A multilevel optimization approach for daily scheduling of combined heat and power units with integrated electrical and thermal storage

Renowned for their remarkable overall efficiencies ranging from 70% to 90%, combined heat and power systems stand as a pivotal strategy for optimizing energy consumption by capitalizing on the synergistic relationship between electricity and thermal energy production. However, achieving optimal performance in combined heat and power systems remains a formidable challenge due to the intricate interplay of numerous variables. This paper presents a novel approach to daily scheduling optimization for combined heat and power units, focusing on the integration of electrical and thermal storage systems and meticulous consideration of security constraints. The optimization of combined heat and power unit scheduling introduces a mixed-integer nonlinear programming challenge, replete with deterministic and random variables. Addressing this complexity requires resilient solutions. In this study, we employ a multilevel optimization technique, transforming the problem into a bilevel structure. The initial step involves mapping operating parameters and minimizing costs through a water cycle optimization algorithm, laying a robust foundation for combined heat and power unit operation. Subsequently, we immerse ourselves in the realm of stochastic contingency scenarios, acknowledging the myriad uncertainties inherent in real-world systems. To empirically validate the efficacy of our proposed algorithm, extensive simulations are conducted on IEEE 18-bus and 24-bus test systems that emulate practical power networks. The results unequivocally showcase the power of our approach in navigating the complexities of optimal CHP unit planning. This paper ' s contributions lie in its innovative multilevel optimization technique, adeptly addressing both deterministic and stochastic aspects, ultimately paving the way for increased energy efficiency and enhanced system reliability in practical applications.