Intelligent energy management control for independent microgrid
详细信息   
  • 作者:T Bogaraj ; J Kanakaraj
  • 刊名:Sadhana
  • 年:2016
  • 出版者:Springer India, in co-publication with Indian Academy of Sciences
  • 期:7
  • DOI:10.1007/s12046-016-0515-6
  • 来源:SpringerLink
  • 类型:期刊
摘要
This work presents a new adaptive scheme for energy management in an independent microgrid. The proposed energy management system has been developed to manage the utilization of power among the hybrid resources and energy storage system in order to supply the load requirement based on multi-agent system (MAS) concept and predicted renewable powers and load powers. Auto regressive moving average models have been developed for predicting the wind speed, atmospheric temperature, irradiation, and connected loads. The structure proposed in this paper includes renewable sources as primary source and storage system as secondary source. A wind generator and solar PV array system together acts as primary source, which supplies power to the local load most of the time in this energy management strategy. When they fail to meet the load demand, the secondary source present in the system will assist the primary source and help to attain the goal of satisfying load demand without interruption. If the primary source and secondary source together are not able to meet the load demand then load shedding will be executed according to the priority set. Thus the developed MAS algorithm co-ordinates the hybrid system components and achieves energy management among renewable energy sources, storage units, and load under varying environmental conditions and varying loads. STATCOM based compensation has been implemented to balance the reactive power demand and to mitigate the voltage fluctuations and harmonics on the AC bus. The proposed microgrid has been simulated with MAS concept in Matlab/Simulink environment. The results presented in this paper show cases the effectiveness of the proposed energy management controller.KeywordsEnergy management controlmulti-agent systemmicrogridenergy forecasthybrid power systempower quality issues