Long-term planning methodology for improving wood biomass utilization

Energy 175 (2019) 818e829

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Long-term planning methodology for improving wood biomass utilization Vladimir Vukasinovic a, Dusan Gordic a, *, Marija Zivkovic b, Davor Koncalovic a, Dubravka Zivkovic a a b

University of Kragujevac, Faculty of Engineering, Sestre Janjic Str. 6, 34000, Kragujevac, Serbia University of Belgrade, Faculty of Mining and Geology, Djusina Str. 7, 11000, Beograd, Serbia

a r t i c l e i n f o

a b s t r a c t

Article history: Received 8 October 2018 Received in revised form 8 March 2019 Accepted 18 March 2019 Available online 24 March 2019

The insufficiently developed forest management system is often followed by undeveloped forest resources supply chain and insufficient institutional support. These cause inefficient usage of fuel-wood as well as huge amounts of unused forest residues. In order to achieve optimal and long-term sustainable utilisation of biomass, an original methodology based on the interaction of mathematical optimization and backcasting approach has been developed. Mathematical optimization is used for both generation and consideration of techno-economic parameters of the forest biomass supply chain. Besides, backcasting allows generating solutions by involving stakeholders (considering ecological and social components). The methodology has been applied on a case study of maximization of forest residues utilisation at one municipality in Serbia. The possibilities of its utilisation under current conditions are minimal and the obstacles for significant biomass utilisation have been defined. Using the methodology, desired future and criteria (ecological acceptability, economical acceptability and reliability) that could be satisfied by desired future have been determined. Drivers and key uncertainties (political will and economic situation) to achieve the desired future have been also specified. Pathways and necessary changes have been developed in order to achieve a desirable future, which should provide maximal utilisation of available biomass. © 2019 Elsevier Ltd. All rights reserved.

Keywords: Long-term planning methodology Forest biomass MINLP Backcasting

1. Introduction Biomass is of great importance in the energy sector of developing countries. Also, in these countries, biomass presents one of the important segments in achieving sustainable development [1]. If it is used in a sustainable way, biomass can be considered as CO2 neutral fuel that can contribute to a GHG emission reduction by substituting fossil fuels [2,3]. Currently, biomass annually covers around 10% (51 EJ) of global primary energy supply [4e6]. Biomass can be combusted in a similar way as coal in order to produce hot water or stream. Unlike coal, it emits 90% less SOx [7]. Biomass is the local and sustainable energy source that can be used as fuel for generating electricity, heat and biofuels. Its utilisation stimulates job creation at the local level [8]. Also, utilising biomass on a sustainable way contributes to reducing GHG emission and

* Corresponding author. E-mail address: [email protected] (D. Gordic). https://doi.org/10.1016/j.energy.2019.03.105 0360-5442/© 2019 Elsevier Ltd. All rights reserved.

energy dependence. It also stimulates economic development. However, in developing countries wood biomass is used on the traditional and often inefficient and unsustainable way. This means incomplete combustion or combustion on high temperatures that further cause high pollutant emission level. In order to improve the wood biomass utilization, especially those that are treated as waste, it is important to move towards modern and efficient technologies [9]. The biomass usage is not always easily and economically justified because biomass resource locations are geographically dispersed. Also, small bulk density significantly increases transportation costs [10,11]. On the other side, biomass influences on many social issues such as social acceptability, behaviour changes of citizens, community economic development, the possibility of job creation etc. [12,13]. Energetically, economically and environmentally optimal utilization of biomass is the first step in order to create necessary conditions for utilisation of available biomass potential. This requires detailed planning and management of forest resources and

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biomass conversion plants [14,15]. The efficiency of supply logistic system is one of the main barriers to efficient biomass utilization. A significant number of research dealt with this issue. Biomass supply chain optimization as one of the key elements and factors affecting energy and economic efficiency of biomass utilization were considered in several types of research [14,16]. Other research considered the most suitable technology and its allocation [17e20]. Biomass is geographically dependent renewable energy source (RES) and the geographical aspect is an important factor that affects the project feasibility. For that reason, the implementation of the geographic information system (GIS) is often very useful and necessary. GIS technologies can be of great importance in analysing the resources, storages and plant locations, as well as in defining transport routes and costs [21e25]. Decision-making process related to the exploitation of forest biomass is a complex process that must take into account a lot of factors [26]. Several research studies considered defining approaches to support the decision-making process related to the exploitation of forest biomass. These approaches were based on mathematical optimisation and GIS technologies [27e29]. Optimization of wood biomass utilization can significantly improve the use of this RES potential. However, considerable time and multi-level planning are required to create the necessary conditions for maximum utilization. Besides, usage of the biomass as one of RES in order to achieve sustainable development is a very complex issue. The tendency for improving the environmental condition as well as the transition to greater use of biomass requires technological, cultural, organizational and institutional changes on several levels. These changes are often related, which can further affect the complexity. In addition to their complexity, changes in some sectors (energy, industry, households, agriculture, transport, etc.) require a long-time of implementation periods (up to several decades) [30]. The complexity of changes in these sectors is based on a large number of variables, a large number of actors and their interests and complex social processes. In order to perform required changes, it is necessary to develop long-time strategies and pathways. Plans, strategies or scenarios related to the use of biomass and other RES most commonly are developed for periods of 15, 20 and more years. The pathways and strategies are usually a part of certain scenarios. According to the state to be achieved, long-time scenarios can be divided into three groups [31]: 1) probable (scenarios of common behaviour e “What will happen?“), 2) possible (prediction scenarios e “What could happen?“) and 3) desirable (normative scenarios e “How to achieve a desirable future?” or “How a solution to a particular problem might look?“). Backcasting is one of the approaches for creating the third group of scenarios. Backcasting could be defined as generating a desirable future and looking backwards from this future in order to define scenarios and pathways. Initially, backcasting was developed for energy purposes [32], and during the time it was applied in wide areas related to energy planning and sustainable development [33e35]. Also during the time, it was recognized that stakeholders participation in activities related to achieving sustainability could be significantly important. As mentioned above, usage of biomass influences on significant numbers of economic, technological, structural and social factors. This is the main reason, why the development of plans shouldn’t be done by individuals or closed group. Stakeholders’ participation is of key importance not only because of their roles. They also have the necessary knowledge and necessary resources [33,36,37]. The process of stakeholder

