Study on the Integrated Vortex-Grid Clarification Process and its Application

2011 ◽  
Vol 183-185 ◽  
pp. 2115-2119 ◽  
Author(s):  
Zhen Gong Tong
Keyword(s):  
Water Quality ◽  
Energy Consumption ◽  
Total Energy ◽  
Energy Cost ◽  
Concentration Zone ◽  
Raw Water ◽  
Total Energy Consumption ◽  
Inclined Tube ◽  
Adaptive Capability

Based on Micro-vortex coagulation and Hazen theory, the process of integrated vortex grid clarification bears four characteristics. Firstly, there are a lot of micro-whirling reactors whose surfaces hole rate is designed by the raw water quality in the first and second flocculation zone. Then, an inclined-tube in the precipitate zone is installed. Thirdly, a sludge concentration zone in the tank is also equipped. Lastly, by applying the low return or non-return technologies and changing some inner structure which will reduce the total energy cost. We have not only achieved a more efficient use of the cubage of the reactors, but also reduced the total energy consumption. The paper argues that in comparison to other clarification technology, the Micro-vortex clarification process deserves wide application for its various advantages, such as a higher coagulation efficiency, a shorter reactivity time, a better quality of finished water, a stronger adaptive capability, a more convenient construction and the like.

scholarly journals Integrated Optimization on Energy Saving and Quality of Service of Urban Rail Transit System

2020 ◽  
Vol 2020 ◽  
pp. 1-22 ◽  
Author(s):  
Wenxin Li ◽  
Qiyuan Peng ◽  
Chao Wen ◽  
Shengdong Li ◽  
Xu Yan ◽  
...  
Keyword(s):  
Quality Of Service ◽  
Energy Consumption ◽  
Total Energy ◽  
Energy Saving ◽  
Urban Rail Transit ◽  
Total Energy Consumption ◽  
Transit System ◽  
Running Time ◽  
Urban Rail

Optimizing to increase the utilization ratio of regenerative braking energy reduces energy consumption, and can be done without increasing the deviation of train running time in one circle. The latter entails that the train timetable is upheld, which guarantees that the demand for passenger transport services is met and the quality of services in the urban rail transit system is maintained. This study proposes a multi-objective optimization model for urban railways with timetable optimization to minimize the total energy consumption of trains while maximizing the quality of service. To this end, we apply the principles and ideas of calculus to reduce the power of the velocity in the train energy consumption model. This greatly simplifies the complexity of the optimization model. Then, considering the conflicting requirements of decision-makers, weight factors are added to the objective functions to reflect decision-makers’ preferences for energy-saving and the quality of service. We adopt the nondominated sorting genetic algorithm-II (NSGA-II) to solve the proposed model. A practical case study of the Yizhuang urban railway line in Beijing is conducted to verify the effectiveness of the proposed model and evaluate the advantages of the optimal energy saving timetable (OEST) in comparison to the optimal quality of service timetable (OQOST). The results showed that the OEST reduced total energy consumption by 8.72% but increased the deviation of trains running time in one circle by 728 s. The total energy consumption was reduced by 6.09%, but there was no increase in the deviation of train running time in one circle with the OQOST.

Energy savings potential of new aeration system: Full scale trials

2012 ◽  
Vol 7 (4) ◽  
Author(s):  
A. Lazić ◽  
V. Larsson ◽  
Å. Nordenborg
Keyword(s):  
Control System ◽  
Energy Consumption ◽  
Total Energy ◽  
Energy Savings ◽  
Treatment Plant ◽  
Full Scale ◽  
Total Energy Consumption ◽  
Aeration System ◽  
Fine Bubble ◽  
Aeration Control

