Performance evaluation of power plants in primary frequency control integrating heuristic parameter extraction optimization and share attribution mechanism

• Quality evaluation of generation units performance in PFC, introducing PTV index. • Integrable index in ancillary service frameworks, compared with similar approaches. • Using heuristic optimization to identify influential parameters of units governor. • Developing a mechanism to allocate parameters impact on imperfect unit performance. • Providing realistic feedback for techno-economic PFC evaluations in large-scale grids. The advent of ancillary service markets and growing penetration of non-synchronous renewable generation have introduced new technical challenges and financial implications to the Primary Frequency Control (PFC) procedure. This paper suggests a novel framework for comprehensive performance evaluation of the power plants participating in the PFC, consisting of three main parts. Firstly, the Participant Technical Value (PTV) is introduced for the overall assessment of the participation quality, comparing the unit action and its expected behavior. Secondly, a new customized heuristic optimization algorithm is proposed for identifying the influential parameters. Thirdly, the contributions of different parameters to imperfect performance are quantified, combining the calculated PTV and extracted parameters. Diverse simulation case studies are conducted for different types of units to show the effectiveness. The PTV correctly assesses diverse perfect (1), deteriorated (<1), and enhanced (>1) performances, while being robust in various incidents. The heuristic optimization has achieved 99.8 % accuracy for parameter identification, which is at least 10.2 % more accurate and 5 times faster than the meta -heuristic algorithms. The correct quantitative share allocation has been achieved, and the manageable overall computation time (5 s for one unit) is discussed for real-world applications. The method’s superior performance is further demonstrated compared to the selected studies from both academia and industry. There are numerous possible applications for different parts of the suggested novel framework, including PTV integration into ancillary service payments, detecting declared inaccurate settings from unit owners, and providing specific feedback for better PFC performance.