PNNL

Abstract

The management of the nation’s power system has progressed to the point where the boundary lines between operations and planning are becoming blurred. The dynamic behavior of smart grid technologies requires the transition from a deterministic to a probabilistic control paradigm, and brings pressure to incorporate the predictive capability from planning to enhance operations. This necessitates smoother, better-integrated interplay between the functional roles of planning and operations. This paper presents a framework to support the fusion of operation and planning. All the function blocks used in the study were built upon the GridOPTICS Software System (GOSS), a middleware platform facilitating deployment of new applications for the future power grid. The framework has been used in a North American operator training class, and its usability and effectiveness have been validated. This paper is an extension of the conference paper published at the International Federation of Automatic Control (IFAC) Symposium on Control of Power & Energy Systems (CPES 2015), with the new addition of integrating a transmission uncertainty prediction tool developed by the Pacific Northwest National Laboratory into the GOSS framework. Two case studies were conducted under the scenario of predicting the intra-hour deficiency in generation capability and transmission congestion under uncertain conditions, and presenting the outputs to operators using advanced visualization tools. The study shows the benefits of fusion and the effectiveness of the framework for these case studies.