Hot Water Supply Operation Plan Correction for Real-Time Load Matching
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing hot water supply systems face energy inefficiencies due to excessive boiling at night for predicted hot water needs, leading to potential hot water shortages and increased energy consumption, especially in systems with low-capacity storage tanks or heat source units.
Innovation Solution
A hot water supply system that dynamically adjusts its operation plan based on real-time load data and stored water levels, using a controller to optimize boiling times and temperatures through a primary and secondary side circuit heat exchange system, allowing for more efficient energy use and reduced reheating needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If hot water is boiled at late night to store in the hot water storage tank, then the energy saving property is improved by utilizing low electricity unit price, but excessive boiling is performed leading to impaired energy saving property when hot water supply load result falls below predicted load
Solution Approach 1:
The system performs preliminary clustering analysis on past hot water supply load data to identify typical load patterns, and generates operation plans in advance based on predicted loads. This allows the system to pre-determine optimal boiling schedules while avoiding excessive boiling by basing decisions on statistically derived typical patterns rather than overestimating requirements.
Solution Approach 2:
The operation plan correction unit continuously monitors actual hot water supply load results and compares them with predicted loads. When the actual load falls below the predicted load, the system corrects the operation plan to reduce subsequent boiling operations, thereby eliminating excessive boiling and improving energy saving property through real-time feedback adjustment.
2Quantity of substance
If hot water storage tank capacity is low or heat source unit capacity is low, then the system cannot store sufficient hot water, but performing multiple boiling or reheating operations throughout the day impairs energy saving property
Solution Approach 1:
The system dynamically adjusts the operation plan based on actual hot water supply load results and remaining stored hot water levels. The operation plan correction unit modifies boiling schedules in real-time to match actual consumption patterns, enabling the system to optimize energy usage while ensuring sufficient hot water supply even with limited storage capacity or heat source capacity.
Solution Approach 2:
The system changes operational parameters such as boiling timing, boiling duration, and reheating schedules based on clustered load patterns and actual consumption data. By adjusting these parameters dynamically, the system achieves efficient energy utilization while maintaining adequate hot water availability despite constraints on storage tank capacity or heat source unit capacity.
3Measurement precision
If hot water supply load prediction is based on past 7 days load result, then the prediction accuracy is improved, but unnecessary reheating operations occur when actual load is lower than predicted load
Solution Approach 1:
The system performs preliminary clustering analysis on past load data to identify typical load patterns before generating predictions. This statistical preprocessing improves prediction accuracy by filtering out anomalies and establishing representative load profiles, while the subsequent feedback mechanism ensures that predictions are adjusted to match actual consumption, preventing unnecessary reheating operations.
Solution Approach 2:
The operation plan correction unit uses feedback from actual hot water supply load results to correct prediction errors. When actual load differs from predicted load, the system adjusts future operation plans accordingly, eliminating unnecessary reheating operations while maintaining the benefits of accurate prediction-based planning.
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 approach improves energy saving properties by matching hot water supply with actual demand, reducing unnecessary boiling and reheating, and ensuring consistent hot water availability while minimizing energy consumption.
Implementation Method 1
a heat exchange unit (8) that exchanges heat between waters supplied thereto
Implementation Method 2
a boiling unit (2) that generates hot water
Data Source
AI summary
An operation plan correction unit is included which, after start of operation based on an operation plan, predicts a subsequent hot water supply load at a predetermined day on the basis of a hot water supply load result at the predetermined day, and changes a subsequent operation plan at the predetermined day generated by an operation plan generation unit, on the basis of the hot water supply load predicted again and a remaining amount of stored hot water in a hot water storage tank.