An enhanced contingency-based model for joint energy and reserve markets operation by considering wind and energy storage systems

This paper presents a contingency-based stochastic security-constrained unit commitment to address the integration of wind power producers to the joint energy and reserve markets. The contingency ranking is a popular method for reducing the computation burden of the unit commitment problem, but performing the contingency analysis changes the high-impact events in previous ranking methods. This paper employs an intelligent contingency ranking technique to address the above issue and to find the actual top-ranked outages based on the final solution. Also, energy storage systems are considered to evaluate the impact of the scheduling of storage under uncertainties. Numerical results on a six-bus and the IEEE 118-bus test systems show the effectiveness of the proposed approach. Furthermore, it shows that utilizing both wind farms and storage devices will reduce the total operational cost of the system, while the intelligent contingency ranking analysis and enough reserves ensure the security of power supply.©2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.fi=vertaisarvioitu|en=peerReviewed

Toward a More Reliable System for Contingency Selection in Static Security Analysis of Electric Power Systems

The reliable supply of electricity plays a key role in the contemporary way of life. In order to provide more benefits to the population, electric networks are getting bigger to produce more energy. This growth, while necessary, brings problems in operation and maintenance, since the networks are more complex. This complexity requires that network security analysis should be performed in real time to avoid decision errors when disconnecting a device from the network or predicting the possibility of operating output from an undersized device. In this article, an intelligent system for contingency selection in the static security analysis of electric power systems is proposed. The severity of contingencies indication is the first step to develop control actions and maintain the system operation integrity. We propose and evaluate the contingency selection as a combinatorial optimization problem, employing an ACO metaheuristic to model the situation. The system is evaluated over the IEEE 30-bus network and a real 810-bus network, considering double outages of branches. Results show an accuracy close to five-nines for severing contingencies