarios
2Reliability
If a blending module is used to combine generator power with photovoltaic or wind DC power, then continuous AC power operation is sustained, but the device complexity and control requirements increase
Solution Approach 1:
The blending module merges multiple power sources (generator, photovoltaic panels, wind turbines) into a unified AC power output. It combines DC power from renewable sources with generator power, converting and synchronizing them to provide continuous, stable AC electricity for HVAC systems and other loads, ensuring uninterrupted operation regardless of individual source availability
Solution Approach 2:
The blending module acts as an intermediary between disparate power sources and the electrical load. It manages the interface between DC and AC systems, handles power conversion and synchronization, and provides a buffer that smooths out fluctuations from intermittent renewable sources, delivering consistent power to the HVAC system
3Productivity
If a predictive algorithm is used for real-time energy management, then energy allocation is optimized, but the computational requirements and system complexity increase
Solution Approach 1:
The predictive algorithm performs preliminary analysis of energy production forecasts and consumption patterns before making allocation decisions. It predicts future power availability from renewable sources and generator output, pre-calculating optimal energy distribution strategies to maximize efficiency and minimize costs before real-time conditions change
Solution Approach 2:
The system continuously monitors actual power generation from all sources and real-time energy consumption, feeding this data back to the predictive algorithm. The algorithm adjusts energy allocation predictions based on deviations between forecasted and actual performance, optimizing the mix of renewable and generator power dynamically to maintain efficiency
4Use of energy by moving object
If a multi-speed condenser and fan system is used to minimize energy consumption, then energy efficiency is improved, but the device complexity and control requirements increase
Solution Approach 1:
The condenser and fan system operates with variable speeds rather than fixed speed, allowing dynamic adjustment to match actual cooling requirements and available power. The system can modulate fan and condenser speeds based on ambient conditions, thermal loads, and power availability, optimizing energy consumption while maintaining effective heat rejection
Solution Approach 2:
The system changes operational parameters (speed, flow rate) of the condenser and fan based on real-time conditions. By adjusting these parameters rather than operating at constant maximum capacity, the system minimizes energy consumption while adapting to varying thermal loads and power source availability
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 system effectively conserves energy by utilizing waste resources, reduces reliance on non-renewable energy, and optimizes energy allocation through real-time management, ensuring continuous power supply and energy efficiency.
Implementation Method 1
operating an on-site engine with the filtered vegetable oil to drive a generator, the generator providing an alternating current (AC) power supply
Implementation Method 2
blending of solar and generator power
Implementation Method 3
the air conditioning system comprises a multi-speed condenser and fan setting controlled by preprogrammed software
Data Source
AI summary
An energy allocation system includes an air conditioning unit with a VDC compressor and a fan configured for variable speed output. The air conditioning unit further includes a built-in power generator. A blending module is configured to split the generator-produced power into AC and DC allocations and combine the DC power allocation with DC power received from a DC energy device.