This paper presents a heuristic reconfiguration algorithm, considering the locational economic signals of the tariffs for the use of the transmission system. Among other aspects, the economic signaling of locational tariffs encourages the rationalization of the use of transmission assets, as well as the reduction of operating costs. Therefore, the proposed algorithm is presented as an optimization problem with a focus on minimizing the transmission system usage. In order to validate the efficiency of the proposed reconfiguration algorithm, the IEEE 33 and 69 nodes test systems are evaluated. In addition, the algorithm is tested for different transmission cost allocation techniques and transmission system capacity scenarios. The results achieved demonstrate the systemic rationalization of the use of assets, which characterize the proposed algorithm as an important tool to avoid the increase in the share of energy transport in the tariff for the final consumer.

The electric power system is a complicated dynamic system with a range of operating states and parametric uncertainties, especially due to change of the network topology, load increment and generation scheduling. Under this circumstance, traditional power system transient stability analysis methods may not always be appropriate. This paper presents the development of a computational methodology for evaluating the effect of parametric uncertainties on the small-signal stability analysis of power systems. A probabilistic approach is applied as a metric for the dynamic performance of the damping ratio of critical eigenvalues. The method is based on a Monte Carlo simulation for the analysis of automatic control of generation. The methodology is used for the performance evaluation of three classical controller tuning techniques: Frequency Response, Approximate Method and Ziegler-Nichols. The results show that the methodology is valid and potentially useful for quantifying the effect of parametric uncertainties in power systems dynamics simulations.

This paper presents a GRASP (Greedy Randomized Adaptive Search Procedure) algorithm applied to resolution of expansion planning of electric power distribution systems (EPDS) under the paradigm of Price Cap regulation. The design of the expansion planning problem considering the tariff methodology becomes an important and challenging problem to be solved. In this sense, this paper presents the results of development of a methodology that considers the variables of Price Cap model along with the classic problem of expansion of electric power distribution systems. The proposed model is a problem of mixed integer nonlinear programming (MINLP), which is solved by employing the metaheuristic GRASP combined with a Constructive Heuristic Algorithm (CHA). Results of two distribution systems are demonstrated in order to analyze the algorithm development.