Simulation of Hydro Power Plant using MATLAB

simulation model of hydro power plant using matlab/simulink and matlab model of hydro power plant and hydro power plant lecture notes video lecture on hydro power plant
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I.J. Intelligent Systems and Applications, 2015, 08, 1-8 Published Online July 2015 in MECS (http://www.mecs-press.org/) DOI: 10.5815/ijisa.2015.08.01 Modelling and Simulation of Hydro Power Plant using MATLAB & WatPro 3.0 Jahnvi Tiwari Shri Mata Vaishno Devi University, Electronics & Communication Engineering, Katra (J&K), 182320, India E-mail: 2011eec30smvdu.ac.in Ashish Kumar Singh, Ashish Yadav, Rakesh Kumar Jha Shri Mata Vaishno Devi University, Electronics & Communication Engineering, Katra (J&K), 182320, India E-mail: 2011eec05, 2011eec23smvdu.ac.in, jharakesh.45gmail.com Abstract— Increase in demand of electricity and clean drinking water has produced a chronic need of a promising and reliable I. INTRODUCTION technology for the supply of both commodities, which should be One of the major problem in present scenario is power entirely based on renewable sources of energy. The authors, in their previous work, had proposed a design of a hybrid power generation, which is the root cause of depletion of fossil plant which used graphene membrane for power generation fuel. An efficient and effective techno-economic using reverse osmosis process. The proposal included removal renewable power generation techniques is proposed for of arsenic, poorly biodegradable pollutants using TiO 2 trapping energy which is released during the mixing of nanoparticles. Chlorine production using the process of seawater and freshwater. In consideration of centralized electrolysis. The plant was also electronically implemented and and decentralized frameworks for drinking water included pump control, fouling detection modules and decision regulation in the context of risk management theory and module for the volume of effluents to be discharged. The practical challenges. The second most critical problem performance of a power system is essential to be analyzed for control, stabilization and efficient modelling. In the present analyzed here is purification of contaminated water. research paper, simulation model of the hybrid plant is analyzed. Chemical purification is analyzed in detail in the paper. The chemical behavior is analyzed with 'Watpro 3.0' industrial The proposed hybrid power and purification plant could software and turbine governance system is studied via be the key for a regular and safe supply of drinking water MATLAB. This plant is a potential replacement of chemical as well as power. This plant is a boon for regions of the purification techniques with high overhead and excess cost. It is world stricken with water or power scarcity and water a better, efficient, safe and reliable system to produce clean and contamination. The basic architecture of the proposed safe drinking water and electricity simultaneously. plant model is shown in figure 1. Index Terms— Reverse Osmosis, Graphene Membrane, Chlorine, Electrolysis, Pump Control, Fouling Detection, TiO 2 Nanoparticles. Fig. 1. Hybrid Model Copyright © 2015 MECS I.J. Intelligent Systems and Applications, 2015, 08, 1-8 2 Modelling and Simulation of Hydro Power Plant using MATLAB & WatPro 3.0 Here, the salty water and fresh water enters the Water container collects raw water and its quantity is osmosis chamber simultaneously for the process of controlled electrically with advanced chemical reverse osmosis. The pressure generated in the chamber is governance system and self-excited induction generator. used to rotate the turbine which in turn, generates From chemical container the disinfectants are injected in electricity which is transmitted to the power line. The appropriate amount, dosage is calculated and water from the turbine chamber is then directed to the automatically valves opens for a fixed time. As shown in clarifier, which separated solid from the water and figure 2, the height of water container is ‗h‘ with its area primarily