Bioenergy Supply Chain Research Articles

Design of a biofuel supply network under stochastic and price-dependent biomass availability

This article presents a framework for profit-maximizing strategic bio-energy supply chain design by taking into account variability in biomass as a response to price set as well as uncertainty in biomass yield. We present our model as a two-stage stochastic integer program for a multi-period integrated design of a network in which the here-and-now strategic decisions include biorefinery locations and size as well as base biomass price. To efficiently solve our model, we suggest an L-shaped-based algorithm along with a Sample Average Approximation approach. Finally, we demonstrate our results in a case study in Texas using realistic data. Within our framework, we present the relationship between biomass and biofuel price, as well as the optimal network design for the biofuel producer.

Contribution of Biomass Supply Chains for Bioenergy to Sustainable Development Goals

This work evaluates the relationships between bioenergy and related biomass supply chains and the United Nations Sustainable Development Goals (SDGs). Using Nilsson et al. (2016) seven-point scoring framework, the relationships between biomass supply for bioenergy and the SDGs were evaluated based on existing synthesis papers, modeling studies and empirical analyses, and expert knowledge. To complement this, contributions to SDG targets of 37 best practice case studies from around the world were documented. In reviewing these case studies, it was found that when supply chains are implemented appropriately and integrated with existing systems, they can have overwhelmingly positive contributions. Beyond directly contributing to SDG 7 (Affordable and Clean Energy), at least half of all case studies supported progress toward SDGs 8 (Decent Work and Economic Growth), 9 (Industry, Innovation, and Infrastructure), and 12 (Responsible Production and Consumption); however, the ways in which supply chains contributed often differed. Agricultural biomass supply chains (energy crops and residues) were most likely to contribute to SDGs 2 (Zero Hunger) and 6 (Clean Water and Sanitation), while waste and forest supply chains were most likely to contribute to SDG 15 (Life on Land). The development of bioenergy systems in rural and indigenous communities also indirectly supports societal SDGs such as SDGs 1 (No Poverty), 4 (Quality Education), 5 (Gender Inequality), and 10 (Reduced Inequalities). This work informs how SDGs can be used as a normative framework to guide the implementation of sustainable biomass supply chains, whether it is used for bioenergy or the broader bioeconomy. Recommendations for key stakeholders and topics for future work are also proposed.

Spatio-temporal assessment of the impact of intensive palm oil-based bioenergy deployment on cross-sectoral energy decarbonization

Although aspects of long-term planning are commonly taken into account in current analyses of bioenergy policy scenarios, representations of the bioenergy supply chain are often spatially aggregated. Multiple questions such as where, when, and how bioenergy is deployed have thus not been sufficiently addressed within a single modeling framework. Moreover, techno-economic models that can capture the dependencies of bioenergy supply chain variables among end-use sectors still need to be explored. The present research connects these gaps by presenting the development of a spatio-temporal techno-economic optimization model for cross-sectoral bioenergy policy evaluations under high spatial resolution and long-term temporal resolution. The research recognizes not only the need for energy decarbonization, but also the importance of improving resource efficiency in the palm oil industry, in this case, Malaysia’s palm oil bioenergy industry. The findings highlight the need for multi-sectoral collaboration between the energy sectors to deliver cost-optimal energy decarbonization at the national scale. This is represented by the substitution of up to 30%, 27%, and 12% of the energy demands in the power, heat, and transport sectors with bioenergy, respectively. The conflict between policy targets was also highlighted, namely, that new policies prioritizing bioenergy in the power and transport sectors reduce CO2 more effectively than policies targeting CO2 reduction alone, however, requiring up to 37% more cost in meeting the CO2 reduction commitment. The findings also outline the requirement of co-locating bioenergy production facilities with the existing facilities (e.g., agricultural mills, coal plants) and extending the existing infrastructure network to deliver the bioenergy capacities needed to meet the policy targets.

