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[DHP] Demand based smart water heater with multi-factors control Disclosure Number: IPCOM000253196D
Publication Date: 2018-Mar-13
Document File: 3 page(s) / 72K

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Demand based smart water heater with multi-factors control

As smarter city technology evolves, a finer grain and dynamic control on energy consumers (e.g., street lights, appliances, etc.) can reduce energy consumption and reduce energy waste. One example is the use of cognitive computing and artificial intelligence to dynamically turn on street lights based on need, instead of based on time of day or level of darkness. This need-based technology detects cars or humans in the area that might need street lights, and accordingly activates the lights. A similar goal to reduce energy consumption at a finer grain and in a dynamic manner is desired for smart homes. The hot water heater is one of the top energy consumers in a home.

The novel contribution is a demand-based smart water heater with multiple factors of control. Based on demands, the system adjusts related factors (e.g., temperature, volume, hot/cold water ratio, etc.) in a water heater control loop to achieve energy savings.

This system performs three main functions:

• Based on demand, dynamically changes the water temperature and water volume for a water heating equipment (e.g., point of use water heater or water heater with storage). This demand includes both the desired water temperature and water volume consumption for a specific time.

• Using an electronically controlled hot and cold-water release valve together with the real-time underground water temperature, reduces the water temperature in the tank and defers reheating of hot water in the tank

• Uses a step-wise water volume increase mechanism to satisfy the demands

The demand can be derived from a historical usage pattern. The determination of a historical pattern is not a novelty for this disclosure; it is used as an enabling art.

For example, User A typically uses one gallon of water for washing hands throughout the day and consumes 30 gallons of water after 8:00pm for a shower. For hand washing, the water temperature is satisfactory at 90 degrees. For a shower, User A prefers water temperature at 105 degrees. In the winter, the room-temperature water is 70 degrees and underground water is 50 degrees. In a completely manual scenario, User A user turns on the tap with X amount of "hot water". The hot water ratio increases when the underground-temperature water starts to come enter the flow (the room temperature water ran out). For both adjustments, User A uses a hand to feel the water temperature. If the water heater does not have enough hot water stored (or the heating is slower than consumption), then the hot water might run out. In this case, User A

might adjust the heater to a higher temperature, such that the hot water will last longer (because lesser volume of hot water is required for each unit of cold water).

With the novel smart water heater, User A's consumption pattern and requirement is learned predicted (existing art). Based on the user-desired temperature at a specific time and underground water temperature, the...