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involvement is not always easy because of the behaviour and the wishes of the citizens to join such processes. This is especially emphasised in the southern European countries [38]. Backcasting was subject of consideration of many researchers. Quist and Vergragt [39] proposed a methodological framework based on the stakeholder’s participation. The aim of the proposed backcasting approach was to find a suitable methodology that would inspire stakeholders to take part in a discussion related to sustainable development. The transition to energy systems with less CO2 emissions has been often accompanied by a large number of uncertainties [40,41]. Backcasting methodology was developed in order to define the scenarios for the reduction of CO2 emissions in the UK area. The main goal of developed methodology was reduced CO2 emissions by 60% by 2050 compared to 1990. Five scenarios were defined by using the methodology [42]. Weddfelt et al. applied a backcasting methodology for defining environmental vision and strategies. The methodology was based on a large number of interviews with stakeholders and the analysis of the obtained data [43]. The reducing energy consumption which comes from fossil fuels in households, commercial and public buildings is of great importance in order to achieve sustainable development. According to the national goal of reducing energy consumption per heating unit in residential and commercial buildings by 50% by 2050 in Sweden, Svenfelt et al. developed a methodology based on backcasting approach and work with focus groups [44]. A similar goal (reduction of final energy consumption per capita by 60% for a 60-year period in households in Stockholm), was the base for developing „target-orientated backcasting” methodology [45]. Both sustainable transformation and improvement of the heating system are essential for achieving goals in the field of improving the environmental condition and the quality of life as
c well as reducing the negative effects of climate change. Zivkovi et al. [46], presented a methodology which combines modelling urban energy systems and a participatory approach. In order to better understanding possible solutions, the paper presents the interaction of different approaches for the development of the scenarios. The use of backcasting in the emerging renewable energy sector in China has been analysed in Ref. [47]. Applying a backcasting approach, obstacles that were at the base of the existing energy system and problems related to technology management were identified. Achieving optimal and sustainable use of biomass requires detailed planning and management of forest resources, supply chains and biomass conversion facilities, as well as consideration of a large number of social and environmental factors. A long-term planning process, which takes into account a large number of factors, requires the use of different techniques and approaches in order to define long-term scenarios. In the paper, the new methodology, based on the interaction of mathematical optimization and backcasting approach, for the development of long-term scenarios for the improvement and maximization of wood biomass utilization is presented. 2. Methodology The proposed original methodology has been based on integral implementation and interaction of mathematical optimization and backcasting approach, Fig. 1. Integral implementation of mathematical optimization and backcasting approach means that results obtained from one are input to another and vice versa. Mathematical optimization is an expert way of generating a solution, while backcasting approach allows generating solutions by

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Fig. 1. Proposed methodology.

involving stakeholders. Stakeholders’ participation contributes to the sustainability of obtained solutions. Mathematical optimization considers techno-economic parameters, while the backcasting approach takes into account an environmental and social component. The mathematical optimisation model of proposed methodology has been developed as an original mixed integer nonlinear programming (MINLP) model. The MINLP model was described in the article [48]. Defined MINLP model describes and considers four groups of biomass valorisation plants (biofuel production, heating plants, CHP plants and thermal power plants). The comprehensive mathematical model also allows obtaining the techno-economic parameters of these plants. These parameters include following: plants locations, plants types and installed capacity, the required quantities of wood biomass, biomass resources locations, the estimated transporting costs, the estimated investment costs and the operating costs of a plant. Thus, in proposed methodology, the mathematical model is used for determining the optimal amount of biomass that can be used in the current conditions, as well for generating optimal solutions in accordance to long-term planning scenarios (when the model is supplemented by the criteria and parameters defined by applying backcasting). On the other side, in the proposed methodology, the backcasting approach is based on stakeholders’ participation through the interviews and one workshop. Based on the research carried out in Ref. [49], it has pointed out that the traditional approach with two workshops negatively affects the quality of the obtained results. Instead of that, it is recommended to provide stakeholders’ participation throughout the complete process and only one workshop. In the proposed methodology, the backcasting approach has been used for defining obstacles for maximum utilization of potentials in the current conditions, and for defining criteria and drivers and obstacles for long-term improvement of use and maximization of utilization of the available wood biomass potential. In addition, the backcasting approach has been used to develop long-term scenarios, i.e. for choosing the optimal solution, analysing optimal solution considering key uncertainties and defining the pathways and the necessary changes. Proposed methodology consists of seven steps, described below.