removes some micro-organisms. The clean ‗A‘ and let us assume the pressure at top of container be effluent is treated with Fe (SO ) and KMnO to reduce , pressure at out valve be , diameter of orifice be 2 4 3 4 metal levels, taste and odor causing compounds. and lower limit of minimum water level be .For In processing plant, channels are working as a storage simple analysis fluid is taken as incompressible. which contains large quantities of fluid which is to be Applying Bernoulli‘s equation we get 1. treated. This fluid should be treated as quickly as possible to maintain the flow rate for reducing contamination. Fig. 2. Model for governance system Where and is the height and velocity of fluid at top of container respectively whereas and is the Mass flow out of container ( ) height and velocity of fluid at bottom of container = (8) respectively. Velocity of fluid at surface is taken to be negligible. Here, we have assumed inlet mass of fluid to be constant . √ With this velocity fluid comes out of container. So, the √ ( ) amount of fluid transferred to reaction tube will be required for chemical addition. From comparing (6) and (10) we get Fluid Mass = Fluid Volume Fluid Density (4) √ ( ) Rate of change of mass inside container can be expressed as difference of fluid mass entering and mass Similarly, chemical additive is also analyzed and flow out 1. numerical model is constructed using Simulink/MATLAB software GUI system. We have Copyright © 2015 MECS I.J. Intelligent Systems and Applications, 2015, 08, 1-8 Modelling and Simulation of Hydro Power Plant using MATLAB & WatPro 3.0 3 designed a GUI system, shown in figure 4, interconnected to Simulink model, as show in figure 3. Fig. 3. MATLAB model for chemical control This plant includes variable fluid container whose dimension is controlled using GUI. Slider are provided to III. GRAPHICAL ANALYSIS OF GENERATED RESULTS change the area of container, input rate of flow, output Using MATLAB, graph has been plotted and detailed flow rate, height of the container and lowest limit unto analysis of these graphs is explained in Table 1. which system will be force to shut-down. With different parametric value, the rate of diffusion of chemical is Table 1. Detail Analysis different and hence, its level is displayed on the LED Time(s) Observation and conclusion screen. Chemical container is also connected with power valve which is controlled using chemical governance Inlet valve to fluid container is ON, as a result of which, container height keeps on increasing. Out system. From simulation point of view parameters are valve status is OFF and flush pulse is not active. fixed using slider panel, as shown in figure 4. 0 - 45 Amount of chemical calculated and injected automatically by GUI decrease the level of chemical. Container reaches its maximum value i.e. 10 m and Input valve is automatically closed i.e. transition from ON to OFF. Flush pulse is not 45 - 49.5 active and out valve status remains constant in OFF mode. GUI transfer chemical in appropriate amount hence level decrease. Container is at its maximum and flush pulse is deactivated, input valve status changes from OFF 49.5 - 50 to ON as a result of ON out valve. Chemical level still keeps on decreasing i.e. chemical is injected. Container fluid level starts decreasing as out valve is in ON mode while input value is ON but 50 - 53 with different flow rate. Flush pulse gets active as chemical additive matches fluid requirement. Fig. 4. GUI for chemical additives Chemical level starts increasing. Container fluid level keep on decreasing with II. RELATED WORK 53 - 72.3 input valve ON. Out valve status is ON with rise in chemical level. Flush pulse not triggered. Many research works have contributed to design quality measuring devices for treatment of water 2.The statkraft decided to set up a promising critical Container fluid level start increasing and input components as membranes and pressure recovery devices valve status is ON with output valve switched 72.3 - 150 which lead to the world‘s first prototype plant in spring OFF. Decrease in level of