• Energy Research

Abstract In many urbanized areas the roadside and nature conservation management offers a biomass-for-bioenergy resource potential which is barely valorized, because of the fragmented biomass production sites and the scarcity of accurate data on the spatial availability of the biomass. In this study, a GIS based assessment was performed to determine the regional non-woody biomass-for-bioenergy potential for biogas from conservation areas and roadsides in Flanders, Belgium. These systems, with an area of 31,055 ha, have an annual herbaceous biomass production of 203 kton dry matter. The full associated biomass-to-bioenergy supply chain was optimized in four scenarios to maximize the net energy output and the profit. The scenario analysis was performed with OPTIMASS, a recently developed GIS based strategic decision support system. The analysis showed that the energetic valorization of conservation and roadside biomass through anaerobic digestion had a positive net energy balance, although there is still much room for improvements. Economically, however, it is a less interesting biomass resource. Most likely, the economic picture would change when other ecosystem services delivered by the protected biodiversity would be taken into account. Future technical advances and governmental incentives, like green energy certificates, will be necessary to incorporate the biomass into the energy chain. By tackling the existing barriers and providing a detailed methodology for biomass potential assessments, this study tries to facilitate the valorization of conservation and roadside biomass in order to reconcile biodiversity and road safety goals with renewable energy targets.

Abstract Jatropha was identified as a potential feedstock to satisfy off-grid and on-grid energy solutions. However, the potential has been questioned due to agronomic frustrations, the lack of an organized value chain and heavy criticism on biofuels due to emissions triggered by land use change (LUC). To contribute to the realistic integration of Jatropha in rural development, this article proposes a modeling approach to probe the feasibility of Jatropha-based electrification in rural Africa and the layout of such a value chain. A multi-component modeling setup is presented, featuring a life cycle inventory, spatial modeling and the optimization model, OPTIMASS. In this modeling setup, OPTIMASS is parameterized with data regarding the global warming potential and the potential location of each operation in the value chain including cultivation sites and related LUC emissions. This enables OPTIMASS to spatially design the Jatropha-based on-grid and off-grid electrification value chain (i.e. cultivation, transport and storage, biofuel production and electricity generation) in Southern Mali with minimal GWP to reach 10% substitution of fossil fuels for Jatropha in electricity production for a current and two future electricity demand scenarios. Analysis of the optimization results demonstrates that emissions from transporting the oil are lower than LUC emissions per harvestable seed of other sites. Finally, it can be said that harnessing the entirety of the Jatropha value chain is crucial to make it GWP competitive relative to fossil fuels in which the location of plantations is crucial to attain low LUC-related emissions and viable yields.

Abstract High logistics and handling costs prevent the bioenergy industry from making a greater contribution to the present energy market. Therefore, a mathematical model, OPTIMASS, is presented to optimise strategic (e.g. facility location and type) and tactical (e.g. allocation) decisions in all kinds of biomass-based supply chains. In addition to existing models, OPTIMASS evaluates changes in biomass characteristics due to handling operations which is needed to meet the requirements set to biomass products delivered at a conversion facility. Also, OPTIMASS considers the re-injection of by-products from conversion facilities which can play a decisive role in the determination of a sustainable supply chain. The scenario analysis illustrates the functionalities of OPTIMASS in the optimisation of an existing supply chain, the definition of the optimal location of new conversion facilities and the definition of the optimal configuration of a supply chain. OPTIMASS, as a deterministic model, does not consider variability related to e.g. seasonal changes which can be a major obstacle. However, a thorough sensitivity analysis of influencing factors must give insight in the induced changes in the supply chain. The sensitivity analysis in this paper investigates the influence of uncertainty in biomass production, energy demand and of changes in transport distance. The analysis demonstrates that OPTIMASS can be used as an inspiring tool to investigate the possible effects of governmental decisions, of considering new biomass material, new facilities, of technology changes, etc. The coupling with GIS allows characterisation and visualisation of problems in advance and visualisation of results in an interpretative way.

