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Technoeconomic evaluation of landfill gas to energy technologies at the landfill site of Pera Galini in Heraklion, Crete

Tsafantakis Konstantinos

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Summary

Landfill Gas (Biogas) is considered as a valuable source of renewable energy. Its quality and production rate are demined factors for the selection of the optimal technology for electric energy production. In addition, environmental legislation, flue gas emissions, carbon footprint and maturity of technology should also be considered. The most common and widespread process for electric energy production from biogas is the use of Internal Combustion Engines (ICE), which can operate if the methane (CH4) concentration is approximately above 40%. On the other hand, a novel technology, determining Gradual Oxidizer (GO), based on the process of gradual oxidation of the incoming gas fuel, can operate at methane concentration as low as 1,5%( technology with small commercial availability).The present dissertation examines, through certain simulation models, the techno-economical applicability of the above mentioned power technologies for electricity production from biogas at the landfill of Pera Galines in Heraklion of Crete. The landfill consists of 4 main sections, two old and two new ones. The first division (dump site A’) started operating in 1992 and was closed in 1997. The disposal of waste in the 2nd section (dump site B') started in 1998 and was closed in 2008. The 3rd section (cell A’ of the landfill) is supernatant of dump site B 'and received the deposits from 2009 until 2012 and the 4th section (cell B’ of the landfill) is an overhead part of the dump site A' and has received waste from 2012 until the beginning of 2016. In the summer of 2016, cell C' has been built, which has been receiving the quantities of waste from the end of 2016 until today.Moreover, concerning the simulation models, this particular study takes into account not only the methane production rate, but also the long term methane concentration in landfill gas, and its modeling was carried out using the LandGEM computational model (introducing the available quantities of MSW by part of the landfill and the parameters L0 of the biogas production potential and the k kinetic biogas production constant), which has been appropriately modified to consider the reduction of methane over time, mainly due to the intrusion of air iside the landfill body. By estimating the amount of methane recovered in the biogas fraction, calculations of the electrical efficiency of biogas were carried out and, depending on the costs (capital, O&M and replacement costs), the annual operational availability and the total installed power of the considering technology, its turnover and the total initial investment, the payback period and the economic results (NPV and IRR) of the following scenarios were obtained.As the landfill site consists of cells and waste disposal segments (dump sites), which have closed during different times, both the quantity and the quality of landfill gas should be evaluated equally for determing the best technology for electricity generation. 5 different scenarios for electric energy production from dump sites A’ and B’ and from cells A’, B’ and C’ have been examined, with the following combinations of technologies, looking for the most convenient scenario, taking into account, both financial and energy efficiency. Scenarios 1 & 2: Use of 3 and 2 ICE engines (500 kW each), respectively, for dump sites A’ & B’ and cells A’, B’ & C’ (Landfill body). Scenarios 3 & 4: Use of 4 and 3 GO engines (250 kW each), respectively, for the total of CH4 produced. (Combined) Scenario 5: Use of one 250 kW GO engine for dump sites A’ & B’ and 2 ICE engines 500 kW each for cells A’, B’ & C’. Modeling indicated that the use of 3 ICE engines, with capacity 500 kW each, yields the highest Net Present Value NPV =4,16 M€ and IRR =19%, followed by the combined scenario with the use of 1 GO engine and 2 ICE engines, with financial indicators: NPV =4,06 M€ and IRR =19%. For better evaluation of modeling results, field measurements need to be made in relation to the quantity and quality of the biogas produced, since all the results of the present dissertation are based on the implementation of the LandGEM computational models. In this way, safer conclusions can be made after verifying and adjusting the models with those measurements.

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