Elsevier

Biosystems Engineering

Volume 120, April 2014, Pages 81-91
Biosystems Engineering

Special Issue: Operations Management
Research Paper
Optimisation and investment analysis of two biomass-to-heat supply chain structures

https://doi.org/10.1016/j.biosystemseng.2013.07.012Get rights and content

Highlights

  • Pellet production has currently higher financial yield than CHP generation.

  • Pellet production financial yield is very sensitive to pellet price changes.

  • CHP generation has a lower investment risk than pellet production.

  • Pellet financial yield is sensitive to biomass price, CHP yield to capital cost.

As oil prices have risen dramatically lately, many people explore alternative ways of heating their residences and businesses in order to reduce the respective cost. One of the options usually considered nowadays is biomass, especially in rural areas with significant local biomass availability. This work focuses on comparing two different biomass energy exploitation systems, aiming to provide heat to a specific number of customers at a specific cost. The first system explored is producing pellets from biomass and distributing them to the final customers for use in domestic pellet boilers. The second option is building a centralised co-generation (CHP) unit that will generate electricity and heat. Electricity will be fed to the grid, whereas heat will be distributed to the customers via a district heating network. The biomass source examined is agricultural residues and the model is applied to a case study region in Greece. The analysis is performed from the viewpoint of the potential investor. Several design characteristics of both systems are optimised. In both cases the whole biomass-to-energy supply chain is modelled, both upstream and downstream of the pelleting/CHP units. The results of the case study show that both options have positive financial yield, with the pelleting plant having higher yield. However, the sensitivity analysis reveals that the pelleting plant yield is much more sensitive than that of the CHP plant, therefore constituting a riskier investment. The model presented may be used as a decision support system for potential investors willing to engage in the biomass energy field.

Introduction

Biomass is a renewable energy source that has been used by mankind since ancient time. Lately, biomass has gained significant attention, due to the necessity of reducing CO2 emissions and the technological improvements in biomass energy conversion. In addition, biomass use has been favoured by the recent increase in oil prices, leading many people to explore alternative means of heating their residences and businesses in order to reduce the respective cost.

Several biomass types currently have alternative uses (for example in the paper and pulp industry, as animal feedstock and bedding etc.), whereas others do not. Usually agricultural residue biomass types do not have an alternative use. In many cases, agricultural residue biomass is either not exploited or in some cases is burned in the fields, as it can be harmful for cultivations if left to decay. Tree prunings (e.g. from apple, olive or peach) are one example of agricultural biomass residues that are currently burned in the fields, which is also examined in this work. Prunings are a woody type of biomass, which means it is suitable for use in most types of biomass processing and energy conversion equipment. Furthermore, the fact that it does not currently have significant alternative use means that it may be procured at lower prices than commercial biomass types.

There exist various systems for generating energy from biomass. Lately, pellets from biomass have been extensively used worldwide (USDA, 2009). In Greece, pellets have also started being produced and are currently used in small quantities, but with a high rate of increase (Karkania, Fanara, & Zabaniotou, 2012). Pellets are a densified form of biomass with very low moisture, increased energy content, easy to handle, store and transport and have the advantage that their specifications can be standardised. For these reasons, using pellets for heating has seen dramatic increase over recent years.

Another option for biomass energy generation that has found many applications, particularly in northern Europe, is centralised Combined Heat and Power (CHP) generation. This option has the advantage that biomass may be used to produce simultaneously electricity and heat. Electricity can be sold to the grid, usually at a premium price, due to the renewable nature of biomass, and heat can be used for industrial, commercial or domestic heating. However, transferring the heat to the final consumers usually entails investing in a district heating pipeline and distribution network.

The two abovementioned options can be used to address the heating needs of the same consumers. However, the respective supply chains have significant differences. The main difference between the two options is that in the pellets case, the production is disengaged from the demand, since pellets can be stored. In the CHP case, heat has to be generated when demanded, as it cannot be stored in significant quantities or for a long time period.

The primary purpose of this work is to examine comparatively these two different energy supply chain options, to address the same heating needs, in regions with significant availability of currently unutilised agricultural biomass sources. The comparison is performed from the perspective of a potential investor willing to engage in the business of renewable energy generation. The question of finding the most appealing investment from the two options while satisfying the same heating needs with the same cost for the customers is to be answered here.

The significance of this work lies in the fact that a comparison of the two options has not been performed in the relevant literature, despite the fact that each of these energy generation options has been studied in isolation. In addition, a detailed optimisation model of the pellet supply chain is presented, including the pellet distribution function. This is a new approach, as the relevant literature contains only simulation models or cost estimations for the complete pellet supply chain.

Section snippets

Biomass energy recovery and biomass supply chain

Energy recovery from biomass has been extensively researched in past (Mitchell, Bridgwater, Stevens, Toft, & Watters, 1995) and in more recent studies (Rentizelas & Tatsiopoulos, 2010). The issue of biomass energy recovery is closely linked to biomass supply chain modelling. Various models concerning the supply chain of biomass have been published. The case of biomass-fired plants, producing CHP, has been researched by Tatsiopoulos and Tolis (2003), whilst the case of energy tri-generation has

Model

This paper aims to compare two biomass-to-energy supply chains. In order to perform this comparison, the supply chain structures are optimised. The first supply chain concerns collecting biomass to produce pellets, which are then distributed to consumers for domestic heat generation. The second supply chain concerns using the same biomass sources in a co-generation unit to generate electricity and heat. Electricity will be fed to the grid, whereas heat will be distributed via a district heating

Case study

The model has been applied to the case study municipality of Ampelonas, Greece. This municipality is located in the plain of Thessaly, where several types of agricultural residue biomass are locally available. In this work, only tree prunings have been considered as raw material for pellet production or CHP generation (Table 1), despite the fact that they are not the dominant cultivations in the region. The reason for including only woody biomass types is to ensure compatibility of the biomass

Results and discussion

The optimum values of the variables found by the optimisation model for both cases examined and the financial criteria values are presented in Table 3, Table 5 respectively.

The facility locations lie very close to one another and are both located on the lower bound of the proximity constraint of the model (equal to 2 km), obviously in order to reduce the distribution logistics cost for the pelleting case and the district heating pipeline investment cost and energy losses for the CHP case.

It is

Sensitivity analysis

Most parameters included in the model have a degree of uncertainty. Therefore, a sensitivity analysis of the optimum solution found has been performed in relation to the most important parameters. Each parameter has been changed within the range of ±50% from the base-case value, in steps of 10%, and the resulting change in the Profitability Index of the investment is presented in Fig. 3 for the pelleting plant and in Fig. 4 for the CHP plant.

The Profitability Index of the Pelleting plant

Conclusions

This work compares two different energy supply chain options, namely pellet production and CHP generation. The main difference between the two options is that, in the pelleting case, production is disengaged from demand, since pellets can be stored. In the CHP case, heat has to be generated when demanded, as it cannot be stored in significant amounts or for long time periods. A model has been presented that simulates the pelleting plant supply chain, both upstream and downstream. The system

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