5,817 research outputs found

    AC OPF in Radial Distribution Networks - Parts I,II

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    The optimal power-flow problem (OPF) has played a key role in the planning and operation of power systems. Due to the non-linear nature of the AC power-flow equations, the OPF problem is known to be non-convex, therefore hard to solve. Most proposed methods for solving the OPF rely on approximations that render the problem convex, but that may yield inexact solutions. Recently, Farivar and Low proposed a method that is claimed to be exact for radial distribution systems, despite no apparent approximations. In our work, we show that it is, in fact, not exact. On one hand, there is a misinterpretation of the physical network model related to the ampacity constraint of the lines' current flows. On the other hand, the proof of the exactness of the proposed relaxation requires unrealistic assumptions related to the unboundedness of specific control variables. We also show that the extension of this approach to account for exact line models might provide physically infeasible solutions. Recently, several contributions have proposed OPF algorithms that rely on the use of the alternating-direction method of multipliers (ADMM). However, as we show in this work, there are cases for which the ADMM-based solution of the non-relaxed OPF problem fails to converge. To overcome the aforementioned limitations, we propose an algorithm for the solution of a non-approximated, non-convex OPF problem in radial distribution systems that is based on the method of multipliers, and on a primal decomposition of the OPF. This work is divided in two parts. In Part I, we specifically discuss the limitations of BFM and ADMM to solve the OPF problem. In Part II, we provide a centralized version and a distributed asynchronous version of the proposed OPF algorithm and we evaluate its performances using both small-scale electrical networks, as well as a modified IEEE 13-node test feeder

    External Network Modeling for MVAr Scheduling in Multi Area Power Systems

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    International audienceMulti area power systems work most often with a poor inter-regional coordination about reactive power concerns. Transmission system operators typically do not possess a detailed knowledge about voltage profile across interconnected power systems. In this context, reactive power scheduling may be inefficient and inter-regional reactive power flows become a decisive issue. This inefficiency, associated with economic constraints and increasing stress on interconnection lines, may lead to conflicts, which could be partially avoided with a better scheduling strategy. In addition to inter-utility agreements, part of the solution could be to use appropriate external network modeling. Different modeling are thus presented in this paper and illustrated with an IEEE 118 bus system with 2 separately controlled regions, whose scheduling objective is to minimize active power losses. The regional scheduling process is described and the state of the interconnected power system is compared with a global optimization. Finally, the influence of the external network modeling parameters and the accuracy of their forecast is commented

    Energy Optimization for Distributed Energy Resources Scheduling with Enhancements in Voltage Stability Margin

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    The need for developing new methodologies in order to improve power system stability has increased due to the recent growth of distributed energy resources. In this paper, the inclusion of a voltage stability index in distributed energy resources scheduling is proposed. Two techniques were used to evaluate the resultingmultiobjective optimization problem: the sum-weighted Pareto front and an adapted goal programmingmethodology.With this newmethodology, the systemoperators can consider both the costs and voltage stability. Priority can be assigned to one objective function according to the operating scenario. Additionally, it is possible to evaluate the impact of the distributed generation and the electric vehicles in the management of voltage stability in the future electric networks.One detailed case study considering a distribution network with high penetration of distributed energy resources is presented to analyse the proposed methodology. Additionally, the methodology is tested in a real distribution network.info:eu-repo/semantics/publishedVersio

    Application of the Multiverse Optimization Method to Solve the Optimal Power Flow Problem in Alternating Current Networks

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    In this paper, we solve the optimal power flow problem in alternating current networks to reduce power losses. For that purpose, we propose a master–slave methodology that combines the multiverse optimization algorithm (master stage) and the power flow method for alternating current networks based on successive approximation (slave stage). The master stage determines the level of active power to be injected by each distributed generator in the network, and the slave stage evaluates the impact of the proposed solution on each distributed generator in terms of the objective function and the constraints. For the simulations, we used the 10-, 33-, and 69-node radial test systems and the 10-node mesh test system with three levels of distributed generation penetration: 20%, 40%, and 60% of the power provided by the slack generator in a scenario without DGs. In order to validate the robustness and convergence of the proposed optimization algorithm, we compared it with four other optimization methods that have been reported in the specialized literature to solve the problem addressed here: Particle Swarm Optimization, the Continuous Genetic Algorithm, the Black Hole Optimization algorithm, and the Ant Lion Optimization algorithm. The results obtained demonstrate that the proposed master–slave methodology can find the best solution (in terms of power loss reduction, repeatability, and technical conditions) for networks of any size while offering excellent performance in terms of computation time
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