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We present a novel algorithm for distributed state estimation in power systems, based on graph theory and exchange of information between nodal entities in combination with local nonJacobian based modeling. The bus-based power balance equations are used to generate a successively better estimate based on locally available data only, which is then sent out to adjacent graph vertices, so that information travels even to parts of the network that have fewer data collected. For this reason, full power system observability is not required, and this procedure could be applied even if parts of the system lack needed measurements. To demonstrate the effectiveness and scalability ofthe proposed algorithm, it is applied to both 14-bus and 300-bus test systems. 

This paper considers achieving flat voltage profiles in a distribution network based on reactive power optimization (RPO) through voltage regulation devices (VRD). These devices include capacitor banks, load-tap-changing and regulating transformers, whose statuses can only assume pre-determined integer value levels, making this a non-convex problem. Two RPO-based algorithms are proposed, which can be applied to any initial states, node priority, topology and load model types. The first algorithm focuses on finding a practical solution by ensuring the VRD constraints are observed at each step. The second one focuses on finding the globally optimal solution by applying a convex relaxation technique and solving the resulting problem with the barrier interior point method. Here, the gradients are computed numerically, thus requiring no analytical functions of voltages in terms of VRDs. Numerical results and their analysis are examined on two test networks: 1) single feeder; and 2) network with laterals. 

This paper explores power system network observability while taking into account realistic communication network behavior. The overall information is obtained by combining SCADA- and phasor measurement unit-derived data, where time stamping (based on Global Positioning System or an equivalent local clock) for all measurements is assumed. Based on simulations performed in communication Network Simulator 2, empirical cumulative distribution functions can be associated with transfer times of measurement packets, which will reflect communication parameters and irregularities. This is further used to form an algorithm which maximizes the number of successful network observability checks, and thus the number of possible state estimations, in a certain time period. Application is demonstrated on the IEEE 14-bus test power system example. 

The paper explores the effects of sensor behavior and communication system (CS) irregularities on power system state estimation (SE). CS are modeled in Network Simulator 2 (NS-2), allowing the quantification of irregularities, including delays and dropped packets. The overall information is obtained combining SCADA measurements with phasor measurement unit (PMU) derived data, where time stamping (based on GPS or an equivalent local clock) for all measurements is assumed. To fully analyze the effects of irregularities, a detailed analysis of sensitivities to different communication system parameters is provided as well. Using the co-simulation environment PiccSIM, a SE with these irregularities is quantified for CS parameter variation, with detailed models of power and communication flows.