Optimal Placement and Sizing of Shunt Capacitors in Radial Distribution System Using Polar Bear Optimization Algorithm

Saddique, Muhammad Waqar; Haroon, Shaikh Saaqib; Amin, Salman; Bhatti, Abdul Rauf; Sajjad, Intisar Ali; Liaqat, Rehan

doi:10.1007/s13369-020-04747-5

Cited by 33 publications

(30 citation statements)

References 42 publications

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“…However, DS has the largest portion of the power loss about 70%, because of its low voltage level with high current carrying configuration [2,3]. Further, voltage profile deviation and high power losses are the major issues in distribution networks due to the high value of R/X ratio, load expansion, and inductive nature of loads [4,5]. Therefore, power loss reduction is one of the most interesting and important matters in power system studies [1].…”

Section: Introduction 1backgroundmentioning

confidence: 99%

“…Furthermore, optimal size and placement of capacitor banks (CBs) in the distribution system need static or switchable capacitors for reactive power compensation at strategically identified locations in the distribution system that resolves the power quality issues. Additionally, it provides numerous technical and economic advantages such as the reduction in power loss, improved load-bus voltage, improved power factor, and reduced reactive power demand from the supply side [4,5,10]. Therefore, efficient and optimal planning for reactive power compensation is mandatory to cope with the ever-growing energy demand and technical and economic issues of distribution networks [4,6,10].…”

Section: Introduction 1backgroundmentioning

confidence: 99%

“…Additionally, it provides numerous technical and economic advantages such as the reduction in power loss, improved load-bus voltage, improved power factor, and reduced reactive power demand from the supply side [4,5,10]. Therefore, efficient and optimal planning for reactive power compensation is mandatory to cope with the ever-growing energy demand and technical and economic issues of distribution networks [4,6,10].…”

Section: Introduction 1backgroundmentioning

confidence: 99%

See 2 more Smart Citations

A Novel Multiobjective Hybrid Technique for Siting and Sizing of Distributed Generation and Capacitor Banks in Radial Distribution Systems

et al. 2021

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Distributed generation (DG) and capacitor bank (CB) allocation in distribution systems (DS) has the potential to enhance the overall system performance of radial distribution systems (RDS) using a multiobjective optimization technique. The benefits of CB and DG injection in the RDS greatly depend on selecting a suitable number of CBs/DGs and their volume along with the finest location. This work proposes applying a hybrid enhanced grey wolf optimizer and particle swarm optimization (EGWO-PSO) algorithm for optimal placement and sizing of DGs and CBs. EGWO is a metaheuristic optimization technique stimulated by grey wolves. On the other hand, PSO is a swarm-based metaheuristic optimization algorithm that finds the optimal solution to a problem through the movement of the particles. The advantages of both techniques are utilized to acquire mutual benefits, i.e., the exploration ability of the EGWO and the exploitation ability of the PSO. The proposed hybrid method has a high convergence speed and is not trapped in local optimal. Using this hybrid method, technical, economic, and environmental advantages are enhanced using multiobjective functions (MOF) such as minimizing active power losses, voltage deviation index (VDI), the total cost of electrical energy, and total emissions from generation sources and enhancing the voltage stability index (VSI). Six different operational cases are considered and carried out on two standard distribution systems, namely, IEEE 33- and 69-bus RDSs, to demonstrate the proposed scheme’s effectiveness extensively. The simulated results are compared with existing optimization algorithms. From the obtained results, it is observed that the proposed EGWO-PSO gives distinguished enhancements in multiobjective optimization of different conflicting objective functions and high-level performance with global optimal values.

