Long-term optimisation model of the Tunisian power system

Dhakouani, Asma; Gardumi, Francesco; Znouda, Essia; Bouden, Chiheb; Howells, Mark

doi:10.1016/j.energy.2017.09.093

Cited by 51 publications

(23 citation statements)

References 24 publications

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“…The enhanced modelling framework can be of use for planning energy infrastructure investments in scenarios where high renewable penetration is targeted and it is expected to be backed up by non-renewable generation, amongst other options. One such case occurs for instance in Tunisia, where the authors are contributing to modelling efforts to support energy supply plans [45]. Here, targets of renewable penetration combine with limited electricity trade capacity with neighbouring countries, limited hydro resources, need for security of supply, and abundance of fossil resources.…”

Section: Discussionmentioning

confidence: 99%

“…The enhanced modelling framework will also be applied to real case studies, featuring more complex energy mix and actual cost trends, to extract policy insights. Application is under development for the Tunisian model developed in a previous study [45]. The engagement with local institutions for future work was made possible by the relevance, accessibility, and documentation of the enhanced modelling framework.…”

Section: Discussionmentioning

confidence: 99%

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Representation of Balancing Options for Variable Renewables in Long-Term Energy System Models: An Application to OSeMOSYS

et al. 2019

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The growing complexity and the many challenges related to fast-changing and highly de-carbonised electricity systems require reliable and robust open source energy modelling frameworks. Their reliability may be tested on a series of well-posed benchmarks that can be used and shared by the modelling community. This paper describes and integrates stand-alone, independent modules to compute the costs and benefits of flexible generation options in the open source energy investment modelling framework OSeMOSYS. The modules are applied to a case study that may work as a benchmark. The whole documentation of the modules and the test case study are retrievable, reproducible, reusable, interoperable, and auditable. They create a case to help establish a FAIR-compliant, user-friendly, and low-threshold model and data standards in modelling practices. As is well known, one of the options for balancing high shares of variable renewables is flexible power generation by dispatchable units. The associated costs need to be considered for short-term operational analyses and for long-term investment plans. The added modules contribute to extending the modelling capacity by introducing (a) costs of ramping, (b) non-linear decrease of efficiency at partial load operation, and (c) refurbishment of existing units in the cost minimisation objective function of OSeMOSYS. From application to the test case study, two main insights are drawn: costs of ramping and decreased partial load efficiency may influence the competitiveness of generation technologies in the provision of reserve capacity; and refurbishment of existing units may represent attractive investment options for increasing flexibility. Both effects are also seen in the long-term and may impact infrastructure investment decisions to meet decarbonisation targets. These effects would not be captured without the introduction of the modules.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Representation of Balancing Options for Variable Renewables in Long-Term Energy System Models: An Application to OSeMOSYS

et al. 2019

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“…Moradi et al [374] presented a Single-node energy model for energy planning. Dhakouani [375] used OSeMOSYS energy model to the power of Tunisia. Lumbreras et al [376] developed an optimum model for transmission network expansion planning.…”

Section: Rajesh Et Al [349] Established a Multi-stage Mixedmentioning

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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“…It is a new code implementation of the open source energy modeling system (the OSeMOSYS modeling framework) [10,11] with the substantial extension of Monte Carlo simulations (MCS). Other code implementations of OSeMOSYS (i.e., GNU MathProg, GAMS, and Python using the software library Pyomo [12,13]) have been extensively used for modeling and analysis of long-term energy planning scenarios in the scientific literature, e.g., see References [14][15][16][17][18][19][20][21]. However, those studies are limited in their usability to run MCS in an automated and convenient way.…”

Section: Rationalementioning

confidence: 99%

“…The user defines a specific model by providing input data to parameters for energy demand, energy supply, energy and/or emission targets, techno-economics, capacity-building constraints, etc. The OSeMOSYS modeling framework has been widely used in scientific studies to generate outlooks and to enhance understanding concerning the impact of structural transformations in energy systems concerning economic, environmental, and social aspects, e.g., see References [14][15][16][17][18][19]. The structure and features of the OSeMOSYS modeling framework have been well described in the scientific literature, see References [10,11].…”

Section: Osemosys Modeling Frameworkmentioning

confidence: 99%

OSeMOSYS-PuLP: A Stochastic Modeling Framework for Long-Term Energy Systems Modeling

Dreier¹,

Howells²

2019

Energies

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Recent open-data movements give access to large datasets derived from real-world observations. This data can be utilized to enhance energy systems modeling in terms of heterogeneity, confidence, and transparency. Furthermore, it allows to shift away from the common practice of considering average values towards probability distributions. In turn, heterogeneity and randomness of the real-world can be captured that are usually found in large samples of real-world data. This paper presents a methodological framework for an empirical deterministic–stochastic modeling approach to utilize large real-world datasets in long-term energy systems modeling. A new software system—OSeMOSYS-PuLP—was developed and is available now.It adds the feature of Monte Carlo simulations to the existing open-source energy modeling system (the OSeMOSYS modeling framework). An application example is given, in which the initial application example of OSeMOSYS is used and modified to include real-world operation data from a public bus transport system.

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Long-term optimisation model of the Tunisian power system

Cited by 51 publications

References 24 publications

Representation of Balancing Options for Variable Renewables in Long-Term Energy System Models: An Application to OSeMOSYS

Representation of Balancing Options for Variable Renewables in Long-Term Energy System Models: An Application to OSeMOSYS

Recent Updates on Energy Planning Models - A Review

OSeMOSYS-PuLP: A Stochastic Modeling Framework for Long-Term Energy Systems Modeling

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