Font Size: a A A

Research On Multi-Microgrid Optimal Scheduling Strategy Considering Flexible Load And Network Loss

Posted on:2024-01-06Degree:MasterType:Thesis
Country:ChinaCandidate:P C GaoFull Text:PDF
GTID:2542307115479044Subject:Master of Electronic Information Engineering (Professional Degree)
Abstract/Summary:PDF Full Text Request
With the rapid development of the global economy,the energy demand of various industries is increasing.In this context,the microgrid has become one of the key research objects in the world because of its flexible scheduling characteristic and the philosophy about low-carbon and environmental protection.However,the stability of the distribution network will be affected because of the high flexibility of the microgrid.At the same time,due to the complexity of the microgrid’s internal system was increased,various scheduling problems are also occurred frequently.This paper studies the scheduling problem when the multi-microgrid system is connected to the distribution network at present,focuses on the network loss problem was generated by the scheduling process,and the impact of flexible load scheduling on the network loss and scheduling strategy are deeply studied.First of all,the development status of microgrid and the existing problems in multi-microgrid scheduling are described,the structure of microgrid and multi-microgrid system are introduced,the output principles of various distributed power sources are explained,and the relevant mathematical models are constructed.Secondly,in order to study the impact of network loss on scheduling and optimize it,the strategy of classifying and scheduling the load according to the industry type is put forward,which is divided into three types: residential load,industrial load and commercial load.The total daily load curve of the three types of loads is decomposed according to the typical daily load curve by studying the power curve of several main electrical equipment in each category,the proportion of flexible load in each type of load is obtained.Thirdly,in order to achieve precise scheduling of flexible loads and enhance the potential of flexible load scheduling,the internal network loss of each microgrid in the multi-microgrid system is modeled.According to the microgrid structure,the network loss generated by the branch line is integrated into the node,so as to intuitively obtain the impact of flexible load scheduling on the network loss.The power flow of the distribution network system is calculated,and the network loss generated by the scheduling is obtained,and the minimum network loss is taken as the optimization objective for optimization.Finally,in order to reduce the complexity of optimizing the scheduling of multi-microgrid systems considering the participation of multiple flexible loads,a two-level optimal scheduling strategy based on multiple time scales is proposed,namely day-ahead scheduling and intraday scheduling.In the day-ahead scheduling phase,the transferable loads and adjustable loads with large power and poor flexibility among flexible loads are optimally scheduled,In the intraday scheduling phase,the reducible and interruptible loads are scheduled.The distribution network with multi-microgrid is taken as the upper layer,the multimicrogrid system is taken as the lower layer,and a two-level optimization model is constructed: the stability and power quality of the distribution network is mainly considering in the upper layer,the power-interaction stability of the distribution network system and the multi-microgrid system and the system loss of the distribution network are taken as the optimization objectives.The network loss and scheduling cost in the multi-microgrid system are taken as the optimization objectives in the lower layer.Aiming at the problems of multi-constraint,multi-objective and nonlinearity in the strategy,the improved intelligent algorithm is used to solve the model,and the modified 9-node system is used for simulation analysis to prove the superiority of the strategy.
Keywords/Search Tags:Flexible load classification, Network loss, Multi-microgrid system, Demand response, Multi-time scale, Two-level optimal scheduling model
PDF Full Text Request
Related items