A Price based scheme for Demand Side Management of Discrete Industrial Process in Smart Grid

Implementation of Demand Response (DR) Energy Management Schemes for industries is critical, as they are the major consumer of electricity and play a pivotal role in economy of a country. The use of Advanced information and communication technologies (ICT) in S

Project Title

A Price based scheme for Demand Side Management of Discrete Industrial Process in Smart Grid

Project Area of Specialization

Electrical/Electronic Engineering

Project Summary

Implementation of Demand Response (DR) Energy Management Schemes for industries is critical, as they are the major consumer of electricity and play a pivotal role in economy of a country. The use of Advanced information and communication technologies (ICT) in Smart Grid provides an opportunity for industrial electricity consumers to manages the load during peak and off-period of electrical demand which reduces the electricity consumption cost. 

DR energy management is a key technology enabling a balance of electricity demand/supply and in improving the grid reliability. Furthermore, DR scheme implementation is essential in Pakistan since, demand/supply Gap is one of the major energy challenges in Pakistan, such as, in 2015, there was average gap about 5,000 MW, which lead to about 10 to 12 hours of load shedding.

In this study, a state-task network (STN) model for a flour mill is utilized to develop a DR energy management scheme. The specific DR algorithm determines the optimal operating points for schedulable task (ST), to manage electrical power demand between peak and off-peak periods. The MATLAB results integrated with the micro-controller as commands to control modelled electrical load. The simulation results exhibit that the DR scheme will act as a tool to reduce the electricity consumption cost up to 33 % without compromising the production process. This cost effective DR scheme is a reality which is feasible to implement on all industrial processes of Pakistan.

Project Objectives

 Aim is to implement DR energy management scheme in industries which manages load during peak and off-peak period to reduce electricity consumption cost.

Objectives:

1. Model a discrete industrial process in Pakistan and develop its specific DR energy management algorithm which manages electrical load during peak and off-peak periods without compromising the production process. Hence, we successfully developed a specific DR algorithm of Flour Mill Industry in Pakistan.
2. Develop a hardware prototype that replicates the electrical load of flour mill industry.
3. Validate the DR energy management algorithm outcomes by integrating MATLAB through a controller with the hardware module.
4. Exhibit schedulable task load operating at optimal operating point for each time interval on the hardware module for efficiently managing electricity consumption cost. 

Project Implementation Method

Our Approach:

Based on the inputs (including electricity price, STN model of industrial facilities, and the operating information of each task), the DR algorithm selects the optimal operating points for each schdeulable task (ST) within pre-specified time intervals to efficiently manage electricity consumption in hardware module representing industrial load demand.

Data Collection:

• A flour mill situated in Pakistan was considered as a reference for modelling State Task Network (STN), which provides with basic information about the load demand in flour production.
• KE Time of Use (TOU) prices for peak and off peak demand periods.

Proposed DR Energy Management Scheme:

By considering industrial requirements, the design of the system is proposed. Our system is comprised of these main components:

1. Excel Sheet Input Data set
2. MATLAB for scheduling Algorithm
3. Main Controller Integration to perform scheduling
4. Load Controller
5. Load

DR algorithm initializes with required production scenario. Then Excel Sheet supplies MATLAB with the task information. These flour mill tasks are then further classified into schedulable task (ST) & non-schedulable task (NST). Constraints are applied which creates multiple data sets with different operating points for each ST while, NSTs are always ON. Finally our cost minimizing function, selects the best dataset without compromising the production process.

After scheduling, MATLAB provides the integrated controller (Arduino) with the following information: the operating mode of the schedulable tasks and the operating time of that operating mode. Finally the load controller switches the load accordingly.

Therefore, our prototype exhibits cost effectivness of 32% achieved by integrating the DR energy managemnt scheme for industrial consumers.

Benefits of the Project

The DR energy mangement scheme provides benefits for the electicity consumers as well as the electrical utility as explained in follwoing points:

1. Financial benefits for the industrial consumers by saving on electrical consumption cost. This supports UN Goal 9 : Industry, Innovation and Infrastructure which is to increase investments in technological innovation and industrialization.  
2. Reducing peak power demand improves the reliability of the electrical grid. Less demand means less stress on transmission and distribution networks which means less power failures or outrages.
3. DR schemes enables reduced need for excess generation capacity to serve peak loads hence better electrical power demand/supply relation.
4. Lower environmental impact due to reduced power generation demand. Hence, UN Goal 7: Affordable and Clean Energy which is to increase energy efficiency and the use of clean energy.

Technical Details of Final Deliverable

Technicalities of our final deliverable are divided into Software and Hardware defining strategies used to compute our final results. 

• Software/Simulation:

To visualize our algorithm, we have used MATLAB version 2017 for programming. Our Algorithm is composed of mixed algorithms covered by MATLAB description of some major are as follows:

Queuing:

Queues order entities; sorting according to queue policies. Concerning our algorithm, we have multiple number of equipment added to a starting queue, which are further sorted by minimization function.

Minimization Function:

MATLAB provides its users to define their optimization problem with functions and matrices. For our algorithm, we have used minimization function as a tool to optimize and choose the data-set formed earlier in our algorithm with minimum electrical cost for a given time interval.

• Smart Draw:

A visual processor used to create flowcharts, and other visuals. We have used this software to create State-task Network (STN) model, to represent the process flow of the flour mill.

• Hardware:

In order to fulfill the load requirement of the DR scheme for Flour Mill, the proof of concept is modelled on these three points:

i.          Low Cost

ii.         Low Power Consumption

iii.        Reliable

The prototype of our concerned project have the following major technicalities:

Integration between Arduino and MATLAB:

MATLAB allows its users to write MATLAB programs that read and write data to your Arduino. We have to integrate Arduino with MATLAB using various function blocks.

Arduino:

We have choosen Arduino as microprocessor for our prototype which is a great tool for developing interactive objects. Concerning our prototype we are integrating Arduino with MATLAB which will act as a channel to convert the resulted data into commands which are forwarded to the relays and sensors, which will further outcast the results on the prototype.

Also two Arduino are integrated to perform serial communication with relationship of sender & receiver in between such as having one Arduino to operate the load of our prototype and sending relay commands to the other which is reading the MATLAB data by sensing the surrounding.

Relay Modules:

The relay module is a separate hardware device used for remote device switching. We use it to supply load according to Arduino signals.

Relay Driver:

Using to switch inductive loads and to drive motors.

1. Connected Load representing the flour mill industry electrical demand,
2. DC motor
3. Blubs

LCD :

Screens are integrated with the two Arduinos which will display the names of processes turned on or off signified as LEDs or motors on our prototype and classify them as either Schedulable and Non-Schedulable loads based on the commands given by the MATLAB.

5V DC Power Supply:

Standard 5V DC power supply for powering the circuit.

Final Deliverable of the Project

HW/SW integrated system

Core Industry

Energy

Other Industries

Core Technology

Artificial Intelligence(AI)

Other Technologies

Sustainable Development Goals

Affordable and Clean Energy, Industry, Innovation and Infrastructure, Responsible Consumption and Production

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com