This work introduces \(\textsf{solar }\) , a collection of ten optimization problem instances for benchmarking blackbox optimization solvers. The instances present different design aspects of a concentrated solar power plant simulated by blackbox numerical models. The type of variables (discrete or continuous), dimensionality, and number and types of constraints (including hidden constraints) differ across instances. The objective or constraints may be deterministic or stochastic outputs of the simulator, with possibilities to execute several replications to control stochasticity. Most instances offer variable fidelity surrogates, two are biobjective and one is constrained only by bounds. The solar plant model takes into account various subsystems: a heliostats field, a central cavity receiver (the receiver), a molten salt thermal energy storage, a steam generator and an idealized power block. Several numerical methods are implemented throughout the \(\textsf{solar }\) code and most of the executions are time-consuming. Great care was applied to guarantee reproducibility across platforms. The \(\textsf{solar }\) tool encompasses most of the characteristics that can be found in industrial and real-life blackbox optimization problems, all in an open-source and stand-alone code.
