Temperature control load hierarchical aggregation control method for intelligent building

Abstract

The invention provides a temperature control load hierarchical aggregation control method for an intelligent building. The method comprises the following steps: 1, constructing the hierarchical control architecture of heterogeneous temperature control load clusters which are aggregated and distributed dispersedly by taking a building as a unit; in an upper-layer control architecture,determining the scheduling capacity which should be provided by each building through distributed containment control based on the aggregation characteristics of the heterogeneous temperature control loads dispersedly distributed in different buildings by means of a load aggregator according to the scheduling requirement of the power distribution network system and the scheduling capacity level which can be provided by each building; sending a scheduling control requirement which contains the scheduling capacity provided by each building to a building controller in a lower-layer control architecture; and inthe lower-layer control architecture, according to the scheduling control requirement sent by the load aggregator, adjusting the running state of a controlled temperature control load in the same building through a conversion time matching control strategy by means of a building controller. According to the invention, the coordination control of load scheduling capacities provided by different buildings in the sparse communication network is realized.

Description

technical field [0001] The invention relates to the technical field of smart grids, in particular to a temperature-controlled load hierarchical aggregation control method for smart buildings under the smart grid demand response mechanism. Background technique [0002] In the context of energy structure transformation, the current massive integration of renewable energy represented by wind power and photovoltaics into the modern power system is in an unprecedented period of rapid development. Unlike traditional power generation units, renewable energy is restricted by natural factors, and its output presents In addition, renewable energy such as wind power and photovoltaics do not use synchronous generators for power generation, and the increase in renewable energy power generation cannot increase the inertia of the system like traditional power generation units. As the penetration rate of renewable energy increases, the proportion of synchronous generators in operation decre...

AI Technical Summary

Problems solved by technology

Therefore, the large-scale access of renewable energy power generation forces the power system to operate in an environment with low inertia, high output fluctuation and high uncertainty, and in order to deal with the volatility and intermittency of renewable energy The traditional dispatching mode that invests in the construction of a large number of conventional power generation units as backup capacity on the power generation side simply relies on the backup capacity on the power generation side to promote the consumption of renewable energy, which makes the backup units frequently start and stop, and operate with long-term low load and deviate from the optimal economic operating point, resulting in possible The economy and low-carbon environmental protection of renewable energy grid connection decline

Therefore, the traditional model that only relies on the reserve capacity of the power generation side for regulation is difficult to meet the development needs of the future high-proportion renewable energy power generation power system, and it is urgent to introduce new dispatching models and participating units to promote the consumption of renewable energy

[0003] In order to meet the challenges brought about by the development of power systems with a high proportion of renewable energy in the future: system volatility, intermittency, random surge, and the lack of flexibility of traditional dispatching models: low flexibility and economic benefits, etc.

[0007] (1) The comfort requirements of users are diverse, and the acceptable control ranges are different, resulting in inconsistent controllability of temperature control loads;

[0008] (2) The number of temperature control loads is large, and centralized control is difficult to meet the reliability and scalability requirements of a large number of loads participating in the control, resulting in high pressure on control communication and low control reliability;

[0009] (3) The characteristics of high heterogeneity of thermal parameters of temperature-controlled loads are coupled with the characteristics of geographically dispersed distribution, whi

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