Robust optimization approach for synthesis of integrated biorefineries with supply and demand uncertainties

Tay, Douglas H. S.; Ng, Denny K. S.; Tan, Raymond R.

doi:10.1002/ep.10632

Cited by 51 publications

(28 citation statements)

References 45 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Studies of the optimal strategic choice between larger packages of energy efficiency and biorefinery investments, such as the ones used in this article, include Ådahl and Harvey, Tay et al and Liu et al [8][9][10]. Ådahl and Harvey [8] have proposed a methodology for evaluating process industry energy investments that considers different scenarios for the long-term development of future climate policy regulations.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Ådahl and Harvey [8] have proposed a methodology for evaluating process industry energy investments that considers different scenarios for the long-term development of future climate policy regulations. Tay et al [9] have proposed an approach to the optimal retrofit of an existing pulp and paper mill into an integrated biorefinery. Tay et al [9] have proposed an approach to the optimal retrofit of an existing pulp and paper mill into an integrated biorefinery.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The studies [7][8][9][10] have considered investment opportunities at the start of the planning period only. The flexibility obtained by enabling investments at later points in time-so-called recourse decisions-as reactions to changing conditions was consequently not considered.…”

Section: Literature Reviewmentioning

confidence: 99%

See 2 more Smart Citations

The value of flexibility for pulp mills investing in energy efficiency and future biorefinery concepts

Svensson

Berntsson

Strömberg

2014

Int. J. Energy Res.

View full text Add to dashboard Cite

SUMMARY Changing conditions in biomass and energy markets require the pulp and paper industry to improve energy efficiency and find new opportunities in biorefinery implementation. Considering the expected changes in the pulp mill environment and the variety of potential technology pathways, flexibility should be a strong advantage for pulp mills. In this context, flexibility is defined as the ability of the pulp mill to respond to changing conditions. The aim of this article is to show the potential value of flexibility in the planning of pulp mill energy and biorefinery projects and to demonstrate how this value can be incorporated into models for optimal strategic planning of such investments. The paper discusses the requirements on the optimization models in order to adequately capture the value of flexibility. It is suggested that key elements of the optimization model are multiple points in time where investment decisions can be made as well as multiple scenarios representing possible energy price changes over time. The use of a systematic optimization methodology that incorporates these model features is illustrated by a case study, which includes opportunities for district heating cooperation as well as for lignin extraction and valorization. A quantitative valuation of flexibility is provided for this case study. The study also demonstrates how optimal investment decisions for a pulp mill today are influenced by expected future changes in the markets for energy and bioproducts. Copyright © 2014 John Wiley & Sons, Ltd.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

The value of flexibility for pulp mills investing in energy efficiency and future biorefinery concepts

Svensson

Berntsson

Strömberg

2014

Int. J. Energy Res.

View full text Add to dashboard Cite

show abstract

“…In a second study, M A N U S C R I P T A C C E P T E D ACCEPTED MANUSCRIPT 5 they used robust optimization in a bi-objective planning model with random objective weights for forest planning (Palma and Nelson, 2010). Other researchers have employed robust models in forestry applications such as Alvarez andVera (2011) &Kazemi Zanjani et al (2010a) for optimizing sawmill planning; Tay et al (2013) for integrating black liquor biorefineries for energy production; Bredström et al (2013) for planning a biofuel heating plant; and Carlsson et al (2014) for considering customer demand in the pulp and paper industry. The method used by Kazemi Zanjani et al (2010a), which combined robust optimization and stochastic programming, was of interest to us and served as a model for developing our hybrid 'stochastic programmingrobust optimization' model.…”

Section: Introductionmentioning

confidence: 97%

A hybrid multi-stage stochastic programming-robust optimization model for maximizing the supply chain of a forest-based biomass power plant considering uncertainties

