Multi-objective feeder reconfiguration by distribution management system

Abstract

system is determined as stage, this solution is by numerical examples. tial benefits since the The problem of optimal feeder rec problem concerned urban distribution occurs on both se infrasmcture stems each distribulocated at the transserved. The problem Id be opened by two urban and rural distribution systems. is mostly underground cable systems works but operated as radial feeders. open/closed status of sectionali former site determines how the as that of finding Utah, May 7-12. 1995.ing switches is not as many as that for urban networks, but the number has increased continuously over the past many years for the purpose of improving reliability.The subject of distribution feeder reconfiguration has been investigated by numerous researchers over the past several years. In the early studies [ 1,2] involving urban distribution systems, a desirable radial distribution system solution is determined from a mesh network in which all normally-open switches are simulated to be closed. Based on a power flow solution to this distribution system of mesh network structwe, switches to be o p e d are then identified. This idea based on a closed-loop power flow solution has been extended and used in later work [6]. Such solution procedures find a final feeder configuration which is independent of the initial status of switches.Simple and efficient branch exchange algorithms were proposed in [3,4]. In [4] a simple formula is presented to estimate the change in feeder losses resulting from feeder reconfiguration. This formula can be used as a criterion to determine how to improve intermediate solutions.[5] shows a heuristic branch exchange scheme designed for handling urban distribution networks. More papers on optimal feeder reconfiguration were published in recent years [7-141. Some of them extexukd early ideas, or tried to find a compromise between fundamental approaches. For instance in [SI, a single loop is optimized in every step of the algorithm within its solution process. Expert systems and artificial intelligence approaches along with heuristic algorithms were employed in [9-141 for the feeder reconfiguration problem. Further developments are needed in order for these algorithms to be practical forimplementation. An interesting trend can be observed from the abovementioned papers as to the 0bjectiV.e functions and constraints used in their problem formulations. While the papers [1,2.4] used power loss reduction as the only objective function, the goal of load balancing was noted in [3.5] and [9]. Either power loss reduction or load balancing was dealt with in [7]. As far as constraints are concerned, voltage drop constraints are accounted for in [13] and protective device coordination is modeled in [lo]. The Aim of the Paper As noted above, solution approaches proposed in all previous papers were designed to deal with feeder reconfiguration from the standpoint of mostly feeder loss reduction and load balancing. However, individual utilities may pursue different goals because of differences in the characteristics of ...

Optimal Feeder Reconfiguration Optimization problem in Power Distribution Networks

“…To ensure radial topology in which every load is connected to a single substation, one of the neighboring currently closed sectionalizing switches needs to open (say S3), and loads on bus N2 will be transferred from Feeder1 to Feeder2. This two-step operation is known as branch exchange method [27]. New status of switch pair S2-S3 changes the network topology and new power flow calculations are needed to calculate objective function for changed network configuration.In case of more than one tie switch, same procedure needs to be repeated forall other initially open switches to ensure that the optimal solution is found.…”

Smart grids investigation and analysis in terms of cost benefits

“…• Minimization of power losses: DMS network operation implemented in the Optimal Network Reconfiguration may provide minimization of power losses [3][4][5]. Besides, improve voltage quality DMS Volt/Var and reduce losses as well [6][7][8], as well as Energy Audit implies tracing and reducing non-technical losses.…”

Fault Locating, Prediction and Protection (FLPPS)

“…A.3.5.1.12 Multi-objective feeder reconfiguration by distribution manager system [76] Summary: This paper proposes a two-stage method for load reconfiguration with a multiple objective function. The multi objectives considered are minimization of power loss, balancing of transformer load, minimization of worst voltage drop, minimization of service interruption, and balancing of service for important customers.…”