scholarly journals Analysis of Energy Consumption and Performance Test on Rice Planting Using Rice Transplanter : A Case Study in West Sumatera Province, Indonesia

2020 ◽  
Vol 4 (1) ◽  
pp. 12-25
Author(s):  
Renny Eka Putri ◽  
Rizka Fadhilah ◽  
Dinah Cherie ◽  
Azkiya Wahyu Novianda
Keyword(s):  
Energy Consumption ◽  
Total Energy ◽  
Performance Test ◽  
Agricultural Sector ◽  
Theoretical Work ◽  
Work Capacity ◽  
Total Energy Consumption ◽  
Effective Work ◽  
Rice Milling ◽  
And Performance

Energy Consumption in the agricultural sector consists of diesel, gasoline, and kerosene for fuel of agricultural machinery (rice transplanter, tractor, rice milling unit, motor sprayer, and water pump) in the sector. The objectives of this study are to determine the total energy consumption of rice planting and to analyse the performance of rice transplanter during rice planting in West Sumatra, Indonesia. This research was conducted on farmer's rice fields in west Sumatera Indonesia. The results obtained from the performance of a rice transplanter machine include working speed of 0.633 m/s, a theoretical work capacity of 0.274 ha/hour, effective work capacity of 0.222 ha/hour and work efficiency of 80.967%. The detail of energy consumption using a rice transplanter are human energy (9.225 MJ/ha), seed energy (255.413 MJ/ha), fuel energy (93.463 MJ/ha) and engine energy (0.821 MJ/ha), so that the total energy consumption is 358.952 MJ/ha.

scholarly journals Energy Consumption in Onion and Potato Production within the Province of El Hajeb (Morocco): Towards Energy Use Efficiency in Commercialized Vegetable Production

2016 ◽  
Vol 9 (1) ◽  
pp. 118 ◽  
Author(s):  
Khalil Allali ◽  
Boubaker Dhehibi ◽  
Shinan N. Kassam ◽  
Aden Aw-Hassan
Keyword(s):  
Energy Consumption ◽  
Total Energy ◽  
Energy Use ◽  
Agricultural Sector ◽  
Potato Production ◽  
Total Energy Consumption ◽  
Energy Use Efficiency ◽  
Energy Indices ◽  
Direct Energy ◽  
Use Efficiency

<p>Energy use efficiency is a key requirement for sustainability in agricultural production, but often overlooked. The aim of this study was to quantify the amount and efficiency of energy consumed in the production of onions and potatoes in El Hajeb province of Morocco. These estimates are of significant importance in informing contemporary policy discourse related to energy subsidy reform in Morocco, and more specifically within an ongoing national strategy for ‘modernizing’ the agricultural sector under the ‘Green Morocco Plan’. Data were collected through the administration of a direct questionnaire with 60 farmers and analyzed using PLANETE. Our results indicate that total energy consumption in onion production is 107483 MJ ha<sup>-1</sup> with butane (79.5%) as the main source of direct energy. Chemical fertilizers (61.53%) and water for irrigation (30%) were main sources of indirect energy. Energy indices related to energy efficiency ratios, energy profitability and energy productivity were estimated at 0.78, -0.22 and 0.54 kg MJ<sup>-1</sup>, respectively. Total energy consumption in potato production was estimated at 74,270 MJ ha<sup>-1</sup>, with direct energy consumption of 28,521 MJ ha<sup>-1</sup> stemming from butane (70%) and diesel (19.14%) as primary sources. Indirect energy consumption was estimated at 45749 MJ ha<sup>-1</sup> and generated principally through the use of fertilizers (60%). Energy indices (efficiency, profitability and productivity) were estimated at 1.54, 0.54, and 0.45 kg MJ<sup>-1</sup>, respectively. GHG emissions were found to be 3.47 t CO<sub>2eq</sub> ha<sup>-1</sup> in the production of onions and 3.63 t CO<sub>2eq</sub> ha<sup>-1</sup> for potatoes. We find that within the study area, increases in the size of production plots are not necessarily consistent with increases in energy use efficiency.</p>

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.

Optimizing the production scheduling of a single machine to minimize total energy consumption costs

2014 ◽  
Vol 67 ◽  
pp. 197-207 ◽  
Author(s):  
Fadi Shrouf ◽  
Joaquin Ordieres-Meré ◽  
Alvaro García-Sánchez ◽  
Miguel Ortega-Mier
Keyword(s):  
Energy Consumption ◽  
Total Energy ◽  
Single Machine ◽  
Production Scheduling ◽  
Total Energy Consumption
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