A Multi-Objective MILP Model for Planning, Design and Operation of Biomass Supply Chains: Capturing the Trade-Offs within the Food-Energy-Water-Environment Nexus

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Biomass is a strategic resource for the production of fuels, energy, chemicals and other valuable materials. Demands for biomass are increasing due to many governments subsidising its use to meet renewable energy and GHG emissions targets. These growing demands can cause greater competition with food production and have profound effects on the environment and ecosystems. Producing biomass requires large areas of land, water for irrigation and often fertilisers and pesticides, which can leach into bodies of water. Large and rapid changes in land use (especially deforestation) degrade biodiversity. Effective management of biomass supply chains is crucial to ensure its production and utilisation are sustainable, do not contribute to global warming and preserve the delicate balance in the food-energy-water-environment nexus.
A spatio-temporal multi-objective optimisation model, based on mixed integer programming, was developed for biomass value chains that can maximise synergies and minimise conflicts within the food-energy-water-environment nexus. The model considers a planning horizon, from 2010 to 2050, in order to model the investment in and retirement of technologies and land use changes, as well as seasonal time steps in order to capture the seasonal production and storage of biomass. The model accounts for spatial dependencies of the problem at a 50 km level in order to model the variation of biomass yield potentials across different locations, suitable siting of biomass plantations and processing facilities, transport of biomass and products etc. Land use is modelled using GIS and different constraints were developed, according to the suitability of the land for cultivation and harvesting and social and environmental criteria, in order to limit the use of land for bioenergy. Different types of biomass are modelled including food crops, energy crops and forestry resources. Different technologies for the production of different types of biofuel, as well heat and electricity, are modelled at different scales. The model optimises a large number of interdependent decisions such as: what biomass to grow, where and when to grow them; what energy services/products to generate (e.g. heat, biofuels, electricity, chemicals); what processing technologies to use, where to locate them, when to invest in them; centralised or distributed processing; whether or not to densify/pre-process biomass before transportation; how to transport biomass and distribute products to customers; and how to manage inventory (as the production of most types of biomass is seasonal and not available all year round), in order to obtain the greatest benefit with the lowest impact on the nexus. In this conference, the MILP model will be presented along with the efficient and robust value chains that are synergistic with the nexus, identified using the model.
Original languageEnglish
Title of host publicationProceedings of the 2018 AIChE Annual Meeting
PublisherAIChE
Publication statusPublished - 29 Oct 2018
Event2018 AIChE Annual Meeting: Today, Tomorrow & Leading the Future - David L. Lawrence Convention Center, Pittsburgh, USA United States
Duration: 28 Oct 20182 Nov 2018
https://www.aiche.org/conferences/aiche-annual-meeting/2018

Conference

Conference2018 AIChE Annual Meeting
Abbreviated title18AIChE
CountryUSA United States
CityPittsburgh
Period28/10/182/11/18
Internet address

Cite this

A Multi-Objective MILP Model for Planning, Design and Operation of Biomass Supply Chains: Capturing the Trade-Offs within the Food-Energy-Water-Environment Nexus. / Samsatli, Sheila.

Proceedings of the 2018 AIChE Annual Meeting. AIChE, 2018.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Samsatli, S 2018, A Multi-Objective MILP Model for Planning, Design and Operation of Biomass Supply Chains: Capturing the Trade-Offs within the Food-Energy-Water-Environment Nexus. in Proceedings of the 2018 AIChE Annual Meeting. AIChE, 2018 AIChE Annual Meeting, Pittsburgh, USA United States, 28/10/18.
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abstract = "Biomass is a strategic resource for the production of fuels, energy, chemicals and other valuable materials. Demands for biomass are increasing due to many governments subsidising its use to meet renewable energy and GHG emissions targets. These growing demands can cause greater competition with food production and have profound effects on the environment and ecosystems. Producing biomass requires large areas of land, water for irrigation and often fertilisers and pesticides, which can leach into bodies of water. Large and rapid changes in land use (especially deforestation) degrade biodiversity. Effective management of biomass supply chains is crucial to ensure its production and utilisation are sustainable, do not contribute to global warming and preserve the delicate balance in the food-energy-water-environment nexus.A spatio-temporal multi-objective optimisation model, based on mixed integer programming, was developed for biomass value chains that can maximise synergies and minimise conflicts within the food-energy-water-environment nexus. The model considers a planning horizon, from 2010 to 2050, in order to model the investment in and retirement of technologies and land use changes, as well as seasonal time steps in order to capture the seasonal production and storage of biomass. The model accounts for spatial dependencies of the problem at a 50 km level in order to model the variation of biomass yield potentials across different locations, suitable siting of biomass plantations and processing facilities, transport of biomass and products etc. Land use is modelled using GIS and different constraints were developed, according to the suitability of the land for cultivation and harvesting and social and environmental criteria, in order to limit the use of land for bioenergy. Different types of biomass are modelled including food crops, energy crops and forestry resources. Different technologies for the production of different types of biofuel, as well heat and electricity, are modelled at different scales. The model optimises a large number of interdependent decisions such as: what biomass to grow, where and when to grow them; what energy services/products to generate (e.g. heat, biofuels, electricity, chemicals); what processing technologies to use, where to locate them, when to invest in them; centralised or distributed processing; whether or not to densify/pre-process biomass before transportation; how to transport biomass and distribute products to customers; and how to manage inventory (as the production of most types of biomass is seasonal and not available all year round), in order to obtain the greatest benefit with the lowest impact on the nexus. In this conference, the MILP model will be presented along with the efficient and robust value chains that are synergistic with the nexus, identified using the model.",
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AB - Biomass is a strategic resource for the production of fuels, energy, chemicals and other valuable materials. Demands for biomass are increasing due to many governments subsidising its use to meet renewable energy and GHG emissions targets. These growing demands can cause greater competition with food production and have profound effects on the environment and ecosystems. Producing biomass requires large areas of land, water for irrigation and often fertilisers and pesticides, which can leach into bodies of water. Large and rapid changes in land use (especially deforestation) degrade biodiversity. Effective management of biomass supply chains is crucial to ensure its production and utilisation are sustainable, do not contribute to global warming and preserve the delicate balance in the food-energy-water-environment nexus.A spatio-temporal multi-objective optimisation model, based on mixed integer programming, was developed for biomass value chains that can maximise synergies and minimise conflicts within the food-energy-water-environment nexus. The model considers a planning horizon, from 2010 to 2050, in order to model the investment in and retirement of technologies and land use changes, as well as seasonal time steps in order to capture the seasonal production and storage of biomass. The model accounts for spatial dependencies of the problem at a 50 km level in order to model the variation of biomass yield potentials across different locations, suitable siting of biomass plantations and processing facilities, transport of biomass and products etc. Land use is modelled using GIS and different constraints were developed, according to the suitability of the land for cultivation and harvesting and social and environmental criteria, in order to limit the use of land for bioenergy. Different types of biomass are modelled including food crops, energy crops and forestry resources. Different technologies for the production of different types of biofuel, as well heat and electricity, are modelled at different scales. The model optimises a large number of interdependent decisions such as: what biomass to grow, where and when to grow them; what energy services/products to generate (e.g. heat, biofuels, electricity, chemicals); what processing technologies to use, where to locate them, when to invest in them; centralised or distributed processing; whether or not to densify/pre-process biomass before transportation; how to transport biomass and distribute products to customers; and how to manage inventory (as the production of most types of biomass is seasonal and not available all year round), in order to obtain the greatest benefit with the lowest impact on the nexus. In this conference, the MILP model will be presented along with the efficient and robust value chains that are synergistic with the nexus, identified using the model.

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