Research On Demand Response Optimization Control Strategy Of Cluster Central Air Conditioning Based On Elastic Temperature Margin Adjustment

In recent years,with the continuous development of society and economy,the electricity demand has shown a trend of continuous growth,and the relationship between supply and demand is relatively tight.On the one hand,with the increasing diversification and scale of power system users and the development of intelligent equipment,the proportion of flexible load with good interactive adjustment potential has steadily increased;on the other hand,with the continuous maturity of demand response technology,the load side users can be more involved in grid-assisted services such as renewable energy fluctuations and grid peak regulation.Among many flexible loads,the central air conditioning load has good demand response potential due to its large power.This paper focuses on the related technologies of the central air-conditioning load group participating in the demand response,and formulates the optimal control strategy for the demand response of the cluster central air-conditioning.The specific work related to central air conditioning load modeling and optimization control strategy formulation is as follows:Firstly,the modeling method of load rate type central air conditioning based on "bottom up" modeling is studied.Based on the equivalent thermodynamic parameter model,the relationship between the consumption of electric energy and the indoor temperature is established,and the relationship between the operating state of the central air-conditioning equipment and its power characteristics is obtained.By considering the operating mechanism and the physical model of the load rate central air conditioning,and the electrical characteristics of the terminal equipment,the dynamic mechanism of the central air conditioning load is modeled.Secondly,based on the user's electricity behavior analysis,the user's elastic temperature adjustable margin is constructed.Firstly,based on the SOM-Kmeans two-stage clustering algorithm,the user load data is analyzed.Secondly,the retail price model is constructed with the goal of minimizing the conditional value at risk and the user's payment cost,and comprehensively considering the factors affecting the user's electricity consumption behavior.Based on the subjective factors such as electricity price and the objective factors of the equipment,the user's willingness model is constructed,and the real-time temperature and the lower limit set value of each air-conditioning terminal are adjusted based on the user's willingness,so that the temperature-adjustable margin of the terminal device has "elasticity".Finally,a double-layer optimal control strategy for demand response of cluster central air conditioning is proposed.In the lower layer,the central air-conditioning terminal equipment is taken as the research object,and a central air-conditioning terminal control strategy based on the elastic temperature adjustable margin is developed.The user's power consumption characteristics are taken into consideration,the frequent start and stop of the equipment is avoided.The upper layer constructs an optimal scheduling model from the perspective of load aggregators,and optimizes the allocation of central air conditioning response targets.Under the premise of meeting the response of the central air conditioning load group to the response target,comprehensive consideration of various factors,in meeting the grid scheduling plan and considering users at the same time,the profit of the aggregator is maximized.The rationality and effectiveness of the proposed strategy are verified by case study.