AI & Machine Learning Approaches in Renewable Energy Systems_ DST - SERB Sponsored Virtual Workshop

AI & Machine Learning Approaches in Renewable Energy Systems_ DST - SERB Sponsored Virtual Workshop

Workshop Contents:

- Introduction to AI & ML

- Introduction to RES

- Recent Trends & Research in RES

- Simulation & Analysis of Solar Energy System using Matlab Simulink

- Modeling & Simulation of Fuel Cells in Matlab Simscape

Rankine Cycle with Reheat Steam Power Plant _Turbine Work output, Thermal Efficiency & T- S Diagram

Rankine Cycle with Reheat Steam Power Plant _Turbine Work output, Thermal Efficiency & T- S Diagram

This video will demonstrates a steam power plant operates on the ideal reheat Rankine cycle. Steam enters the high pressure turbine at 8 MPa and 500 C and leaves at 3 MPa. Steam is then reheated at constant pressure to 500 C before it expands to 20 kPa in the low pressure turbine. Determine the turbine work output, in kJ/kg, and the thermal efficiency of the cycle. Also show the cycle on a T-s diagram with respect to the saturation lines.

"!Pump analysis" P[1] = P[6] P[2]=P[3] x[1]=0 "Sat'd liquid" h[1]=enthalpy(Steam,P=P[1],x=x[1]) v[1]=volume(Steam,P=P[1],x=x[1]) s[1]=entropy(Steam,P=P[1],x=x[1]) T[1]=temperature(Steam,P=P[1],x=x[1]) W_p_s=v[1]*(P[2]-P[1]) "SSSF isentropic pump work assuming constant specific volume" W_p=W_p_s/Eta_p h[2]=h[1]+W_p "SSSF First Law for the pump" v[2]=volume(Steam,P=P[2],h=h[2]) s[2]=entropy(Steam,P=P[2],h=h[2]) T[2]=temperature(Steam,P=P[2],h=h[2]) "!High Pressure Turbine analysis" h[3]=enthalpy(Steam,T=T[3],P=P[3]) s[3]=entropy(Steam,T=T[3],P=P[3]) v[3]=volume(Steam,T=T[3],P=P[3]) s_s[4]=s[3] hs[4]=enthalpy(Steam,s=s_s[4],P=P[4]) Ts[4]=temperature(Steam,s=s_s[4],P=P[4]) Eta_t=(h[3]-h[4])/(h[3]-hs[4]) "Definition of turbine efficiency" T[4]=temperature(Steam,P=P[4],h=h[4]) s[4]=entropy(Steam,T=T[4],P=P[4]) v[4]=volume(Steam,s=s[4],P=P[4]) h[3] =W_t_hp+h[4] "SSSF First Law for the high pressure turbine" "!Low Pressure Turbine analysis" P[5]=P[4] s[5]=entropy(Steam,T=T[5],P=P[5]) h[5]=enthalpy(Steam,T=T[5],P=P[5]) s_s[6]=s[5] hs[6]=enthalpy(Steam,s=s_s[6],P=P[6]) Ts[6]=temperature(Steam,s=s_s[6],P=P[6]) vs[6]=volume(Steam,s=s_s[6],P=P[6]) Eta_t=(h[5]-h[6])/(h[5]-hs[6]) "Definition of turbine efficiency" h[5]=W_t_lp+h[6] "SSSF First Law for the low pressure turbine" x[6]=quality(Steam,h=h[6],P=P[6]) "!Boiler analysis" Q_in + h[2]+h[4]=h[3]+h[5] "SSSF First Law for the Boiler" "!Condenser analysis" h[6]=Q_out+h[1] "SSSF First Law for the Condenser" T[6]=temperature(Steam,h=h[6],P=P[6]) s[6]=entropy(Steam,h=h[6],P=P[6]) x6s$=' ('||Phase$(steam,h=h[6],P=P[6])||')' "!Cycle Statistics" W_net=W_t_hp+W_t_lp-W_p "net work" Eff=W_net/Q_in "cycle eficiency" Kindly Subscribe My YouTube Channel... Please like, share and comments on My Videos 🙏 Please click the below links to Subscribe/Join & View my Videos https: //www.youtube.com/c/DrMSivakumar For More Details about this Video Join/ View the following Telegram : t.me/Dr_MSivakumar website : drmsivakumar78.blogspot.com

