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The control of heliostats in existing Concentrated Solar Power (CSP) fields is performed based on wired communications, resulting in high installation, maintenance, and operation cost. This paper introduces a wireless communication system for CSP fields based on the Integrated Access and Backhaul (IAB) technology, a distributed resource management mechanism, and an artificial intelligent or AI-based clustering mechanism for the heliostats. The proposed system ensures efficient communication between the heliostats and their cluster-heads as well as among the cluster-heads themselves in order to communicate with the Central Station (CS) residing in the CSP field. The clustering is optimized using the Optimistic Q-learning with Upper Confidence Bound (OQ-UCB) algorithm, accounting for the CSP fields’ topology and channel gain characteristics. Furthermore, a game-theoretic approach is employed to optimize the transmission power and bandwidth allocation, aiming to enhance the energy efficiency while meeting the stringent latency demands of the heliostat autocalibration. Experiments and numerical results from a CSP field with 7,683 heliostats validate the system’s efficacy in maintaining robust wireless communication and energy efficiency and highlight the proposed model’s capability to support the wireless communication needs of CSP fields.
Rahman et al. (Wed,) studied this question.