The role of digital technologies for fostering sustainability and efficiency in forest-based supply chains is well acknowledged and motivated several studies in the scope of precision forestry. Sensor technologies can collect relevant data in forest-based supply chains, comprising all activities from within forests and the production of the woody raw material to its transformation into marketable forest-based products. Advanced planning systems can help to support decisions of the various entities in the supply chain, e.g., forest owners, harvest companies, haulage companies, and forest product processing industry. Such tools can help to deal with the complex interdependencies between different entities, often with opposing objectives and actions—which may increase efficiency of forest-based supply chains. This paper analyzes contemporary literature dealing with digital technologies in forest-based supply chains and summarizes the state-of-the-art digital technologies for real-time data collection on forests, product flows, and forest operations, as well as planning systems and other decision support systems in use by supply chain actors. Higher sustainability and efficiency of forest-based supply chains require a seamless information flow to foster integrated planning of the activities over the supply chain—thereby facilitating seamless data exchange between the supply chain entities and foster new forms of collaboration. Therefore, this paper deals with data exchange and multi-entity collaboration aspects in combination with interoperability challenges related with the integration among multiple process data collection tools and advanced planning systems. Finally, this interdisciplinary review leads to the discussion of relevant guidelines that can guide future research and integration projects in this domain.

Abstract This paper presents t-OPTIMASS, a multi-period mixed integer linear programming model to optimise strategic and tactical decisions in all kinds of biomass supply chains taking into account the geographical fragmentation and temporal availability of biomass and changing biomass characteristics due to handling operations. Unlike existing models, t-OPTIMASS considers the growth and regeneration of biomass to determine the optimal harvesting moment(s). t-OPTIMASS is demonstrated based on the use of grass from nature reserves and road verges to substitute maize in the digestion mixture converted in the currently available wet anaerobic digesters or potential dry anaerobic digesters in Limburg (Belgium). The results highlight that the decision process is driven by the requirements imposed to the characteristics of the biomass to be converted at the conversion facility. The harvesting moment is defined and pre-treatment operations are introduced to make sure that biomass is delivered with characteristics that fit best these requirements. The analyses indicate that storage facilities are indispensable to deal with the temporal availability of biomass, the conflicting temporal demand and the required constant feeding of the digesters. t-OPTIMASS allows users, interested in macro-analysis, to define biomass potentials, to support policy decisions, to evaluate the feasibility of new facilities, etc.

Abstract Biomass supply chain optimisation is essential to overcome barriers and uncertainties that may inhibit the development of a sustainable and competitive bioenergy market. The number of research papers presenting optimisation models in the field of bioenergy systems rises exponentially. This paper gives an overview of the optimisation methods and models focussing on decisions regarding the design and management of the upstream segment of the biomass-for-bioenergy supply chain. After a general description of the supply chain and the decisions coming along with the design and management, all selected publications are classified and discussed according to (1) the mathematical optimisation methodology used, (2) the decision level and decision variables addressed and (3) the objective to be optimised. This classification allows users to identify existing optimisation methods or models that satisfy specific requirements. Moreover, the factual description of the presented optimisation methods and models points to opportunities for development of an integrated, holistic approach to optimise decisions in the field of biomass supply chain design and management. Such approach must be based on the consideration of the interrelationships and interdependence between all operations in the entire biomass-for-bioenergy supply chain.

Abstract This paper presents a generic and flexible reference data model meant as the blueprint of the database component of information and decision support systems related to different types of biomass-based supply chains (e.g. first to fourth generation biomass for production of bioenergy and biomaterials). The data model covers the biomass types and handling operations as characterised by their attributes and mutual relationships resulting from a life cycle inventory analysis. The data model enables the identification of the possible operation sequences in the specified chain. This functionality is demonstrated in a case study in which biomass from tall herb communities and mesotrophic grasslands is supplied for biogas or compost production. A comparative analysis has pointed out that the data model includes the required object types to add specific attributes of biomass supply chain simulation and optimisation models (such as spatial and temporal dimensions).