Improved Feasibility Analysis under Volatile Conditions: Case of Waste-to-Energy
Ferdan, T.
Šomplák, R.
Pavlas, M.
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How to Cite

Ferdan T., Šomplák R., Pavlas M., 2014, Improved Feasibility Analysis under Volatile Conditions: Case of Waste-to-Energy, Chemical Engineering Transactions, 39, 691-696.
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Abstract

In these days, the majority of the EU countries, mainly these from Central and Eastern Europe, promised gradual decrease of the municipal solid waste (MSW) landfilled. This has been leading or will lead to landfilling bans or taxation with the aim to establish other methods of MSW treatment. One of these possibilities is waste-to-energy (WTE).
This paper deals with the issue of a new WTE plant conceptual design. The price of MSW treatment at the plant (gate-fee) is the key parameter for the project sustainability. Once the gate-fee is determined from comprehensive cash-flow analysis, it is affected by other incomes and costs and their future unpredictable escalations. This is more and more important in nowadays dynamic world (volatile energy prices etc.). One of the key elements, entering such an analysis, is the heat delivery to third parties (i.e. residential heating via district heating systems or integration with industrial utilities) and related trends in amounts and prices. At the same time, the proposed gate-fee has to guarantee the competitiveness of the project in terms of fulfilling the designed capacity. Every project is very specific and its economy responds to potential scenarios differently, which makes the situation even more unforeseeable.
A new approach towards risk analysis in case of WTE is presented in this paper. It assesses the impact of different scenarios on plant economy. A complex techno-economic model is used to demonstrate the relation between gate-fee and time variable parameters (heat, electricity, gas, chemical, maintenance costs etc.) for specific projects. Fixed return on investment is expected. Afterwards the transportation costs associated with waste delivery are included and results compared to evaluate plant competitiveness. This is performed by in-house developed optimisation tool NERUDA.
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