Technical and economic analysis of biomass-fired power plants in North part of Poland Jerzy Buriak Gdansk University of Technology
Assumptions of biomass supply n n Direct observations of biomass supply potential Cultivated areas where not considered Straw is fuel for heat production in local sources Max. 20 km distance for biomass truck transport to railway sidings
--------------------- Gościcino Wejherows Luzino Strzebielino Morskie Bożepole Wielkie Godętowo Lębork Leśnice Pogorzelice Potęgowo Głuszyno Pomorskie Strzyżyno Słupskie Damnica Jezierzyce Słupskie Słupsk Reblino Sycewice Wrześnica Sławno Karwice Wiekowo Skibno Koszalin Niekłonice Dunowo Nosówko Kościernica Białogard Czarnowęsy Pom. Rąbino Nielep Świdwin
Estimations and data n n 18600 hectares of suitable areas adjoining the railway Gdansk-Szczecin: unused meadows, little boggy meadows, pine forests, mixed forest, low quality mixed forests, fields-unused lands, wastelands, hills, wide verges of roads 25 sidings between Goscicino and Lobez
![Assumed yield coefficients [ha/ha] - base level: 7 ton of dry matter per hectare](https://present5.com/presentation/891380de601837dd51f642ad77055059/image-5.jpg "Assumed yield coefficients [ha/ha] - base level: 7 ton of dry matter per hectare")
Assumed yield coefficients [ha/ha] - base level: 7 ton of dry matter per hectare n n n n n meadows meadow-use lands boggy meadow pine forests mixed forest low quality mixed forests fields-unused lands wastelands hills wide verges 1 1 1, 2* 0, 1** 0, 3 0, 4 1 1 0, 6****
Final estimation n 20% of potential will be exploited A part of fuel is transported by trucks farther than 20 km n 50 thousands of hectares: n 3 power plants 25. 5 MW each, 500 t of dry matter per day utilization time 5000 h/yr, efficiency 25, 3%
Estimation of maximal biomass supply potential in equivalent of Salix viminalis plantations (7 t of dry matter) n 186 thousands of hectares enough to supply 330 MW power plant and fully loaded 6000 h/yr
Calorific value of wet wood n n n high caloric value of dry wood [MJ/kg] humidity [%] water evaporation heat [k. J/kg] calorific value of wet wood [MJ/kg] 18. 7 30(45) 2442 11. 4(8. 5) Wet wood combustions technology with efficiency 25. 3% was chosen
Investment assumptions n n n Source of data: Joule R&D Programme investment in Wood Reception and Storage reduced by 50% Investment in Boiler House reduced by 33% Investment in Steam and Condensate System and Utilities not reduced Totaly: 1. 53 mln of Euro per 1 MWe
Operating and maintenance n n Maintenance, repairs and materials 66 000 Euro/MW/yr NOx emissions – 350 Euro/MW/yr (peak load utilization time 5 500 h/yr)
Railway transport cost c = 2 · d · a · udt + mt n n n tc –cost of railway truck transport to power plant and back d – distance a – number of railway truck axes udt – tariff per axe and kilometre (Attachment 3 of PKP Tariff) mt – tariff per specific mass of commodity and specific distance (Attachment 3 of PKP Tariff)
Transport cost assumptions n n The utilizations costs of railway sidings not included (as PKP contribution in intensification of railway exploitation) Time of back and forth trip of railway truck with loading – 5 days
Fuel costs n Cost related to amortization of railway trucks: 4. 5 Euro per 1 ton of wood (humidity of wood as delivered – ad. ) n n n Cost of 50 km, back and forth railway transport: 5. 25 Euro per 1 ton of ad. Wood Costs of railway truck loading on the sidings: 0, 75 Euro/t The considered range of wood fuel prices from farmers and forestry and wood companies: 28 ÷ 53 Euro per 1 ton of ad. fuel (30% of humidity)
Parameters of economic analysis n n n Discount rate: 8 ÷ 10 % Electricity price: 67 ÷ 85 Euro/MWh Fuel price
The influence of fuel price on profitability
The influence of fuel price on profitability
Tasks related to election of modeling system and model preparation and parameterization for chosen region: · Preliminary analysis of the energy potential of bioenergy usage in Poland; · An analysis of actual state of art in bioenergy law and actual projects in renewable energy in Poland on the World; · The analysis of existing in Poland on the World models for planning of energy system development; · Technical and economical analysis of basic energy systems in Poland; · The energy demand forecasts; · A mathematical description of simple model of energy system development – model is suitable for modeling of renewable energy use; · A work out of a model of the professional power system – data aggregation and model parameterization; · Regional applications of MARKAL family models; · The investigation of MARKAL model applications and description of TIMES model features – TIMES is next generation of MARKAL
Other tasks: n n n Technical and economical analysis of local system supplied by biomass-fired source; Tentative project analysis of the group of the biomass-fired power plants located in north part of Poland; Application of computer tool Ret. Screen to assessment and analysis of small district heating projects; The biomass based supply of heat of housing estate in the city suburbs – the technical and economical analysis; Trade conditions in electricity generated from biomass and waste; Development directions of energy systems in Poland in example of collective noun for the cities of Gdańsk, Sopot and Gdynia.
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