1ST OLYMPUS INTERNATIONAL CONFERENCE ON SUPPLY CHAINS, 1-2 OCTOBER, KATERINI, GREECE

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1 Biomass Supply Chain Development in Greece with Special Focus on the Utilization of Biomass Residues Ch. Papapostolou 1, M. Minoyiannis 2, E. Kondili 3 1,2,3 Department of Mechanical Engineering, Technological Education Institution of Piraeus, Aegaleo, Greece 1 [email protected], 3 [email protected] Abstract Traditionally, biomass derived energy, due the dispersed character of its primary recourses and the easiness in their processing, has been exploited mainly at a local level, by the existing agricultural industry, employing well known practices. Nevertheless, concentrated biomass production could be competitive today both in terms of yield and of economic profitability. The increase of the production rates by shifting from local to centralized (national level) production will contribute significantly to this direction. In addition, biomass residues utilization, which do not compete at any level with the primary food needs, could be utilized as an important input to the raw material supply side. Considering the above, the aim of the present work is the analysis of the biomass and biomass residues supply chain. The work will attempt to apply the traditional supply chain principles to the biomass in order to organize its best exploitation either for power or for heat generation. To that effect, a mathematical optimization model will be developed. The appropriate optimization criteria (supply chain performance measures) will be defined and the constraints will be identified for such a novel supply chain optimization problem. The parameters determining the problem will be identified and, if possible, quantified. Finally, one of the most important characteristics and added value of the work is the knowledge transfer from conventional to a novel supply chain and valuable conclusions for the implementation of existing knowledge to new concepts. Keywords: biomass supply chain development, residues utilization, mathematical optimization, decentralized production. 1. Introduction scope Urging to play a pioneer role to the energy security supply scheme as well as to meet the mandates of the Kyoto protocol, seeking for a significant reduction of green house gas emissions, the penetration of alternative energy sources had been reinforced. In that PROCEEDINGS 1

2 framework wind as well as solar energy had been extensively applied to deal with the renewable electricity issue. In contrast to the technological evolution which stimulated the penetration rate of wind turbines, photovoltaics and solar based in general systems, biomass penetration rate has followed a rather slow time evolution, as its exploitation is not proportional to the technological progress. Proof evidence to that is the fact that in ancient years in small, undeveloped societies, biomass had been used as a primary energy supplier covering mainly cooking and heating needs. As biomass encompasses an extended range of end- products, its dispersed character along with its world-wide techno-economic potential, has motivated the academic community to appraise its contribution in the future energy supply, both at a regional and at a global level (Ahumada et al., 2009, Dunnett et al., 2007, Sokhansanj et al., 2006, IEA, 2009). Biomass could be a substantial input to the global primary energy supply side by 2050 with optimistic scenarios claiming for a contribution between 25%-30% (IEA, 2009). This is why biomass has been the focus of many researchers assessing the theoretical technical and economicpotential contribution of biomass (De Wit, 2010, EEA, 2006, Van der Hilst, 2010, Van Dam, 2007). It is the only renewable source that can replace fossil fuels in all energy markets in the production of heat, electricity and transportation fuels. However, its viability as a primary energy supplier has been jeopardized by the food vs. fuel debate that put at first place in doubt the sustainability of biofuels, mainly because of their intensive demand of resources, such as land, water and labour. These concerns essentially focused on the first generation of biofuels and less on the second, have put significant barriers to biomass further penetration and set under re-consideration the EU associated targets (European Commission, 2009). The production of second-generation biofuels with special focus on waste residues as feedstock is currently supported, in order to avoid the direct and side effects that stem from the utilization of energy crops and to support the up-scaling of new technologies towards the biorefineries concept. Waste-to-energy plants offer both, generation of clean electric power and environmentally safe waste management and disposal. Seeking to evaluate biomass performance and demonstrate its possible future strategic role, the present work aims to the optimization of the integrated biomass supply chain with special focus on biomass residues utilization. For this purpose, biomass supply chain is firstly analyzed in its generic form (logistics, process steps, parameters, constraints and energy streams). Then, the biomass to residues supply chain with the feedstock been met at national level is examined in detail. In addition a qualitative analysis of the interrelated parameters and the critical variables is carried out aiming at maximizing the total value of the system either in PROCEEDINGS 2