Effects of Production of Woody Pellets in the Southeastern United States on the Sustainable Development Goals

Wood-based pellets are produced in the southeastern United States (SE US) and shipped to Europe for the generation of heat and power. Effects of pellet production on selected Sustainability Development Goals (SDGs) are evaluated using industry information, available energy consumption data, and published research findings. Challenges associated with identifying relevant SDG goals and targets for this particular bioenergy supply chain and potential deleterious impacts are also discussed. We find that production of woody pellets in the SE US and shipments to displace coal for energy in Europe generate positive effects on affordable and clean energy (SDG 7), decent work and economic growth (SDG 8), industry innovation and infrastructure (SDG 9), responsible consumption and production (SDG 12), and life on land (SDG 15). Primary strengths of the pellet supply chain in the SE US are the provisioning of employment in depressed rural areas and the displacement of fossil fuels. Weaknesses are associated with potential impacts on air, water, and biodiversity that arise if the resource base and harvest activities are improperly managed. The SE US pellet supply chain provides an opportunity for transition to low-carbon industries and innovations while incentivizing better resource management.

Converting Forest Biomass to Bioenergy for Improved Community Livelihoods: A Review

A wide range of forest biomass from both natural and plantation forests constitutes an essential natural asset to a large number of households. The ever-increasing development of biofuels as a potentially sustainable and cleaner replacement for conventional fuels represents a key challenge for the forest industry and the opportunity for forest fringe communities. This, typifies a unique situation to understand the challenges and opportunities for designing sustainable bioenergy supply chains that require simultaneous consideration of economic, social, and environmental aspects. The objective of this study was to examine the conversion of forest biomass to bioenergy for improved community livelihoods. Desk study, content analysis and authors’ personal experiences were employed in carrying out this study. The study finds that forest environ abounds with biomass as feedstock for bioenergy. Positively, there are different technologies in converting biomass to bioenergy. However, it calls for the technical know-how and other factors such as infrastructure, market, full participation of critical players and policy incentives to facilitate bioenergy enterprises at the local level. In conclusion, policies and support mechanisms on bioenergy in creating sustainable livelihoods should be the priority for most countries where biomass abounds and could be established to provide clean and efficient energy.

Social sustainability of treatment technologies for bioenergy generation from the municipal solid waste using best worst method

Despite the fundamental role of the social aspect in the implementation of sustainability in the bio-based industries, most of the sustainability assessments research have addressed the environmental and economic dimensions. However, the social dimension has been neglected and it can cause an irreparable outcome in the biotechnology industries. Following this issue, this study propounds a modified systemic approach for a social sustainability impact assessment of the treatment technologies for converting waste into bioenergy, based on a review on the common social assessment methods. As it is known, the guideline presented by the United Nations Environment Program (UNEP) and the Society of Environmental Toxicology and Chemistry (2009) due to considering social life cycle assessment has a comprehensive look at the stakeholders. Therefore, in this paper, UNEP method was selected. However, it needs to be modified based on the bio-energy supply chain derived from municipal solid waste. For this purpose, the bioenergy value chain derived from municipal solid waste was designed and combined with UNEP guideline, to complete the level of stakeholder subgroups and the levels of the indicators. The final method of the social assessment system was presented to the board of experts and finalized. In order to design the measurement part of the social assessment system, because of a multi criteria decision making nature of the social sustainability evaluation of the conversion technologies of municipal solid waste to bio-energies, a recent developed multi-criteria decision making method so-called Best Worst Method (BWM) was used in two stages. The criteria are ranked according to their average weight obtained through Best Worst method. One of the major novelties in this research is the way of application of the best worst technique in the second stage. The model was implemented in the case of Tehran as one of the pioneering Iranian municipalities with high potential to produce bioenergy. The results of this study help decision makers to decide where to concentrate their attention during the implementation stage, and to increase social sustainability in their bioenergy supply chains derived waste.

A two-phase sequential approach to design bioenergy supply chains under uncertainty and social concerns

The use of renewable energies has become very attractive, because it protects the environment and boosts regional development. In this paper, a sustainable two-phase sequential approach is proposed for the design of bioenergy SCs under uncertainties. The first phase, integrating geographical information, social aspects, and multi-criteria decision-making techniques, helps find appropriate locations for the bio-refineries. High rates of unemployment, and high vulnerability to the variation in the markets in an economic crisis are considered as social concerns. Integrating these factors filters the areas for the second phase. The first phase reduces complexity in the computation of the problem, and helps set up sustainable development in the supply chain. In the second phase, to cope with the uncertainties in the bioenergy supply network, a robust model is introduced. It reduces the sensitivity to inaccurate input data, and the obtained solutions stay optimal when the parameters change slightly. In order to validate this two-phase sequential approach, a case study is investigated. The results of tests show that integrating the concepts of uncertainties and sustainability with geographical information of the area in a two-phase sequential approach outperforms the traditional models, and leads to the creation of 262 jobs. The jobs have a high impact on the surrounding area.

