No abstract

No abstract

This paper proposes an algorithm for distribution state estimation with included unmonitored (or partially monitored) photovoltaic generation and wind turbine&asynchronous generator based models, as well as distributed loads. These data are treated as pseudo measurements and included in the state estimation with lower weights. Initial state estimations for unmonitored (partially monitored) distributed generation and loads are calculated from the weather forecast data or daily load profiles, respectively. The pseudo measurements are additionally re-adjusted by the optimal load/generation reallocation procedure to fit the real-time measurements inside the weighted least square (WLS) based state estimation algorithm. The results and practical aspects of the proposed methodology are demonstrated on characteristic real-life urban distribution network with 40 buses.

Summary This paper proposes a novel method for determining optimal arrangements of overhead double‐circuit power line conductors aimed to reduce electric and magnetic field emissions. Extremely low frequency electric and magnetic field optimization problems have multiple objectives. Multiple‐objective optimization allows the simultaneous optimization of two or more conflicting objectives and determination of mutually non‐dominated solutions. The multi‐objective optimization technique used in this paper is based on Genetic Algorithm to obtain a set of mutually non‐dominated solutions (Pareto optimal set) for the two objectives: the electric and magnetic field strengths near overhead double‐circuit power line. Also, additional assessment criteria were defined for the selection of several decision scenarios from the Pareto optimal set. The results and practical aspects of the proposed methodology are demonstrated on two typical 400‐kV double‐circuit overhead power lines. The efficiency of the proposed multiple‐objective optimization method is compared with the existing one based on single‐objective optimization function. Copyright © 2016 John Wiley & Sons, Ltd.

No abstract