Building energy system with predictive control of battery and green energy resources
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Solution Overview
Problem
Building energy systems face challenges in optimizing electric energy storage and discharge from batteries, especially when green energy sources are integrated, leading to difficulties in reducing energy costs and managing energy consumption effectively.
Innovation Solution
A building energy system incorporating HVAC equipment, green energy generation, and a predictive controller that optimizes energy consumption by defining energy components from grid, green, and battery sources, using energy pricing data to determine optimal power setpoints and temperature settings for HVAC and battery operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If batteries are used to store and discharge electric energy to reduce energy costs, then energy cost reduction is improved, but optimization difficulty increases due to multiple energy sources
Solution Approach 1:
The patent segments the total energy consumption into source-specific components (grid energy component, green energy component, battery energy component). This segmentation allows the controller to independently optimize each energy source's contribution to the total load, transforming a complex multi-source optimization problem into manageable sub-problems that can be solved separately while maintaining overall system coordination.
2Adaptability or versatility
If green energy generation is integrated to supplement grid energy, then energy sustainability is improved, but optimization difficulty increases
Solution Approach 1:
The patent applies segmentation by creating distinct energy components for each source (grid, green, battery) with separate optimization strategies. Each component can be independently managed according to its characteristics - green energy is optimized for sustainability, grid energy for cost-effectiveness, and battery energy for load balancing - thereby managing the complexity of integrating multiple energy sources with different properties.
Solution Approach 2:
The predictive controller is designed with multi-functionality to handle different types of energy sources simultaneously. It can optimize for multiple objectives (cost reduction, sustainability, load balancing) across different energy sources (grid, green, battery) using a unified optimization framework, making the system adaptable to various energy source combinations and configurations.
3Productivity
If predictive control is implemented to optimize energy components, then energy efficiency is improved, but system complexity increases
Solution Approach 1:
The patent implements predictive control that performs preliminary optimization calculations for future time steps. By predicting future energy prices, green energy availability, and load requirements, the controller can proactively determine optimal energy component allocations before actual consumption occurs, improving energy efficiency while managing complexity through advance planning rather than reactive adjustments.
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 effectively reduces energy costs by optimizing energy usage based on time-varying prices and demand charges, enhancing the integration of green energy and battery storage to minimize peak power consumption and improve overall energy efficiency.
Implementation Method 1
The battery is configured to store electric energy including at least a portion of the green energy provided by the green energy generation and grid energy purchased from an energy grid and configured to discharge the stored electric energy for use in powering the HVAC equipment
Data Source
AI summary
A building energy system includes HVAC equipment, green energy generation, a battery, and a predictive controller. The HVAC equipment provide heating or cooling for a building. The green energy generation collect green energy from a green energy source. The battery stores electric energy including at least a portion of the green energy provided by the green energy generation and grid energy purchased from an energy grid and discharges the stored electric energy for use in powering the HVAC equipment. The predictive controller generates a constraint that defines a total energy consumption of the HVAC equipment at each time step of an optimization period as a summation of multiple source-specific energy components and optimizes the predictive cost function subject to the constraint to determine values for each of the source-specific energy components at each time step of the optimization period.