3 terms of energy and/or in economic profitability. By the incorporation of Geographic Information System (GIS) in the input data / side the visualization of the results will be facilitated regarding not only for the quantities of the derived end fuel, power and heat but also their siting in the appropriately selected Greek territories. The result of the present work will serve as a generic Decision Support System (DSS), which under the flexibility that modelling offers, will be able to incorporate all available biomass supply chain infrastructures switching from operational/ tactical to strategic, state level decision making. 2. Biomass characteristics and conversion routes The biomass and more specifically the biomass derived energy (bionergy) is the renewable energy made from any organic material from plants or animals. Sources mobilized to be converted to bioenergy incorporate a wide range of feedstock from diverse origins like agricultural and forestry residues, municipal solid wastes, industrial wastes, and terrestrial and aquatic crops grown solely for energy purposes. Additionally according to the different end energy uses i.e. heating, power (electricity) generation or transportation specific terminology to biomass may also be applied. However in the general case biomass characterization follows two key principles: the supply side (which types of raw materials are used) and the demand side (in which type of end product/ energy it is transformed) exceptionally for biofuels, the categorization to 1st, 2nd, 3rd and 4th generation is a bilateral resolution between feedstock and the processing technology. As one may note from the following illustration three major process technologies are employed to biomass energy conversion: thermo-chemical (combustion, pyrolysis, and gasification), bio-chemical (digestion and fermentation) and mechanical extraction with transesterification (McKendry, 2002a). The selection criterion of the raw material and accordingly of the end product is the moisture content of the biomass i.e. sugar cane (which has high moisture content) requires an aqueous conversion like fermentation and leads to biofuels, while a dry biomass such as wood is more economically suitable for pyrolysis; finally, gasification is suitable for heat and power (McKendry, 2002b). Usually bioenergy refers either to energy systems that produce heat and/or electricity or 'biofuels' referring to liquid fuels for transportation (Figure 1). PROCEEDINGS 3

4 5 Oil crops (rape, sunflower, et c.), waste oils, animal fats 6 Sugar and starch crops 7 Lignocellulosic biomass (wood, st raw, energy crop, MSW, et c.) 8 Biodegradable MSW, sewage sludge, manure, wet wastes (farm and food wastes) and/or 1 (Biomass upgrading)+ Combustion POWER 2 Gasification (+ secondary process) POWER 3 Pyrolysis (+ secondary process) 4 Anaerobic Digestion (+ biogas upgrading) HEAT and/or POWER 9 Oil crops (rape, sunflower, et c.), waste oils,animal fats 10 Sugar and starch crops 11 Lignocellulosic biomass (wood, st raw, energy crop, MSW, et c.) 12 Biodegradable MSW, sewage sludge, manure, wet wastes (farm and food wastes) 13 Photosynthetic micro- organisms, e.g microalgae and bacteria 14 Trans-esterification or hydrogenation 15 (Hydrolysis) + Fermentation 16 Gasification (+ secondary process) 17 Pyrolysis (+ secondary process) 18 Anaerobic Digestion (+ biogas upgrading) 19 Other biological /Chemical routes 20 Bio-photochemical routes Biodiesel, Bioethanol Syndiesel Renewable diesel Methanol Dimethylether Hydrogen Biomethane Figure 1. Bioenergy conversion routes and processes (Papapostolou et al., 2010) However biomass penetration had initially faced traditional - economic barriers related to its effective organization. More recently, more serious barriers have appeared, concerning issues like land availability for energy crops, food demand increase, access to natural recourses like water, the choice of the energy crops and the associated biomass yields. A valuable solution to that could be given if switching from traditional feedstock to residue based one. Waste derived raw materials do not compete either in environmental or in social level with primary goods and resources as the majority of the other traditional biomass recourses does. As far as it concerns Greece, it has a significant technical and economic exploitable potential of this kind of feedstock (Table 1). Currently at local level there are over 30,000 calf-breeding farms with more than 700,000 breeding animals and 36,500 pig breeding farms with 140,600 sows (Zafiris, 2007), (Figures 2,3). Moreover as one may note, the equal distribution of piggeries (Figures 2,3) being located in the northern Greece provides the opportunity for decentralized energy generation, with the creation of a suitable distributed power network. PROCEEDINGS 4

5 Table 1. Biomass availability and characteristics from different types of feedstock in Greece (EL. STAT., 2008) Raw material availability in Greece Type of raw (tn/year) (Average material quantity of ) Crop yield (tn/acre/year) Humidity (%) (Average crop yield of ) dry ash free 1 Animal Waste (t/unit/year) basis Energy Energy yield content (GJ/acre) (MJ/kg) 19,00-2 Straw ,97 270,415 15% 17, Beet ,531 48% 5, Olive Trees , ,37 60% 15, Corn ,949 20% air dry 14, Hard Wheat ,678 20% air dry 14, Cotton ,204 42,96% 17, Barley ,825 20% air dry 14, Sunflower ,572 dry weight 25, Rice ,535 20% air dry 14, Soya 25 0,335 20% air dry 14,70 5 Figure 2. Animal waste potential in Greece (Zafiris, 2007) Figure 3. Spatial Distribution of piggeries in Greece (Zafiris, 2007). In the following session the generic biomass supply chain will be analyzed and the basic streams and characteristics of the residues to energy supply chain will be identified on the basis of the types of feedstock, the process technologies and the end products. Then, the PROCEEDINGS 5

