A novel dynamic strategy differential evolution technique to solve heat and power combined economic dispatching problem

Units for combined heat and power (CHP) exhibit dual energy production capabilities through simultaneous electricity and thermal energy generation. Therefore, CHP economic dispatch (CHPED) constitutes a critical nonlinear optimization challenge. Recent decades have witnessed extensive exploration of computational solutions for this complex engineering task. In this study, a dynamic strategy differential evolution (DSDE) algorithm is proposed to address CHPED challenges. DSDE introduced a random-selection based mutation strategy and a performance-based adaptive selection method to escaped trapping in a local optimum. Experimental verification involves three distinct benchmark configurations to assess algorithm performance. Comparative studies conducted against existing approaches reveal that DSDE achieves enhanced convergence stability while maintaining superior solution quality parameters.