RETRACTED ARTICLE: Design of ANFIS controller for intelligent energy management in smart grid applications

Abstract

Processing of information in minimum time duration with maximum accuracy is the prime factor for efficient functioning of any network. A smart grid (SG) is a network structure that supplies electricity using digital communication technology by the application of computer intelligence for the purpose of control and automation of various components like smart meters, smart appliances and renewable energy resources connected to it. A hybrid power system (HPS) is one which has multiple power generating sources like photo voltaic (PV) system, Wind turbine, fuel cell etc. interconnected to supply electric power for varying demand requirements with/without energy storage backup which is the key component of a SG. This paper focuses on the integration and control automation of renewable energy sources viz. PV system, solid oxide fuel cell (SOFC) with nickel-metal-hydride (Ni-MH) battery together with a variable load present in a SG. The proposed energy management system (EMS) used in the designed HPS focuses on the use of PV which is 100% clean in nature with no toxic emissions on power generation. Here, PV system with maximum power point tracking (MPPT) is used as the major supply contributor in the HPS to meet with variable load demands. If there is deficit of power supply from PV, the power from the Ni-MH battery/SOFC is utilized to meet with the varying load demands. On the other hand, if there is excess supply from PV system, the excess energy will be stored in the Ni-MH battery. For efficient supply demand balance, the EMS makes use of various control strategies namely proportional-integral (PI) and adaptive neuro fuzzy inference system (ANFIS).