Plantwide Decentralized Controller Design for Hybrid Solar Thermal Power Plant

Solar Thermal Power (STP) plants are promising avenues for solar energy assisted power generation. However, they face operational challenges due to diurnal and seasonal variations in available solar radiation, and varying atmospheric conditions in terms of cloud cover, dust levels, etc. Thus, to operate an STP plant at high efficiency and to meet the electricity demand, optimization and control strategies are critical. This paper focuses on designing decentralized controllers to ensure the safe and efficient operation of a hybrid STP which was designed and commissioned a few years ago (Nayak et al., Current Science, 2015, 109, 1445–1457). The STP is hybrid as it uses two different technologies for solar power collection, namely Parabolic Trough Collector (PTC) for heating oil and a Linear Fresnel Reflector (LFR) for generating direct steam. Superheated steam, generated using heat exchangers, subsequently drives the turbine generator block to generate electricity. In the current work, we develop decentralized controllers which ensure safe operation while meeting the production target of the hybrid STP. Towards this end, key control loops in the plant are identified. Continuous transfer function models are identified for these control loops using step tests. PID controllers are then obtained for these loops based on the resulting transfer function models. Wherever relevant, the feedback action of PID controllers is supplemented by a feedforward control action that reacts to the disturbances. Override control action is also implemented to ensure safe operation. The utility of the proposed plantwide decentralized control scheme is demonstrated via simulation studies by comparing the performance of the hybrid STP under open-loop and closed-loop in presence of disturbances and significant dynamic variability in the plant operation via two case studies. Results indicate significantly superior performance of closed-loop operation across various performance metrics.