27 research outputs found
BVCM: a comprehensive and flexible toolkit for whole system biomass value chain analysis and optimisation – mathematical formulation
Abstract This paper presents the novel MILP formulation of the Biomass Value Chain Model (BVCM), a comprehensive and flexible optimisation toolkit that models a large number of bioenergy system pathways. The model accounts for the economic and environmental impacts associated with the end-to-end elements of a pathway: crop production, conversion technologies, transport, storage, local purchase, import (from abroad), sale and disposal of resources, as well as CO2 sequestration by CCS technologies and forestry. It supports decision-making around optimal use of land, biomass resources and technologies with respect to different objectives, scenarios and constraints. Objectives include minimising cost, maximising profit, minimising GHG emissions, maximising energy/exergy production or any combination of these. These objectives are combined with a number of scenarios (such as including different CO2 prices, different technology and climate scenarios, import scenarios, waste cost scenarios), different credits (e.g. by-product and end-product, CCS and forestry carbon sequestration) and a number of constraints such as minimum levels of energy production and maximum environmental impacts. The toolkit includes an extensive database of different biomass technologies including pretreatment, densification, liquid and gaseous fuel production, heat and power generation (separately or combined, biodedicated or co-fired), waste-to-energy conversion and carbon capture and sequestration. A large number of resources are considered including a variety of bio-resources (e.g. energy crops such as Miscanthus and SRC willow, arable crops such as winter wheat, sugar beet and oilseed rape and short and long rotation forestry), intermediates, products, by-products and wastes. The BVCM is a spatio-temporal model: currently it is configured for the UK using 157 square cells of length 50 km and the planning horizon is from the 2010s to the 2050s, with seasonal variations considered. The framework is data-driven so the model can be easily extended: for example adding new resources, technologies, transport modes, etc. or changing the time horizon and the location to another country is only a matter of changing the data. Results of example UK case studies are presented to demonstrate the functionality of the model
Optimal design and operation of integrated wind-hydrogen-electricity networks for decarbonising the domestic transport sector in Great Britain
Sustainable bio-economy that delivers the environment-food-energy-water nexus objectives: the current status in Malaysia
Biomass is a promising resource in Malaysia for energy, fuels, and high value-added products. However, regards to biomass value chains, the numerous restrictions and challenges related to the economic and environmental features must be considered. The major concerns regarding the enlargement of biomass plantation is that it requires large amounts of land and environmental resources such as water and soil that arises the danger of creating severe damages to the ecosystem (e.g. deforestation, water pollution, soil depletion etc.). Regarded concerns can be diminished when all aspects associated with palm biomass conversion and utilization linked with environment, food, energy and water (EFEW) nexus to meet the standard requirement and to consider the potential impact on the nexus as a whole. Therefore, it is crucial to understand the detail interactions between all the components in the nexus once intended to look for the best solution to exploit the great potential of biomass. This paper offers an overview regarding the present potential biomass availability for energy production, technology readiness, feasibility study on the techno-economic analyses of the biomass utilization and the impact of this nexus on value chains. The agro-biomass resources potential and land suitability for different crops has been overviewed using satellite imageries and the outcomes of the nexus interactions should be incorporated in developmental policies on biomass. The paper finally discussed an insight of digitization of the agriculture industry as future strategy to modernize agriculture in Malaysia. Hence, this paper provides holistic overview of biomass competitiveness for sustainable bio-economy in Malaysia
IMAGE CLASSIFICATION FOR MAPPING OIL PALM DISTRIBUTION VIA SUPPORT VECTOR MACHINE USING SCIKIT-LEARN MODULE