chemical occurs with 2009 in the southeast of Norway 3.The wastewater flush pulse to be deactivated. treatment plants market in India is expected to grow at a CAGR of 15% till 2018, the ―Deep Pond System‖ in Hyderabad treats 37,854 liters of wastewater per day; this system was implemented as a low-cost wastewater treatment unit in 2004 at the Jawaharlal Nehru Technology University campus in Hyderabad, India4. Copyright © 2015 MECS I.J. Intelligent Systems and Applications, 2015, 08, 1-8 4 Modelling and Simulation of Hydro Power Plant using MATLAB & WatPro 3.0 IV. CHEMICAL ANALYSIS USING WATPRO 3.0 Chemical addition to water is again a very important work to be done with exact concentration value dosage of additives. This can be dreadful if human error occurs which is highly probable. Therefore, an automated system is developed for governance of concentration of chemical additives with appropriate fluid concentration. Governance system is simulated using WatPro 5 and analyzed for better results, so for small prototype we have assumed some parameters and observed the result. Watpro software model of chemical addition is show in figure 6. From figure 6, different block position is expressed: A1 (Raw Water Influent), A3 (Measurement), B3 (Channel), C3 (Flocculator), D1 (Addition Ferrous Sulfate), D3 (Membrane), E3 (Settling Basin), F1 (Addition CO2), F3 (Transfer/Distribution Pipe), G1 (Potassium Permanganate), G3 (Filtration), H3 (Ultraviolet Contactor), H4 (Calcium Hydroxide) I1 (Disinfect Addition Chlorine), J3 (Measurement), K3 (Final Treated Water Effluent). We will discuss independently every single step involved for water Fig. 5. Graphical Status of Chemical Governance System purification. Fig. 6. Chemical Analysis Table. 2. Initial properties of contaminated water A1 Raw Water Influent The outlet of turbine is connected to advance electronic Property Value Unit 3 system which is designed to remotely access the chemical Flow 64800 m /day 0 and disinfectant additives. Small prototype of this hybrid Temperature 10 C plant is stimulated using WatPro 3.0 a water treatment pH 7.5 simulation software. For simulation propose, raw water Turbidity 0.5 NTU influent which is further transferred to small channel for UV254 0.1 1/cm suspension of heavy sediment. Total Organic Carbon 3 mg/L Carbonates (aq) 218.17 mg/L A3 Measurement Calcium 80 mg/L Raw water which is to be treated is measured for Magnesium (aq) 20 mg/L different properties. We have assumed input flow rate to 3 0 Alkalinity 100 mg/L be 64800 m /day at a temperature of 10 C with other Hardness 100 mg/L parameters stated in table 2. It can be observed that water pH is around 7.5 and hardness 100 mg/L which Ammonia as N mg/L contributes to the scaling of water boiler. Bromide 0.10 mg/L Giardia 1.00 cysts/100L Copyright © 2015 MECS I.J. Intelligent Systems and Applications, 2015, 08, 1-8 Modelling and Simulation of Hydro Power Plant using MATLAB & WatPro 3.0 5 Turbidity allowed is maximum 5 NTU. Above 5 NTU, E3 Settling Basin consumer acceptance decreases. The permissible limit of Settling basin is used for settlement and to reduce the pH is 6.5 to 8.5, beyond this range it affects mucous outlet turbidity. membrane and water supply systems. Presence of Table. 7. Turbidity details calcium carbonates which is also the measure of hardness can be maximum 300 mg/L. Above this level Property Value Unit Encrustation in water supply structure takes place and it 3 Volume 200.00 m also has adverse effects on domestic use. Alkalinity Measured Turbidity 0.15 NTU measured in mg/L, can be maximum upto 200. Beyond this limit taste becomes unpleasant. F1 Addition CO2 CO addition in water causes leaching of various 2 B3 Channel elements which could be hazardous to life. It is used to Fluid container is used for storing water and to control reduce the effect of arsenic, zinc, lead etc. Raw water the rate of flow of fluid toward pipeline. In MATLAB absorbs CO and due to chemical reaction reduction in 2 model we have assumed a variable channel whose length pH and carbonate ion concentration is observed. and area can be adjusted using GUI. Table. 