برنامه ریزی هماهنگی رله اضافه جریان جهت دار (Overcurrent) جهت سیستم توزیع DG

ABSTRACT Planning the Coordination of Directional Overcurrent Relays for Distribution Systems Considering DG

CONVENTIONAL unidirectional power flow between utility and consumer is no longer valid due to distributed generation (DG) interconnection. Furthermore, the direction of the fault current is also influenced by the introduction of DG to the system, which consequently affects the performance of protection devices. The protection system should isolate the minimum number of elements in a system in order to ensure secure operation of the unaffected part. In all types of distribution systems, for each fault location there exists a primary relay, which should operate as fast as possible, coordinated with a back-up relay. Traditionally radial systems are protected by overcurrent relays (OCRs) and fuses, however, meshed distribution systems are protected using directional OCRs (DOCRs). Installation of the DG units influences both the level and direction of short circuit currents, which may lead to nonselective protection actions. Consequently, the relay settings have to be frequently revised to accommodate for sequential increase in DG penetration.

Different optimization techniques can be employed to determine the settings of the relays. Several formulations have been proposed in order to solve the protection coordination problem. In [1] and [2], the problem is formulated as a linear programming (LP) problem with pick-up current settings defined as the parameters. On the contrary, in [3], the protection coordination problem is formulated as a nonlinear programming (NLP) problem with both relay settings being the decision variables of the problem. Additionally, in [4], a mixed integer NLP approach is presented. Finally, with respect to the formulation, deterministic or heuristic optimization techniques can be utilized to solve the protection coordination problem. According to the presented formulations those techniques include, two-phase simplex [5], sequential quadratic problem [3], genetic algorithm [6]–[7], particle swarm optimization [8], and evolutionary algorithm [9].

Majority of the work presented in the literature optimizes the relay settings assuming that the DG capacity is known [10]–[13]. One major problem is that the optimized relay settings in such case will only be valid for those specific DG capacities. In other words, any new DG addition will require an update to the existing relay settings [14], [15]. The studies proposed in [7], [12], [14], and [15] consider a predefined DG capacity and thus any changes in the DG capacity will require modifications in the existing relay settings. With the current interest in smart grids, it is expected that there will be more frequent interconnection of DGs, which in such case will result in numerous changes in relay settings. In order to plan smart grids, taking into account future possible DGs, a different approach to the protection coordination problem needs to be developed that can plan the relay settings such that the number of changes in a protection system is minimized. This paper proposes a novel method to determine the optimal settings of the DOCRs that are feasible for all possible future DG capacities. Consequently, it provides to the utility planners one set of relay settings valid for different capacities of DG units varying between zero and the maximal desired capacity. The protection coordination problem is formulated as a LP problem and is solved using the simplex algorithm.

A comparative analysis is conducted to highlight the number of changes in protection system required to accommodate for changes of DG capacities if the settings are not well planned. The simulations are conducted on the distribution part of the modified IEEE 14-bus system and the IEEE 13-bus radial distribution system. The structure of this paper can be described as follows. First, the formulation of the optimization problem is presented and described. The following section describes the test system under study and the optimization techniques used to solve the formulated problem. Thereafter, the results of the conducted simulations are presented. The penultimate section examines the influence of the fault current limiters (FCLs) on the obtained results. The conclusion is drawn in the last section.