The world has been alarmed with the global warming effects. Global warming has been a distress towards the environment, thus shorten the Earth’s lifespan. It is a challenging task to reduce the global warming effects in a short period, knowing that the human population is increasing along with the electricity and energy demand. In order to reduce the effects, renewable energy is presented as an alternative method to produce energy in a way that will not harm the environment. Oil palm is one of the agricultural crops that produces huge amount of biomass which can be processed and used as a renewable energy source. In 2016, Malaysia has reported over 5 million hectares of land were covered by oil palm plantations. Placing Malaysia as the second largest country of oil palm producer in the world has given it an advantage to produce renewable energy source. However, there is a need to monitor the sustainability of oil palm plantations in Malaysia via effective mapping approaches. This study utilised two different platforms (open source and commercial) using a machine learning algorithm namely Support Vector Machine (SVM) to perform oil palm mapping. An open source Python programming-based technique utilising Scikit-learn module was performed to map the oil palm distribution and the result produced had an overall accuracy of 91.39%. To support and validate the efficiency of the Python programming-based image classification, a commercial remote sensing software (ENVI) was used and compared by implementing the same SVM algorithm and the result showed an overall accuracy of 98.21%
A general spatio-temporal model of energy systems with a detailed account of transport and storage
Towards a sustainable bio-economy: Working in harmony with the environment–food–energy–water nexus
Bio-aviation fuel: A comprehensive review and analysis of the supply chain components
The undeniable environmental ramifications of continued dependence on oil-derived jet fuel have spurred international efforts in the aviation sector toward alternative solutions. Due to the limited options for decarbonization, the successful implementation of bio-aviation fuel is crucial in contributing to the roster of greenhouse gas emissions mitigation strategies for the aviation sector. Since fleet replacement with low-carbon technologies may not be a feasible option, due to the long lifetime and significant capital cost of aircraft, “drop-in” alternatives, which can be used in the engines of existing aircraft in a seamless transition, may be required. This paper presents a detailed analysis of the supply chain components of bio-aviation fuel provision: feedstocks, production pathways, storage, and transport. The economic and environmental performance of different potential bio-feedstocks and technologies are investigated and compared in order to make recommendations on short- and long-term strategies that could be employed internationally. Hydroprocessed esters and fatty acids production pathway, utilizing second-generation oil-seed crops and waste oils, could be an effective immediate solution with the potential for substantial greenhouse gas emissions savings. Microalgal oil could potentially offer far greater yields of bio-aviation fuel and reductions in greenhouse gas emissions, but the technology for large-scale algae cultivation is inadequately mature at present. Fischer-Tropsch production pathway using lignocellulosic biomass has the potential for the highest greenhouse gas emissions savings, which could potentially be the solution within the medium- to long-term plans of the aviation industry, but further research and optimization are required prior to its large-scale implementation due to its limited technological maturity and high capital costs. In practice, the “ideal” feedstocks and technologies of the supply chains are heavily dependent on spatial and temporal criteria. Moreover, many of the parameters investigated are interlinked to each other and the measures that are effective in greenhouse gases emissions reduction are largely associated with increased cost. Hence, policies must be streamlined across the supply chain components that could help in the cost-effective and sustainable deployment of bio-aviation fuel. © Copyright © 2020 Doliente, Narayan, Tapia, Samsatli, Zhao and Samsatli
The curious case of the conflicting roles of hydrogen in global energy scenarios
As energy systems transition from fossil-based to low-carbon, they face many challenges, particularly concerning energy security and flexibility. Hydrogen may help to overcome these challenges, with potential as a transport fuel, for heating, energy storage, conversion to electricity, and in industry. Despite these opportunities, hydrogen has historically had a limited role in influential global energy scenarios. Whilst more recent studies are beginning to include hydrogen, the role it plays in different scenarios is extremely inconsistent. In this perspective paper, reasons for this inconsistency are explored, considering the modelling approach behind the scenario, scenario design, and data assumptions. We argue that energy systems are becoming increasingly complex, and it is within these complexities that new technologies such as hydrogen emerge. Developing a global energy scenario that represents these complexities is challenging, and in this paper we provide recommendations to help ensure that emerging technologies such as hydrogen are appropriately represented. These recommendations include: using the right modelling tools, whilst knowing the limits of the model; including the right sectors and technologies; having an appropriate level of ambition; and making realistic data assumptions. Above all, transparency is essential, and global scenarios must do more to make available the modelling methods and data assumptions use