How to set up a parametric table, re-solves for Power in & Vol.outflow rate for outlet temperatures

This Video shows how to solve thermodynamic problem using EES

Problem: A compressor takes in 1.2 kg/s of R-134 that is in a saturated vapor state at -24°C. The compressor outlet state is at 0.8 MPa and 100°C. Find: The power input of R-134 by the compressor, the volumetric flow rate at the exit and how much power must be provided by an electric motor if the compressor’s efficiency is 70%. Then, set up a parametric table that re-solves for both the power input and volumetric outflow rate for outlet temperatures: 180, 160, 100, and 80° C. No more than three sig figs for results computed for EES. In this video, we will use a thermodynamics problem - Courtesy of ES2310 taught by Dr. Paul Dellenback Step 1: Enter the problem information Step 2: Use EES to obtain the values of enthalpy and density at states one and two. Step 3: Enter the thermodynamics equations we want to solve for in EES Step 4: Build a Parametric Table for a range of temperatures at state two.

How to solve equations using EES Solver _ Step by Step Introduction to Engineering Equation Solver

How do you solve an equation with EES?

EES is a general equation- solving program capable of solving hundreds of non-linear algebraic and differential equations.

EES has built-in functions for the thermodynamic and transport properties of many substances and the capability for you to easily add your own functions.

EES can do regression and optimization.

The following will demonstrate how to solve simultaneous equations using EES.

The techniques used to solve the example problem may be applied to solve much more complicated problems.

Predict the Partial Load Performance of Rankine cycles: Spencer_ Cotton Cannon_Method _ Using Matlab (Modeling of Rankine Cycles using the Spencer, Cotton and Cannon method )

Modeling of Rankine Cycles using the Spencer, Cotton and Cannon method

This program uses the Spencer, Cotton and Cannon method to predict the partial load performance of Rankine cycles, using as input data the pre-design characteristics of the cycle's components. https://in.mathworks.com/matlabcentral/fileexchange/64914-modelling-of-rankine-cycles-using-spencer-cotton-and-cannon Félix Pérez Cicala (2022). Modelling of Rankine cycles using Spencer, Cotton and Cannon (https://github.com/FelixPerezCicala/ modRankineSCC), GitHub. The purpose of this video is to study the partial load performance of Rankine cycles using the Spencer, Cotton and Cannon method. This method can predict the isentropic performance of steam turbines in off - design conditions, using empirical correlations obtained by the method’s authors. A procedure was developed to calculate the performance and operating conditions of a Rankine cycle, using as input data the characteristics of the cycle’s components at the pre-design stage. The steam turbines and the feedwater heaters where modelled in detail. A Matlab program was developed using this procedure, thus enabling for the setting of different cycle options and an easy visualization of the results. The feedwater heaters are dimensioned and calculated using a thermal model. The program allows the user to simulate operation with off- line feedwater heaters and with partially closed extraction valves. The cycle’s pumps and condenser use a simplified model, and the steam gene- rator as well as the electric generator are not modelled, in order to give flexiblility program. Also See the examples below Modeling & Analysis of Residential Air Conditioning & Refrigeration System https://youtu.be/bfxEjDs7ENs Click here to download the file: https://drive.google.com/file/d/1BIgYCgE-lUU9_HnNGz7IeXwtaOmqGxO2/view?usp=sharing Click here to download the thesis file: https://drive.google.com/file/d/16rJ7Wo-DsLmNHMW-5g9d_yY1ZySvrP6-/view?usp=sharing https://in.mathworks.com/matlabcentral/fileexchange/64914-modelling-of-rankine-cycles-using-spencer-cotton-and-cannon Félix Pérez Cicala (2022). Modelling of Rankine cycles using Spencer, Cotton and Cannon (https://github.com/FelixPerezCicala/ modRankineSCC), GitHub.