🇳🇱 NL 2030 V2G Analysis — Merit Order & Battery Scenario Simulation

This MATLAB script performs a simulation of the Dutch electricity market in the year 2030 under different Vehicle-to-Grid (V2G) battery storage scenarios. Developed as part of the master's thesis by Mayk Thewessen, the model explores how increasing V2G capacity affects the hourly electricity price profile, based on merit order dispatch, solar PV and wind generation assumptions, and projected demand profiles.

🧠 Objective

To assess the impact of V2G penetration in the Netherlands in 2030 on:

• Hourly electricity prices
• Load shifting potential
• Renewable curtailment avoidance
• System-wide efficiency based on dynamic dispatch

🧮 Core Concepts

• Merit Order Pricing: Simulated hourly market prices based on generator marginal cost ranking.
• V2G Batteries: Simulated as flexible demand/supply depending on grid condition.
• Scenario Years: Simulation can span multiple test years.
• Renewables in 2030: Includes predefined solar PV and wind capacity.

📂 Main Steps in the Script

1. Initialize Environment (clear memory, set format)
2. Load Demand Data (readtable from XML/XLSX/CSV formats)
3. Reshape & Convert Load Vectors
4. Define V2G Storage & Renewable Scenarios
5. Loop Over Simulation Years
6. Calculate Hourly Merit Order
7. Adjust Load/Price with V2G Dispatch
8. Export Results to Excel

📊 Example Output

• Excel files with hourly price profiles
• Time-series plots of load vs. generation
• Scenario comparison of price volatility

📈 Screenshot

📦 Dependencies

• MATLAB R2020b or higher recommended
• Compatible with .xlsx, .xml, and .csv data input
• Uses built-in readtable, plot, and xlswrite

📘 File Overview

File	Description
Lipton_v4_6_export_xlsx.m	Main simulation script
ACTUAL_TOTAL_LOAD_*.xml	Input files with hourly load data
*.xlsx or *.csv	(Optional) Alternative data input formats

🧪 Example Use

run('Lipton_v4_6_export_xlsx.m');