Three very different methods of accomplishing the same task-managing the operation of the transmission system in the deregulated power system operating environment-have been implemented as deregulated market structures have been created around the world. They are first, the optimal power flow (OPF) model found in various implementations in the United Kingdom, parts of the United States, and in Australia and New Zealand. Second, the point tariff, price area congestion control model used in the Nordpool market area in Norway and Sweden. Third, the US transaction-based model. All are pragmatic solutions implemented in advance of complete theoretical understanding. Each has strengths and flaws, and there are some surprising inter-relationships. Each maintains power system security but differs in its impact on the economics of the energy market. No clearly superior method has so far emerged. In the future, methods of combining decentralized market solutions with operational use of optimal power flow may provide better solutions to existing and emerging problems.

A broad overview of on-line power system security analysis is provided, with the intent of identifying areas needing additional research and development. Current approaches to state estimation are reviewed and areas needing improvement, such as external system modeling, are discussed. On-line contingency selection has become practical, particularly for static security. Additional work is necessary to identify better indices of power system stress to be used in on-line screening filters for both static and dynamic security analysis. Use of optimal power flow schemes to recommend optimal preventive and corrective strategies is presented on a conceptual level. Techniques must be further developed to provide more practical contingency action plans, which include real-world operating considerations and use a reasonably small number of control actions. Techniques must be developed for costing operating variables which are not easily quantified in dollars. Soft or flexible constraints and time variables must be included in the preventive and corrective strategy formulation. Finally, the area of on-line transient and dynamic security analysis is presented.>

Concerns about the effectiveness of conventional alarm processing systems have prompted the development of expert systems designed to present a clearer description of disturbances to the power system operator. The features of the various intelligent alarm processors which are described in the technical literature are discussed in order to highlight the issues which must be addressed and the design decisions which must be made in the development of these systems. A number of systems described in the technical literature under the name intelligent alarm processor are in fact fault diagnosis systems. The authors attempt to clarify the criteria which separate these two types of systems.>

Power system operators often reach a cognitive barrier when information arrives too fast during a power system emergency. At such times it becomes difficult to reach a correct diagnosis of the problem or to formulate the correct decision when actions must be taken. Artificial Intelligence gives designers of Energy Management Systems a way to solve many of the diagnosis and decision problems so as to make the EMS more useful. This paper explores reasons why AI techniques, such as knowledge-based expert systems, are being used in EMS designs and the differences between knowledge-based expert systems and traditional numeric algorithm development. The differences between expert systems and the numeric approach extend to the basic conception and design of the applications. This is illustrated using a relay fault diagnosis system, showing both the traditional and rapid prototyping approaches to its development. Finally, issues concerned with the implementation of AI in EMS computers are explored along with the authors' predictions of possible AI applications to power system operations.