The program for the solution of problems of optimization of reliability of system with dynamic reservation by the choice of optimum distribution of a reserve between system blocks

2021 ◽  
Vol 13 (12) ◽  
pp. 6708
Author(s):  
Hamza Mubarak ◽  
Nurulafiqah Nadzirah Mansor ◽  
Hazlie Mokhlis ◽  
Mahazani Mohamad ◽  
Hasmaini Mohamad ◽  
...  

Demand for continuous and reliable power supply has significantly increased, especially in this Industrial Revolution 4.0 era. In this regard, adequate planning of electrical power systems considering persistent load growth, increased integration of distributed generators (DGs), optimal system operation during N-1 contingencies, and compliance to the existing system constraints are paramount. However, these issues need to be parallelly addressed for optimum distribution system planning. Consequently, the planning optimization problem would become more complex due to the various technical and operational constraints as well as the enormous search space. To address these considerations, this paper proposes a strategy to obtain one optimal solution for the distribution system expansion planning by considering N-1 system contingencies for all branches and DG optimal sizing and placement as well as fluctuations in the load profiles. In this work, a hybrid firefly algorithm and particle swarm optimization (FA-PSO) was proposed to determine the optimal solution for the expansion planning problem. The validity of the proposed method was tested on IEEE 33- and 69-bus systems. The results show that incorporating DGs with optimal sizing and location minimizes the investment and power loss cost for the 33-bus system by 42.18% and 14.63%, respectively, and for the 69-system by 31.53% and 12%, respectively. In addition, comparative studies were done with a different model from the literature to verify the robustness of the proposed method.


2011 ◽  
Vol 314-316 ◽  
pp. 2027-2032
Author(s):  
Jiao Jian Liu ◽  
Wen He Liao ◽  
Yu Guo ◽  
Wen Bin Wang

In order to maximize knowledge sharing and reuse in networked manufacturing process and improve the rapidity and reliability of decision-making, a knowledge-integration model and its implementation methods are proposed in this paper. First, the requirement for knowledge integration in networked manufacturing is analyzed. On this basis, a knowledge-integration model is built, and then three key technologies are studied, namely knowledge representation and organization based on ontology, knowledge correlation analysis based on complex network and knowledge supply based on decision-making context. This model provides an effective way to realize the optimum distribution of knowledge in networked manufacturing process and to improve the efficiency of decision-making process.


1952 ◽  
Vol 19 (1) ◽  
pp. 109-113
Author(s):  
Waloddi Weibull

Abstract An analytical expression connecting fatigue lives with applied stresses, and methods for computing the values of its parameters from experimental data are given. Formulas for estimating the uncertainty of computed parameter values, caused by scatter of loads and fatigue lives, for optimum distribution of specimens, and for optimum choice of stress levels, are deduced. Testing time and costs may be reduced by more than 40 per cent by using the formulas.


2022 ◽  
Vol 1048 ◽  
pp. 15-20
Author(s):  
Ruey Shan Chen ◽  
Sahrim Ahmad

In this study, liquid natural rubber (LNR) toughened polylactic acid (PLA) incorporated with magnetite (Fe3O4) nanocomposites were fabricated via melt-compounding in an internal mixer and followed by hot/cold pressing. The effects of ultrasonic treatment time (1-3 hours) and Fe3O4 (0.5-4.0 wt%) nanoparticles loading on tensile, morphology and thermal stability were investigated. Based on tensile testing results, the ultrasonication time of 1 hour was served as the most suitable treatment period to achieve the optimum distribution of Fe3O4 within PLA/LNR matrix. Among the investigated nanoparticles loading, 1 wt% Fe3O4 nanocomposite presented the highest tensile strength of 23.7 MPa, Young’s modulus of 1293.5 MPa and strain at break of 2.8%. SEM micrographs showed that the over-treated nanocomposites with 2-3 hours and over-high nanoparticles loading had resulted in the formation of clusters in the matrix. With increasing Fe3O4 loading, the decomposition of PLA/LNR nanocomposites was initiated earlier.


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