Fuel Used Analysis on Boiler Efficiency Variations and Water Intake Temperature Affected by Palm Oil Varieties

Several factors that affect the use of fuel in boilers are combustion efficiency, quality of feed water management, calorific value, and the potential for available fuel from oil palm varieties. The purpose of this research is to identify the use of fuel and its potential savings based on variations in boiler efficiency and water temperature that entered the boiler. The materials used in this research are FFB mass balance data and boiler fuel composition. Based on the analysis results, the lowest used fuel mass and the highest fuel savings are found in the DxPLangkat variety with an intake water temperature of 105o C and 80% boiler efficiency. The use of fuel is 4,231 kg/hour with shell savings of 967 kg/hour with a value of IDR 725,701. Fiber savings was 487 kg/hour with a value of IDR 121,751.The highest used fuel mass and the lowest fuel savings were found in the Yangambi derivative variety with an intake water temperature of 85o C and 60% boiler efficiency.The fuel consumption is 5,830 kg/hour with shell savings totalling -380 kg/hour. There is no fiber analysis because it is used up hence additional fuel is needed. Additional fuel can be done by asking for other palm oil mill units or buying. If they buy a shell with a requirement of 380 kg/hour, the funds required are IDR 284,939

Adaptively Receding Galerkin Optimal Control for a Nonlinear Boiler-Turbine Unit

The boiler-turbine unit is really a complex system in thermal power engineering due to its large-scale nonlinearity, unmeasured state, unknown disturbances, and constraints imposed on both controls and outputs. To design a controller with appropriate performance in above synthetical cases, this paper intends to propose an adaptively receding Galerkin optimal controller design method, in which, the mathematical dynamics of unit can be directly used as a predictive model without any linearization, and the unmeasured state in the predictive model is adaptively estimated using a predesigned state observer. With the help of a mathematical predictive model, optimal control law is then obtained based on a Galerkin optimization algorithm. Due to the application of the useful information measured at every sampling time instant, the proposed method can deal with the tracking problem with constraints rather than the stabilization problem that can be only done by the traditional Galerkin optimal control. Furthermore, it can also be easily extended to estimate and thus eliminate constant disturbances in an output channel using an independent model strategy. Some simulations suggest that satisfactory tracking performance can be achieved even when the unit experiences wide-range load change