Shabani

Sowlati

2016

Journal of Cleaner Production

120

View full text Add to dashboard Cite

Please cite this article as: Shabani N, Sowlati T, A hybrid multi-stage stochastic programming-robust optimization model for maximizing the supply chain of a forest-based biomass power plant considering Abstract Electricity generated from forest-based biomass is an attractive source of renewable energy. However, the cost of generating heat and/or electricity is relatively high due to the low energy density of wood, high moisture content and variations in its quality and availability. Models have been developed to optimize the supply chain and reduce the cost per kilowatt hour generated. This paper focuses on incorporating uncertainty in the supply chain of such a model. The model considers the tactical supply chain planning of a power plant over a one-year time horizon with monthly time steps. Uncertain parameters which impact the net profit of the power plant include 'biomass quality,' namely moisture content and higher heating value, and 'monthly available biomass' from different suppliers. Robust optimization is used to model uncertainty in the quality of biomass. Then a hybrid, multi-stage, 'stochastic programming-robust optimization' model is presented in order to simultaneously include uncertainty in biomass quality and biomass availability. It is demonstrated that the hybrid model takes advantage of both modelling approaches to balance the profit estimates and the tractability to various circumstances. The model provides solution considering all instances of the uncertain parameters within the defined sets and scenario tree. The results revealed a major trade-off between profit and range of biomass quality. Profit decreased by up to 23% when there was ±13% variation in moisture content and ±5% change in higher heating value. The model achieved a biomass purchase cost that was lower M A N U S C R I P T A C C E P T E D ACCEPTED MANUSCRIPT 2 than the current commercial costs at the power plant. Implementing the model could prevent production curtailment and undesirable fluctuation in storage levels which occurred in the past due to variations in biomass availability and quality.Keywords: Forest-based biomass, Bioenergy, Forest-based biomass supply uncertainty, Forestbased biomass quality uncertainty, Mixed integer programming model, Supply chain optimization, Multi-stage stochastic model, Robust optimization.

show abstract

“…(25). In fact, such fractions are estimated subjectively in practice (Hampton et al 1973;Tay et al 2013).…”

Section: Selection Of Steam Turbinesmentioning

confidence: 99%

Hybrid Optimisation Model for the Synthesis of Centralised Utility System in Eco-Industrial Park

Teo

Wau

et al. 2017

Process Integr Optim Sustain

View full text Add to dashboard Cite

Eco-industrial park (EIP) is a community of manufacturing and service businesses collaborating to manage environmental and resource (e.g. water, material and energy) issues together to preserve the environment while bringing financial benefit to the individual party. One way to achieve this goal is to integrate the EIP network via a centralised utility system (CUS), which facilitates the material and energy exchange among participating companies (or individual actors, IAs) in EIP. This work presents a hybrid model that combines superstructure-based optimisation approach and insight-based, automated targeting approach to synthesise a sustainable CUS for an EIP with the consideration of variations. The superstructure encompasses tri-generation system, wastewater treatment system and a steam distribution network that consider the use of mechanical drive steam turbine (MDST). Meanwhile, automated targeting approach is adapted to provide valuable insight and detailed allocation of resources within the network. In this work, the synthesis of CUS is analysed based on the economic performance and the total potential environmental impact of the system. Since such objectives are frequently contradictory in nature, fuzzy optimisation approach is adapted in this work to synthesise a sustainable CUS which fulfils the two important objectives. In addition, multi-period optimisation approach is applied to address the multiple operational periods with the presence of variations in supply of raw materials, market price of raw materials, demand for desired end products, etc. To illustrate the proposed framework, a palm oil processing complex (POPC) case study is solved.

show abstract

Robust optimization approach for synthesis of integrated biorefineries with supply and demand uncertainties

Cited by 51 publications

References 45 publications

The value of flexibility for pulp mills investing in energy efficiency and future biorefinery concepts

The value of flexibility for pulp mills investing in energy efficiency and future biorefinery concepts

A hybrid multi-stage stochastic programming-robust optimization model for maximizing the supply chain of a forest-based biomass power plant considering uncertainties

Hybrid Optimisation Model for the Synthesis of Centralised Utility System in Eco-Industrial Park

Contact Info

Product

Resources

About