1 Copyright © 2012 by ASME OPTIMIZATION OF THERMAL POWER PLANTS OPERATION IN THE GERMAN DE-REGULATED ELECTRICITY MARKET USING DYNAMIC PROGRAMMING G. SCARABELLO Department of Industrial Engineering University of Padova, Italy S. RECH* Department of Industrial Engineering University of Padova via Venezia, 1 - 35151 Padova, Italy Email: sergio.rech@studenti.unipd.it A. LAZZARETTO Department of Industrial Engineering University of Padova, Italy A. CHRISTIDIS Institute for Energy Engineering, Technische Universität Berlin, Germany G. TSATSARONIS Institute for Energy Engineering, Technische Universität Berlin, Germany ABSTRACT The prospect of clean electrical energy generation has recently driven to massive investments on renewable energies, which in turn has affected operation and profits of existing traditional thermal power plants. In this work several coal-fired and combined cycle power units are simulated under design and off-design conditions to adequately represent the behavior of all modern thermal units included in the German power system. A dynamic optimization problem is then solved to estimate the short-run profits obtained by these units using the spot prices of the German electricity market (EEX) in years 2007-2010. The optimization model is developed using a Mixed Integer Linear Programming approach to take the on-off status into account and reduce computational effort. New market scenarios with increasing renewable shares (and consequently different spot prices) are finally simulated to analyze the consequences of a larger capacity of renewable energies on the optimal operation of traditional thermal power plants. INTRODUCTION In the last years environmental concerns and high oil prices has led in Germany to a relevant growth of renewable energy capacity. So, power utilities are facing new market conditions: lower spot electricity prices and higher volatility, which can greatly affect operation and earnings of traditional power units. Moreover, the continuous fluctuation in the renewable energy supply not only complicates the unit commitment planning, but also considerably increases the reserve requirement for the stable electricity supply in the whole system. Since the introduction of the European Union Greenhouse Gas Emission Trading Scheme (EU ETS) in 2005, also CO 2 allowance prices have been participating in the electricity price formation as an essential part of specific generation costs. For all these reasons uncertainty on fossil fuel utilities is great (lower prices reduce full load hours and earnings, while volatility requires higher flexibility [1]), and investments on these plants need to be supported by accurate economical estimations, which require:  Knowledge of thermodynamic models of the plants . General principles of energy system modeling at design (see, e.g., [2-4]) and off-design (see e.g., [5, 6]) conditions are widely discussed in the literature. Several paper deal with the application of these principles to traditional thermal power plant simulations. Interesting applications to coal- fired power plants are shown in [7-9]. In particular [7] compares two different control strategies in terms of part load efficiency. Other significant applications on combined cycle power plants are presented in [10, 11] where part load performance is evaluated using different control strategies.  Definition of the plant optimization strategy . General principles of energy system design and operation optimization are presented in [12, 13]. A review of a large number of modeling methods is shown in [14]. Searching the optimal operation strategy of power plants under conditions of deregulated market is usually a dynamic problem. In order to reduce the computational effort the optimization model is generally simplified by using only linear relationships, and the on-off status of each plant is Proceedings of the ASME 2012 International Mechanical Engineering Congress & Exposition IMECE2012 November 9-15, 2012, Houston, Texas, USA IMECE2012-86113