Strategi Kendali Kadar Nitrat Berbasis Fuzzy-PID pada Proses Nitrogen Removal di Instalasi Pengolahan Air Limbah

Main Article Content

Gutama Indra Gandha
Dedi Nurcipto

Abstract

Tingginya tingkat pencemaran air menyebabkan peningkatan kadar nitrogen pada eksosistem perairan, telah memicu terjadinya fenomena eutrofikasi yang berbahaya bagi ekosistem perairan. Instalasi pengolahan air limbah atau Wastewater Treatment Plant (WWTP) merupakan solusi pengendalian pencemaran air. Pengendalian kadar cemaran nitrogen pada instalasi pengolahan air limbah tergolong tidak mudah dikarenakan perilaku bakteri pada reaktor biologis yang sukar diprediksi. Pengujian strategi kendali kadar nitrogen dilakukan dengan menggunakan model BSM1(Benchmark Simulation Model no.1). Manipulasi laju sirkulasi internal digunakan untuk mengendalikan kadar nitrogen. Dengan mengimplementasikan pengendali nitrat berbasis Fuzzy-PID, didapatkan kualitas cemaran dengan kadar nitrogen dan ammonia lebih rendah dibandingkan dengan kendali PID konvensional. Kadar nitrogen dan ammonia berkurang sebesar 0.17 mg N/l (0.99%) dan 0.1 mg N/l (3.4%). Konsumsi energi listrik yang dibutuhkan instalasi pengolahan limbah selama 14 hari turun sebesar 193 kWh.

Downloads

Download data is not yet available.

Article Details

How to Cite
[1]
G. Gandha and D. Nurcipto, “Strategi Kendali Kadar Nitrat Berbasis Fuzzy-PID pada Proses Nitrogen Removal di Instalasi Pengolahan Air Limbah”, INFOTEL, vol. 8, no. 2, pp. 124-131, Nov. 2016.
Section
Articles

References

[1] V G Gude, "Energy and water autarky of waste water treatment and power generation system," Renewable and Sustainable Energy Reviews, pp. 52-68, 2015.
[2] G V Gnaneswar, "Energy storage for desalination processes powerred by renewable energy and waste heat source," Appl Energy, pp. 77-98, 2015.
[3] China Water Risk. (2014) www.chinawaterrisk.org. [Online]. www.chinawaterrisk.org
[4] Zhang Wenqiang , Jin Xin , Liu Dong, Lang Chao, and Shan Baoqing, "Temporal and spatial variation of nitrogen and phosphorus and eutrophication assessment for a typical arid river- Fuyang River in northern China," Journal of Environmental Sciences, pp. 2-7, 2016.
[5] International Water Association, The description of Benchmark Simulation Model.: International Water Association, 2004.
[6] Haimi Henri, Mulas Michela, and Vahala Riku, "Process automation in Wastewater Treatment Plants: the Finnish experience," Official Publication of the European Water Association (EWA), pp. 1-17, 2010.
[7] S Wenshao, C Xiaochuan, and P C Jean, "Application of model predictive control to the BSM1 benchmark of wastewater treatment process," Computer and Chemical Engineering, vol. 32, pp. 2849-2856, 2008.
[8] Alex Jen, Benedetti Lorenzo, Copp John, and V Kris, Benchmark Simulation Model no.1(BSM1)., 2008.
[9] Vilanova Ramon, Katebi Reza, and Wahab NoraLiza, "N-Removal on Wastewater Treatment Plants: A Process Control Approach," Journal of Water Resource and Protection, pp. 1-11, 2011.
[10] M Sustarsic, "Waste water treatment : Understanding the activated sludge process," Safety in ammonia Plants and related facilities symposium, pp. 26-29, 2009.
[11] A Water, Biological Nutrient Removal. Washington, United States: United States Environmental Protection, 2007.
[12] S Jeyanayagam, "True Confessions of the Biological Nutrient Removal Process," Florida Water Resource Journal, 2005.
[13] L T Hao and C Hongping, "Nitrification at full-scale municipal wastewater treatment plants:Evaluation of inhibition and bioaugmentaion of nitrifiers," Biosure Technology, pp. 76-81, 2015.
[14] L Viktor, Energy savings with a new aeration and control system in a mid-size Swedish Waste Water Treatment Plant. Sweden: Upsalla Universitet, 2011.
[15] I Smets, "Analysis and synthesis of mathematical algorithms for optimization and control of complex (bio) chemical conversion processes," Katholieke Universiteit Leuven, Belgium, Ph.D. Thesis 2002.
[16] S Wenhao, T Erpan, and L Tianlong, "Study of Composite Fuzzy Control of Dissolved Oxygen in a Sequencing Batch Reactor Pilot Process of Synthetic Papermaking Wastewater," International Conference on Robotics and Biomimetics, pp. 1262-1267, 2012.
[17] B Holenda, E Domoskos, A Redey, and J Fazakas, "Dissolved oxygen control of the activated sludge wastewater treatment process using model predictive control," Computers and Chemical Engineering , vol. 32, pp. 1270-1278, 2007.
[18] K S Holkar and L M Waghmare, "An Overview of Model Predictive Control ," International Journal of Control and Automation, vol. 3, pp. 47-64, 2010.
[19] V M Cristea, P Christian, and S A Paul, "Model Predictive Control of the Waste Water Treatment Plant Based on the Benchmark Simulation Model No.1-BSM1," 18th European Symposium on Computer Aided Process Engineering, pp. 1-6, 2008.
[20] I Santin, C Pedret, and R Villanova, "Fuzzy Control and Model Predictive Control Configurations for Effluent Violations Removal in Wastewater Treatment Plants," I&EC Research, pp. 2763-2775, 2015.
[21] Gutama Indra Gandha and Yiqi Liu, "Control of WWTP Integrating Model Predictive Control with Fuzzy Theory," South China University of Technology, Guangzhou,China, Master Thesis 2015.
[22] J Alex et al., "Benchmark for evaluating control strategies in wastewater treatment plants," in ECC'99(European Control Conference), Karlsruhe,Germany, 1999.
[23] Dong Shu-cheng, Jiang Feng-xin, Chen Jie, Zhang Hong-fei, and Wang Jian, "Fuzzy-PID Based Heating Control System," Senior Member, IEEE, May 2016.
[24] Santin Ignacio, Pedret Carles, and Vilanova Ramon, "Control strategies for ammonia violations removal in BSM1 for dry, rain and storm weather conditions," 2015 23rd Mediterranean Conference on Control and Automation (MED), pp. 577-582, 2015.
[25] S Kim K, C Kim Y, H Keel L, and P Bhattacharyya S, "PID controller design with time response specifications," American Control Conference, 2003. Proceedings of the 2003, June 2003.