Minimizing water consumption of a CSP plant, by using an optimization algorithm for cooling operation.

Today's thermal power plant cooling systems aim at reaching high steam cycle efficiencies in all operating points while keeping the water consumption as low as possible. For this purpose, cooling systems are becoming more and more complex, such that finding an optimal operation strategy for the cooling components is no longer a trivial problem. To tackle this problem, this paper introduces a cooling operation optimization algorithm. The algorithm is applicable to a black box model of the power plant including the cooling system. Thereby it can easily be applied as online optimizer for existing cooling systems or to investigate different cooling options for different CSP plant configurations during a planning phase. Additionally, the weight of water consumption and electricity production can be adjusted for each optimization run. In this work, we present the algorithm itself by providing a methodology to transform the optimization problem into an oriented decision tree and to solve the resulting problem with a stochastic solution approach developed from an Ant Colony Optimization algorithm. Furthermore, the operability of the algorithm is validated using a performance model of a 50 MW parabolic trough plant with a hybrid cooling system, consisting of a wet cooling tower and a cold thermal energy storage. [ABSTRACT FROM AUTHOR]