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International Handbook on the Economics of Energy

Edited by Joanne Evans and Lester C. Hunt

As an essential component for economic growth, energy has a significant impact on the global economy. The need to meet growing energy demand has prompted cutting-edge innovation in clean technology in an attempt to realise environmental and cost objectives, whilst ensuring the security of energy supply. This Handbook offers a comprehensive review of the economics of energy, including contributions from a distinguished array of international specialists. It provides a thorough discussion of the major research issues in this topical field of economics.
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Chapter 12: The Structure and Use of the UK MARKAL Model

Ramachandran Kannan, Paul Ekins and Neil Strachan


Ramachandran Kannan, Paul Ekins and Neil Strachan* 1 Introduction The previous chapter introduced and reviewed the widely applied bottom-up, dynamic, linear programming optimisation model known as the MARKAL model. Developed in the late 1970s, MARKAL has been continually supported by the International Energy Agency (IEA) via the Energy Technology and Systems Analysis Program (ETSAP) and has contributed to numerous and wide-ranging energy policy studies; for example, the IEA Energy Technology Perspectives (ETP) project (IEA, 2006). This chapter illustrates the use of the model in more depth, reporting on the development and initial use of the United Kingdom (UK) MARKAL model.1 Section 2 describes the general structure and methodological process of the MARKAL model. Section 3 elucidates the development of the UK MARKAL with respect to its input data assumptions, validation and calibration processes. More detailed information on the development of the UK MARKAL model is given in Strachan et al. (2006, 2008a). Section 4 provides indicative results2 from the model to demonstrate its analytical strength, range of outputs, and how it deals with uncertainties. Section 5 concludes. 2 MARKAL Model Description The MARKAL energy system model is a data-driven, technology-rich bottom-up costoptimisation modelling framework. The optimised quantity is the total energy system cost, with the decision variables the investment and operation of all the interconnected system elements. The model is energy-service driven and encompasses the entire energy system from imports and domestic production of fuel resources, through fuel processing and representation of infrastructures, conversion to secondary energy carriers and end-use...

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