More Sustainable Bioenergy by Making Use of Regional Alternative Biomass?

Bioenergy is a building block of the ongoing transformation toward renewables-based energy systems. Bioenergy supply chains are regionally embedded and need to be seen in a place-based context with specific characteristics and constraints. Using a German case study, the potential of regionally embedded bioenergy chains in the past and the future is analyzed and discussed in this paper. The analysis integrates socio-ecological data and applies sustainability criteria in a multi-criteria decision analysis (MCDA) using the Preference Ranking Organization Method for Enriched Evaluation (PROMETHEE) methodology. The case study is focused on an industrial biogas fermenter in northwestern Germany, which currently uses predominantly maize as a substrate for bioenergy. Objectives for future development according to the ambitions of the UN Sustainable Development Goals and the EU Renewable Energy Directive (RED II) discussion are set and include the involvement of the farmer as biogas plant operator and other regional stakeholders. Since the focus of the research is put on the contribution of alternative biomass, such as grass, for the optimization of bioenergy settings, the question concentrates on how different mixtures of alternative biomass can be embedded into a sustainable management of both the landscape and the energy system. The main findings are threefold: (i) bioenergy supply chains that involve alternative biomass and grass from grasslands provide optimization potentials compared to the current corn-based practice, (ii) with respect to more sustainable practices, grass from grassland and alternative bioenergy supply chains are ranked higher than chains with increased shares of corn silage, and, more generic, (iii) optimization potentials relate to several spheres of the social–ecological system where the bioenergy structure is embedded. To conclude, sustainable enablers are discussed to realize optimization potentials and emphasize the integration of regional stakeholders in making use of alternative biomass and in making regional bioenergy more sustainable.

A Two-Stage DSS to Evaluate Optimal Locations for Bioenergy Facilities

Research Highlights: A set of 128 potential bioenergy facility locations is established and evaluated based on the transport cost to select optimal locations. Background and Objectives: The identification of optimal facility locations to process recovered forest biomass is an important decision in designing a bioenergy supply chain at the strategic planning level. The result of this analysis can affect supply chain costs and the overall efficiency of the network, due to the low density and dispersed nature of forest biomass and the high costs associated with its logistics operations. In this study, we develop a two-stage decision support system to identify the optimal site locations for forest biomass conversion based on biomass availability, transport distance and cost. Materials and Methods: In the first stage, a GIS-based analysis is designed to identify strategic locations of potential bioenergy sites. The second stage evaluates the most cost-effective locations individually using a transportation cost model, based on the results from stage one. The sensitivity of inputs, such as maximum allowable transport cost, the distance of transport and their relations to the profit balance, and changes in fuel price are tested. The method is applied to a real case study in the state of Queensland, Australia. Results and Conclusions: The GIS analysis resulted in 128 strategic candidate locations being suggested for bioenergy conversion sites. The logistics analysis estimated the optimal cost and transportation distance of each one of the locations and ranked them according to the overall performance between capacities of 5 and 100 MW.

The water‐energy nexus at the hybrid bioenergy supply chain: A sustainable network design model

Nowadays, the fossil fuel price fluctuations are high, their doubtless exhaustion is distressing, air pollution is a severe problem, and these issues seriously threaten the global economy. Bioenergy is a significant alternative source, with positive environmental, social, and economic impacts, that can reduce the world’s heavy dependence on fossil fuels. As a result, the importance of the design, implementation, and management of bioenergy supply chains have increased in recent years. This research, hence, is aimed to develop a bioenergy supply chain network design (BSCND) model to study the hybrid second (i.e., Jatropha; agricultural residues; and livestock manure) and third (i.e., microalgae) generations of biomass. Since water and energy are two momentous sources for sustainable development of societies where the increasing demand has become a worldwide concern, the water-energy nexus concept is another subject discussed in this study. And since sustainability is another issue to be dealt with in modern energy supply chains, a multi-objective sustainable mathematical model is developed in this study to present. A three-echelon sustainable hybrid bioenergy supply chain model has been proposed with four objective functions that minimize the total cost, reduce the environmental impacts, maximize the energy production, and minimize the water consumption to produce bioenergy. The GIS-based model, also, has been used to form a suitability map of Jatropha/microalgae cultivation. Results of a case study conducted to show the model performance using the MINMAX goal programming method. It has revealed that producing energy from microalgae/Jatropha is more viable compared to agricultural residues and livestock manure.

