Minimising the Plot Size of Carbon Capture Plant:

Layout Optimisation Considering Cost and Safety Factors

Overview

This repository contains research, computational models, and analysis for optimizing the land footprint of carbon capture plants (CCPs). The study employs Mixed-Integer Linear Programming (MILP) to determine the optimal placement of process units while considering cost and safety constraints.

The objective is to reduce land footprint while ensuring compliance with safety regulations, focusing on piping/pumping costs, land purchase, and safety distances.

📌 Objectives

• 🏭 Optimize plant layout to minimize space usage.
• 🔥 Ensure safety compliance using Fire & Explosion Index (F&EI) and Chemical Exposure Index (CEI).
• 💰 Develop a cost estimation model based on engineering principles.
• 📊 Analyze land footprint trends for plant capacities ranging from 300MWe to 2200MWe.
• 📏 Compare square vs. rectangular plots to determine efficiency gains.

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🛠 Methodology

1️⃣ MILP-Based Layout Optimization

• Applied a 2D MILP model to optimize equipment placement.
• Considered land purchase, piping costs, and pumping costs as constraints.

2️⃣ Safety and Risk Assessment

• Dow Fire and Explosion Index (F&EI) and Chemical Exposure Index (CEI) used.
• Incorporated Industrial Risk Insurers' safety distances.

3️⃣ Cost Estimation Approach

• Based on Towler & Sinnott's cost correlations.
• Compared against IEA's cost estimates.

4️⃣ Computational Strategy

• Problem decomposition was used to manage large-scale flowsheets (up to 161 units).
• Layouts were tested for square vs. rectangular plots.

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📊 Key Findings

✔ Rectangular plots reduce land footprint by 40-47% compared to square plots.
✔ Land footprint is mainly dictated by safety distances, not process unit sizes.
✔ Reduction in footprint is limited by safety regulations.
✔ Land requirement per MWe decreases sharply from 300MWe to 1300MWe, then stabilizes.

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