Скачать или смотреть Demand Response of Electric Vehicle EV in IEEE 33 Bus Part 2/4

In this video, we explore Demand Response (DR) for Electric Vehicles (EVs) in the IEEE 33 Bus System using Particle Swarm Optimization (PSO). We optimize EV charging/discharging to minimize power losses, reduce peak load, and lower system & customer costs while considering key constraints like SOC, line limits, and EV locations.

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🔍 Key Topics Covered:
✔ Introduction to Demand Response (DR) in EV Charging
✔ IEEE 33 Bus System Overview
✔ Particle Swarm Optimization (PSO) for EV Load Management
✔ Objective Functions: Minimizing Losses, Peak Load & Costs
✔ Constraints: SOC, Line Limits, EV Locations, Charging/Discharging Ability
✔ Input Parameters & Assumptions
✔ Two Scenarios: Base (No DR) vs. Optimized (With DR)
✔ Results & Graphs: Power Loss, Voltage Profile, Cost Analysis, Load Profile, EV Charging Behavior

📊 Results & Graphs Shown:
📉 Power Loss Comparison (Base vs. Optimized)
⚡ Voltage Profile Improvement
💰 Total System Cost & Customer Charging Cost Analysis
🔌 Load Profile & Peak Load Reduction
🚗 EV Charging/Discharging Profile

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