Abstract
Energy systems modelling aims to introduce a sustainable energy system design with an improved understanding of present and future interactions between demand-supply, environment, and economy. Treating energy systems started in the 1950s and have led to various approaches and models. Amongst common metrics, the discount rate impacts time horizon costs, benefits, demand and supply. This chapter presents an objective overview of energy systems approaches based on their historical evolutions. In order to point out social benefits and costs, the use of social discount rate for the Tunisian power system is argued.
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Notes
- 1.
Ceteris Paribus Assumption consists in drawing the relation between the price and the quantity of goods consumed while holding other determinants fixed.
- 2.
In statistical analysis of time series data, models are sometimes built on variables predicted based on historical evolution. This is called auto-regression or autoregressive models, and the values of the variables would be predictive variables, called lagged variables.
- 3.
End-use called as well engineering-economic or accounting.
- 4.
Artificial neural networks called as well combined or hybrid.
- 5.
Confusion occurs due to the utilisation of different lexical meaning for parameters. Access to equations gives a clearer insight about the meaning of these parameters.
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Dhakouani, A., Znouda, E., Bouden, C. (2021). The Role of Social Discount Rate in Energy Modelling. In: Asif, M. (eds) Energy and Environmental Security in Developing Countries. Advanced Sciences and Technologies for Security Applications. Springer, Cham. https://doi.org/10.1007/978-3-030-63654-8_19
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