Integrated spatial and pinch analysis of optimal industrial energy supply mix with consideration of BioCNG derived from palm oil mill effluent

Utilisation of palm oil mill effluent (POME) appears to be a promising source of bioenergy production specifically biogas. Biogas products have different spatial structure varying on the level of centrality and dispersion of palm oil mill (POM), significantly impacting the transportation and total cost of biogas production. Pinch analysis provides systematic solution to industrial energy planning. However, the current pinch analysis lacks the ability to simultaneously consider CO2 emission target and to minimise cost for bioenergy supply chain. This study presents an integrated spatial and pinch analysis to determine the least cost energy mix to satisfy industrial energy demand and GHG emission target. The selection of cost-competitive energy substitution is evaluated based on supply cost factor constructed with spatial consideration, emission reduction to cost increase (ECI) ratio and emission reduction with cost decrease (ECD) values. To demonstrate the proposed framework, a case study to meet 120 MW of industrial energy demand in the state of Johor, Malaysia was presented. The results indicated that natural gas from grid extension and bio-compressed natural gas (BioCNG) with upgrading were required to achieve 30% GHG emission reduction. The total cost of energy mix was reduced significantly from 25.16 M USD/y to 17.56 M USD/y.

Feasibility of locating biomass-to-bioenergy conversion facilities using spatial information technologies: A case study on forest biomass in Queensland, Australia

There are large volumes of forest biomass available, distributed over extensive geographic areas in Australia. However, it is largely a low-value resource sensitive to high procurement costs. Transportation cost is typically the biggest factor in the cost of a forest biomass supply chain and is a critical factor in the planning of profitable bioenergy conversion facilities. This study presents an example of using geographical information systems (GIS) to 1) evaluate the feasibility of setting up new bioenergy facilities, 2) evaluate the location of existing bioenergy facilities, and 3) optimize the locations of facilities in Queensland, Australia. This study uses forest biomass availability estimated from 5-year harvest log volumes. The log volumes are refined to biomass energy (PJ) using a model that considers forest type, sustainable retention of residues on sites, residue proportions of total above-ground biomass and energy conversion factors. The strategic locations of bioenergy conversion facilities are defined using cluster and outlier analysis of biomass energy distribution and transportation distance using the local index of spatial autocorrelation (LISA) in a GIS environment. The tactical selection of bioenergy conversion facilities is then established based on the required number of facilities and capacity, together with the maximal distance for transporting the forest biomass. This study uses Queensland, Australia as the study area to demonstrate the effectiveness of modern GIS tools to achieve more scientific planning in bioenergy conversion facility networks and supply chain.

Subsidize farmers or bioenergy producer? The design of a government subsidy program for a bioenergy supply chain

AbstractThe success of the bioenergy industry will depend, in part, on enough biomass feedstocks being grown. To increase the reliability of feedstocks supply, a government can offer two types of subsidy program: a farmer subsidy program (FSP) and a bioenergy producer subsidy program (PSP). We develop models to analyze the optimal subsidy program by capturing the interactions between the government, the bioenergy producer, and the farmers. The models incorporate the subsidy budget constraint, the environmental benefits from the use of bioenergy, the farmer's risk aversion and land capacity constraint, as well as the yield uncertainty of feedstocks. The findings reveal that both FSP and PSP are effective as long as the farmers' land capacity exceeds a threshold. If both the subsidy budget and the land capacity are sufficiently large, PSP outperforms FSP; if only the subsidy budget is limited, FSP is better; if only the land capacity is limited, FSP and PSP are equivalent. Counter‐intuitively, we find that PSP always favors farmers more, while FSP favors the bioenergy producer more under certain conditions. Also, we find that FSP can better mitigate risk than PSP when yield uncertainty is high. Lastly, insights for policy makers to promote bioenergy development are highlighted.