2.1. Goal The goal or the result of applying methodology should be to create a condition for optimal and sustainable use of the available wood biomass potential from the considered region. It means, the goal of the proposed methodology should be set according to the case study that will be conducted. 2.2. Current state analysis Current state analysis has meant analysing both the wood biomass potential and usage of them. Also, it has included collection, analysis and systematization of data on the potential of wood biomass, as well as mapping of locations and determination of available quantities of wood biomass. Mapping the location of wood biomass can be carried out on several ways (in dependence on its type): obtaining data from SOE Srbija
sume, using statistical data, obtaining data from the wood processing industry, etc. [48]. As wood biomass is usually located on a large number of locations the estimation of their potential is a challenging task [50]. In the proposed methodology the usage of GIS technologies is recommended in order to map these locations. Also, the mapping of biomass valorisation plant locations could be conducted in the same way. Mapping the location of wood biomass and a location of the plant for its valorisation enables the determination of optimal transport routes. All of the above data should be systematized into a database that is used as an input to a mathematical model. 2.3. Optimal quantity of biomass for using under current condition A certain amount of available biomass can be used in existing plants (under current conditions), where the technical conditions allow it (without significant C-T-S (cultural-technological-structural) changes). These may be sites where some form of biomass is already utilised or where the modification of existing plants is possible. In this step, developed mathematical model can be converted into linear programming (LP) model because both annual heat consumption and characteristic of existing plants are usually known. The objective function of this linear model has been the maximization of biomass amounts y [t] from location i, which is

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possible to utilise in existing plants on location j (Eq. (1))

max

XX yi;j i

! (1)

i

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Based on their answers, the vision of the desirable future can be defined. The vision includes defining the type of biomass on which the desirable future would be based, the technologies to be used and the level of biomass usage (supply). 2.6. Generating and analysing solutions

2.4. Obstacles for maximum utilization of available potential under current conditions After determining the optimal amount of biomass that can be used under current conditions, the next step has been the identification of obstacles for maximum utilization of the available biomass potential. It is often necessary to identify the reasons why a significant part of the wood biomass potential is unused. It is recommended to define obstacles by stakeholders’ participation. The stakeholders have been involved based on the analysis of the current state and based on defined tools that enable the selection of adequate stakeholders [38,44,49]. Stakeholders’ interest and power are different depending on the particular problem and it is quite important to select stakeholders that have an adequate interest or/ and power. Within the presented methodology it has been proposed to apply power - interest analysis. Obstacles to maximizing the utilization of available wood biomass potential should be generated during stakeholder comprehensive interviews1. Interviews have been based on a prepared questionnaire [51]. One part of the questionnaire has been related to the current energy system and the possibility of using wood biomass. Questions from this part of questionnaire are related to the current energy system, current biomass usage (and which types of biomass) and whether such use is adequate, which are the drivers and obstacles to the use of biomass, whether some activities are beginning carried out, whether environmental protection is taken into account, and whether citizens are provided with information related to the use of biomass (potential and opportunities). 2.5. Criteria and driving forces for long-term maximization and defining desirable future Criteria and driving forces to the long-term maximization of available potential biomass utilization, as well as desirable future in terms of improving the use of wood biomass, have been defined by systematization and critical analysis of the results of the interview. Questions related to the long-term planning are also a separate (third) part of the questionnaire. The purpose of this part of the questionnaire is to obtain information that would help in the creation of long-term scenarios. Answers to these questions provide information on existing long-term plans and projects, as well as about the stakeholders’ experience in the long-term planning process. Stakeholders define the criteria that should be satisfied by desirable future, as well as give opinions on which systems and technologies the desirable future should be based on. Through this process, many criteria can be defined. It is also possible that similar criteria have been defined in a different way by different stakeholders [46,61]. A large number of criteria are impractical for further work, so it is recommended to select a few (usually up to five) most valuable criteria and sub-criteria. Defining the criteria, analysing the proposed criteria and selecting the most valuable criteria should be done at the workshop and obtained solution must be the result of the consensus of all stakeholders. Stakeholders give their vision of the desirable future through interviews.

1

It means that during interviews stakeholders have answered on questions related to several steps of proposed methodology.