The objective of this work is to decrease energy consumption of the aeration system at a mid-size conventional wastewater treatment plant in the south of Sweden where aeration consumes 44% of the total energy consumption of the plant. By designing an energy optimised aeration system (with aeration grids, blowers, controlling valves) and then operating it with a new aeration control system (dissolved oxygen cascade control and most open valve logic) one can save energy. The concept has been tested in full scale by comparing two treatment lines: a reference line (consisting of old fine bubble tube diffusers, old lobe blowers, simple DO control) with a test line (consisting of new Sanitaire Silver Series Low Pressure fine bubble diffusers, a new screw blower and the Flygt aeration control system). Energy savings with the new aeration system measured as Aeration Efficiency was 65%. Furthermore, 13% of the total energy consumption of the whole plant, or 21 000 €/year, could be saved when the tested line was operated with the new aeration system.

scholarly journals Energy Recovery Potential in Industrial and Municipal Wastewater Networks Using Micro-Hydropower in Spain

Water ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 691
Author(s):  
Aida Mérida García ◽  
Juan Antonio Rodríguez Díaz ◽  
Jorge García Morillo ◽  
Aonghus McNabola
Keyword(s):  
Energy Consumption ◽  
Total Energy ◽  
Energy Recovery ◽  
Energy Production ◽  
Municipal Wastewater ◽  
Distribution Networks ◽  
Total Power ◽  
Energy Potential ◽  
Total Energy Consumption ◽  
Recovery Potential

The use of micro-hydropower (MHP) for energy recovery in water distribution networks is becoming increasingly widespread. The incorporation of this technology, which offers low-cost solutions, allows for the reduction of greenhouse gas emissions linked to energy consumption. In this work, the MHP energy recovery potential in Spain from all available wastewater discharges, both municipal and private industrial, was assessed, based on discharge licenses. From a total of 16,778 licenses, less than 1% of the sites presented an MHP potential higher than 2 kW, with a total power potential between 3.31 and 3.54 MW. This total was distributed between industry, fish farms and municipal wastewater treatment plants following the proportion 51–54%, 14–13% and 35–33%, respectively. The total energy production estimated reached 29 GWh∙year−1, from which 80% corresponded to sites with power potential over 15 kW. Energy-related industries, not included in previous investigations, amounted to 45% of the total energy potential for Spain, a finding which could greatly influence MHP potential estimates across the world. The estimated energy production represented a potential CO2 emission savings of around 11 thousand tonnes, with a corresponding reduction between M€ 2.11 and M€ 4.24 in the total energy consumption in the country.

scholarly journals Linear Weighted Regression and Energy-Aware Greedy Scheduling for Heterogeneous Big Data

Electronics ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 554
Author(s):  
Suresh Kallam ◽  
Rizwan Patan ◽  
Tathapudi V. Ramana ◽  
Amir H. Gandomi
Keyword(s):  
Big Data ◽  
Energy Consumption ◽  
Total Energy ◽  
Optimal Solution ◽  
Data Locality ◽  
Weighted Regression ◽  
Heterogeneous Environments ◽  
Energy Aware ◽  
Total Energy Consumption ◽  
Greedy Scheduling

Data are presently being produced at an increased speed in different formats, which complicates the design, processing, and evaluation of the data. The MapReduce algorithm is a distributed file system that is used for big data parallel processing. Current implementations of MapReduce assist in data locality along with robustness. In this study, a linear weighted regression and energy-aware greedy scheduling (LWR-EGS) method were combined to handle big data. The LWR-EGS method initially selects tasks for an assignment and then selects the best available machine to identify an optimal solution. With this objective, first, the problem was modeled as an integer linear weighted regression program to choose tasks for the assignment. Then, the best available machines were selected to find the optimal solution. In this manner, the optimization of resources is said to have taken place. Then, an energy efficiency-aware greedy scheduling algorithm was presented to select a position for each task to minimize the total energy consumption of the MapReduce job for big data applications in heterogeneous environments without a significant performance loss. To evaluate the performance, the LWR-EGS method was compared with two related approaches via MapReduce. The experimental results showed that the LWR-EGS method effectively reduced the total energy consumption without producing large scheduling overheads. Moreover, the method also reduced the execution time when compared to state-of-the-art methods. The LWR-EGS method reduced the energy consumption, average processing time, and scheduling overhead by 16%, 20%, and 22%, respectively, compared to existing methods.

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