Model predictive control-based energy consumption flexibility control method for intelligent building

Abstract

The invention discloses a model predictive control-based energy consumption flexibility control method for an intelligent building. The method includes the following steps that: an intelligent building energy consumption prediction model considering different heating zones in the building is constructed according to building heat storage characteristics, and the building system, adopted as a flexible and controllable unit, is integrated into a power distribution network; based on model predictive control, room temperature is optimally adjusted within a temperature comfort range through the internal heating ventilation air conditioning system of the building, so that the flexible management of the energy consumption of the building system can be realized, and the operating costs of the building can be reduced; and optimized scheduling analysis is performed on building clusters under the control of different heating ventilation air conditioning systems, and comparative analysis is performed on the impact of the optimized scheduling of the building cluster on the operating state of the power distribution network. With the method of the invention adopted, the demand response potentialof the intelligent building can be fully explored under the premise of ensuring temperature comfort, the operating cost of the building can be reduced; and the problem of large deviation between the day-ahead control plan of the building and an actual operation scene which is caused by renewable energy output prediction data error can be solved.

Description

technical field [0001] The invention relates to the field of power distribution networks, in particular to a model predictive control-based flexible control method for energy use in intelligent buildings. Background technique [0002] In recent years, scholars at home and abroad have carried out a series of work on the energy consumption prediction of large buildings. Energy consumption prediction models are mainly divided into physical models, data-driven models and gray box models. Use of a simplified physical model reduces the amount of validation data and saves computation time [1] . [0003] Due to the flexible operation mode of the building's controllable load, the power dispatching center can effectively manage the energy consumption of the building system through direct control or price incentives, reduce the operating cost of the building, and improve the economy and safety of the power grid operation [2] . However, at this stage, when it comes to the flexible l...

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Problems solved by technology

However, at this stage, when it comes to the flexible load demand management method of intelligent buildings, the demand response potential of flexible loads in buildings has not been fully tapped, and with the increase of the forecast time scale, the uncertainty of renewable energy and load forecasting continues to expand, and the cumulative error of forecast data Gradually increasing, which in turn makes it difficult for the day-ahead optimal scheduling results to meet the actual operating needs of the system, which brings great obstacles to the operation of the distribution network based on the flexibility of building energy consumption

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