Optimal allocation of microgrid considering economic dispatch based on hybrid weighted bilevel planning method and algorithm improvement

Wu, Hongbin; Zhuang, Huaidong; Zhang, Wei; Ding, Ming

doi:10.1016/j.ijepes.2015.08.011

Cited by 26 publications

(18 citation statements)

References 28 publications

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“…The noticeable numerical techniques addressed in the literature (Table 3) include; ε-constraint method [121,135,161]; second order cone programming [124]; lexicographic method [135]; MCS [122,139,157]; OPF [158]; integer programming [85]; graph theory [85,150]; penalty factor (funchion) method [130,140]; CCP [145,157]; compromise method [153]; ICSP [160]; linear programming (LP) [164] and non-linear programming (NLP) [152,160]. Moreover, goal programming (GOP), exhaustive search, sequential quadratic programming (SQP) and dynamic programming methods have sucessfully employed in conventional DN related planning problems [26].…”

Section: B Numerical Methodsmentioning

confidence: 99%

“…The decision making (DM) methods are vital, both as main op means of sorting out a trade-off solutions among a set of mult prominent DM techniques addressed in the literature (Table 3) inclu both weighted sum (WSM) and product (WPM) me [132,139,140,148,149,157]. The analytical hierarchy process (AHP) ha and short term SDN planning, as in [124,154].…”

Section: Decision-making Methodsmentioning

confidence: 99%

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Smart Distribution Networks: A Review of Modern Distribution Concepts from a Planning Perspective

et al. 2017

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Smart grids (SGs), as an emerging grid modernization concept, is spreading across diverse research areas for revolutionizing power systems. SGs realize new key concepts with intelligent technologies, maximizing achieved objectives and addressing critical issues that are limited in conventional grids. The SG modernization is more noticeable at the distribution grid level. Thus, the transformation of the traditional distribution network (DN) into an intelligent one, is a vital dimension of SG research. Since future DNs are expected to be interconnected in nature and operation, hence traditional planning methods and tools may no longer be applicable. In this paper, the smart distribution network (SDN) concept under the SG paradigm, has presented and reviewed from the planning perspective. Also, developments in the SDN planning process have been surveyed on the basis of SG package (SGP). The package presents a SDN planning foundation via major SG-enabling technologies (SGTF), anticipated functionalities (SGAF), new consumption models (MDC) as potential SDN candidates, associated policies and pilot projects and multi-objective planning (MOP) as a real-world optimization problem. In addition, the need for an aggregated SDN planning model has also been highlighted. The paper discusses recent notable related works, implementation activities, various issues/challenges and potential future research directions; all aiming at SDN planning.

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Section: B Numerical Methodsmentioning

confidence: 99%

Section: Decision-making Methodsmentioning

confidence: 99%

Smart Distribution Networks: A Review of Modern Distribution Concepts from a Planning Perspective

et al. 2017

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“…The economic dispatch was adopted by using bi-level planning method with the objective of reducing the load loss probability, daily fixed cost of investment and excess energy rate for the best placement of microgrid [20]. Also, cost of pollutant disposal and cost of operation taking as another objective to determine the distributed generation output power.…”

Section: Literature Survey On Economic Dispatch Of Hybrid Systems / Mmentioning

confidence: 99%

A review to economic dispatch of hybrid microgrids

Vankadara¹,

Raglend²

2019

Serb J Electr Eng

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Hybrid Microgrids are being widespread for power generation in remote locations. The improvement in non-conventional energy sources and rise in the price of existing electrical energy production sources led to the advancement of hybrid renewable sources. Economic characteristics of these technologies are adequately capable to include in emerging power generation. Advances and research in solar, wind and other non-conventional energy sources are required to continue for improving their performance, creating techniques for exactly forecasting their outputs and reliably integrating with other conventional sources used for generation. Economic dispatch is being taken into consideration as the optimal output of the electricity generation facilities. These are to be met as per the load at the lowest possible cost. The problem on Economic Dispatch (ED) and different technical constraints considering power balance in the network satisfying the objective are to be formulated. This paper presents a brief review on economic dispatch of hybrid microgrids.

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“…D. H. Ackley et al proposed an iterative genetic algorithm with hillclimbing methods of a complex probability election mechanism. The method determines the value of a new individual through m "voters" [10] [11]. Experimental results indicated that the solution speed of the random iterative genetic algorithm with hillclimbing methods was higher than that of genetic algorithm, simulated annealing algorithm, tabu search, and a combination of several intelligent algorithms.…”

Section: State Of Artmentioning

confidence: 99%

Improved Adaptive Genetic Algorithm for Course Scheduling in Colleges and Universities

Wang¹

2018

Int. J. Emerg. Technol. Learn.

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Abstract-Traditional artificial intelligence and computer-aided course scheduling schemes can no longer meet the increasing demands caused by the informatization of teaching management in colleges and universities. To address this problem, this study designed an improved adaptive genetic algorithm that is based on hard and soft constraints for course scheduling. First, the mathematical model of the genetic algorithm was established. The combination of time, teacher, and course number was regarded as the gene coding. The weekly course schedule of each class was a chromosome, and the course schedule of the entire school was the initial population. The fitness was designed according to the priority of each class, curriculum dispersion, and teacher satisfaction. Local columns between individuals were selected through the roulette principle for a variation of crossover and random columns. Iterative calculation was implemented on the basis of the default mutation and crossover rates to study the optimal course scheduling scheme. Experimental results demonstrate that the improved adaptive genetic algorithm is superior to the original genetic algorithm. When the number of iterations is 150, population evolution is optimal and the fitness does not increase. When the population size is 150 classes, the average scheduling time is the shortest. The basic, adaptive, and improved adaptive genetic algorithms are compared in terms of the number of average iterations required for convergence, maximum individual fitness, and average individual fitness. Comparison results show that the improved adaptive genetic algorithm is superior to the two other algorithms. This study provides references for the model building and evaluation of course scheduling in colleges and universities.

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Optimal allocation of microgrid considering economic dispatch based on hybrid weighted bilevel planning method and algorithm improvement

Cited by 26 publications

References 28 publications

Smart Distribution Networks: A Review of Modern Distribution Concepts from a Planning Perspective

Smart Distribution Networks: A Review of Modern Distribution Concepts from a Planning Perspective

A review to economic dispatch of hybrid microgrids

Improved Adaptive Genetic Algorithm for Course Scheduling in Colleges and Universities

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