Integrating Renewables in Electricity Markets ― Operational Problems

This addition to the ISOR series addresses the analytics of the operations of electric energy systems with increasing penetration of stochastic renewable production facilities, such as wind- and solar-based generation units.

As stochastic renewable production units become ubiquitous throughout electric energy systems, an increasing level of flexible backup provided by non-stochastic units and other system agents is needed if supply security and quality are to be maintained.

Within the context above, this book provides up-to-date analytical tools to address challenging operational problems such as:

‧ The modeling and forecasting of stochastic renewable power production.
‧ The characterization of the impact of renewable production on market outcomes.
‧ The clearing of electricity markets with high penetration of stochastic renewable units.
‧ The development of mechanisms to counteract the variability and unpredictability of stochastic renewable units so that supply security is not at risk.
‧ The trading of the electric energy produced by stochastic renewable producers.
‧ The association of a number of electricity production facilities, stochastic and others, to increase their competitive edge in the electricity market.
‧ The development of procedures to enable demand response and to facilitate the integration of stochastic renewable units.

This book is written in a modular and tutorial manner and includes many illustrative examples to facilitate its comprehension. It is intended for advanced undergraduate and graduate students in the fields of electric energy systems, applied mathematics and economics. Practitioners in the electric energy sector will benefit as well from the concepts and techniques explained in this book.

Juan Morales received his B.S. degree in Industrial Engineering at the University of Malaga and his Ph.D. in Electrical Engineering at the University of Castilla – La Mancha. His research interests include power system economics, operations, planning and control; renewable energy sources; reliability, stochastic programming and optimization; and electricity markets.

Antonio J. Conejo received the M.S. degree from Massachusetts Institute of Technology, Cambridge, MA, in 1987 and the Ph.D. degree from the Royal Institute of Technology, Stockholm, Sweden, in 1990. He is currently Professor of Electrical Engineering at the Universidad de Castilla – La Mancha, Ciudad Real, Spain.

Henrik Madsen received his M.Sc. in Civil Engineering from the Technical University of Denmark (DTU) and his Ph.D. in Mathematical Statistics and Operational Research from IMSOR. His research interests include modeling of dynamic systems; nonlinear and non-stationary processes; estimating of parameters in stochastic differential equations; time series analysis; grey box modeling; and biostatistics.

Pierre Pinson received his M.Sc. in Applied Mathematics from the National Institute of Applied Sciences, Toulouse, and his Ph.D. in Energetics from the Ecole des Mines de Paris. His research interests include statistical modelling; forecasting; stochastic optimization; decision making under uncertainty; renewable energies; meteorology; energy management; and energy trading.

Zugno Marco received his M.Sc. in Electrical Engineering from the University of Padua; a M.Sc. in Electrical Engineering from the Technical University of Denmark (TDU); and will receive his Ph.D. in 2013, supervised by Madsen and Pinson.