Development of a Load Shedding and Demand Response System

 

Development of a Load Shedding and Demand Response System - Electrical Engineering Guide

1. Introduction

Load shedding and demand response are essential strategies to maintain grid stability during peak load conditions. This project involves developing a system that intelligently sheds or shifts loads based on real-time energy consumption and grid signals.

2. Objectives

• Design an automated system for load prioritization and shedding
• Enable real-time demand response to grid signals
• Improve energy efficiency and reduce power outages

3. System Overview

The system monitors total power consumption and controls appliances or circuits based on priority levels. In critical conditions, it sheds low-priority loads and maintains essential services.

4. Key Components

• Microcontroller (Arduino, ESP32)
• Current and voltage sensors
• Relays for switching loads
• Wi-Fi/GSM module for communication
• Display and indicators

5. Load Prioritization Strategy

Loads are categorized into high, medium, and low priority. During demand surges, low-priority loads are disconnected first, followed by medium if necessary.

6. System Design and Architecture

• Central control unit reads sensor data
• Uses logic to determine shedding requirements
• Interfaces with relays to disconnect specific loads

7. Microcontroller and Sensor Integration

• Voltage and current sensors measure consumption
• Data is processed by the microcontroller
• Loads are controlled via output relays

8. Control Algorithms and Logic

• Load shedding triggered when consumption exceeds threshold
• Algorithms determine which loads to shed and when to reconnect them
• Can incorporate AI or rule-based methods

9. Communication Infrastructure

• GSM or Wi-Fi module sends data to server/cloud
• Alerts users about load shedding events
• Can receive signals from utility for demand response

10. Implementation and Testing

• Simulate varying loads
• Test system’s ability to shed and restore loads
• Monitor performance under real-time scenarios

11. User Interface and Monitoring

• Web or mobile app for user access
• LCD for real-time status display
• Manual override options

12. Safety and Reliability Measures

• Circuit breakers for protection
• Watchdog timer in code to prevent hangs
• Isolation between control and load sections

13. Applications and Benefits

• Smart homes and buildings
• Industrial load management
• Improves grid reliability
• Reduces blackout risks

14. Limitations and Challenges

• Complexity of demand prediction
• Latency in communication
• Integration with legacy systems

15. Future Scope

• AI-based predictive load management
• Integration with renewable sources
• Cloud-based analytics and automation

16. Conclusion

This project presents an effective solution for automated load shedding and demand response, contributing to smarter and more efficient energy systems.