An Improved Inverse-Time Over-Current Protection Method for a Microgrid with Optimized Acceleration and Coordination

Abstract

This paper presents an improved inverse-time over-current protection method based on the compound fault acceleration factor and the beetle antennae search (BAS) optimization method for a microgrid. The proposed method can not only significantly increase the operation speed of the inverse-time over-current protection but also improve the protection coordination by considering the possible influential factors in terms of microgrid operation modes, distributed generation (DG) integration status, fault types, and positions, which are marked as the most challenging problems for over-current protection of a microgrid. In this paper, a new Time Dial Setting (TDS) of inverse-time protection is developed by applying a compound fault acceleration factor, which can notably accelerate the speed of protection by using low-voltage and short-circuit impedance during the fault. In order to improve the protection coordination, the BAS algorithm is then used to optimize the protection parameters of the pick-up current, TDS, and the inverse time curve shape coefficient. Finally, case studies and various evaluations based on DIgSILENT/Power Factory are carried out to illustrate the effectiveness of the proposed method.

Optimal setting of DOC relay in distribution system in presence of D-FACTS

“…The algorithm maintains diversity and converges steadily until it reaches a fitness value that is within 7%. 0.5200 0.5000 0.9700 0.1800 0.6300 TDS 2 1.2400 1.3400 1.6000 0.3400 0.5000 TDS 3 1.0600 0.0900 1.4400 1.1600 0.3800 TDS 4 0.9200 0.1400 1.1400 1.1800 0.5500 TDS 5 1.1300 0.8200 1.4600 0.4700 0.5200 TDS 6 1.1500 0.1000 1.0100 0.8200 0.3700 TDS 7 1.1200 0.5200 1.3800 1.0000 0.4700 TDS 8 1.0800 0.1400 1.2000 0.5800 0.1800 TDS 9 1.0800 1.1100 1.5000 0.8100 0.1700 TDS 10 1.0600 1.0900 1.0000 1.0100 0.5300 TDS 11 1.0300 0.1800 1.3100 1.0800 0.5400 TDS 12 1.2000 0.0900 1.1900 0.8600 0.1100 TDS 13 1.1100 0.1000 1.0700 0.5400 0.1900 TDS 14 1.0400 0.1400 0.9800 1.2000 0.2300 TDS 15 1.1300 0.3000 1.0800 0.4600 0.1200 TDS 16 1.1800 0.1900 1.0700 0.4100 0.3700 TDS 17 1.0500 0.1800 1.2800 0.8500 0.1100 TDS 18 1.1600 0.1700 1.4100 0.7300 0.3500 TDS 19 0.9700 0.6400 1.2500 1.1200 0.1200 TDS 20 1.2400 0.1900 1.2900 0.8400 0.1300 TDS 21 1.1800 0.2100 1.0400 0.3100 0.4700 TDS 22 1.1000 0.1000 1.1600 1.0100 0.2000 TDS 23 1.1400 0.3700 1.5700 0.4500 0.4000 TDS 24 1.1300 0.6800 1.3700 1.1200 0.3000 TDS 25 0.7200 0.1900 1.1500 0.5200 0.4700 TDS 26 1.0300 0.1900 1.1300 1.1400 0.3000 TDS 27 1.0900 0.1900 1.1000 0.7800 0.1100 TDS 28 1.1100 0.1700 1.3500 1.1400 0.4400 TDS 29 1.1300 1.0800 1.0200 1.0000 0.5000 TDS 30 1.1600 0.4200…”

“…The IP is the minimum current value for which the relay operates and the TDS defines the tripping time [11], [12]. In (1), the standard mathematical formula for modeling the operating time of relays according to IEC 60255 [13]:…”

Protection of Future Electricity Systems

“…This issue is no exception. You will find some fine examples of unconventional thinking and innovation in most of the presented papers (e.g., [3,5,7,8], to highlight a few).…”

An Improved Beetle Antennae Search Algorithm Based on the Elite Selection Mechanism and the Neighbor Mobility Strategy for Global Optimization Problems

“…In addition, its program code is simple and can quickly obtain the optimal solution under the condition of a stable convergence [20][21][22][23]. At present, it has been successfully applied to a variety of industrial engineering optimization problems, and has a high potential research value [24][25][26][27][28][29]. Ameer Tamoor Khan et al proposed the quantum beetle antennae search algorithm and applied it in the constrain portfolio problem [30].…”