A generic algebraic targeting approach for integration of renewable energy sources, CO2 capture and storage and negative emission technologies in carbon-constrained energy planning

Nair, Purusothmn Nair S. Bhasker; Tan, Raymond R.; Foo, Dominic Chwan Yee

doi:10.1016/j.energy.2021.121280

Cited by 29 publications

(4 citation statements)

References 33 publications

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“…For example, CEPA has been extended to the planning of CCS systems [83] and more recently to NETs deployment planning (see Fig 3A; [84]). Derivative graphical [84,85] and algebraic techniques [86] have been proposed for the optimum deployment of NETs. A CEPA study of the UK's decarbonization concluded that net-zero emissions can be achieved with BECCS [87].…”

Section: Graphical and Algebraic Pinch Analysis Extensionsmentioning

confidence: 99%

Optimization and decision support models for deploying negative emissions technologies

Migo-Sumagang

Aviso

Foo

et al. 2023

PLOS Sustain Transform

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Negative emissions technologies (NETs) will be needed to reach net-zero emissions by mid-century. However, NETs can have wide-ranging effects on land and water availability, food production, and biodiversity. The deployment of NETs will also depend on regional and national circumstances, technology availability, and decarbonization strategies. Process integration (PI) can be the basis for decision support models for the selection, planning, and optimization of the large-scale implementation of NETs. This paper reviews the literature and maps the role of PI in NETs deployment. Techniques such as mathematical programming, pinch analysis (PA), process graphs (P-graphs), are powerful methods for planning NET systems under resource or footprint constraints. Other methods such as multi-criteria decision analysis (MCDA), marginal abatement cost curves, causality maps, and machine learning (ML) are also discussed. Current literature focuses mainly on bioenergy with carbon capture and storage (BECCS) and afforestation/reforestation (AR), but other NETs need to be integrated into future models for large-scale decarbonization.

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Section: Graphical and Algebraic Pinch Analysis Extensionsmentioning

confidence: 99%

Optimization and decision support models for deploying negative emissions technologies

Migo-Sumagang

Aviso

Foo

et al. 2023

PLOS Sustain Transform

Self Cite

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“…Like solar energy, the CO 2 intensities and costs of renewable energies are expected to decrease across periods [45,46]. In the final period, solar energy would be the cheapest [43,45] and has the lowest CO 2 intensity [19,47]. The superstructural model in this work would determine the optimal deployment of renewable energy sources (if necessary) to meet the demand and CO 2 emissions limits.…”

Section: Case Studymentioning

confidence: 99%

“…Recognising that a portfolio of NETs would be required to accelerate CDR, this work was later revamped for the combined deployment of both EP-NETs and EC-NETs [18]. The limitations of the graphical targeting technique were overcome with the development of an algebraic targeting technique in which renewable energy sources, CCS and NETs were considered during energy planning [19]. An optimal source-sink matching for CDR via biochar was initially conducted via a MILP model [20].…”

Section: Introductionmentioning

confidence: 99%

DECO2—An Open-Source Energy System Decarbonisation Planning Software including Negative Emissions Technologies

et al. 2023

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The deployment of CO2 capture and storage (CCS) and negative emissions technologies (NETs) are crucial to meeting the net-zero emissions target by the year 2050, as emphasised by the Glasgow Climate Pact. Over the years, several energy planning models have been developed to address the temporal aspects of carbon management. However, limited works have incorporated CCS and NETs for bottom-up energy planning at the individual plant scale, which is considered in this work. The novel formulation is implemented in an open-source energy system software that has been developed in this work for optimal decarbonisation planning. The DECarbonation Options Optimisation (DECO2) software considers multiperiod energy planning with a superstructural model and was developed in Python with an integrated user interface in Microsoft Excel. The software application is demonstrated with two scenarios that differ in terms of the availabilities of mitigation technologies. For the more conservative Scenario 1, in which CCS is only available in later years, and other NETs are assumed not to be available, all coal plants were replaced with biomass. Meanwhile, only 38% of natural gas plants are CCS retrofitted. The remaining natural gas plants are replaced with biogas. For the more aggressive Scenario 2, which includes all mitigation technologies, once again, all coal plants undergo fuel substitution. However, close to half of the natural gas plants are CCS retrofitted. The results demonstrated the potential of fuel substitutions for low-carbon alternatives in existing coal and natural gas power plants. Additionally, once NETs are mature and are available for commercial deployment, their deployment is crucial in aiding CO2 removal in minimal investment costs scenarios. However, the results indicate that the deployment of energy-producing NETs (EP-NETs), e.g., biochar and biomass with CCS, are far more beneficial in CO2 removal versus energy-consuming NETs (EC-NETs), e.g., enhanced weathering. The newly developed open-source software demonstrates the importance of determining the optimal deployment of mitigation technologies in meeting climate change targets for each period, as well as driving the achievement of net-zero emissions by mid-century.

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“…In the context of carbon peak and carbon neutrality, renewable energy sources, which can replace fossil energy on a large scale, present new opportunities for development (Liu et al, 2020a;Ben Yosef et al, 2021;Jiang et al, 2021;Liu et al, 2020b;Ma et al, 2021;Nair et al, 2021). The development of renewable energy sources is currently restricted because they are inherently intermittent, being dependent on weather conditions and daily cycles.…”

Section: Introductionmentioning

confidence: 99%

Experimental Study on the Mechanical and Permeability Properties of Lining Concrete Under Different Complex Stress Paths

et al. 2022

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A promising large-scale energy storage is underground compressed air energy storage (CAES) in lined rock caverns. To ensure the safety and stability of storage caverns because of the influence of periodic injection during production, it is crucial to understand the mechanical behavior of lining concrete under different complex stress paths. In this study, three types of uniaxial compressive fatigue test and uniaxial creep test were conducted on concrete. The following conclusions were obtained from the results. 1) The irreversible deformation after the interval was larger than that before the interval in the discontinuous multi-step cyclic loading (DMCL) test. 2) Loading velocity significantly influenced concrete fatigue, and the irreversible deformation in the cycle of low loading velocity was greater than that in the cycle of high loading velocity. 3) The residual strain increased with an increase in stress level. 4) The creep strain increased with an increase in stress level during the multi-step creep loading test; the fractional derivative results were more consistent with the experimental results. 5) The permeability of concrete increased rapidly under the influence of an external force when the stress level exceeded 0.73.

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A generic algebraic targeting approach for integration of renewable energy sources, CO2 capture and storage and negative emission technologies in carbon-constrained energy planning

Cited by 29 publications

References 33 publications

Optimization and decision support models for deploying negative emissions technologies

Optimization and decision support models for deploying negative emissions technologies

DECO2—An Open-Source Energy System Decarbonisation Planning Software including Negative Emissions Technologies

Experimental Study on the Mechanical and Permeability Properties of Lining Concrete Under Different Complex Stress Paths

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