## Author - Emilia Rocha Ojeda, Lina Silva-Rodriguez, Anibal Sanjab, Madeleine Gibescu, and Elena Fumagalli	
## Paper - Societal Effects of Large-Scale Energy Storage in the Current and Future Day-Ahead Market: A Belgian Case Study	
## Faculty - Geoscience
## Department - Energy and resources
## Date - 07/07/2022

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General
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This readme.txt file briefly describes the contents of the datapackage required to replicate the results of the case study included in the paper 
"Societal Effects of Large-Scale Energy Storage in the Current and Future Day-Ahead Market: A Belgian Case Study". It includes the input data for 
the simulation and the used modeling assumptions. 

The mathematical formulation and the explanation of the different scenarios are described in the mentioned paper. The case study was modelled in 
Julia using JuMP and solved using GLPK and Ipopt.

The case study models the Belgian day-ahead electricity market, in which the existing pumped hydroelectricity storage capacity is considered, 
in addition to large-scale battery energy storage systems of different sizes for varying renewable energy shares. 
Twenty-four-hour periods are modelled for four representative days of the year, selected in such a way to consider seasonal changes 
in demand and renewable generation. Interconnection to the neighbouring bidding zones (i.e., the Netherlands (NL), France (FR),
Germany/Luxembourg (DE-LU), and the United Kingdom (UK)) was included using historical flows from the ENTSO-E transparency platform [1]. 

The following scenrios are included in the case study:

	*Baseline scenario: corresponds to the energy mix of Belgium in 2019. The supply and demand were modelled according to the
information available on the website of the Belgian transmis-
sion system operator Elia [2]  
	* large shares of renewables scenario (LVRES): In this scenario the 2019 generation mix was modified to represent a higher penetration 
of renewables as expected in 2030. As such, the new generation mix was based on the “Large Scale RES” scenario proposed by Elia for 2030 [3]

The baseline and LVRES scenarios described above are simulated with five storage levels: no storage, the existing PHES, and three
different levels of ESS installed capacities. 

Please notice that this dataset does not replace the open access information available in [1]-[2] related to the aforementioned scenarios. 
For the accessing the data, please visit the websites in [1]-[2].


Folder Structure
================

	--Belgium Model Input Data.xlsx
	--Modelling Assumptions.pdf
	--readme.txt (this file)
	


Folder contents
===============
In the main folder, the user finds the following files:
	* Belgium Model Input Data.xlsx
	* Modelling Assumptions.pdf



**The Belgium Model Input Data file includes the following sheets: 
1. Generation - Detailled data corresponding to the generation park of Belgium in 2019
		Includes the following fields: [Generating Units, Owner, Type, Fuel, Technical Nominal Power (MW), Efficiency, Fuel Price (€/GJ), 
		Emissions Factor (tonnes CO2/GJ), Marginal Cost (€/MWh), Ramp Up ( % of installed net capacity per minute), Ramp down(% of installed net capacity per minute),
		Min load (% of net capacity)]
 
2. VRES CF - Variable Renewable Energy Sources Capacity Factors per country during each representative date 
		Includes the following fields: [Time, VRES Type, Date] 			

3. Available capacity - Available Capacity considering Planned and Forced Outages per power plant during each representative date
			Includes the following fields: [Generator, Nominal Power, status on date]

4.  BE Demand -  Total demand of Belgium during the representative dates. It also includes a demand elasticity estimation. 

5. Imports - Actual physical flow (MW) from nerbouring countries during the representative dates.

6. Exports - Actual physical flow (MW) to nerbouring countries during the representative dates.

7. Historic prices - Historic day ahead market prices during representative dates used for price-taker operation



**The modelling assumptions file describes the modelling assumptions used to build the case study. The modelled scenarios are described in the paper.




Software version required
=========================
The files can be opened using microsoft excel and adobe pdf. No additional software is required.




Formats
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The folder contains files in the folling formats:
- .pdf files
- .xlsx




Abbreviations
=============
VRES - Variable renewable energy sources
BE- Belgium 
NL - the Netherlands
FR - France 
DE - Germany
LU - Luxembourg (DE-LU)
UK - United Kingdom (UK)




[1] “ENTSO-E Transparency Platform.” [Online]. Available: https://transparency.entsoe.eu/dashboard/show. [Accessed: 06-Jul-2022].
[2] “Grid data.” [Online]. Available: https://www.elia.be/en/grid-data. [Accessed: 06-Jul-2022].
[3] "ELIA Electricity Scenarios for Belgium Towards 2050,” Tech. Rep., 2017