An Information-Theoretic Approach to PMU Placement in Electric Power Systems
نویسندگان
چکیده
منابع مشابه
A Unifying Framework for the Electrical Structure-Based Approach to PMU Placement in Electric Power Systems
The electrical structure of the power grid is utilized to address the phasor measurement unit (PMU) placement problem. First, we derive the connectivity matrix of the network using the resistance distance metric and employ it in the linear program formulation to obtain the optimal number of PMUs, for complete network observability without zero injection measurements. This approach was developed...
متن کاملElectrical Structure-Based PMU Placement in Electric Power Systems
Recent work on complex networks compared the topological and electrical structures of the power grid, taking into account the underlying physical laws that govern the electrical connectivity between various components in the network. A distance metric, namely, resistance distance was introduced to provide a more comprehensive description of interconnections in power systems compared with the to...
متن کاملAn Electrical Structure-Based Approach to PMU Placement in the Electric Power Grid
The phasor measurement unit (PMU) placement problem is revisited by taking into account a stronger characterization of the electrical connectedness between various buses in the grid. To facilitate this study, the placement problem is approached from the perspective of the electrical structure which, unlike previous work on PMU placement, accounts for the sensitivity between power injections and...
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Placement of phasor measurement units (PMUs) in power systems has often been formulated for achieving total network observability. In practice, however, the installation process is not implemented at once, but at several stages, because the number of available PMUs at each time period is restricted due to financial problems. This paper presents a novel integer linear programming framework for o...
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In this paper, optimal placement of Phasor Measurement Unit (PMU) using Global Positioning System (GPS) is discussed. Ant Colony Optimization (ACO), Simulated Annealing (SA), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) are used for this problem. Pheromone evaporation coefficient and the probability of moving from state x to state y by ant are introduced into the ACO. The modifi...
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ژورنال
عنوان ژورنال: IEEE Transactions on Smart Grid
سال: 2013
ISSN: 1949-3053,1949-3061
DOI: 10.1109/tsg.2012.2228242