2 the Impact of Field Data

The concept of Supervisory Control and Data Acquisition (SCADA) system was introduced in the late sixties and subsequently the Energy Management System (EMS) solution with set of functionalities that relied on SCADA data was introduced in the seventies. This EMS design was based on the notion that power system goes through distinct states such as normal, alert, emergency and restorative, and hence the EMS functionalities need to support operators’ ability to monitor the system behaviour as it goes through various operating states and make decisions to steer it back to the normal state. As the time went by, many things have changed in the area of power systems: introduction of the electricity markets to accommodate competitive trading, the growth of the power system infrastructure to meet demands for renewable resources, EMS technology to improve computations, communications and visualization. Hence, almost 50 years after the initial proposals for the EMS solution as we know it today, the question whether we need a new EMS design and if so, how the next generation EMS design is going to look like may be raised. While this is a complex question requiring analysis well beyond what may be achieved through a discussion in a single paper, there are a few requirements of the next generation EMS design that are becoming rather obvious. They revolve around three simple questions: a) can the operator’s ability to monitor the system be improved and how, b) what are the requirements for the better decision-making tools for the operators and how such tools may be implemented, and c) how the design may evolve from the current legacy design to the stages of future EMS implementation. This paper is focused on trying to answer those three questions. The discussion is facilitated by using specific examples of the developments that the author was or is involved with. The examples include the discussion of spatial and temporal improvements in data management by merging operational and non-operational data, development of improved operator decision-making tools by better matching data and models, and introduction of a development and implementation strategy that relies on gradual transition from legacy to future design.