Optimal allocation and control of fixed and switched capacitor banks on distribution systems using grasshopper optimisation algorithm with power loss sensitivity and rough set theory

Elsayed, Abdallah M.; Mishref, Mohammed M.; Farrag, Sobhy M.

doi:10.1049/iet-gtd.2018.5494

Cited by 34 publications

(20 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As mentioned above, a comparison between automated distribution systems using the proposed ITSA and the nonautomated system (Case 1) is introduced. Table 7 gives comparative results in terms of the total system losses, minimum and maximum voltage and different quality indices illustrated previously (24)(25)(26)(27)(28)(29). From the obtained results, it is found that the proposed technique successfully reduces the system daily power losses from 973.019 kW/day to 324.021 kW/day, which seems identical to the power losses obtained with hourly operation of the DNR, CBs and DGs (Case 2).…”

Section: ) 33-bus Test Systemsupporting

confidence: 60%

“…The proposed ITSA and classical TSA are applied, tested and compared on three standard test systems. The first test system is the 33-bus radial distribution system with 33-bus, 12.66-kV rated and total demand of 3.715 MW and 2.3 MVAr [26]. The second test system is the 69-bus power system with a total load of 3.802 MW and 2.694 MVAr [26].…”

Section: Resultsmentioning

confidence: 99%

“…The first test system is the 33-bus radial distribution system with 33-bus, 12.66-kV rated and total demand of 3.715 MW and 2.3 MVAr [26]. The second test system is the 69-bus power system with a total load of 3.802 MW and 2.694 MVAr [26]. The third system is the large-scale standard IEEE 11kV, 119-bus radial distribution system with 118 branches.…”

Section: Resultsmentioning

confidence: 99%

“…Also, the quality verification of introduced automation process is evaluated in terms of different numerical indices compared to the nonautomated system. Equations (24)(25)(26)(27)(28) formulate the suggested indices to be deemed for this case study.…”

Section: Optimal Dnr With Optimal Control Of the Cbs And Dgs At DImentioning

confidence: 99%

“…To optimize the utilization of CBs, DGs and DNR, new meta-heuristic techniques have been introduced in many literatures in the last two decades. Capacitors' allocations and control have been studied using a range of metaheuristic methods such as; plant growth algorithm [20]; evolutionary algorithm [21]; teaching learning optimization algorithm [22]; particle swarm optimization algorithm [23]; gravitational search algorithm [24]; ant-colony optimization algorithm [25]; grasshopper optimization algorithm [26]. Similarly, DGs got attention from researchers for optimal allocation.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Optimal Control and Operation of Fully Automated Distribution Networks Using Improved Tunicate Swarm Intelligent Algorithm

Fetouh

Elsayed

2020

IEEE Access

Self Cite

View full text Add to dashboard Cite

Simultaneous control and operation of Capacitor Banks (CBs) and Distributed Generators (DGs) with Distribution Network Reconfiguration (DNR) is the most important modern trend for distribution systems performance enhancement. The complexity and variety of the control variables of this problem represent a challenge for distribution systems planners and operators as well as interested researchers. Optimal solution can provides quantitative as well as qualitative power service to satisfy consumers' satisfaction and reduces dissipated energy. Furthermore, performance enhancement of distribution systems is very vital where improving their performance directly affects the performance of transmission and generation systems. For solving the considered problem, an improved Tunicate Swarm Algorithm (ITSA), which imitates the swarming behaviors of the marine tunicates and their jet propulsions during its navigation and foraging procedure, is proposed. In ITSA, Lévy flight distributions are emerged in the traditional Tunicate Swarm Algorithm (TSA), which improves the diversification searching abilities of the TSA and consequently avoids the stagnation possibilities. The proposed ITSA is applied and tested for optimal DNR simultaneously with optimal control of the switched CBs and dispatchable DGs taking into account daily load variations. The ITSA is compared with other techniques on the standard 33-bus, 69-bus and the large-scale 119-bus distribution systems considering different automation scenarios of the distribution systems. The simulation results reveal that significant enhancement in distribution system performance is obtained through the application of the proposed automation process using the ITSA. ITSA can efficiently search for the optimal solutions of the problem and outperforms the other existing algorithms in the literatures.

show abstract