6 supply chain optimization model will be developed exploiting all the aforementioned information. 3. Biomass supply chain with special focus on biomass residues The analysis of the biomass supply chain basic structure leads to four major processing steps (Figure 4): 1. Feedstock production (harvesting and collecting). 2. Feedstock processing (either to biofuel or drying and chipping for the production of heat and power and storage afterwards). 3. Biofuels distribution and blending / digestion to biogas (only applicable if animal wastes are used as raw material). 4. End product consumption in the case of biofuels and combustion in the case of heat and power generation). In case that the end output is heat and power the following stages maybe encountered: 1. Biomass harvesting/collection (from single or several locations). 2. Treatment and storage (in one or more intermediate locations). 3. Digestion to biogas - (energy conversion) (Figure 5). 4. Combustion to heat and power. Figures 4, 5. Biomass to fuel heat and power supply chain with the incorporation of animal wastes input stream and theirs characteristics (Papapostolou et al., 2010) Resources Drying Anaerobic Digestion* Heat and Power Raw Materials Storage Biogas *This stage applies Animal wastes only if there are animal wastes in Chipping supply side Dealing with the biomass feedstock in the residues supply side it can be noted that there is a wide variety of agricultural, forestry, municipal and animal derived residues. There are mainly by-products of mills, animal manures and land clearing residues, fruit ones and tree trimmings crop residues from corn and small grains i.e. wheat straw. Biomass today predominant use for heating purposes simply consists of fuel wood applications. PROCEEDINGS 6

7 The selection of the appropriate technology - in the case of residues as feedstock - mainly depends on the biomass moisture content and the biomass end fuel applications. In the following table an appropriate matching of the most common conversion technologies in relation to the end product and to the type of raw material is presented. Again the factors that influence the assortment of the conversion process include the desired form of the produced energy and the type and quantity of biomass feedstock (Table 2). Table 2. Major feedstock and conversion processes to fuel, heat and power (Iakovou et al., 2010) Major biomass feedstock Technologies Conversion process Energy or fuel produced Wood waste Aerobic (ethanol production) Bio - chemical Ethanol Animal manure Agricultural waste Anaerobic (biogas production) Bio - chemical Biogas Aerobic decomposition Bio - chemical Heat Direct combustion Thermochemical Heat, Steam, Electricity Anaerobic (biogas production) Bio - chemical Biogas Aerobic decomposition Bio - chemical Heat In the view of the above, one may note that waste to biomass supply chain in its generic form has a very complicated structure, incorporating a wide range of parameters (raw materials, fuel production costs in the plant, transportation/logistics costs). That broad range of combinations ensures that the examined modelling problem has at least one, feasible solution, even if solved at strategic (country level) and/ or at operational (prefecture level). 4. Optimization of biomass supply chain The proposed model has the capability to incorporate parametrically a large number of biomass residues types so as to produce heat, power and biofuels. The outcome indicates, among other results, which biomass types should be chosen and in which quantities in order to optimize the total value of the supply chain. Furthermore, the results of the optimization will indicate the location that any new plant if needed- should be sited with the incorporation of GIS. This integrated approach takes into account in an integrated way all the PROCEEDINGS 7

8 problem parameters and characteristics and leads to the optimal efficiencies of the biomass to waste supply chain. In the general case, the structure and main characteristics of the optimization model are the following: Problem definition For a given time horizon For a set of selected geographical areas For a set of raw materials Optimization criterion Maximize the total value (in economic terms and appropriately defined) deriving from biomass exploitation Subject to: Conversion constraints Conversion of raw material into heat and or power. The delivered quantity of heat for each raw material is determined by the corresponding conversion factor. Conversion of raw material into biofuels. The delivered quantity of heat for each raw material is determined by the corresponding conversion factor. Availability constraints Raw materials availability (residues production capacity, seasonality, animal wastes production capacity). Plants storage facilities- processing units availability (production capacity, of the existing infrastructures). Capacity constraints Capacity of the processing facilities. Capacity of the storage facilities. Biomass safety stock for full-load operation. Capacity of the CHP units. The delivered quantity of biofuels is determined by the capacity of the each production plant. Mass balances considering yields in the production units. Energy demand constraints Satisfying the energy demands. The produced energy mix must satisfy the heat, power and transportation demands. Variables Raw material produced quantities, facilities siting, creation or not of new infrastructures, end products produced quantities (heat- power- biofuel). Parameters Land s availability, feedstock to end product conversion factors, end-fuel production cost in the plants, productions plants capacities, end products selling prices etc, transportation/logistics costs, environmental (measurable) impacts for each of the selected methods. 5. The use of GIS for supply chain optimization In the last decade there has been a renewed interest towards the use of biomass for energy production, both at strategic and policy making as well as at operational level. Therefore Geographical Information System (GIS) has widely been used as an assessment tool in biomass exploitation, incorporating agricultural, economic, climatic, and infrastructural data PROCEEDINGS 8

