Cost-inclusive heuristic power management of hybrid power generation plant with ANN-regulated biogas plant

Abstract

To mitigate the negative effects of fossil fuels, renewable energy sources are being promoted for power generation. Biomass, a renewable energy source, is also being promoted to reduce the negative impact of organic waste generated in societies and industries. Waste biomass is used to produce biogas fuel in a biogas plant via an anaerobic digestion process, which is typically used to generate electricity as well as fuel for cooking and vehicles. However, the high local electrical load in biogas plants reduces profit for plant owner. Biogas-based power generation is hybridised with Photovoltaics (PV) and Battery energy storage systems (BESS), to meet power demand, to increase profit and power generation capacity while reducing the burden of local electrical load on biogas plants. A Proton-exchange membrane fuel cell (PEMFC) stack has been used for power generation from the hydrogen produced from the biogas obtained from the anaerobic digestion process. A cost-inclusive heuristic power management system has been designed for power management in hybrid power generation, considering the availability of sources and their dynamic tariffs. An artificial neural network (ANN) has also been designed to determine the digester operating temperature according to methane yield requirements. The designed system has been investigated for hydrogen consumption, carbon emission, power generation cost, operating cost, power factor, frequency, distortion, efficiency, and voltage regulation. The proposed system effectively meets the load demand at a lesser cost in different scenarios. Cost saving of 28.42%, carbon emission reduction by 96% and 4.53% Total harmonic distortion (THD) at a power factor of 0.99 has been observed. The complete proposed hybrid power plant is ideal for implementation in societies and industries.