Building heating ventilation air conditioning load optimization control method based on partial linear model

Abstract

The invention provides a building heating ventilation air conditioning load optimization control method based on a partial linear model, and belongs to the technical field of power demand response. The method comprises the following steps: firstly, respectively establishing a thermal inertia model and a heating ventilation air conditioning system model of a building, converting the two models to obtain a heating ventilation air conditioning load prediction model comprising a linear part and a data driving part, and carrying out fitting by utilizing historical data to obtain parameters of the load prediction model; and then according to the load prediction model, establishing an optimization model of the indoor temperature of the building, solving the optimization model, obtaining the optimal indoor temperature of the building at the next time point through calculation, and realizing optimization control over the heating ventilation air conditioning load of the building. According to the method, a physical model and a data driving model are combined, so that the heating ventilation air conditioning prediction model has interpretability and high prediction precision at the same time, the indoor temperature can be optimized according to the model under the real-time electricity price, and the energy consumption cost of the building is reduced on the premise that the indoor temperature is kept within a certain comfortable range.

Description

technical field [0001] The invention belongs to the field of power demand response, and in particular proposes a building HVAC load optimization control method based on a partial linear model. Background technique [0002] With the acceleration of the global urbanization process, the construction industry consumes more and more energy, causing nearly 40% of the global greenhouse gas emissions. HVAC systems account for nearly 50% of a building's energy consumption. Due to the thermal inertia of buildings, HVAC is a typical electrothermal coupled load that can adjust electricity demand in a short period of time with little impact on user comfort, and has the potential to provide flexibility to the grid. Proper demand-side management can greatly improve the economics of grid operation, which requires modeling and optimal control of HVAC loads. [0003] Many literatures have confirmed the application of HVAC systems in demand response, such as implementing optimal control of i...

AI Technical Summary

Problems solved by technology

[0004] To sum up, the existing simple model of HVAC load cannot be applied to real scenarios; the data-driven model is too complex, and it is difficult to optimize the control on this basis

Images