EV-HVAC Joint Control Using Thermal Mass and Dynamic Scheduling
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Solution Overview
Problem
Existing building energy management systems struggle to efficiently manage the increased energy demand from electric vehicles (EVs) due to their stochastic charging patterns, which overlap with peak electricity pricing hours, leading to higher energy costs and sub-optimal performance in HVAC systems.
Innovation Solution
A joint control system that utilizes a trained HVAC agent and a trained EV agent to optimize EV charging/discharging rates and HVAC power draw, minimizing overall energy consumption while maintaining thermal comfort and EV state of charge constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If EV charging is allowed during working hours, then user convenience is improved, but energy costs increase due to peak-time pricing
Solution Approach 1:
The system performs preliminary cooling of the building during off-peak hours when electricity prices are low, storing thermal energy in the building's thermal mass. This allows the HVAC system to be reduced or shut off during peak pricing hours while maintaining comfort, thereby avoiding high energy costs during EV charging periods
Solution Approach 2:
The system dynamically adjusts HVAC operation and EV charging schedules based on real-time electricity pricing signals, weather forecasts, and building thermal state. This dynamic coordination allows the system to shift loads away from peak pricing periods while maintaining both user convenience and cost efficiency
2Quantity of substance
If EV charging load is added to building, then power demand increases, but system complexity increases for managing stochastic power demand
Solution Approach 1:
The system merges EV charging management with HVAC control into a unified energy management framework. By coordinating these two major loads together and treating them as interchangeable flexible demands, the system simplifies control complexity while efficiently managing total power demand
Solution Approach 2:
The system implements closed-loop feedback control that continuously monitors electricity prices, building thermal state, EV state of charge, and weather conditions. This feedback enables automatic dynamic scheduling adjustments without requiring complex manual intervention, managing stochastic demand through real-time adaptive coordination
3Temperature
If HVAC system operates at full capacity, then thermal comfort is maintained, but energy consumption increases during peak pricing hours
Solution Approach 1:
The system pre-cools or pre-heats the building during off-peak hours when electricity prices are low, storing thermal energy in the building's thermal mass (walls, floors, furniture). This thermal storage allows the HVAC system to operate at reduced capacity or be temporarily shut off during peak pricing hours while maintaining thermal comfort
Solution Approach 2:
The system introduces thermal mass of the building structure as an intermediary energy storage medium between the HVAC system and the environment. This thermal buffer decouples the HVAC operation from immediate thermal demands, enabling load shifting to off-peak hours and reducing peak-hour energy consumption
Data Source
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AI summary
Current approaches for minimizing energy requirement of buildings are not designed to handle multi-input multi-output systems, such as electric vehicle-heating, ventilation, and air conditioning (EV-HVAC) system. Further, scalability of the solutions is another challenge. Present disclosure provides method and system for jointly controlling EV-HVAC system of a building. The system utilizes the potential of electric vehicle (EVs) in building energy management by treating EVs as buffers with random availability. The system performs EV-HVAC joint control that scales seamlessly with increasing EVs while respecting both thermal constraints of HVAC and state of charge (SoC) constraints of EV users.