ANFIS BASED Intelligent Energy Management and optimization of CHPB System with Multiobjective function

A combined system of heating, power and biogas (CHPB) system has been developed and tested in a single building in MinQin County, Gansu Province, China. The CHPB system shows favorable performances of heating in most winter days. However, when bad weather lasts over two days, the system would not meet the heating. Therefore, for the sake of reduce the operation cost and the environmental impact of the CHPB system considering its preoperational variable is the future availability of renewable energy, intelligent energy management of the CHPB system is proposed in this paper. The factors, such as the ambient temperature, humidity, power availability, and wind speed, are predicted by adaptive Neuro-fuzzy inference system (ANFIS) and then are combined with the instantaneous value of the backup batteries state of charge (SOC) and a gas tank level to make a decision whether to use the gas or electricity stored in the backup batteries to satisfy the user demand by fuzzy system. The cost saving of the proposed multiobjective intelligent energy management (MIEM) approach compared to operation based on opportunity was equal to 9.24% compared to 12.9% for the next day as a result of the intelligent switch scheduling, and lS.49 % compared to 26.5 for CO
2
emission.