An integrated GIS-MARKAL toolbox for designing a CO2 infrastructure network in the Netherlands

Broek, Machteld van den; Brederode, Evelien; Ramírez, Andrea; Kramers, L.; Kuip, Muriel van der; Wildenborg, Ton; Faaij, André; Turkenburg, Wim

doi:10.1016/j.egypro.2009.02.214

Cited by 23 publications

(13 citation statements)

References 4 publications

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“…For large-scale CCUS implementation, it is critical to optimally integrate capture, compression, transportation, utilization and sequestration activities. Although CO 2 management using CO 2 capture and sequestration infrastructure has been considered, these studies did not include utilization opportunities (Tan et al, 2013;Kazmierczak et al, 2009;Johnson and Ogden, 2011;Zheng et al, 2010;van den Broek et al, 2009;Brunsvold et al, 2011;Fimbres Weihs et al, 2011;Svensson et al, 2004;Van den Broek et al, 2010;Strachan et al, 2011;Bakken et al, 2008;Middleton et al, 2012;Alhajaj et al, 2013).…”

Section: Ccus and Ccu Challengesmentioning

confidence: 97%

A multi-scale framework for CO2 capture, utilization, and sequestration: CCUS and CCU

Hasan

First

Boukouvala

et al. 2015

Computers & Chemical Engineering

265

107

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a b s t r a c tWe present a multi-scale framework for the optimal design of CO 2 capture, utilization, and sequestration (CCUS) supply chain network to minimize the cost while reducing stationary CO 2 emissions in the United States. We also design a novel CO 2 capture and utilization (CCU) network for economic benefit through utilizing CO 2 for enhanced oil recovery. Both the designs of CCUS and CCU supply chain networks are multi-scale problems which require decision making at material, process and supply chain levels. We present a hierarchical and multi-scale framework to design CCUS and CCU supply chain networks with minimum investment, operating and material costs. While doing so, we take into consideration the selection of source plants, capture processes, capture materials, CO 2 pipelines, locations of utilization and sequestration sites, and amounts of CO 2 storage. Each CO 2 capture process is optimized, and the best materials are screened from large pool of candidate materials. Our optimized CCUS supply chain network can reduce 50% of the total stationary CO 2 emission in the U.S. at a cost of $35.63 per ton of CO 2 captured and managed. The optimum CCU supply chain network can capture and utilize CO 2 to make a total profit of more than 555 million dollars per year ($9.23 per ton). We have also shown that more than 3% of the total stationary CO 2 emissions in the United States can be eliminated through CCU networks at zero net cost. These results highlight both the environmental and economic benefits which can be gained through CCUS and CCU networks. We have designed the CCUS and CCU networks through (i) selecting novel materials and optimized process configurations for CO 2 capture, (ii) simultaneous selection of materials and capture technologies, (iii) CO 2 capture from diverse emission sources, and (iv) CO 2 utilization for enhanced oil recovery. While we demonstrate the CCUS and CCU networks to reduce stationary CO 2 emissions and generate profits in the United States, the proposed framework can be applied to other countries and regions as well.

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Section: Ccus and Ccu Challengesmentioning

confidence: 97%

A multi-scale framework for CO2 capture, utilization, and sequestration: CCUS and CCU

Hasan

First

Boukouvala

et al. 2015

Computers & Chemical Engineering

265

107

View full text Add to dashboard Cite

show abstract

“…The Delta Change cycle-based heuristic is also used in an algorithm described by Brimberg et al (2003) referred to as "Local Search" (LS). However, in Local Search, the steepest-descent form is used, in which all the possible cycles of the 1-neighbourhood are explored before the minimum-cost solution is chosen, if an improvement is found.…”

Section: B Local Searchmentioning

confidence: 99%

“…Instead, graph optimization schemes are used to achieve lower cost trees rapidly, to the detriment of not insuring true optimal soluitions. Multiple approaches exist, including multi-Mixed Integer Linear Programming, that make use of traditional solver tools from mathematical programming and optimization (van den Broek et al 2009;Brimberg et al 2003;Sun & Chen 2016), agent-based methods such as Ant Swarm Optimization (Maier et al 2003), Genetic Algorithms (Weihs et al 2011), or graph-based heuristic algorithms (Kazmierczak et al 2009;Bietresato et al 2013;André et al 2013;Heijnen et al 2020). A formal mathematical description of the problem can be found in Heijnen et al (2020) or Xue et al (1999).…”

Section: Introductionmentioning

confidence: 99%

Comparison of heuristic methods for achieving minimum-cost capacitated networks with a new metaheuristic based on node valency

Yeates¹,

Schmidt‐Hattenberger²,

Weinzierl³

et al. 2020

Preprint

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Designing low-cost networks is an essential step in planning linked infrastructure. For the case of capacitated trees, such as oil or gas pipeline networks, the cost is usually a function of both pipeline thickness (i.e. capacity) and pipeline length. Minimizing cost becomes particularly difficult as network topology itself dictates local flow material balances, rendering the optimization space non-linear. The combinatorial nature of potential trees requires the use of graph optimization heuristics to achieve good solutions in reasonable time. In this work we perform a comparison of known literature network optimization heuristics and metaheuristics, and propose novel algorithms, including a metaheuristic based on transferring edges of high valency nodes. Our metaheuristic achieves performance above similar algorithms studied, especially for larger graphs, usually producing a significantly higher proportion of optimal solutions, while remaining in line with time-complexity of algorithms found in the literature. Data points for graph node positions and capacities are first randomly generated, and secondly obtained from the German emissions trading CO2 source registry. Driven by the increasing necessity to find applications and storage for industry CO2 emissions, finding minimum-cost networks increases the business case for large-scale CO2 transportation pipeline infrastructure.

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“…Bojic [130] developed a network of energy module based on dynamic programming procedure for the optimization of energy system. Many researchers including [131][132][133][134][135][136][137][138][139][140] applied MARKAL energy model for large scale energy planning. The EFOM energy model was used in different states including [141][142][143][144][145][146][147][148].…”

Section: Review Of Literaturementioning

confidence: 99%

Recent Updates on Energy Planning Models - A Review

Hafeez

Gulshan

Tahira

2020

Journal of Mechanical and Energy Engineering

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Energy is the most important part for community and financial growth of any country. Energy planning models play a vital role in strategy formulation and power sector progress. In this paper a systematic review and comparison of energy planning models developed and applied from 1977-2019 has been presented. The review indicates that most of the energy planning models has been presented and applied in developed nations. Only few numbers of energy planning models have been presented and applied in under developing countries. The review also shows the comparison of energy planning models applied in developed and under-developed countries. This review article will assistance the energy managers, scholars and strategy makers broadly.

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An integrated GIS-MARKAL toolbox for designing a CO2 infrastructure network in the Netherlands

Cited by 23 publications

References 4 publications

A multi-scale framework for CO2 capture, utilization, and sequestration: CCUS and CCU

A multi-scale framework for CO2 capture, utilization, and sequestration: CCUS and CCU

Comparison of heuristic methods for achieving minimum-cost capacitated networks with a new metaheuristic based on node valency

Recent Updates on Energy Planning Models - A Review

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