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

A technology of model predictive control and flexibility, which is applied in the field of distribution network, can solve the problems of distribution network operation obstruction, the increase of accumulated error of forecast data, and the difficulty of optimizing dispatching results to meet the operation requirements of the system, so as to reduce operating costs and promote Reproducible, robust effects

Inactive Publication Date: 2019-01-25
NORTHEAST DIANLI UNIVERSITY
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

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

Method used

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

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Embodiment 1

[0048] The embodiment of the present invention provides a method for flexible regulation and control of energy consumption in intelligent buildings based on model predictive control, such as Figure 1-Figure 3 As shown, the method includes the following steps:

[0049] 101: According to the heat storage characteristics of the building, construct an intelligent building energy consumption prediction model considering different heating areas inside the building, and integrate the building system into the distribution network as a flexible and controllable unit;

[0050]102: Based on the model predictive control method, the internal HVAC system of the building is used to optimize and adjust the room temperature within the temperature comfort range, so as to realize the flexible management of energy consumption of the building system and reduce the operating cost of the building;

[0051] 103: Taking the heating scene in winter as an example, the optimal scheduling analysis of bui...

Embodiment 2

[0054] The scheme in embodiment 1 is further introduced below in conjunction with specific calculation formulas and accompanying drawings, see the following description for details:

[0055] 201: According to the heat storage characteristics of the building, through the building RC (thermal resistance heat capacity) network, construct an intelligent building energy consumption prediction model considering different heating areas inside the building, and then carry out the next step of optimization based on the MPC strategy;

[0056] Wherein, the step 201 includes:

[0057] 1) In an uncertain environment, through the division of uncertainty levels [3] , to obtain basic data, including: building parameter information, HVAC system parameters, light intensity, outdoor temperature, and real-time electricity price [4] ;

[0058] The division of the uncertainty level and the steps of obtaining the basic data are well known to those skilled in the art, and will not be described in d...

Embodiment 3

[0103] The following combined with specific examples, Figure 4 , Figure 5 , Figure 6 And table 1, table 2 carry out feasibility verification to the scheme in embodiment 1 and 2, see the following description for details:

[0104] This example takes a typical day in winter in northern my country as an example to verify the effectiveness of this method. The energy consumption prediction model of a single heating area in an intelligent building and the schematic diagram of the distribution network of an integrated intelligent building are as follows figure 2 , image 3 shown.

[0105] For a typical residential building, the comfortable temperature range set by the user is 22°C to 24°C. Considering a day's rolling optimization regulation, a time section is taken every 15 minutes, and the prediction time domain and control time domain are selected for 4 hours. The embodiment of the present invention takes a single-family five-story residential building as an example. Each f...

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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...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B13/04H02S20/23
CPCG05B13/042H02S20/23Y02B10/10Y02E10/50
Inventor 陈厚合姜涛李雪李泽宁李国庆张儒峰李本新王长江张嵩李曙光李晓辉
Owner NORTHEAST DIANLI UNIVERSITY
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