In Brescia, Italy, heat is delivered to 70% of 200.000 city inhabitants by means of a district heating system, mainly supplied by a waste to energy plant, utilizing the non recyclable fraction of municipal and industrial solid waste (800,000 tons/year, otherwise landfilled), thus saving annually over 150,000 tons of oil equivalent and over 400,000 tons of CO(2) emissions. This study shows how the performance of the waste-to-energy cogeneration plant can be improved by optimising the condensation system, with particular focus on the combination of wet and dry cooling systems. The analysis has been carried out using two subsequent steps: in the first one a schematic model of the steam cycle was accomplished in order to acquire a knowledge base about the variables that would be most influential on the performance. In the second step the electric power output for different operating conditions was predicted and optimized in a homemade program. In more details, a thermodynamic analysis of the steam cycle, according to the design operating condition, was performed by means of a commercial code (Thermoflex (c)) dedicated to power plant modelling. Then the off-design behaviour was investigated by varying not only the ambient conditions but also several parameters connected to the heat rejection rate, like the heat required from district heating and the auxiliaries load. Each of these parameters has been addressed and considered in determining the overall performance of the thermal cycle. After that, a complete prediction of the cycle behaviour was performed by simultaneously varying different operating conditions. Finally, a Matlab (c) computer code was developed in order to optimize the net electric power as a function of the way in which the condensation is operated. The result is an optimum set of variables allowing the wet and dry cooling system to be regulated in such a way that the maximum power is achieved. The best strategy consists in using the maximum amount of heat rejection in the wet cooling system to reduce the operational cost of the dry one. (C) 2010 Elsevier Ltd. All rights reserved.