A method for scheduling and controlling a building heat pump unit

By predicting heat load and optimizing global scheduling and control, the problems of unpredictability and imbalance in heat pump units have been solved, achieving low-consumption, stable, and high-precision operation of heat pump units to meet the energy supply needs of smart buildings.

CN122429408APending Publication Date: 2026-07-21济南工达捷能科技发展有限公司
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
济南工达捷能科技发展有限公司
Filing Date
2026-04-24
Publication Date
2026-07-21

AI Technical Summary

Technical Problem

Existing heat pump unit scheduling and control systems suffer from problems such as lack of heat load prediction capability, imbalance in heat load distribution among multiple units, insufficient energy supply stability, and poor anti-interference capability due to fixed power parameters. This results in high operating energy consumption, large heating fluctuations, and severe losses due to frequent equipment start-ups and shutdowns, failing to meet the low-consumption, stable, and precise control requirements of smart buildings.

Method used

By collecting historical building heat load time series data and future meteorological data, and combining LSTM prediction model and artificial bee colony algorithm, heat load demand forecast values ​​are generated. An improved deep Q network and PID controller are constructed, and an improved dual heuristic algorithm is used to optimize the PID controller parameters to achieve global optimization and precise control.

Benefits of technology

It enables building heat pump units to move from post-event correction to pre-event prediction, global optimization, and precise control, thereby reducing operating energy consumption, improving the balance of heat load distribution and control accuracy, reducing losses from frequent start-up and shutdown of units, and meeting the energy supply and management needs of smart buildings and green buildings.

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Abstract

The present application belongs to the technical field of dispatching control, and particularly relates to a kind of dispatching control method for building heat pump unit.The method first collects building historical heat load time series data and meteorological data, selects core meteorological influence factor, obtains future heat load demand prediction value through LSTM model combined with meteorological correction;Then build a scheduling model with optimal energy consumption as the target, introduce unit operation constraints, and generate pre-scheduling feasible solution by using artificial bee colony algorithm global optimization;Subsequently, an improved deep Q network with time sequence attention mechanism is constructed, and the final operating parameters of each unit are output;Finally, a hierarchical integral PID controller is built, and the PID parameters are optimized by improving the double heuristic algorithm to realize accurate control of the unit.The present application solves the problems of existing heat pump scheduling without pre-judgment, high energy consumption, unbalanced load distribution and poor control stability, and can realize low consumption, stable and high precision operation of heat pump unit, and adapt to the energy management and control needs of intelligent building and green building.
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