Autonomous And Collaborative Energy Management Optimization Framework For User-Side Intelligent Integrated Electrical System

With the development of distributed generation(DG)and electric vehicle(EV),the regional aggregation system(RAS)and many kinds of local intelligent integrated electrical systems(IIES),such as microgrid,charging station,battery swap station and smart building,are becoming an important trend of the utilization side electrical system.RASs and IIESs are the most popular structure of integrating local resources into smart grid which can realize regional collaborative energy management of multi-SIESs and the interaction with smart grid.RASs and IIESs are also regarded as the key components of high efficiency energy-saving and emission-reduction of utilization side.The research work of the thesis is focused on the autonomous energy management of different IIESs and the collaborative energy management of RAS which is composed of multi-IIESs.The main research and innovations are as follows:According to the characteristics of EV charging behavior,four parameters(initial SOC(State of Charge),target SOC,start charging time and end charging time)are taken into consideration of modeling feasible charging region(FCR).An adjustment ability factor is proposed based on the FCR model and it is applied to EVs classification.The randomness of charging process is analyzed and four random events are modeled.In order to cope with random events,the synergitic energy management is proposed based on the framework of dynamic event triggering state machine.Finally,considering the principles of systisfying charging demand and promoting self-consumption of PV energy,a kind of rule-based power allocation strategy is proposed.The mechanism of battery swaping procedure and battery charging procedure are analyzed,and the interation model is studied based on the inherent relation between the two procedures.With the basis of interaction model,a charging strategy is proposed for battery swap station based on PV output and forecasted battery swapping demand.Quality of battery swapping service,PV self-consumption and profit are regarded as three indices to evaluate the validity of the proposed strategy.The negative influence caused by forecasting error is analyzed and a method is proposed to cope with the negative influence by adjusting battery reserve amount.Finally,the echelon use batteries are used to deal with the flucturation of charging power for battery swap station.The system structure and advantages of solid state transformer(SST)are analyzed.And then,the SST is introduced into charging station to realize the intergration of PV system and EV charging facilities.The regulation ability model and energy region model are proposed based on the characteristics of charging station.And then,a power allocation strategy is proposed for PECS participating in frequency regulation service.Finally,the proposed PECS structure and energy management strategy are examed on experiment platform.The advantages of day-ahead optimization method and real-time optimization method are analyzed.In order to combine the advantage in global optimization and real-time adjustment,an automatic demand response(ADR)model is proposed based on rolling linear programming.A real-time price vector formation model is prosed based on K-means algorithm.It is designed to provide the price information of future time to the ADR model.In order to avoid the concentrated charging impact on grid voltage,an energy demand model for future time considering voltage regulation factor is propose to manage the peak charging power.Then,the charging power can be well controlled according to the grid voltage amplitude.Finally,the primal-daul feasible route tracking method is studied to solve the optimization model.The roles of aggregator and subsystems,and the communication between aggregator and subsystems are analyzed in the top-down manner.The framework of energy management for aggregation system is designed in a decentrialized collaborative fashion and the profit model of aggregator and subsystems are studied.Under the decentrialized collaborative framework,a two-stage ADR model for aggregation system is proposed based on the utilization demand,objectives and constraints of subsystems.Finally,the strategy for internal pricing problem and the decentrialized collaborative ADR is studied based on the interaction mechanism among systems.