The reconfiguration of distribution networks is an important combinatorial problem. This work addresses the particular case of reconfiguration after an outage caused by the loss of a single branch of the network. The reconfiguration is carried out over two domains simultaneously: re-switching strategies and transformer tap-changer adjustments. The approach was tested using a real large-scale network within the concession area of Energy Australia. The model considers four operational elements: an AC power flow model, the network's radial topology when operating, voltage limits and load limits. Two evolutionary algorithms were implemented and tested. The first was a genetic algorithm, applied over the space of possible re-switching strategies, and for both re-switching and tap-changer adjustments, simultaneously. The second was a memetic algorithm, applied over the same two variations of the reconfiguration problem. Computational tests consider the evaluation of the loss of every branch, reporting the number of buses affected, and the number of overloaded branches after the reconfiguration.
N-1) contingency planning has been object of study and branches. Distribution networks in Energy Australia's conin the area of distribution networks for several decades. Energy cession area operate a radial topology. Such radial networks, as distribution companies have to reconnect areas affected by the name says, have no cycles and each load is served by only an outage within a very short time, and observe operational one feeder. When designing a distribution network, though, constraints, to avoid the possibility of severe financial penalties by regulatory bodies. Distribution networks are often operated companies create robustness by adding excess connectivity, with a radial topology, but, ideally, should have more than one allowing power to follow different paths to reach the same route to deliver energy to any node of the network. Switches in customer, if needed. Together with the excess connectivity, the network are opened to create the radial topology used in switches are positioned in strategic points of the network and normal operation, and, in the case of an outage, alternate routes can be set either as closed or opened. Specific switching conare activated by opening or closing switches located at specific points of the network. Given an outage situation (in our case figurations will create the radial topology of the power flow, represented by the disconnection of a single branch), the choice assigning each load to a generator or feeder. Redundancy in of which switches should change their state is a combinatorial the distribution network is particularly critical in situations of optimisation problem, with a search space of 2 k , where k is the (n-1) contingency, in which a cable becomes faulty, affecting number of switches. Because of the exponential complexity, exact the supply for all customers located after it. In this case, an methods are prohibitively time-consuming. This work presents a genetic algorithm that provides a rapid answer to network alternate path to supply power to the affected area can be managers in terms of a switching strategy to reconnect the activated by a series of switching states changes. affected area. The method takes into account the radial topology The problem of finding alternate routes for the power of the power flow and the operational limits of voltage and cable supply, given an outage scenario, is very complex and has been load. Computational tests were conducted on a real network with studied for several decades. Alternate routes are determined 96 buses and 16 switches, located within the operational area of Energy Australia. This paper describes the genetic algorithm in by searching the solution space of switches states. That is, detail, presents thorough computational tests, and a complete if there are k switches present in the network, the search contingency plan for the test network.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.