Deterministic and probabilistic multi-objective placement and sizing of wind renewable energy sources using improved spotted hyena optimizer

Naderipour, Amirreza; Nowdeh, Saber Arabi; Saftjani, Parvin Barat; Abdul‐Malek, Zulkurnain; Mustafa, Mohd Wazir; Kamyab, Hesam; Davoudkhani, Iraj Faraji

doi:10.1016/j.jclepro.2020.124941

Cited by 62 publications

(23 citation statements)

References 46 publications

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“…Depending on the number of tie switches, five loops have been formed as 𝐿 1 to 𝐿 5 , these switches are operated during fault cases, load balancing conditions and to reduce the system losses. L1= [ 3,4,5,6,7,8,9,36,37,38,39,40,41,42,35]; L2= [ 11,12,13,14,44,43,45]; L3 = [ 15,16,17,18,19,20]; L4= [ 21,22,23,24,25,26,59,60,61,62,63,64]; L5 = [ 47,48,49,53,54,55,56,57,52,46, To evaluate the effectiveness of proposed method, test system 2 is also simulated at different load levels such as light (0.5), nominal (1.0), and heavy (1.6), and obtained results are conferred in Table 3. From Table 3, we can infer that base case PL in the DS (in kW) at light load is 51.60, which is reduced to 23.43, 18.14, 11.54 and 9.545 using scenarios II, III, IV, and V, respectively.…”

Section: Test System-ii: Ieee 69-bus Systemmentioning

confidence: 99%

“…DGs allocation in an optimal location and suitable sizes may minimize active power loss and improve the system voltage profile and power quality. Many meta-heuristic algorithms have been introduced to solve DG allocation problems for last decades, such as genetic algorithm and particle swarm optimization [22], modified bacterial foraging optimization algorithm [23], analytical approach [24], invasive weed optimization algorithm [25], quasi-oppositional teaching-learning based optimization [26], intelligent water drop algorithm [27], Krill herd algorithm [28], Flower Pollination algorithm [29], Shuffled Bat algorithm [30], Stud Krill herd Algorithm [31], hyper-spherical search algorithm [32], one rank cuckoo search algorithm [33], symbiotic organism search-based method [34], stochastic fractal search algorithm [35], combined evolutionary algorithm [36], mutated salp swarm algorithm [37], Multi-Objective Hybrid Teaching-Learning Based Optimization-Grey Wolf Optimizer [38], coyote optimization algorithm (COA) and electrical transient analyzer program (ETAP) [39], improved spotted hyena algorithm [40]. These methods are easy to implement and widely used in the DS to obtain a global optimum solution with less computation time.…”

Section: Introductionmentioning

confidence: 99%

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Distribution network reconfiguration considering DGs using a hybrid CS-GWO algorithm for power loss minimization and voltage profile enhancement

Kumar¹,

Rudramoorthy²

2021

IJEEI

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This paper presents an implementation of the hybrid Cuckoo search and Grey wolf (CS-GWO) optimization algorithm for solving the problem of distribution network reconfiguration (DNR) and optimal location and sizing of distributed generations (DGs) simultaneously in radial distribution systems (RDSs). This algorithm is being used significantly to minimize the system power loss, voltage deviation at load buses and improve the voltage profile. When solving the high-dimensional datasets optimization problem using the GWO algorithm, it simply falls into an optimum local region. To enhance and strengthen the GWO algorithm searchability, CS algorithm is integrated to update the best three candidate solutions. This hybrid CS-GWO algorithm has a more substantial search capability to simultaneously find optimal candidate solutions for problems. The obtained test results for the 33-bus system show that minimization of active power loss was enhanced by 74.73%,73.35%, and 80.37% for light, nominal, and heavy load conditions, respectively, and similarly for 69-bus system is 81.50%, 84.74%, and 88.86%. The minimum voltage value for 33-bus system under nominal load condition was enhanced from 0.9130 p.u to 0.9865 p.u and similarly for the 69-bus system is 0.9094 p.u to 0.9842 p.u. Respectively. Furthermore, to validate the effectiveness and performances of the proposed hybrid CS-GWO algorithm with existing methods is presented. This method is tested and evaluated for standard IEEE 33-bus and 69-bus RDSs by considering different scenarios. Finally, the comparative analysis shows that the proposed algorithm was more efficient in minimizing power losses and enhancing the voltage profile of the system.

