Modules

Prerequisites

Contents

The course covers the basic ideas of optimization theory with applications to energy systems. Mathematical models are introduced to allow for quantitative analyses of the competitive behaviour and strategic interactions of relevant market participants. A number of illustrative numerical problems will be applied to discuss the following aspects of energy markets: • Economic fundamentals of electricity systems and markets • Pricing and investments (Short-term dispatch and long-term equilibrium) • Market integration of renewable energy sources • Emissions from electricity production (CO2 cap vs CO2 tax) • Electricity transport and distribution (Congestion in electricity networks and nodal & zonal pricing schemes) • Unit commitment decision of power plants • Energy storage systems • Demand elasticity • Stochastic and integer programming

Learning outcomes

The course provides knowledge and tools tounderstand thefundamental interactionsin energy systems. Participants will learn: • the basic theory behind LP, MILP, NLP and MCP modelling approaches, • the specifics of energy systems and their conversion into mathematical problems, • to implement and solve these mathematical problems with software packages and • to choose appropriate optimization methods and interpret results.

Assessment

• 2 Hometasks, code and 1-2 page report each (33%) • 1 Study Project, code, 5-page paper, and 10-min presentation (34%) • Written examination, 60 min (33%)