8. Carbon dioxide dosage Table. 3. Water storage tank dimension Property Value Unit Property Value Unit Chemical Dosage 10.00 mg/L Length 10.0 M Depth 10.0 M Width 10.0 M F3 Transfer/Distribution Pipe Dimension of pipe is estimated for appropriate addition of chemical additives which reduces the chance of excess C3 Flocculator chemical concentration. Flocculator chamber is used for separating small particles. In this chamber, a process take place where Table. 9. Dimension of pipeline colloids are separated from suspension in form of flakes. Turbidity of raw water is decreased from 0.5 to 0.2 NTU Property Value Unit which Length 100.00 m Diameter 1.00 m Table. 4. Turbidity details Property Value Unit G1 Potassium Permanganate (KMnO ) 4 3 Volume 200.00 m This is used for the removal of taste and odor from Turbidity 0.20 NTU flowing water, to oxidize a wide variety of inorganic and organic substances and to completely inactivate bacteria. D1 Addition Ferrous Sulfate Water borne diseases are major threat which can be Distribution pipe drives water to chamber for treatment decreased by controlling dosage of KMnO from 0.25 to 4 with Fe (SO ) for removal of heavy metals. It is more 20 mg/L 3. 2 4 3 efficient coagulant which removes chromium (89.58%), Table. 10. Dosage of KMnO Ni (99.73%), Zn (68.42%) and Mn (35.29%) from fluid 4 with 13 mg/L dosage 6. Property Value Unit Dosage 4.00 mg/L Table. 5. Chemical amount of Fe (SO ) 2 4 3 Property Value Unit G3 Filtration Filter type used is conventional because it follows Chemical Dosage 22.5 mg/L coagulation and sedimentation and it can be used for variable turbidity and bacteria level. Fluid flow rate D3 Membrane should be maintained, if flow rate is very high sediments Molecular weight cut-off can be defined as the will cross the pores. molecular weight at which 80% of the analytes (or solutes) are prohibited from membrane diffusion. Here, user Table. 11. Filtered output fluid specifies the water production percentage through Property Value Unit membrane and optionally the effluent turbidity 7. 3 Volume 300.00 m Table. 6. Fluid properties at membrane Measured Turbidity 0.1 NTU Property Value Unit Molecular weight cut-off 500.0 g/mol H3 Ultraviolet Contactor Operating pressure 300.0 kPa It is the most commonly used for disinfection of water Recovery 30.00 by causing damage to the genetic structure of bacteria, Copyright © 2015 MECS I.J. Intelligent Systems and Applications, 2015, 08, 1-8 Hardness (mg/L) 6 Modelling and Simulation of Hydro Power Plant using MATLAB & WatPro 3.0 viruses, and other pathogens, making them incapable of has adverse effect on domestic uses and water supply multiplication 8. Non-biodegradable substance is structures. treated in presence of titanium oxide nanoparticle 9. K3 Final Treated Water Effluent Table. 12. Properties of fluid after ultra violet treatment Finally raw water after crossing numerous process gives pure and safe drinking water. One of the major Property Value Unit factor is turbidity which is reduced from 0.5 to 0.1 NTU. Log Inactivation Giardia 2.00 log(10) It is measured by scattering of light, if intensity is low Log Inactivation Virus 4.00 log(10) turbidity is less while, high intensity leads to high turbidity. Log Inactivation Cryptosporidum 2.00 log(10) Table. 15. I1 Disinfect Addition Chlorine Disinfection Criteria Status Result Unit In contaminated water it is necessary to kill sever harmful microorganisms and for this chlorination of Req. Giardia Reduction 4.00 OK 4.50 log(10) water is necessary. In this plant, chlorine is produced Req. Virus Reduction 5.00 OK 6.00 log(10) using brackish water for electrolysis and generating free Req. Crypt Reduction 2.00 OK 4.00 log(10) chlorine. It reacts with ammonia if present in raw water and forms chloramines. For simulation purpose, 2 mg/L Max Chlorine Allowed 4.00 OK 2.00 mg/L chlorine dosage is used for chlorination. Max Turbidity Allowed 0.50 OK 0.10 NTU Table. 