Incorporation of defined criteria in the mathematical model as additional constraints ensures that generating solutions in the mathematical model is in accordance with defined criteria. It is of great importance because opinions of stakeholders have been described by criteria. Thus, the sustainability of generated solutions is provided. Defined desirable future related to biomass exploitation can often require the inclusion of new parameters in the optimization model. These parameters can include, for example, new consumers, the new location of plants etc. Parameters can be added directly to the model or to the database. After analysing criteria and desirable future that have been defined through interviews and their inclusion as new constraints or parameters to the model, solutions are generated using mathematical optimization. It is proposed to create solutions according to several scenarios and objective functions in order to find optimal solutions. In the proposed methodology, three objective functions have been used for generating solutions, Table 1. According to the developed MINLP model [48], the objective functions can be calculated according to (Eq. (2) e Eq. (5)). NPV can be calculated as:

NPV ¼ ANP,

1  ð1 þ dÞlc  Inv d

(2)

where: ANP [V] - Annual Net Profit, d [%] - discount rate. lc [year] - project lifecycle. Inv [V] - investment. NPVQ is the ratio between NPV and investment:

NPVQ ¼

NPV Inv

(3)

For the previous equations, ANP has been defined as the difference between revenues and costs:

ANP ¼ G  ðCpr þ Ctr þ CplÞ

(4)

where: G [V] - total revenue from all plants. Cpr [V] - cost of biomass on all primary storages. Ctr [V] - total transportation costs. Cpl [V] - total operational and maintenance cost for all plants. Finally, the last objective function determines the amount of wood biomass that could be utilised:

Y¼

XXX yi;j;k $bj;k i

j

(5)

k

G, Cpr, Ctr, Cpl, Inv, as well as Y, represent functions of decisional variables. Decisional variables are: yi,j,k [t/year] - variable which represents the annual amount of biomass that is transported from primary storage i to plant location j with used technology k.

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Table 1 Description of selected objective functions. Objective function

Description

maxNPVQ

Maximization of Net Present Value Quotient e shows which project is the most cost-effective. Higher NPVQ value means a more profitable project and allows ranking potential projects with regard to profit/investment [52,53]. This objective function is very important when the budget is limited. Maximization of Net Present Value e shows project’s earnings after a defined time period. Unlike a previous objective function, projects with the highest NPV value are not always the most cost-effective. On another side, higher values of NPV mean more funds for the next projects. Maximization of the utilised amount of wood biomass - represents the goal of developed methodology. This objective function determines the amount of wood biomass that could be utilised. In order to generate a cost-effective solution, it is necessary to include additional constraints in form of minimum acceptable NPV value.

maxNPV maxY

bj,k [] - binary variable - b ¼ 1 if on location j exists plant which utilizes technology k; b ¼ 0 otherwise. Driving forces have been defined during interviews and workshop, but it is important to define key uncertainties. The key uncertainties are drivers that have an influence on issues under consideration, but which changes during the time cannot be predicted or that do not belong to existing trends. Identification of key uncertainties has been done by positioning driving forces on diagram impact-uncertainties (see Fig. 7). It is proposed to find two or three key uncertainties. Since the key uncertainties are one of the main factors that affect the feasibility, generated solutions should be analysed according to them. This implies an analysis of generated solutions according to extreme values of identified key uncertainties and consideration of how to avoid or reduce their impact (see Fig. 8).

Fig. 3. Heating systems in residential buildings.

2.7. Development of long-term scenarios The last phase of the proposed methodology is a backcasting analysis, which means looking backwards from a desirable future to nowadays. Backcasting analysis provides identification of necessary changes to achieve a desirable future. This requires answers to following questions and defining action plan [54]: 1) What changes are necessary? 2) Who should do these changes? 3) How can changes be done? Defining an action plan encompasses planning specific activities in order to achieve the desirable future. Finally, it is proposed as useful to re-analyse stakeholder’s power and interest. It is possible to involve additional stakeholders in order to ensure the quality in some cases.

Fig. 4. Areas considered under scenario S4.

3. Results Developed methodology has been applied and tested on a case study e Improving and maximizing utilization of forest biomass in Ivanjica Municipality. General information about the case study is shown in Table 2. According to data obtained from SOE Srbija
sume, annual forest cutting is about 87,400 m3 of wood of which 14.30% are forest residues [55]. Cutting/increase ratio is about 59% which is lower than the proposed sustainable ratio (75%). But one part of the forest is on the protected area (I and II level of protection) under the Park of Nature “Golija” and the significant increase of this ratio should not be expected. The total energy potential of forest residues is significant (about 33,917.6 MWh), Table 3. However, due to the lack of investment funding in the energy sector as well as due to citizen Fig. 2. Fuels used for heating.

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Fig. 5. Economic parameters of optimal solution generated according to objective functions (S4 scenario).