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Section: Test System-ii: Ieee 69-bus Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Distribution network reconfiguration considering DGs using a hybrid CS-GWO algorithm for power loss minimization and voltage profile enhancement

Kumar¹,

Rudramoorthy²

2021

IJEEI

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“…The load demand has uncertainty and its uncertainty should be considered in the hybrid system design. The suggested PDF for the load demand is a normal PDF [38], which is defined as follows.…”

Section: Load Demand Modelsmentioning

confidence: 99%

Optimal design of an off-grid hybrid renewable energy system considering generation and load uncertainty: the case of Zanjan city, Iran

2021

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In this paper, designing a hybrid stand-alone photovoltaic/wind energy system with battery storage (PV/WT/Batt) is presented to minimize the total cost of the hybrid system and considering reliability constraints for Zanjan city in Iran country considering generation and load uncertainties. The total cost includes the cost of the system components and load losses cost and also deficit power probability-hourly interruption probability index, which is defined as the reliability constraint. The optimal size of the system components is found using an improved crow search algorithm based on mutation and crossover operators of the genetic algorithm to prevent premature convergence. The optimal designing of the hybrid system is implemented considering the uncertainty of photovoltaic and wind resources as well as the load demand of the system based on the probability distribution functions of uncertain parameters using Monte Carlo simulation. The simulations are implemented in two deterministic and probabilistic scenarios. In the deterministic scenario, the optimal design of various combinations of the hybrid system is investigated in view of the system cost and deficit power probability probability-hourly interruption probability index based on the improved crow search algorithm with and without the cost of load loss. The results of the deterministic scenario showed that the system cost is increased considering the cost of load loss, but the system load is supplied with higher reliability. Also, the deterministic results cleared the superiority of the improved crow search algorithm compared with conventional crow search algorithm and particle swarm optimization methods. Moreover, the results of the system designing showed that considering the uncertainty, the system cost increases, and the reliability is significantly improved. The results cleared that the system cost in deterministic and probabilistic designing is obtained 1.0108 M$ and 1.210 M$, respectively for load supply equal to 153.87 MWh. So, due to the inherent nature of the uncertainty in the renewable resources power generation as well as continuous load changes, a probabilistic approach of the hybrid system designing is necessary to know the accurate cost and reliability. Article highlights Effective performance of the proposed method in system designing with lowest cost and higher reliability. Achieving to a more reliable hybrid energy system with considering cost of load losses in designing. Increasing the system the cost and improving the reliability considering uncertainties of generation and load.

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“…The authors of [19] proposed the algorithm for detecting the vulnerable buses using VSI, and determined the optimal location and size of RDGs using Multi Leader Particle Swarm Optimization (MLPSO). Recently, the authors of [20] proposed the improved meta-heuristic method, called the b-chaotic sequence spotted hyena optimizer, for determining the optimal size and location of wind turbines considering reducing power losses and improving voltage profile. This method reached the minimum power losses and improved the voltage profiles.…”

Section: Introductionmentioning

confidence: 99%

Optimal Location and Sizing of Renewable Distributed Generators for Improving Voltage Stability and Security Considering Reactive Power Compensation

et al. 2022

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The integration of renewable resources into the existing power distribution system is expanding to reduce gas emissions, treat climate change and satisfy the current global need for clean energy. If the location and size of these renewable generators are determined without considering uncontrollable reactive power compensation caused by their intermittent nature, the resultant power system may suffer from system instability and decreased reliability. Therefore, the issue of optimal location and size of renewable resources attracts great attention. In this paper, a methodology is proposed to optimize the locations and capacities of distributed renewable generators installed in conventional power distribution systems. In particular, uncontrollable reactive power compensation of these renewable resources is considered in this paper and managed through the proposed methodology to ensure power system reliability and stability. As a result, the proposed methodology reminds us of the importance of reactive power compensation by performing better in power losses reduction and the robustness of voltage stability against variable reactive power compensation.

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Deterministic and probabilistic multi-objective placement and sizing of wind renewable energy sources using improved spotted hyena optimizer

Cited by 62 publications

References 46 publications

Distribution network reconfiguration considering DGs using a hybrid CS-GWO algorithm for power loss minimization and voltage profile enhancement

Distribution network reconfiguration considering DGs using a hybrid CS-GWO algorithm for power loss minimization and voltage profile enhancement

Optimal design of an off-grid hybrid renewable energy system considering generation and load uncertainty: the case of Zanjan city, Iran

Optimal Location and Sizing of Renewable Distributed Generators for Improving Voltage Stability and Security Considering Reactive Power Compensation

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