scholarly journals Improved wind-driven optimization algorithm for the optimization of hydropower generation from a reservoir

Author(s):  
Yin Liu ◽  
Shuanghu Zhang ◽  
Yunzhong Jiang ◽  
Dan Wang ◽  
Qihao Gu ◽  
...  

Abstract The improvement of reservoir operation optimization (ROO) can lead to comprehensive economic benefits as well as sustainable development of water resources. To achieve this goal, an algorithm named wind-driven optimization (WDO) is first employed for ROO in this paper. An improved WDO(IWDO) is developed by using a dynamic adaptive random mutation mechanism, which can avoid the algorithm stagnation at local optima. Moreover, an adaptive search space reduction (ASSR) strategy that aims at improving the search efficiency of all evolutionary algorithms is proposed. The application results of the Goupitan hydropower station show that IWDO is an effective and viable algorithm for ROO and is capable of obtaining greater power generation compared to the classic WDO. Moreover, it is shown that the ASSR strategy can improve the search efficiency and the quality of scheduling results when coupled with various optimization algorithms such as IWDO, WDO and particle swarm optimization.

Author(s):  
Prachi Agrawal ◽  
Talari Ganesh ◽  
Ali Wagdy Mohamed

AbstractThis article proposes a novel binary version of recently developed Gaining Sharing knowledge-based optimization algorithm (GSK) to solve binary optimization problems. GSK algorithm is based on the concept of how humans acquire and share knowledge during their life span. A binary version of GSK named novel binary Gaining Sharing knowledge-based optimization algorithm (NBGSK) depends on mainly two binary stages: binary junior gaining sharing stage and binary senior gaining sharing stage with knowledge factor 1. These two stages enable NBGSK for exploring and exploitation of the search space efficiently and effectively to solve problems in binary space. Moreover, to enhance the performance of NBGSK and prevent the solutions from trapping into local optima, NBGSK with population size reduction (PR-NBGSK) is introduced. It decreases the population size gradually with a linear function. The proposed NBGSK and PR-NBGSK applied to set of knapsack instances with small and large dimensions, which shows that NBGSK and PR-NBGSK are more efficient and effective in terms of convergence, robustness, and accuracy.


2021 ◽  
Vol 13 (3) ◽  
pp. 1274
Author(s):  
Loau Al-Bahrani ◽  
Mehdi Seyedmahmoudian ◽  
Ben Horan ◽  
Alex Stojcevski

Few non-traditional optimization techniques are applied to the dynamic economic dispatch (DED) of large-scale thermal power units (TPUs), e.g., 1000 TPUs, that consider the effects of valve-point loading with ramp-rate limitations. This is a complicated multiple mode problem. In this investigation, a novel optimization technique, namely, a multi-gradient particle swarm optimization (MG-PSO) algorithm with two stages for exploring and exploiting the search space area, is employed as an optimization tool. The M particles (explorers) in the first stage are used to explore new neighborhoods, whereas the M particles (exploiters) in the second stage are used to exploit the best neighborhood. The M particles’ negative gradient variation in both stages causes the equilibrium between the global and local search space capabilities. This algorithm’s authentication is demonstrated on five medium-scale to very large-scale power systems. The MG-PSO algorithm effectively reduces the difficulty of handling the large-scale DED problem, and simulation results confirm this algorithm’s suitability for such a complicated multi-objective problem at varying fitness performance measures and consistency. This algorithm is also applied to estimate the required generation in 24 h to meet load demand changes. This investigation provides useful technical references for economic dispatch operators to update their power system programs in order to achieve economic benefits.


Author(s):  
Arja Rautio ◽  
Natalia Kukarenko ◽  
Lena Maria Nilsson ◽  
Birgitta Evengard

Climate change in the Arctic affects both environmental, animal, and human health, as well as human wellbeing and societal development. Women and men, and girls and boys are affected differently. Sex-disaggregated data collection is increasingly carried out as a routine in human health research and in healthcare analysis. This study involved a literature review and used a case study design to analyze gender differences in the roles and responsibilities of men and women residing in the Arctic. The theoretical background for gender-analysis is here described together with examples from the Russian Arctic and a literature search. We conclude that a broader gender-analysis of sex-disaggregated data followed by actions is a question of human rights and also of economic benefits for societies at large and of the quality of services as in the health care.


2012 ◽  
Vol 588-589 ◽  
pp. 1685-1688 ◽  
Author(s):  
Lian Yong Wang ◽  
Jing Fan Zhang ◽  
Lei Dai ◽  
Jiu Ju Cai

Technical analysis was used to analyze the roasting of molybdenum concentrate on the basis of thermal balance test of rotary furnaces used for Roasting, and the results indicate that, on the condition of commercial production, the Roasting of MoS2 can occur spontaneously because the heat of reaction is so much that proper cooling measures should be adopted in case overheating happens. According to above analysis, carbon-free roasting technology of molybdenum concentrate was proposed in this paper. The results, which come from thermal balance test and technical analysis of rotary furnaces used for carbon-free roasting of molybdenum concentrate, indicate that outer heat source used in traditional Roasting technology is not needed in carbon-free roasting technology, because enough heat is generated during Roasting to ensure spontaneous reaction. In fact, heating is not needed in operating process except at the beginning, to make molybdenum concentrate catching fire, and when reaction completing, to remove residual sulphur. The technology in this paper is obviously advantageous in aspects of energy saving, output, quality of production, heat loss, the concentration of SO2 in flue gas, etc. and will have remarkable environmental benefits, economic benefits and social benefits.


2006 ◽  
Vol 16 (07) ◽  
pp. 2081-2091 ◽  
Author(s):  
GEORGE D. MAGOULAS ◽  
ARISTOKLIS ANASTASIADIS

This paper explores the use of the nonextensive q-distribution in the context of adaptive stochastic searching. The proposed approach consists of generating the "probability" of moving from one point of the search space to another through a probability distribution characterized by the q entropic index of the nonextensive entropy. The potential benefits of this technique are investigated by incorporating it in two different adaptive search algorithmic models to create new modifications of the diffusion method and the particle swarm optimizer. The performance of the modified search algorithms is evaluated in a number of nonlinear optimization and neural network training benchmark problems.


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