Fig. 6. Analysis of driving forces.

political will

economic situation

Fig. 7. Sustainability of scenario S4 related to key uncertainties.

behaviour, usage of forest residues is on the very low level. Forest residues are the most important unused energy potential at Ivanjica municipality. Therefore, forest residues have been considered as the main subject of the case study. So, maximisation of exploitation of forest residues for energy purposes has been defined as the goal of the methodology applied to the case study. 3.1. Current energy system in the municipality Fuelwood is the main energy source for heating and cooking in

9772 households (more than 96%) Fig. 2. Only a quarter of the households use wood biomass in a relatively efficient way, whilst other use biomass on the traditional and inefficient way, Fig. 3 [58]. Traditional usage of fuelwood considers using fuelwood in lowefficiency furnaces with a low level of consumers comfort. In such heating systems, heat distribution in the building is often uneven. An additional problem is related to the traditional usage of fuelwood in multifamily residential buildings since they are not constructed for biomass-based individual heating systems. Also, most of buildings in Ivanjica are not adequate insulated (more than 83%). This is an additional problem for obtaining heating demand. About 85% of residential buildings were built more than 25 years ago [56,57]. Taking into account these data and data from both the National Typology of Residential Buildings in Serbia [59] and National Spatial Data Infrastructure e NSDI, the possible heating demand of certain region has been estimated. On the territory of the municipality, the municipal government finances several public buildings. These buildings are large energy consumers and they need significant funds, especially in the case of buildings that use fuel oil. In Table 4, the energy characteristics of public buildings (heating area, type of energy source, specific annual heat consumption and annual heat demand) are shown. This data have been provided by local authority representatives. Data collection has been done in accordance with the methodology recommended by the Ministry of Mining and Energy [60]. 3.2. Possibility of utilising available forest biomass under current condition Available location in the municipality area for utilising the available potential of forest residues are those where are possible to modify boilers or furnaces and where the fuel wood is used as the heating source. However, in most of the buildings, there is a wornout heating system which requires deep reconstruction. Only one heating system (“O
S Mico Matovic e Brezova”) is available for utilising forest residues because its heating system was reconstructed in 2007. Applied optimisation LP model shows that only 60 t of available forest residues can be used under the current condition without significant C-T-S changes. 3.3. Obstacles for maximum utilization of available potential under current conditions Obstacles for maximum utilisation of available potential have been defined by analysis of results obtained from interviews. Identification of stakeholders has been done on basis of previous

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Fig. 8. Defined changes.

Table 2 Data related to Ivanjica municipality. 1090 km2 31,963 553.07 km2 55% 4.5 m3/ha [55] beech, spruce/fir, pine about 85% older than 25 years [56] 83% [57] 34% [57]

Area Population Forest area State forest Average increases in wood volume Prevailing species Age of residential buildings Buildings without thermal insulation Average efficiency of boilers/furnaces in residential buildings

Table 3 Energy potential of forest residues. Species

Cutting [m3]

Forest residues [m3]

Biomass [t]

LHV [MWh/t]

Energy potential [MWh]

Hardwood deciduous Softwood deciduous Conifers TOTAL

50,770.00 12,180.00 24,450.00 87,400.00

7,260.00 1,740.00 3,500.00 12,500.00

5,805.00 1,045.00 1,920.00 8,770.00

3.86 3.50 4.09

22,407.30 3,657.50 7,852.8 33,917.60

experience [61] and realised research described in Refs. [31,42,44,49]. After identification, preliminary analysis of stakeholders has been done in accordance with the proposed methodology. List of invited and involved stakeholders have participated in both interviews and workshop is shown in Table 5. 3.3.1. Interviewing and data analysis Interviewing stakeholders has been done during one week in several locations. During the interviews, stakeholders have answered questions from the position of their affiliation. Basic information about biomass and the possibility of its usage in current condition has been presented to stakeholders on begin of interviews. It is important to emphasise that about 55% territory of the municipality is covered by forest and that about 95% of households use fuelwood as the main energy source for heating. In

accordance to this, stakeholders have presented decent knowledge about fuelwood and appropriate heating systems. However, their noticeable unfamiliarity related to other types of biomass such as forest residues, agricultural residues, pruning residues etc. has been observed. This has indicated that a lack of information about other types of biomass and possibilities for this utilisation is the first obstacle to the more significant use of available potential. On the other side, according to stakeholders’ opinion, usage of biomass (especially fuelwood) has been defined as the most costeffective. But, this claim should not be taken for granted, because there are only quarters of households with installed individual central heating systems. It means that most of households use fuelwood on the traditional way with low comfort. In opposite, almost all stakeholders have been familiar with advantages of modern biomass-based hating systems (wood pellet and chips

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Table 4 Energy characteristics of public buildings. Public Building

Area

Energy source

Specific heat annual consumption [kWh/m2]

Annual heat demand [kWh]

Dom zdravlja Tehni
cka
skola
Milinko Ku
si Gimnazija/OS c/Obdani
ste ÐurCevak Obdani
ste Zvon
cica
Svetozar Markovi OS c
Milan Vu
OS ci cevi c

