The paper analyzes options of using smart meters for power flow calculation and for assessing the state of a real three-phase four-wire secondary distribution network based on measurements of average values of active and reactive power and of voltages. The work is based on the authors’ research on allocation of measurements to ensure secondary distribution network observability and on selection of the most efficient method for linear and non-linear state estimation. The paper illustrates solution of a problem on identification composition of load nodes in the phases and reveals challenges related to voltage account in the neutral wire and in its grounding.

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In order to control the electric power system operation it is important to know the sensitivity of random state variables to disturbances and the factors affecting the sensitivity of the variables to ensure feasible ranges of their changes. The stochastic problem of electric power system control is solved iteratively and is reduced to successively solving the equivalent deterministic problems, including determination of numerical characteristics of the variables by the methods of probabilistic load flow. To minimize the number of controls it is suggested to use the tracing method in each step of the deterministic equivalent method. The presented numerical results demonstrate the high performance of the suggested approach.

The paper proposes a new approach to the problem of state estimation of a low voltage distribution network by the measurements coming from smart meters. The problem of nonlinear state estimation based on the measurements of nodal powers and voltages is solved by the method of simple iteration which minimizes the quadratic function of the residues with and without the consideration of the constraint on the zero currents in the transit nodes. The same algorithms are proposed to use for linear state estimation based on the measurements of nodal currents and voltages. The effectiveness of the proposed methods for linear and nonlinear state estimation is illustrated on the 33 nodes three-phase four-wire low-voltage network.