Fuel Optimization in Multiple Diesel Driven Generator Power Plants

This paper presents two fuel optimization approaches for independent power producer (IPP) power plants consisting of multiple diesel driven generator sets (DGs). The optimization approaches utilize assumed information about the fuel consumption characteristics of each DG in an effort to demonstrate the potential benefits of acquiring such information. Reasonable variations in fuel consumption characteristics are based on measurements of a DG during restricted air filter flow operation. The two approaches are: (i) a gradient search approach capable of finding the optimal power generation for each DG in a fixed selection of DGs accommodating a given plant power reference and (ii) a genetic algorithm approach further capable of determining the optimal selection of DGs to operate in an IPP power plant. Both approaches show notable potential benefits, in terms of fuel savings, compared to current market-leading solutions

Fuel Optimization in Multiple Diesel Driven Generator Power Plants

This paper presents two fuel optimization approaches for independent power producer (IPP) power plants consisting of multiple diesel driven generator sets (DGs). The optimization approaches utilize assumed information about the fuel consumption characteristics of each DG in an effort to demonstrate the potential benefits of acquiring such information. Reasonable variations in fuel consumption characteristics are based on measurements of a DG during restricted air filter flow operation. The two approaches are: (i) a gradient search approach capable of finding the optimal power generation for each DG in a fixed selection of DGs accommodating a given plant power reference and (ii) a genetic algorithm approach further capable of determining the optimal selection of DGs to operate in an IPP power plant. Both approaches show notable potential benefits, in terms of fuel savings, compared to current market-leading solutions

Use of SMS texts for facilitating access to online alcohol interventions: a feasibility study

A41 Use of SMS texts for facilitating access to online alcohol interventions: a feasibility study In: Addiction Science & Clinical Practice 2017, 12(Suppl 1): A4

Multi-neighborhood search for discrimination of signal peptides and transmembrane segments

Abstract. A key step in study of biosynthesis of membrane proteins is to look for the code that could be used to explain and predict which proteins would eventually be inserted in the membrane and which proteins would be secreted into the ER lumen when they cross the translocon channel. The aim of this work is to present an improvement of a previous method based on a local search approach. The proposed method relies on new in-depth biological observations to design a new search space for the local search algorithm. Experiments conducted on a dedicated dataset show that our new approach leads to improved outcomes in terms of prediction rates