5,715.00 1,900.00 7,300.00

fuel oil fuel oil fuel wood

319.5 95.16 227.22

1,898,083.19 184,800.72 1,658,731.00

1,030.00 900.00

fuel wood fuel wood

194.65 136.13

200,484,94 122,520.45

800.00

fuel wood

292.69

234,150.00


Vu
OS ci c Veli
ckovi c
Mi OS co Matovi c e Brezova
Mi OS co Matovi c e Mo
cioci
Nedeljko Ko
sanin OS

2,500.00

fuel wood

60.48

151,200.00


Major Ili OS c
Sreten Lazarevi OS c
Kirilo Savi OS c
Milinko Ku
si c/Obdani
ste - Bukovica OS SO Ivanjica TOTAL

100.00

fuel wood

168.00

16,800.00

807.00

fuel wood/wood chips

124.91

100,802.37

882.00

fuel wood

313.81

276,780.42

815.00

fuel wood

206.13

167,995.95

2,070.00

fuel wood

146.09

302,407.42

5,240.00

fuel wood

144.27

755,974.80

1,300.00

fuel wood

208.38

270,900.00

1,300.00 32,659.00

fuel oil

165.85

215,600.00 6,557,324.32

Table 5 Stakeholders involved in the process. Affiliation

Description

Local authority Local authority Municipal administration Municipal administration Municipal administration
Golija SE Srbija
sume, SG
Golija SE Srbija
sume, SG

Municipal council Municipal council Department for Economic Development Department for Economic Development Sector for Environmental Inspection Sector for Planning and Analysis


Golija SE Srbija
sume, SG Civil Society “Zeleni EPI-centar” Civil Society “Zeleni EPI-centar” PUC “Komunalno” SZR Milur Citizens Citizens

Forestry Engineer

Sector for Planning and Analysis Promotion of ecology, environmental protection and sustainable development of Ivanjica Promotion of ecology, environmental protection and sustainable development of Ivanjica Waste management Service activities in exploitation of forest resources Citizens Citizens

based heating systems), but the poor economic situation is also the main obstacle for their utilisation. Also, stakeholders have identified next obstacles for maximum utilization of available potential under current conditions:       

lack of information related to biomass, the poor economic situation, energy-inefficient buildings and heating systems, “hard” citizens behaviour, lack of central systems for biomass valorisation, the investment cost of technology and, complex legislation procedures regard to the build-up of larger plants.

3.4. Criteria and driving forces for long-term maximization and defining desirable future There have not been conducted and finished activities related to long-term planning in the Ivanjica municipality. It was the main reason why stakeholders are without experience in the long-term planning process. Despite that, almost all of them have said that necessary changes related to the improvement of biomass utilisation cannot be realised in short-term. A system based on fuelwood and forest residues as main energy sources have been defined as desirable future by stakeholders. Also, heating plants and/or CHP (combined heat and power) plants should be applied as technologies for the supply of public and

residential buildings in municipality central area. It is also, necessary to develop the market in order to use forest residues for energy purposes. According to stakeholders’ opinions, desirable future should fulfil several criteria presented in Table 6. Achieving desirable future has been often accompanied by several driving forces. During interviews, the stakeholders have proposed the list of driving forces that can influence on achieving desirable future. Proposed drivers have been:       

ecological issues, natural disasters, economic situation, political will, climate changes, fuel prices, changes in EU legislation.

3.5. Incorporation of criteria in the mathematical model Solutions that can potentially contribute to the improvement and/or maximization of the exploitation of available forest residues should be in accordance with defined criteria. Some of the criteria are possible to incorporate an optimisation model in the form of mathematical constraints. “Environmental friendly” criterion contains two sub-criteria GHG emissions and cutting/increase ratio. Annual GHG emission ghgj;k [t] on location j on which technology k

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Table 6 Defined criteria. Criterion

Sub-criterion

Unit

Value 2016

Desirable value

Environmental friendly

GHGa emission Cutting/increase ratio Unit cost of heat Annual costs of energy Days without supply

[t] [%] [V/kWht] [V/y] no. days

705 59% 0.04 1,380,000.00 0

e 65% <0.04 <1,380,000.00 0

Economic acceptability Reliability a

Related only to public buildings that use fuel oil as energy source.

is installed should be lower than current emission tr ghgj [t], and can be mathematically defined as (Eq. (6)): K X

ghgj;k  tr ghgj

(6)

k¼1

Similarly, cutting/increase ratio CIR [m3] can be mathematically described as (Eq. (7)) I X ðresi =0; 143Þ  CIR,0; 75

(7)

i¼1

where: resi [t] - available forest residues on location i. Economic acceptability includes also two sub-criteria unit cost of heat and annual costs of energy. The unit cost of heat pricej;k [V/kWh] can be described as (Eq. (8)), K X

pricej;k  spec pricej

(8)

k¼1

Whilst the annual cost of energy costsj [V] can be defined as (Eq. (9)).

