An information physical modeling and control method for aggregating large-scale air conditioner loads

Abstract

The invention relates to an information physical modeling and control method for aggregating large-scale air conditioner loads, and the method comprises the steps: the air conditioner loads is regarded as an information physical system (CPS) at a load layer, an air conditioner load probability control method based on a semi-Markov process is provided, and the locking time of an air conditioner canbe guaranteed and the diversity of a cluster state is kept; A hybrid system model is utilized to establish a coupling relation between the air conditioner load physical process and the control process, and autonomous control over the air conditioner load is achieved; In an aggregator layer, a coordination control method for aggregating air conditioner loads into virtual peak shaving units is provided based on a market balance mechanism, and the method can effectively protect user data privacy and remarkably reduce the communication cost. Meanwhile, the virtual peak regulation unit can providea quotation curve and regulation capacity similar to a conventional unit for scheduling, so that the virtual peak regulation unit participates in optimal scheduling of a power grid layer. Compared with the prior art, the method has the advantages of remarkably reducing the communication cost, facilitating optimal scheduling and the like.

Description

technical field [0001] The invention relates to a temperature-controlled load participating in peak-shaving technology in a power system, in particular to a cyber-physical modeling and control method for aggregating large-scale air-conditioning loads. Background technique [0002] With the large-scale grid-connection of wind power and the increasing peak-to-valley load difference, peak-shaving services play an increasingly important role in maintaining the balance between supply and demand in the power system. The traditional approach is to increase the output of generator sets during peak load hours. However, the peak load period is often short, and the utilization rate of the increased investment in power generation and transmission and distribution to meet this part of demand is very low. In addition, most peak-shaving units are thermal power units with high cost and poor environmental protection [see Document 1 for details]. At the same time, the proportion of air cond...

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Problems solved by technology

However, the above method has some limitations, such as the need to collect load model parameters and user preferences [see literature 13,14 for details], and only for the same type of temperature control load with the same parameters [see literature 10,13], etc.

In addition, the above models and control methods still have the following common problems: 1) Frequent communication between the aggregator and the temperature-controlled load is required to obtain the load status and send control commands, and the control cost is high; 2) No matter whether the temperature-controlled load is controlled by switching [See Document 7 for details], temperature set point control [see Documents 8,9] or probability control [see Documents 12,13 for details], all of which have information security problems, such as being vulnerable to the implementation of "same switch and same switch" for loads malicious control [see Document 15]; 3) It is necessary to collect model parameters and user preferences of temperature control loads, which is difficult to guarantee user data privacy; 4) does not consider the air conditioner locking time constraint, which is easy to aggravate equipment wear [see Document 12, 13]

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