9 (Beccali et al., 2008, Noon and Daly, 1996, Ranta, 2005, Vianna et al., 2010,). Traditionally GIS has been used for siting and routing problems (Haddad et al., 2008, Ma et al., 2005, Panichelli et al., 2008) seeking to determine the optimal site selection for the allocation of production/processing plants as well as the shortest paths to them. Today the incorporation of multiple statistical and other data basis in combination to the application of optimization algorithms has rendered GIS a valuable tool to the optimal biomass exploitation both in terms of energy yield and economic profitability (Fiorese and Guariso, 2010, Kinoshita et al., 2009, Nibbi et al., 2004, Voivontas et al., 2001). More specifically, considering the examined problem of biomass to wastes supply chain exploitation, GIS has been used as a livestock assessment tool teaming up with relational data management tools in order to estimate the energy and biogas potential of livestock residues of all major groups of stock-raising animals (Batzias, 2005). Also the best energy crops mix/ bioenergy maximization has also been carried out by the integration of GIS data (spatially continuous) with data derived from the agricultural field (spatially discrete) (Fiorese and Guariso, 2010). Furthermore other applications of GIS include definition of potential areas for gathering the residues originating from the pruning of olive groves, vineyards and other agricultural crops, and to assess biomass available for energy cultivation (Vianna et al., 2010). In Figure 6 one may see the coupling of the optimization algorithm with the GIS for the geo- spatial representation of the modelling results, as well as the representative or the case study layers. GIS representative layers Geomorphologic variables (slope- altitude) Geotechnical characteristics Land use Climate Protected areas Set aside lands Transportation network Road infrastructures Storage infrastructures Conversion infrastructures End consumers location Industrialized zones PROCEEDINGS 9

10 Inputs Layers (Parameters Variables) Objective function Variables Parameters Mathematical modeling formulation Outputs Data Maps (Optimization criterion, quantities of end products, site selection for feedstock production, site selection for feedstock, geo- spatial representation) Figure 6. Algorithm implementation under the idea of Nibbi, L., et al Conclusions The aim of the present work is the analysis of the biomass and biomass residues supply chain. With special focus on Greece and the local feedstock availability, the traditional supply chain principles have been applied to a more specific, waste -to- energy supply chain as to optimally exploit its output for fuel, heat and power generation. To that effect, a mathematical optimization model has been developed with the objective function of the problem being the optimal total value (of the system defined as the total energy produced and/or the profitability of the system). Additionally, as the biomass exploitation has a strong spatial dimension, the coupling of the optimization algorithm with GIS has also been considered. The results of the analysis will not only provide to the users an optimal value and the quantities of end products, but also the site selection for the considered feedstock as well as the siting of the power plants, if the model evaluates it as necessary. In its future prospects, the methodology developed will be implemented to two representative case studies, seeking to provide the decision makers with real alternatives concerning the strategic as well as the operational prospects of biomass exploitation in Greece. References 1. Ahumada O. and Villalobos J.R. (2009), Application of planning models in the agrifood supply chain: A review. European Journal of Operational Research, 196 (1), pp Batzias, F.A., Sidiras, D.K.and Spyrou E.K. (2005), Evaluating livestock manures for biogas production: a GIS based method. Renewable Energy, 30 (8), pp PROCEEDINGS 10