X X costsj  ANP  costsj j

(9)

j

3.6. Creating and analysing solutions Desirable future is related to the installation of heat or CHP plants. Technologies for the valorisation of biomass in order to produce biofuel as well as electricity have been also considered. These technologies have considered for control purposes in order to evaluate stakeholders opinions. In order to find the optimal solution, four scenarios based on defined desirable future, criteria and drivers have been proposed and analysed in the optimisation model. These scenarios have presented to stakeholders during the workshop. The maximum utilised quantity of forest residues has been defined for each scenario. Description of scenarios as well as the maximum quantity of potentially utilised forest residues is shown in Table 7. Based on analysis of results obtained from the optimization model in accordance to the proposed scenarios and objective functions, it can be concluded that all generated solution would contribute to improving the utilization of the available potential of forest residues. Solutions generated in accordance with S4 scenario would also contribute to a sustainable maximization of the exploitation of this potential. Therefore, solutions generated in accordance with this scenario and maxY objective function have been analysed during a workshop in detail.

As mentioned in the description of the scenarios, scenario S4 includes one or more public buildings and residential buildings near them. In accordance with stakeholders’ opinion of desirable future, considered territory has been divided into three areas (ie. three potential plants - plant43, plant44, plant46), Fig. 4. Based on the available data obtained from local authority annual heat demand for each area is presented in Table 8. Solutions generated according to S4 scenario using objective functions maxNPV and maxY have provided maximization of usage of available potential. Technical parameters of these solutions are shown in Table 9, whilst economic parameters are shown in Fig. 5. As it can be seen in the table, optimal solutions have been based on the heating plant for location plant43 and CHP plant for location plant44. The installed capacity of the heating plant is enough for the fulfilment of about 69% of the heating load on this area. During backcasting workshop, these solutions have been analysed in relation to key uncertainties. Key uncertainties have been defined based on driving forces identified during interviews. Impact-uncertainty analysis has been conducted for each identified driving. During the analysis, driving forces have been positioned (Fig. 6). Economic situation and political will have been defined as key uncertainties by the consensus of all stakeholders. It could be said that the sustainability of S4 scenario (a scenario which allows maximization of utilising available forest residues) depends on the economic situation and political will. In accordance with stakeholders opinions, the S4 scenario would be sustainable when political will exists and when the economic situation is good Fig. 7. Namely, as mentioned above, citizens often give up comfort in order to reduce costs and it is evident that economic situation would be the key factor which will influence on the number of consumers connected to the district heating network. Although plants would generate heat with a lower price, costs of connection to on network and internal heating installations can influence a number of connected consumers (households). On another side, construction of plants requires large investment which cannot be provided without an adequate political will. Political will would be also important in the process of adopting the regulations at the local level. Terms of connecting users to the system will also be defined by the local authorities and will have a large impact. The weakening political will when the economic situation is good should not affect the sustainability of the scenario, but small political will have to exist. If there is no political will, it would not be possible to realise any activities in order to achieve the scenario. Any activity related to the construction of biomass valorisation plants on the local level cannot be realised without support from local authorities. The influence of political will may be minimised with a good economic situation, but it cannot be avoided. On the other side, the poor economic situation could be compensated by the adequate institutional support. Stakeholders’ opinion has been that political will cannot fully compensate poor economic situation. For that reason, the S4 scenario would not be sustainable under the poor economic situation.

V. Vukasinovic et al. / Energy 175 (2019) 818e829

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Table 7 Proposed scenarios. Scenario Description

quantity of forest residues [%]

S1

9.2

S2 S3 S4

Defines quantity of forest residues which can be used when investments are directed to heat/CHP plants for supply only separate public building. In this scenario, only public buildings that have used fuel oil for energy purposes have been considered. Defines quantity of forest residues which can be used when investments are directed to heat/CHP plants for supply one or more geographically close public buildings. In this scenario at least one public building should be heated by fuel oil. Defines quantity of forest residues which can be used when investments are directed to heat/CHP plants for supply one or more public buildings and multifamily residential buildings. Defines quantity of forest residues which can be used when investments are directed to heat/CHP plants for supply one or more public buildings and multifamily residential buildings as well as individual residential buildings.

15.7 35.7 100.0

Table 8 Areas considered under the S4 scenario. Location ref.

Description

Annual heat demand [kWh]

plant43


Milinko Ku
si Dom Zdravlja þ Gimnazija, OS c i obdani
ste ÐurCevak þ multifamily residential buildings þ individual residential buildings
Tehni
cka Skola þ Op
stinska uprava þ multifamily residential buildings þ individual residential buildings Obdani
ste Zvon
cica þ þ multifamily residential buildings þ individual residential buildings

