⚡ Battery Optimization Simulation

An end-to-end simulation platform to assess the performance and economic viability of battery energy storage systems (BESS) when co-located with renewable energy sources like solar or wind. The model considers real-world constraints like degradation, price volatility, and system limits to provide actionable insights.

🔍 Objectives

• Simulate BESS behavior under different market and generation scenarios.
• Optimize dispatch to maximize revenue or minimize cost.
• Evaluate financial indicators such as NPV, ROI, and payback period.
• Model degradation over time to reflect battery aging realistically.

🧠 What It Does

The simulation framework includes:

📈 Renewable + Market Inputs

• Uses SCADA-like profiles for solar or wind generation.
• Pulls or simulates day-ahead price data for market participation.

🔋 Battery Modeling

• Charge/discharge logic with:
• Round-trip efficiency
• Power and energy constraints
• Cycle limits per day
• SOC tracking with initial state and ramping rules

🧮 Optimization Layer

• Solves for daily or hourly dispatch schedules
• Uses linear programming to maximize revenue or arbitrage opportunities
• Constraints ensure operational feasibility

📉 Degradation Modeling

• Calendar and cycle degradation combined
• Impacts available capacity over time
• Affects revenue and ROI in the long run

💰 Financial Analysis

• Initial investment, O&M cost, and degradation-related replacement
• Revenue from energy arbitrage or peak shaving
• Outputs:
• NPV
• IRR
• Payback Period
• Total Profit

🛠️ Technologies Used

• Python (Pandas, NumPy, Matplotlib, SciPy)
• PuLP for optimization
• Dash or Streamlit (optional UI layer)
• CSV/Excel for input-output compatibility

📊 Sample Visuals

(Insert images here from your /images/ folder if available)

• SOC over time
• Price vs battery dispatch
• Capacity fade over years
• NPV vs battery size

🌍 Applications

• Pre-investment feasibility for utility-scale or C&I batteries
• Trade-off analysis between battery size and economics
• Scenario planning for market volatility and degradation stress