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Section: Introduction 1backgroundmentioning

confidence: 99%

Section: Introduction 1backgroundmentioning

confidence: 99%

Section: Introduction 1backgroundmentioning

confidence: 99%

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A Novel Multiobjective Hybrid Technique for Siting and Sizing of Distributed Generation and Capacitor Banks in Radial Distribution Systems

et al. 2021

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“…In terms of computational complexity, it is an NP-hard problem with the highest complexity; the solution time increases exponentially with the problem scale, and there is no accurate optimal solution in the polynomial time [14][15][16]. At present, most studies use heuristic methods to solve optimization problems, such as polar bear optimization [17][18][19][20], grey wolf optimizer [21][22][23], and genetic algorithm [24][25][26], which can find good approximate solutions in a limited time.…”

Section: Introductionmentioning

confidence: 99%

“…The one-dimensional cutting sto timization problem. In terms of computational complexity, it is the highest complexity; the solution time increases exponentia and there is no accurate optimal solution in the polynomial tim studies use heuristic methods to solve optimization problems, zation [17][18][19][20], grey wolf optimizer [21][22][23], and genetic algorit good approximate solutions in a limited time. The one-dimensional cutting stock problem has been stu Common layout methods include column generation, greedy optimization algorithms.…”

Section: Introductionmentioning

confidence: 99%

Solution to Solid Wood Board Cutting Stock Problem

et al. 2021

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In the production process for wooden furniture, the raw material costs account for more than 50% of furniture costs, and the utilization rate of raw materials depends mainly on the layout scheme. Therefore, a reasonable layout is an important measure to reduce furniture costs. This paper investigates the solid wood board cutting stock problem (CSP) and establishes an optimization model, with the goal of the highest possible utilization rate for original boards. An ant colony-immune genetic algorithm (ACIGA) is designed to solve this model. The solutions of the ant colony algorithm are used as the initial population of the immune genetic algorithm, and the optimal solution is obtained using the immune genetic algorithm after multiple iterations are transformed into the accumulation of global pheromones, which improves the search ability and ensures the solution quality. The layout process of the solid wood board is abstracted into the construction process of the solution. At the same time, in order to prevent premature convergence, several improved methods, such as a global pheromone hybrid update and adaptive crossover probability, are proposed. Comparative experiments are designed to verify the feasibility and effectiveness of the ACIGA, and the experimental results show that the ACIGA has better solution precision and global search ability compared with the ant colony algorithm (ACA), genetic algorithm (GA), grey wolf optimizer (GWO), and polar bear optimization (PBO). The utilization rate increased by more than 2.308%, which provides effective theoretical and methodological support for furniture enterprises to improve economic benefits.

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Optimum estimation of series capacitors for enhancing distribution system performance via an improved hybrid optimization algorithm

Mohamed

Abdelaziz

Darwish

et al. 2023

Energy Science & Engineering

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As the load on distribution networks grows, system operators and planners are constantly challenged with the issue of voltage regulation or enhancing the quality of supply to customers at the load end of lengthy distribution lines. This paper presents the optimum determination of series capacitor units in a distribution system to maximize energy-saving and enhance voltage levels. Interestingly, series capacitors can enhance the capability of transmission lines, reduce line losses, enhance the performance of buses with large induction motor loads and reduce voltage flicker. At the same time, the limitations of series compensation are taken into consideration while calculating its optimum values. To achieve the planning objective and optimal load flow objective, two strategies: The Improved Grey Wolf Optimization method (I-GWO) and Tabu Search (TS), are hybridized to get the benefit of their advantages. The I-GWO has a movement strategy called dimension learning-based hunting for enhancing the balance between global and local search and maintaining diversity. The proposed (I-GWO-TS) algorithm can solve mixed-integer programming to achieve the planning and the optimal load flow objectives. The proposed method can be applied to a real Egyptian distribution system that is heavily loaded, with poor voltage regulation, and also has high-power losses. The obtained results demonstrate the capability of the proposed approach to determine optimal series capacitors' location and sizing for maximization of energy saving. Further, the proposed method improves the network performance regarding the voltage profile and power losses, although the limitations of including series compensation were considered in the distribution system.

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Optimal Placement and Sizing of Shunt Capacitors in Radial Distribution System Using Polar Bear Optimization Algorithm

Cited by 33 publications

References 42 publications

A Novel Multiobjective Hybrid Technique for Siting and Sizing of Distributed Generation and Capacitor Banks in Radial Distribution Systems

A Novel Multiobjective Hybrid Technique for Siting and Sizing of Distributed Generation and Capacitor Banks in Radial Distribution Systems

Solution to Solid Wood Board Cutting Stock Problem

Optimum estimation of series capacitors for enhancing distribution system performance via an improved hybrid optimization algorithm

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