Assessment of the bioenergy policy for the sustainable development of rural-based bioenergy systems in Zambia

Traditional biomass remains the primary energy source in rural Zambia – providing 98% of the energy needs. Its use is unsustainable, inefficient, and leads to harmful emissions with serious health implications, and deforestation. Modern bioenergy systems offer viable energy supply alternatives - but only if sustainably developed. Among other causes, the limited provision of modern bioenergy in rural areas is attributed to an ineffective public policy for promoting these systems in Zambia. Accordingly, this study evaluates the policy in place that seeks to promote sustainable bioenergy systems for rural areas in Zambia through the analysis of related strategies. It is observed that one of the significant weaknesses of the bioenergy policy framework is its lack of consideration of the bioenergy supply chains. These are influenced by four main elements – i.e., feedstock availability, conversion technology, intermediate energy carriers, and energy service demands - that considerably differ across rural localities within districts. Thus, the bioenergy policy-making process should be considered at such subnational levels (district). A suggestion that is well-aligned with the country’s decentralized governance agenda that is being implemented. Considering that there are numerous rural communities within a district and that information regarding the different elements of the bioenergy supply chain is required for the local government policy-making process, a framework to guide the generation of such information has been proposed.

Design and optimization of biomass electricity supply chain with uncertainty in material quality, availability and market demand

Biomass electricity supply chains are prone to a range of uncertainties that emanate internally or externally. Therefore, design of robust supply chains that remain resilient in the face of disruptions becomes of important interest. This study presents a two-stage stochastic mixed integer non-linear programming (MINLP) model combined with chance constraint to minimize the total cost of producing electricity from woody biomass in a four-level integrated bioenergy supply chain. The strategic decisions such as location and capacity of infrastructure are incorporated into the first stage, and decisions for sourcing the materials, inventory policy and are included in the second-stage. The proposed model considers detailed climate factors such as temperature and dew point, which are highly influential on moisture content, higher heating value, energy values, and ultimately, the performance of bioenergy supply chain. Given the NP-hard nature of the problem, hybrid metaheuristic approach is proposed that benefits from genetic algorithm (GA) operators and chaos theory in the structure of an improved cross entropy (CE) algorithm. Compared to the results of exact solution, the proposed ICE performs better compared to conventional CE by 5.6%.

Social Sustainability Dilemma: Escape or Communicate? Managing Social Risks Upstream of the Bioenergy Supply Chain

Supply chain risk management has been well researched over the years. However, management of social risks in bioenergy supply chains has been studied less in contemporary research. The ability of bioenergy companies to identify, properly address, and communicate social sustainability has become crucial for many global producers. In order to meet current EU’s energy and climate targets, the development of sustainable bioenergy production is vital. However, over last decade, research of bioenergy production supply chains has indicated that upstream areas of global bioenergy production systems are vulnerable in terms of social sustainability risks. The main objective of this research was to demonstrate how the socially sustainable supply chain practices in bioenergy supply chains can help a production company manage social risks and resources-use related conflicts upstream of the supply chain. These practices can be applied in the process of negotiation between bioenergy producers, local authorities, and communities for creating win-win situations for all parties while planning new bioenergy production systems. This study pays special attention to social sustainability risks at the upstream of the supply chain in countries of raw material origin. Use of social sustainability practices intends to help identify, assess, and address social risks of supply chain activities for bioenergy companies. Moreover, such practices aim at supporting companies and their stakeholders in making right choices and preparing effective strategies ahead of time. We based our research on empirical evidence and offer solutions to multi-national bioenergy production companies on how to manage social risks, allowing them to make the right decisions and necessary adjustments before entering potential markets. Our findings show that even avoidance of market entrance can carry sustainability-related social risks for both the company and the local communities. We suggest that although the financial element plays an important role in decision-making, the no-go decision often means missed opportunities for local communities to improve their respective sustainability states.

Hybrid optimization-simulation for integrated planning of bioenergy and biofuel supply chains

Traditionally, biomass supply chain planning has been done hierarchically at the strategic, tactical, and operational levels. Hierarchical planning might result in inconsistent or infeasible solutions at lower planning levels because short-term variations, e.g., those in biomass supply and demand, are not considered in long-term plans. To address this issue, an integrated strategic, tactical, and operational plan is developed in this paper in to consider the variations and details of lower planning levels. The integrated plan is developed as a hybrid model based on the recursive optimization-simulation approach. The optimization model integrates the strategic and tactical plans, while the simulation model incorporates the variations at the operational level. A procedure is developed to adjust the plans according to the variations in the model parameters using a feedback mechanism between the operational and the strategic/tactical level plans. The hybrid model is applied to a case study in British Columbia, Canada. The results show that the operational level variations and constraints could affect the long-term investment decisions and their profitability. For the given case study, the operational level variations decreased the estimated net present value by 21% due to the higher demand for logging residues. However, compared with the initial solution considered in the hybrid model, the final solution has a 17% higher net present value. The final design from the hybrid model suggests small-scale bioenergy and biofuel conversion facilities rather than large-scale ones as their demand for biomass could be met using more sawmill residues and less roadside logging residues.