11 3. Beccali, M., Columba, P., D'Alberti, V. and Franzitta, V. (2009), Assessment of bioenergy potential in Sicily: A GIS-based support methodology. Biomass and Bioenergy, 33 (1), pp De Wit, M. and Faaij, A. (2010), European biomass resource potential and costs. Biomass and Bioenergy 34 (2), pp Dunnett, A., Adjiman, C. and Shah, N. (2007), Biomass to Heat Supply Chains: Applications of Process Optimization. Process Safety and Environmental Protection, 85 (5), pp EL. STAT, Hellenic Statistical Authority (2008), General Secretariat of the National Statistical Service of Greece [online]. [Accessed 11 November 2009]. Available from: < 7. EEA, European Environmental Agency (2006), How Much Bioenergy can Europe Produce Without Harming the Environment? EEA, Copenhagen, Denmark, p European Commission & Council, Directive 2009/28/EC of the European Parliament and of the Council on the promotion of energy from renewable sources and amending and subsequently repealing Directives 2001/77/EC and 2003/30/EC, April Fiorese, G. and Guariso, G. (2010), A GIS-based approach to evaluate biomass potential from energy crops at regional scale. Environmental Modelling & Software, 25 (6), pp Haddad, M.A. Anderson, P.F. (2008, A GIS methodology to identify potential corn stover collection locations. Biomass and Bioenergy, 32 (12), pp Iakovou, E., Karagiannidis, A., Vlachos, D., Toka, A. and Malamakis, A. (2010), Waste biomass-to-energy supply chain management: A critical synthesis. Waste Management, In Press, Corr. Proof, Avail. online IEA BIOENERGY (2009), Bioenergy a Sustainable and Reliable Energy Source A review of status and prospects. Report ExCo: 2009:05, available on line at: Kinoshita, T., Inoue, K., Iwao, K., Kagemoto, H. and Yamagata, Y. (2009), A spatial evaluation of forest biomass usage using GIS. Applied Energy, 86 (1), pp Ma, J., Scott,N.R., DeGloria,S.D. and Lembo,A.J. (2005) Siting analysis of farmbased centralized anaerobic digester systems for distributed generation using GIS. Biomass and Bioenergy, 28 (6), pp McKendry, P. (2002), Energy production from biomass (part 2): conversion technologies. Bioresource Technology, 83 (1), pp PROCEEDINGS 11

12 16. McKendry, P. (2002), Energy production from biomass (part 1): overview of biomass. Bioresource Technology, 83 (1), pp Nibbi, L., Tondi, G., Martelli, F., Maltagliati, S., Chiaramonti, D., Riccio, G., Bernetti, I., Fagarazzi, C. and Fratini R. (2004), GIS Methodology And Tool To Analyse And Optimise Biomass Resources Exploitation. 2nd World Conference on Biomass for Energy, Industry and Climate Protection, May 2004, Rome, Italy. 18. Noon, C.E. and Daly, M.J. (1996), GIS-based biomass resource assessment with BRAVO. Biomass and Bioenergy, 10 (2-3), pp Panichelli, L. and Gnansounou,E. (2008), GIS-based approach for defining bioenergy facilities location: A case study in Northern Spain based on marginal delivery costs and resources competition between facilities. Biomass and Bioenergy, 32 (4), pp Papapostolou, Ch., Kondili, E. and Kaldellis, J.K. (2010), Technological and Environmental Impacts Evaluation of Biomass and Biofuels Supply Chain. Paper accepted for presentation in World Renewable Energy Congress (WREC XI), September 2010 Abu Dhabi UAE. 21. Ranta, T. (2005), Logging residues from regeneration fellings for biofuel production-a GIS-based availability analysis in Finland. Biomass and Bioenergy, 28 (2), pp Sokhansanj, S., Kumar A. and Turhollow, A.F. (2006), Development and implementation of integrated biomass supply analysis and logistics model (IBSAL), Biomass and Bioenergy, 30 (10), pp Van der Hilst, F., Dornburg, V., Sanders, J.P.M., Elbersen, B., Graves, A., Turkenburg, W.C., Elbersen, H.W., van Dam, J.M.C., Faaijet, A.P.C. (2010), Potential, spatial distribution and economic performance of regional biomass chains: The North of the Netherlands as example. Agricultural Systems, In Press, Corr. Proof, Avail.online Van Dam, J., Faaij, A.P.C., Lewandowski, I. and Fischer, G. (2007), Biomass production potentials in Central and Eastern Europe under different scenarios. Biomass and Bioenergy, 31 (6), pp Viana, H., Cohen,W.B., Lopes,D. and Aranha, J. (2010), Assessment of forest biomass for use as energy. GIS-based analysis of geographical availability and locations of wood-fired power plants in Portugal. Applied Energy, 87 (8), pp PROCEEDINGS 12

13 26. Voivontas, D., Assimacopoulos, D. and Koukios, E.G. (2001), Assessment of biomass potential for power production: a GIS based method. Biomass and Bioenergy, 20 (2), pp Zafiris, C. (2007), Biogas in Greece: Current situation and Perspective. [Accessed 6 June 2010]. Available online at: < III/Christos_Zafiris.pdf>. PROCEEDINGS 13