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

An optimisation tool for minimising fuel consumption, emissions and costs from biofuel powered diesel generator-PV-battery hybrid mini-grids in developing countries

The purpose of this research was to develop a cost optimisation tool to improve the performance of diesel generators within hybrid microgrids for increasing electrification rates in rural areas of developing countries, especially in sub-Saharan Africa. This study considered the use of widely available vegetable oils, such as castor oil, to widen the fuel options to power diesel generators and reduce their environmental impact and operating costs. Castor oil-diesel blends were used to assess the performance of a diesel generator and find new fuel estimation equations, which were used to develop a cost optimisation tool for diesel/PV/battery microgrids. The best performance occurred above 60% engine load for all the blends and higher fuel consumption was found for the blends with higher castor oil content. The developed cost optimisation tool was used to compare the Levelized Cost of Energy (LCOE) and the pollutant emissions (CO2e, PM2.5, and NOx) of 8 microgrid system configurations for three estimated electricity demand profiles (high, medium, and low) in the Lindi Region in Tanzania. Installing diesel/PV/battery hybrid systems gives lower LCOE than diesel/battery or conventional systems (only diesel generators). Hybrid systems reduce CO2e emissions between 20% and 24%, whereas PM2.5 and NOx can be reduced between 32% and 47%, relative to conventional systems