Optimizing Radial Distribution System for Minimizing Loss Reduction and Voltage Deviation Indices Using Modified Grey Wolf’s Algorithm

In the present days, power systems are operated favourably close to their stability limit. System stability can be safeguarded by employing an emergency control technique, known as load shedding; this technique is affected by shedding some loads. Such a technique implemented only when the voltage or frequency deterioration below a specific voltage or frequency threshold. In this work, an advanced emergency load shedding model is forwarded based on the voltage stability indicator aimed at enhancing voltage. This indicator facilitates online monitoring of voltage stability and predicts the voltage problem of the system with sufficient accuracy, fast and simple numerical calculation, also can work well in the steady-state as well as during the transient process. The proposed model and algorithm have been tested firstly on the IEEE 14 bus system as a standard system and then implemented on the Iraqi National Power Grid (INPG) as a particular reference system. The obtained results for the voltage profile has recovered by 11.1% for the standard system and 2.03% for the particular system.

“…By using load flow results, acquired for given system loading conditions, the voltage stability indicator (L-index) at bus j is computed using Eq. (5) [13,15]:…”

Section: ) the Relation Between Voltage Stability Indicator And Statementioning

confidence: 99%

“…22 21 (15) Commonly, a relation between real and imaginary power at load bus j can be written as below:…”

Section: C) the Relation Between Voltage Stability Indicator And Loadmentioning

confidence: 99%

Emergency Load Shedding for Voltage Stability Enhancement: With Particular Reference to the Iraqi National Power Grid

Al-Rubayi¹,

Kdair²

2020

“…14 network reconfiguration with the addition of a distributed generator [8,9]. The enhance water cycle algorithm and grey wolf's algorithm are proposed by [10,11] for power system distribution. [10,11] focuses on enhancing the voltage stability index and minimizing the system power losses.…”

Section: Introductionmentioning

confidence: 99%

Optimal Sizing of Supercapacitor Energy Storage Based on Firefly Algorithm for Enhancing Critical Clearing Time

Sari¹,

Sari²,

Sulistyo³

et al. 2021

In the present day, the electrical power demand is increasing and expected to continue growing. The renewable energy sources as the power supply are also increasing but not much as needed. As a result, the power systems operate close to their maximum stability limit. This paper proposed to extend the value of Critical Clearing Time (CCT) to enhance the stability system, especially the transient stability. A Supercapacitor Energy Storage (SCES) is installed at one of the generator bus; however, the sizing of SCES must be optimized due to the economics and power balance constraint. In this paper, the Firefly Algorithm (FA) is used to obtain the optimal sizing of SCES with the objective function is the highest value of CCT. Lagrange interpolation is used to validate the effectiveness of FA, such as computation time and accuracy. According to the simulation result obtained, the proposed method using FA has a faster calculation time than Lagrange interpolation. Moreover, the proposed method is validated on a modified IEEE 9 bus with various cases. By using FA, the best increase of CCT is obtained when the optimal size of SCES is 0.120 p.u. The overall CCT increase is 0.15766s or around 54.61%.

“…These researchers have believed that other methods such as capacitor placement and cable size upgrading might add more additional cost burdens to the distribution system utilities. In [4][5][6][7], the system losses and voltage profile are improved by formulating the network reconfiguration problem as a mixed-integer nonlinear optimization problem using various metaheuristic algorithms with considering operational constraints. Due to the rapid growth of the integration of the distributed generations (DGs) into the distribution system, the use of the network reconfiguration technique without considering the presence of the DGs is no longer applicable.…”

Section: Introductionmentioning

confidence: 99%

Optimal Network Reconfiguration and DG Integration in Power Distribution Systems Using Enhanced Water Cycle Algorithm

Ibrahim¹,

Alwash²,

Ahmed³

2020

This paper presents an Enhanced Water Cycle Algorithm (EWCA) to optimize the network reconfiguration and distributed generation (DG) integration simultaneously for minimizing system power losses and improving voltage stability index (VSI) in the distribution system while considering all operational constraints. For validation, the performance of the proposed method is compared with other methods, which utilized well-known meta-heuristic algorithms. Different cases for network reconfiguration and DG integration are carried out in order to evaluate the performance of the proposed method. The effectiveness of the proposed method is assessed using the IEEE 69-node radial distribution system. According to the simulation results obtained, the proposed method in which the simultaneous optimal network reconfiguration and the DG size and location are implemented can provide a remarkable solution in terms of power loss reduction and voltage profile improvement. The proposed method also proved its superiority compared with other existing methods in terms of power loss reduction (i.e., 84.2% loss reduction compared with the base case).