The recent addition of information and communication technologies in electric power distribution systems has introduced a new class of electricity theft or nontechnical loss. Energy consumption data can be hidden and altered through cyber-attacks that are characterized by the unauthorized access to the application database and digital tampering of smart meters. The development of cost-efficient algorithms to address these types of nontechnical losses also targets the reduction of commercial losses because the full protection of an information system is very expensive. Thus, this paper proposes a strategy to detect nontechnical losses using a multivariate control chart that establishes a reliable region for monitoring the measured variance. After the detection of nontechnical losses, a pathfinding procedure based on the A-Star algorithm is able to locate the consumption point with the non-technical loss. Moreover, a geographical information system application displays the consumption point that is the target of the cyber-attack. The numerical results demonstrate the selectivity and efficiency of the proposed methodology applied for monitoring a real distribution network.

The increase in information and communication technologies in the electric power system has led the distribution network to a new evolutionary stage known as a smart grid. In this scenario, automatic local switching plans based on an understanding of the network topology and load behavior allow the implementation of self-healing strategies. Self-healing aims at the minimization of the number of switching operations within the shortest time interval to restore the maximum load affected by a fault and to preserve distribution network operation limits. In this paper, multiagent system concepts are employed to develop a self-healing strategy, where all switching local agents have some awareness regarding the current network state and work cooperatively to reach the global purpose of distribution network automatic restoration.

Since the origin of energy management systems, state estimation applications have aided in automatic power system operations, mainly for transmission systems. Currently, however, smart grid concepts are modifying the behavior of distribution systems through a rapid increase of controllable distributed generators, demand response, and electric vehicles. Consequently, the advanced metering infrastructure is providing a large amount of synchronized metering data with high accuracy and resolution, which favors the development of state estimation procedures to sustain distribution management systems. Therefore, this paper presents the formulation of a novel algorithm for state estimation solution in distribution networks using the Hamiltonian cycle theory, where the network states are quickly obtained through a calculation scheme under the normal operating conditions. Index Terms-Advanced metering infrastructure (AMI), automatic operations, distribution management system (DMS), Hamiltonian cycle, smart grid, state estimation. 1949-3053

Protection of transmission lines is essential to ensure a correct operation of power systems. In this paper a pilot protection scheme, known as permissive overreaching transfer trip, is used. This structure combine two different protection relays: directional overcurrent relay, a backup protection for phase-earth faults, and distance relay for phase-phase faults. An intelligent method was developed to the optimal coordination of protection relays in meshed networks like transmission networks. The proposed method employs the genetic algorithm as optimization procedure that considers network characteristics (maximum load current and minimum fault current) and adjustment parameters of overcurrent and distance relays. Two testing networks, one of 8-bus and other of 39-bus, were used to evaluate the proposed method that obtained feasible and good solutions for the coordination problem.

No abstract

Since the origin of energy management systems, state estimation applications have aided in automatic power system operations, mainly for transmission systems. Currently, however, smart grid concepts are modifying the behavior of distribution systems through a rapid increase of controllable distributed generators, demand response, and electric vehicles. Consequently, the advanced metering infrastructure is providing a large amount of synchronized metering data with high accuracy and resolution, which favors the development of state estimation procedures to sustain distribution management systems. Therefore, this paper presents the formulation of a novel algorithm for state estimation solution in distribution networks using the Hamiltonian cycle theory, where the network states are quickly obtained through a calculation scheme under the normal operating conditions.

No abstract

No abstract