13. Fluid chlorination dosage Property Value Unit V. CONCLUSION Chemical Dosage 2.00 mg/L The paper here proposes and analyses an efficient, productive hybrid plant for power generation and water For chlorination the main disinfecting agents can be purification. The central idea is to combine two separate produced from the naturally occurring ions found in the efficient entities for the purpose. waste salty water (unpressurised water) itself as stated by Chen-Yu Chang Yi-Tze Tsai 10. 110 110 Alkalinity 100 Hardness J3 Measurement 100 90 This indicator flashes output and treats fluid with 90 appropriated chemical addition, stabilization and 80 mineralization. Rate of flow is decreased to maintain the 70 80 flow in pipeline and for reaction time. Drinking water pH 60 70 is around 7 which is near to ideal. The high energy 50 associated with short wavelength UV energy, primarily at 60 40 254 nm, is absorbed by cellular DNA can damage the 30 DNA of living organisms by creating nucleic acid dimers 50 20 11. 40 10 Table. 14. Properties of treated fluid 0 30 A3 C3 E3 G3 J3 Property Value Unit Stage 3 Fig. 6. Alkalinity and Hardness of water at different stages Flow 19440 m /day 0 Temperature 10 C Electricity production with purification of water with pH 7.01 this eco-friendly advance system is a cost effective Turbidity 0.1 proposed solution for lack of clean water and electricity. UV254 1/cm Raw drinking water is finally converted to pure form with proper balancing of hardness and alkalinity. This can be Total Organic Carbon 0.69 mg/L shown in figure 6. Water pH is another important Carbonates (aq) 34.39 mg/L parameter for drinking. Initially raw water is taken whose Calcium 35.32 mg/L pH was not safe therefore due to treatment through Magnesium (aq) 0.39 mg/L different stages its pH value is brought down towards Alkalinity 13.37 mg/L neutral. Treatment process on different versus pH is Hardness as CaCO 35.70 mg/L shown in figure 7. 3 Ammonia mg/L Manganese (as Mn) mg/L can be nearly 0.3-0.4. Beyond this range taste/ appearance are affected which Copyright © 2015 MECS I.J. Intelligent Systems and Applications, 2015, 08, 1-8 Alkalinity (mg/L) Modelling and Simulation of Hydro Power Plant using MATLAB & WatPro 3.0 7 1 Germeles, A. E. "Forced plumes and mixing of liquids in 7.5 tanks." Journal of Fluid Mechanics 71.03 (1975): 601-623. 2 Pawan Whig, Syed Naseem Ahmad,"Performance Analysis 7.4 of Various Readout Circuits for Monitoring Quality of Water Using Analog Integrated Circuits", IJISA, vol.4, no.11, pp.91-98, 2012. 7.3 3 Skrå mestø , Øystein S., Stein Erik Skilhagen, and Werner Kofod Nielsen. "Power production based on osmotic 7.2 pressure." Waterpower XVI (2009). 4 Grail Research, Water - The India Story, 2009. 7.1 5 http://www.hydromantis.com/WatPro.html. 6 Tiwari, Jahnvi, Ashish Kumar Singh, Ashish Yadav, and Rakesh Kumar Jha. "Sustainable power production and 7.0 purification of water." In Advances in Computing, Communications and Informatics (ICACCI, 2014 6.9 A3 C3 E3 G3 J3 International Conference on, pp. 2258-2263. IEEE, 2014. 7 Dudley J, Dillon G, et. al. 2008, ―Water Treatment Stage Simulators: State-of-Theart Review‖ Fig. 7. pH of water at different stages 8 Note for Guidance on Virus Validation Studies: The Design, Contribution and Interpretation of Studies Water turbidity is measure of water clarity. Here Validating the Inactivation and Removal of Viruses, different filtration technique is used for the proper EMEA CPMP BWP, 268/95 1996. separation of suspended particles from water and make it 9 T.A. Egerton, P.A. Christensen, S.A.M. Kosa, B. Onoka, pure enough to drink. This suspended particle are not J.C. Harper, J.R. Tinlin ―Photoelectrocatalysis by titanium visible from naked eyes and from below figure 8, it can dioxide for water treatment‖ Int. J. of Environment and be seen that finally turbidity is 0.1 NTU. Pollution, 2006 Vol.27, No.1/2/3, pp.2 – 19. doi: 10.1504/IJEP.2006.010450. 10 Chen-Yu Chang Yi-Tze Tsai, Yung-Hsu Hsieh, Chia- Lin 0.5 Yang Shu- Hai You, ―Using membrane electrolysis method to generate chlorine dioxide‖, International Conference on Environment Science and Engineering IPCBEE vol.8, Singapore, 2011. 