Energy consumption analysis in wastewater treatment plants using simulation and SCADA system: Case study in northern Taiwan
| Autor: | Ya-Yun Chu, Lili Lorensia Mallu, Jian-Gu Chen, Han-Yang Liu, Wu-Yang Sean |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Renewable Energy
Sustainability and the Environment 020209 energy Strategy and Management 05 social sciences Airflow Environmental engineering 02 engineering and technology Building and Construction Energy consumption Industrial and Manufacturing Engineering SCADA 050501 criminology 0202 electrical engineering electronic engineering information engineering Range (statistics) Environmental science Sewage treatment Water quality Aeration Effluent 0505 law General Environmental Science |
| Zdroj: | Journal of Cleaner Production. 276:124248 |
| ISSN: | 0959-6526 |
| DOI: | 10.1016/j.jclepro.2020.124248 |
| Popis: | Energy consumption is a crucial aspect in wastewater treatment plants. Biological processes using aeration systems contribute significantly to energy usage. Tao-bay plants in northern Taiwan are recent plants that have not introduced automated control on aeration systems yet. The use of numerical methods aims to predict optimized airflow rate and energy consumption and to provide references for the first-phase plant operation. In this study, a steady-state modeling using GPS-X 7.0 is presented. Measured monthly data in a yearly basis for parameters such as BOD, COD, total N, N–NH4+, and total P were used as the input data. The measured effluent concentrations for these parameters were compared with numerically calculated values for calibration purposes. An empirical correlation is also proposed for an alternative calculation of airflow and relative electricity consumption. A supervisory control and data acquisition (SCADA) system that consisted of current and water quality sensors with an online interface was developed to monitor the aeration system of the case-study plant. Selected real-time data for DO and electricity usage related to the biological treatment were recorded in the cloud server and used for verifying and compensating existing data measured in the plant. According to the monthly energy-consumption data for Tao-bay plant in 2018, the energy-saving rate predicted using the GPS-X model was approximately 20%, which is consistent with the global values (18–21%) of the plant operating in the range of 50,000–10,000 CMD. Moreover, when adjusting DO every 1 mg/L to fit a sewage-discharge criterion, the energy-saving rate was approximately 5–7%. |
| Databáze: | OpenAIRE |
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