Optimization for Biogas Power Plants using Automatic Control of Gas Pressures
In many cases, gas storages on biogas power plants are not used optimally to store gas as much as their capacity. The digester is sometimes overload to store gas and the controller cannot deliver gas to other storage. Consequently, gas is often released from digester to avoid over pressure. At the end, biogas power plant has less efficiency. Hence, a mechanism to control gas pressure to make different pressure between its storages is required. Fans were used to manipulate the most majority system pressures on a biogas power plant using frequency converters. Measurements, simulations, and experiments were conducted to create a new system on a biogas power plant. A controller, Programmable Logic Controller was used to control the entire system pressure using Proportional-Integral-Derivative algorithm. When the gas pressures are not in the allowable range of pressure, then the controller changes the fans’ frequency to the desired conditions. As a result, gas moves to another storage and system pressures are in the allowable range.
Biogas Plant Control and Optimization Using Computational Intelligence MethodsBiogasanlagenregelung und -optimierung mit Computational Intelligence Methoden
Abstract The optimization of agricultural and industrial biogas plants with respect to external influences and various process disturbances is essential for efficient plant operation. The fact that most biogas plants are manually operated because of a lack of online-measurements and limited knowledge about the anaerobic digestion process makes it necessary to develop new optimization and control strategies. However, the optimization and control of such plants is a challenging problem due to the underlying highly nonlinear and complex digestion processes. One approach to address this challenge is to exploit the flexibility and power of computational intelligence (CI) methods such as Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO). The use of CI methods in conjunction with a validated plant simulation model, based on the Anaerobic Digestion Model No. 1, allows optimization of the substrate feed mix, a key factor in stable and efficient biogas production. Results show that an improvement of up to 20% in biogas production and substrate reduction can be achieved when compared to conventional manual operation.
Sumner, William Graham
William G. Sumner was born October 30, 1840 in Paterson, New Jersey, and graduated from Yale College (now Yale University) in 1863. 
 
 
Keywords: 
 
ethnocentrism; 
sociology