0.4 11 Das, Tapas K. (August 2001). "Ultraviolet disinfection application to a wastewater treatment plant". Clean Technologies and Environmental Policy (Springer Berlin/ 0.3 Heidelberg) 3 (2): 69–80. doi:10.1007/S100980100108. 0.2 Authors’ Profiles Jahnvi Tiwari was born on February 9, 0.1 1993. She is expecting her bachelor of technology degree from Shri Mata A3 C3 E3 G3 J3 Vaishno Devi University, India, in 2015. Stage In 2014, she received Summer Fig. 8. Turbidity of water at different stages Undergraduate Research Grant for Excellence (SURGE) from Indian Institute Of Technology, Kanpur. Her research This system is designed to operate in any situation interests include systems designing, irrespective of fault occurrence like scaling, fouling and implementation, analysis and operation of embedded systems. clogging. WatPro 3.0 and MATLAB simulated result High efficiency Solar cell, water treatment plants power shows that raw water is treated and finally can be used for generation and optimization. Peer to peer network software safe drinking water. The automated chemical and valve development, tapestry and JXTA. She has publication in field of control reduces the risk of human error and over or under solar energy (Journal of Energy), water purification. dosing of effluents. This also reduces the manpower to be employed for the smooth working of the hybrid hydro Ashish Kumar Singh was born on power plant. October 3, 1992. He is expecting his bachelor of technology degree from Shri Mata Vaishno Devi University, India, in ACKNOWLEDGMENT 2015. His research experience include analysis and Impact of ART and DPC The authors acknowledge the use of Water Treatment on AODV Routing Environment for Simulation Model Version 3.0 program developed by Dynamic Network using QualNet 7.1 at Hydromantis Environmental Software Solutions, Inc. Indian Institute Of Technology, Varanasi in 2014 and Ge-content dependent efficiency of Si/SiGe heterojunction solar cell analysis at Indian School Of Mines, Dhanbad in 2013. He has contributed with his REFERENCES Copyright © 2015 MECS I.J. Intelligent Systems and Applications, 2015, 08, 1-8 Turbidity (NTU) pH8 Modelling and Simulation of Hydro Power Plant using MATLAB & WatPro 3.0 publication in several fields like photonics, silicon solar cells, autonomous irrigation system and power generation. Ashish Yadav was born on May 26, 1994. He is expecting his bachelor of technology degree from Shri Mata Vaishno Devi University, India, in 2015. He has experience as an intern at Visvesvaraya National Institute of Technology, Nagpur in designing, Testing and Verification of ADC Systems using nano-CMOS technology with low power/process design. His interest includes process variation tolerant circuit design, testing and verification of VLSI circuit systems and nano-CMOS technology, low power/process aware VLSI design. He has published in renowned journal and presented papers in various international conference. Rakesh K Jha: currently an assistant professor in school of electronics and communication department, SMVD University Katra (J&K). He is carrying out his research in WiMAX and Security issues in the laboratory ECED Lab, SMVDU. Involved research topics include WiMAX performance analysis, LBRRA, power optimization and security analysis. He has done B.Tech in Electronics & Communication from Bhopal and M.Tech from NIT Jalandhar, INDIA. Received his PhD degree from NIT Surat in 2013. Published more than 50 International Conference and Journal papers. His area of interest is Wireless communication, Communication System and computer network, and Security issues (Opti System). One concept related to router of Wireless Communication has been accepted by ITU (International Telecommunication Union) in 2010. Received young scientist author award by ITU in Dec 2010 and APAN fellowship in 2011. Also received student travel grant from COMSNET 2012. Dr. Rakesh K Jha is a member of IEEE, GISFI and SIAM, International Association of Engineers (IAENG) and ACCS (Advance Computing and Communication Society). Copyright © 2015 MECS I.J. Intelligent Systems and Applications, 2015, 08, 1-8