Profit allocation in collaborative bioenergy and biofuel supply chains

In this paper, the profit allocation problem, which was overlooked in the collaborative bioenergy and biofuel supply chain literature, is considered. The optimization model for the strategic and tactical planning of a bioenergy and biofuel supply chain is modified and a number of cooperative game theory allocation methods are evaluated for a case study of collaboration among three potential bioconversion facilities in British Columbia, Canada. Moreover, a sensitivity analysis is conducted to evaluate the stability of the methods with changes in parameters. The results show that the collaboration of three bioconversion plants would generate the highest profit compared with other coalitions. Based on the results, the savings from collaboration could improve the total net present value by 5%. The results highlight that the profitability and stability of collaboration are closely related to bio-oil market prices and demand. The proportional allocation methods hardly generate stable (efficiency and individual rationality) results. Therefore, caution should be taken about the frequent use of proportional methods for costs/benefits allocation by the industry. Instead, the nucleolus and equal profit methods are recommended as alternative methods since they are always stable regardless of variations in model parameters, such as bioproduct demand and prices.

Optimization of biomass to bioenergy supply chain with tri-generation and district heating and cooling network systems

Bismil district of Diyarbakir (Turkey) is a region where agricultural activities are very common. About 60% of the terrain is irrigable. Cotton and corn are mostly grown in these irrigable lands. Given the bioenergy incentive provided by the Republic of Turkey and the extensiveness of agricultural lands in Turkey, energy production from cotton and corn residues in the tri-generation facility through gasification conversion technology seems like a quite profitable investment. In this study, a mixed-integer linear programming model, which optimizes the numbers, locations, and capacities of the tri-generation facility/s, was developed and empirically solved. The model tries to maximize the net present value of the potential investment by comparing the trade-offs between the raw material/end-product transportation costs, facility/s, and pipeline installation costs. Electricity and heating/cooling energy were sold to the government and settlements through the closest interconnected lines and pipelines, respectively. In this study, electricity, the heating/cooling energy and the fertilizer (biochar) sale were considered for the calculation of annual revenue, while transportation of raw materials and heating/cooling energy, losses during heat transfer and electricity transmission, operation and maintenance costs of facilities and pipelines were considered for the calculation of annual expenses. Initial investment cost includes facility, pipeline, and electricity transmission installation costs. The model proposes one facility with an installed power of approximately 35 MW which met cooling energy demand of 3 settlements, both cooling and heat energy demand of 2 settlements. The net present value of the investment is almost 338 million EUR and the repayment period is 1.3 years.

Why are tall-statured energy grasses of polyploid species complexes potentially invasive? A review of their genetic variation patterns and evolutionary plasticity

Perennial tall-statured grasses are regarded as a sustainable source of renewable energy for their high yields of lignocellulosic biomass, low resource input, wide ecological tolerance and capacity for storing large amounts of atmospheric CO2 in their perennial underground rhizome systems. These same traits, that make such crops agronomically attractive and sustainable, make these species highly competitive and potentially invasive. Several perennial energy crop grasses are outbreeding species that belong to cosmopolitan polyploid species complexes, i.e. groups of interbreeding species with ploidy variation. The cultivation of such highly productive and genetically diverse crops can have unwanted consequences through the evolution of invasive species. The goal of this review is to provide the scientific community, including agronomists, breeders, users and nature managers, with an introduction to the genetic dynamics occurring within the polyploid species complexes of the emerging energy species Arundo donax, Miscanthus × giganteus, Panicum virgatum, Phalaris arundinacea and Phragmites australis, and the broad biogeographical extent of their gene flow impact. Such aspects are difficult to predict, and are not captured by invasion risk assessments and by the sustainability certifications of the bioenergy supply chain. The review integrates literature from the phylogenetic, cytology, population ecology and agronomic research and focuses on the evolutionary processes that shape invasiveness that can be activated post-introduction by the dispersal of pollen, seeds and plant fragments from the energy crops to the environment. Due to the high genetic diversity of the crops, the adverse effects that genetic drift and founder effect can have on the establishment of small populations are very unlikely. On the contrary the data collected suggests that the risk of fostering panmictic continental invasive populations is high. Agronomic measures, regulations and genetic improvements that can contain dispersal from crops are discussed, as well as urgent research needs.