Research On Hybrid System Modeling And Optimal Controling Of Air Conditioning Load

Because of the random renewable energy sources connected to grid and peak-valley difference caused by the rising power demand,the security of grid is faced with great challenges.Aggregating flexibility of large-scale air conditioning loads(ACLs)can solve this problem effectively.From the perspective of cyber-physical system(CPS),this paper researches on the new control strategies of ACLs based on the idea of the hybrid system modeling method.Firstly,this paper regards ACL as a CPS and makes depth analysis to the physical and the control model of ACL.The equivalent thermal parameter model is used to modeling the physical process and the finite-state machine is used to modeling the control process simultaneously.Then this paper establishes the connection of the physical and the control process of ACL through mixed logical dynamical(MLD)model and describes constraint conditions and control logic in the cyber-physical coupling process by a group of linear equalities and inequalities.Then a distributed control strategy which tracks day-ahead schedule power of tie-line in microgrid is proposed.This strategy can develop ACL's autonomous control as far as possible to increase the schedulability of the tie-line power.The correctness of the MLD model and effectiveness of this method on tracking accuracy and ensuring lock out time and users' comfort is verified by simulation.Secondly,this paper establishes the coupling model of physical and control model by another hybrid system model---stochastic hybrid automation model and proposes a three-layer control system that can aggregate large-scale ACLs to achieve virtual peak shaving.In the load layer,an ACL probability control method is designed based on semi-markov process to ensure ACL's lock out time and status diversity.In the load aggregators(LAs)layer,a coordination control method is proposed based on the market equilibrium mechanism to aggregate ACLs as a virtual peak shaving unit.The LAs can provide information including bidding curve and peak shaving capacity like conventional units to participate in the grid layer's optimization process.Then this paper verifies the system's effectiveness in tracking accuracy,peak shaving cost saving and users' comfort by a simulation.Finally,on the basis of the preceding content,this paper proposes an energy optimization method based on aggregating dynamical model.A single ACL dynamical model is built through the relationship of the state of air-conditioner(SOA)and dynamical power,an aggregating dynamical model of ACLs is built simultaneously which can be used rolling optimization in finite time domain to reduce system dimension.Then an energy optimization is proposed based on model predictive control(MPC).The correctness of this aggregating model and sensitivity of users' electricity consumption behaviors to real-time price in different utility functions is verified by simulation.