Power system voltage stability monitoring using artificial neural networks with a reduced set of inputs

Calculation of weighting factors of static security indices used in contingency ranking of power systems based on fuzzy logic and analytical hierarchy process

This paper presents a methodology to calculate the transmission capability between two areas in a power system, considering both static and dynamic security assessment. An optimal power flow (OPF) algorithm is used to compute the transmission capability from the static point of view. The dynamic security assessment of the operating point obtained from the OPF is then evaluated. Transient, voltage, and small-signal stability assessment are considered. If any dynamic security criterion is violated, additional constraints are added to the original OPF formulation, and a new and secure transmission limit is calculated. These new constraints can be very simple, such as to limit the transmitted power, or more elaborated, based on some rules obtained from an intelligent system. The intelligent system adopted is a fuzzy inference system (FIS) that drives the redispatch of the active power generation. The FIS output is used to formulate the new constraints to the OPF. In addition to the OPF, the proposed methodology makes use of other power systems analysis tools, such as full time-domain simulation, fast simulation, and modal analysis. The methodology was implemented in a computational platform that integrates all these tools in a single framework. The results for two test systems have shown the potential benefits of the proposed methodology and the importance of considering different dynamic aspects in transmission capability calculation.

Dynamic Transmission Capability Calculation Using Integrated Analysis Tools and Intelligent Systems

Based on a new perspective in coordinating with the traditional “N-1” criteria and system risk, a real-time electricity market model is presented, in which the system risk is employed to model the system’s overall security level. This new model is called the risk-based security-constrained economic dispatch (RB-SCED). Relative to the security-constrained economic dispatch (SCED) used in the power industry today, the RB-SCED finds more secure and economic operating conditions. It does this by obtaining solutions that achieve a better balance between post-contingency flows on individual branches and the overall system risk. The method exploits the fact that, in a SCED solution, some post-contingency branch flows which exceed their limits impose little risk while other post-contingency branch flows which are within their limits impose significant risk. The RB-SCED softens constraints for the former and hardens constraints for the latter, thus achieving simultaneous improvement in both security and economy. In this work, the basic concept and the mathematical formulation of the RB-SCED model are systematically described. Experimental results on a 9-bus system and the ISO New England actual system have demonstrated the advantages of RB-SCED over SCED.

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Risk-based security-constrained economic dispatch in power systems

Enhanced look-ahead load margin estimation for voltage security assessment

Voltage stability has become a challenging problem for many power systems. Contingency screening and ranking (CS&R) is one of the important components of on-line voltage stability assessment. The objective of CS&R is to quickly and accurately select a short list of critical contingencies from a large list of potential contingencies and rank them according to their severity. Suitable preventive control actions can be implemented considering contingencies that are likely to affect the power system performance. An effective method for contingency ranking is proposed in this paper. This method calculates the voltage stability margin considering branch outages. Test results based on the IEEE 300 bus power system, a 600 bus power system as well as two utility systems (197 bus and 1254 bus) are presented.

B. Jeyasurya

Papers

Contingency ranking for on-line voltage stability assessment