8,855,095.36

plant44 plant46

19,041,387.44 5,429,972.83

Table 9 Technical parameters of optimal solution generated according to objective functions (S4 scenario). Obj. function

location

technologies

heat [kW]

electricity [kW]

the number of forest residues [%]

maxNPV

plant43(69%) plant44 plant43(69%) plant44

heating plant CHP heating plant CHP

2,075 7,050 2,075 7,050

e 1,590 e 1,590

100

maxY

100

3.7. Pathway and necessary changes

4. Discussion & Conclusion

Achieving a desirable future requires large investment as well as several changes that should be realised. During the workshop, necessary changes have been defined by stakeholders, Fig. 8. Defining both necessary changes and pathways has been realised by backward-looking from desirable future and by answering next questions: Technological changes: 1) determination of primary storages locations; 2) determination of plant location and district heating network; 3) reconstruction of heating infrastructure in public buildings; 4) construction of plants; 5) installation of district heating network; 6) harvesting and storing forest residues; 7) connection of plants to electricity distribution network; 8) connection of consumers (households). Structural changes: 1) feasibility study; 2) establishment of public company which will manage the plants; 3) contract about usage of forest residues; 4) making environmental impact assessment and obtaining necessary permits; 5) determination of incentives for potential consumers; 6) providing investment found; 7) providing commercial banks loans for customers; 8) engagement of machinery and labour; 9) establishment of information service; 10) obtaining status of privileged power producer; modification of local ecological legislation. Cultural changes: 1) informing citizens about desirable future; 2) raising awareness of the citizens; 3) education of citizens about the possibility of improving environmental condition; 4) citizens’ survey; 5) education of citizens about the possibility of improving the energy efficiency of buildings; 6) public hearings; 7) education of decision makers.

Usage of biomass in order to achieve sustainable development is often a very complex issue because the tendency for improving the state of the environment as well as the transition to greater use of biomass requires technological, cultural, organizational and institutional changes on several levels. Achieving optimal and sustainable usage of wood biomass requires detailed planning and management of forest resources, supply chains, and biomass conversion facilities, as well as consideration of a large number of social and environmental factors. A long-term planning process that takes into account a large number of factors requires the use of different techniques and approaches in order to define long-term scenarios. Existing approaches using mathematical optimisation for considering biomass utilisation issues and can significantly improve the utilization of the available potential when necessary conditions exist. However, using only mathematical optimization is not enough for providing sustainable usage of wood biomass. A significant amount of time and multi-level planning are also required for creating necessary conditions. In general, in addition to applying mathematical optimisation, it is necessary to consider a large number of technological, cultural and structural influences and changes to improve the state of the environment and to begin the significant use of biomass. It means that mathematical optimisation is only an initial step toward establishing conditions for improving the use of the available potential. In order to create necessary condition for the utilisation of available potential and to consider mentioned impacts and changes, it is recommended to use some of the participatory approaches. A participatory approach,

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such as backcasting, considers the identification of stakeholders from the considered region and their involvement in the process. Stakeholders’ participation is necessary because they have the necessary knowledge and resources. In order to create a comprehensive approach, the proposed methodology includes originally developed mathematical optimisation model [48] supplemented with the backcasting approach. The proposed methodology consists of 7 steps that represent the interaction of mathematical optimization and backcasting approach. The developed mathematical optimisation model has been used in the initial stages of the methodology in order to define optimal amounts of biomass that can be used under current conditions as well as for defining a suitable way for its utilisation. Mathematical optimization represents an expert way of generating a solution. However, in order to define the long-term scenarios, it is not enough to use only the mathematical optimisation model, as above-mentioned. It is predicted in methodology to supplement the model with parameters and criteria (constraints) that quantify different influences. Parameters and criteria are defined by stakeholders’ participation, which ensures their quality. Defining those parameters and criteria in another way is often unfeasible. According to the proposed methodology, scenarios are additionally analysed according to defined drivers and key uncertainties, in order to ensure the sustainability of solutions and the selection of suitable optimal scenarios. Finally, in order to achieve defined desirable future (scenario), the proposed methodology allows identification of necessary changes and pathways with stakeholders’ participation. Acknowledgements This research was part of the project III42013 of Integral and Interdisciplinary investigations of the Ministry of Education, Science and Technological Development of the Republic of Serbia. The authors would like to thank the Ministry for the financial support during the investigation. References [1] Shabani N, Sowlati T, Ouhimmou M, Ronnqvist M. Tactical supply chain planning for a forest biomass power plant under supply uncertainty. Energy 2014;78:346e55. [2] Hendricks A, Wagner J, Volk T, Newman D, Brown T. A cost-effective evaluation of biomass district heating in rural communities. Appl Energy 2016;162: 561e9. [3] Thr€ an D, Seidenberger T, Zeddies J, Offermann R. Global biomass potentials resources, drivers and scenario results. Energy Sustain Dev 2010;14:200e5. [4] Parikka M. Golobal biomass fuel resources. Biomass Bioenergy 2004;27(6): 613e20. [5] Steubing M, Zah R, Waeger P, Ludwig C. Bioenergy to climb: assessing the domestic sustainable biomass potential. Renew Sustain Energy Rev 2010;14(8):2256e65. [6] Kraxner F, Aoki K, Kindermann G, Leduc S, Albrecht F, Liu J, Yamagata Y. Bioenergy and the city e what can urban forests contribute? Appl Energy 2016;165:990e1003. [7] Sartor K, Quoilin S, Dewallef P. Simulation and optimization of a CHP biomass plant and district heating network. Appl Energy 2014;130:474e83. [8] Gavrilescu M. Biomass power for energy and sustainable development. Environ Eng Manag J 2008;7(5):27e42.
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