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MASTER SO: Model for the Analysis of SusTainable Energy Roadmaps. Static Optimization version

Dr. Pedro Linares Llamas

Description of the MASTER_SO model

The MASTER SO (Model for the Analysis of Sustainable Energy Roadmaps. Static Optimization version) model is a static model that describes the energy sector in a bottom-up fashion (that is, it is built from the components of the system). It is property of Comillas University, and was developed by Álvaro López-Peña, supervised by Pedro Linares and Ignacio Pérez Arriaga. MASTER.SO is built around five blocks in which the different levels of energy conversion are described, from natural resources to the final use of energy (López-Peña, 2014).

  • 1. PE Primary energy sources (nuclear, coal, gas, renewables...).
  • 2. CE Energy conversion processes (electricity generation, refining, etc.).
  • 3. TE Transport of energy to the different consuming sectors (through e.g. gas or electriicty networks).
  • 4. DS Consumption of energy by the different economic sectors (e.g. industry or residential).
  • 2
  • 5. ES Final use of energy (e.g. for heating, lighting or transport).
  • 2

The model starting point is a given, exogenous demand for energy services (km to be driven, or sq.m to be heated), which can be satisfied by different shares of the technologies available. These demands change in different scenarios. Besides, MASTER.SO considers the available infrastructure (hydro, regasification plants, refineries, and transmission and distribution networks), and potential investments in this infrastructure. The model also takes into account the costs and technical parameters of the different technologies (energy conversion and fuel use) as well as fuel prices.

The model determines the optimal use of primary energy sources to satisfy final energy services´ demand. It may install new energy conversion capacity of those technologies more efficient.

MASTER.SO includes a simplified version of the electricity system, which includes the operation and the need for reserves. These reserves have been assumed as equivalent to the loss of a nuclear power plant, plus a certain percentage of demand as prediction error, plus a certain share of non-dispatchable renewable production. Transmission and distribution costs are also estimated in an approximate way, inferring them from the total amount of energy transported.

The model also includes the potential of different technologies (something very relevant for renewables), and a limit to carbon emissions (assumed as a result of different emission reduction policies). Therefore, the model does not take a given price for CO2 emissions, but instead obtains it from the optimization of the system.

The optimization problem is solved a linear programming problem, in which MASTER.SO returns installed capacities, the use of primary energy, final energy use, electricity prices, or CO2 prices.

The model has two other enlarged versions:

- A multiple criteria version, in which the objective function includes other optimization criteria (like emissions or job creation)

- A water-energy nexus version, in which the energy model is coupled to a hydrological model in order to allow for a joint planning of energy and water demands.

Projects in which it has been used:

Papers resulting from the use and development of the model:

[1] Z. Khan, P. Linares, M. Rutten, S. C. Parkinson, N. Johnson, J. García González. "Spatial and temporal synchronization of water and energy systems: towards a single integrated optimization model for long-term resource planning", Applied Energy. vol. 210, pp. 499-517, January 2018. DOI: 10.1016/j.apenergy.2017.05.003

[2] Z. Khan, P. Linares, J. García González. "Integrating water and energy models for policy driven applications. A review of contemporary work and recommendations for future developments." Renewable & Sustainable Energy Reviews. vol. 67, pp. 1123-1138, January 2017. DOI: 10.1016/j.rser.2016.08.043

[3] Z. Khan, P. Linares, J. García González. "Adaptation to climate-induced regional water constraints in the Spanish energy sector: an integrated assessment." Energy Policy. vol. 97, pp. 123-135, October 2016. DOI: 10.1016/j.enpol.2016.06.046

[4] A. López-Peña, I.J. Pérez Arriaga, P. Linares. "Renewables vs. energy efficiency: the cost of carbon emissions reduction in Spain." Energy Policy. vol. 50, pp. 659-668, November 2012. DOI: 10.1016/j.enpol.2012.08.006

[5] A. López-Peña, P. Linares, I.J. Pérez Arriaga. "Análisis retrospectivo de la eficiencia de la promoción de las renovables y del ahorro energético para la reducción de emisiones de CO2 en España." Información Comercial Española, ICE: Revista de Economía. vol. 862, pp. 19-32, September 2011.


Pedro Linares