Coordination of directional overcurrent relays in a multiloop subtransmission or distribution network is formulated as an optimization problem. In this paper, the coordination of directional overcurrent relays is formulated as a mixed-integer nonlinear programming problem and is then solved by a new seeker optimization technique. Based on the act of human searching, in the proposed seeker technique, the search direction and step length are determined in an adaptive way. The proposed method is implemented in three different test cases. The results are compared with previously proposed analytic and evolutionary approaches.

This paper presents a decision tree based method for out-of-step prediction of synchronous generators. For distinguishing between stable and out-of-step conditions, a series of measurements are taken under various fault scenarios including operational and topological disturbances. The data of input features and output target classes are used as the input-output pairs for decision tree induction and deduction. The merit of decision tree based detection of transient instability lies in robust classification of new unseen samples. The performance of the proposed method is verified on two test cases including a 9-bus dynamic network and the practical 1696-bus Iran national grid. The simulation results are presented for various input features and learning parameters.

The activation of under frequency load shedding (UFLS) is the last automated action against the severe frequency drops in order to rebalance the system. In this paper, the setting parameters of a multistage load shedding plan are obtained and optimized using a discretized model of dynamic system frequency response. The uncertainties of system parameters including inertia time constant, load damping, and generation deficiency are taken into account. The proposed UFLS model is formulated as a mixed-integer linear programming optimization problem to minimize the expected amount of load shedding. The activation of rate-of-change-of-frequency relays as the anti-islanding protection of distributed generators is considered. The Monte Carlo simulation method is utilized for modeling the uncertainties of system parameters. The results of probabilistic UFLS are then utilized to design four different UFLS strategies. The proposed dynamic UFLS plans are simulated over the IEEE 39-bus and the large-scale practical Iranian national grid.

In this paper, a dynamic (i.e. multi-year) hybrid model is presented for Transmission Expansion Planning (TEP) utilizing the High Voltage Alternating Current (HVAC) and multiterminal Voltage Sourced Converter (VSC)-based High Voltage Direct Current (HVDC) alternatives. In addition to new HVAC and HVDC lines, the possibility of converting existing HVAC transmission lines to HVDC lines is considered in the proposed model. High shares of renewable resources are integrated into the proposed hybrid AC/DC TEP model. Due to the intermittency of renewable resources, the planning of large-scale Energy Storage (ES) devices is considered. In order to accurately estimate the total TEP costs and hence capturing the scenarios of load and renewable generation uncertainty, using a clustering approach, each year of the planning horizon is replaced with four representative days. The proposed model is formulated as a Mixed-Integer Linear Programming (MILP) problem. Using Benders Decomposition (BD) algorithm, the proposed model is decomposed into a Master investment problem to handle the decision variables, and Sub-problems to check the feasibility of master problem solution and optimize the operation and ES investment cost. Three test systems are used as case studies to demonstrate the effectiveness of the proposed hybrid AC/DC TEP model.