In the second lecture, we will talk about how to model electricity markets using mathematical programming tools.
In the practical session, we will get familiar with a dataset of electricity market hourly data from California, learn about how to simplify the data using clustering techniques, and set up an economic model of a simple electricity market.
Slides: day2.pdf
The exercise will be based on the paper by Reguant (2019), "The Efficiency and Sectoral Distributional Impacts of Large-Scale Renewable Energy Policies". Reading the paper in advance is encouraged.
Exercise file: day2.ipynb
Data file: data_jaere.csv, data_technology_simple.csv
❗ Save the exercise Julia file (.ipynb) and the data CSV file in the same folder. Then, open the exercise Julia file from Jupyter Notebooks to start exploring. Note that the .pdf file provides a snapshot of the exercise. It does not require any installation but it will not allow interactions.
Bushnell, J. (2011). Building blocks: Investment in renewable and nonrenewable technologies. In Harnessing Renewable Energy in Electric Power Systems: Theory, Practice, Policy: Vol. WP-202R (pp. 159–180). https://doi.org/10.4324/9781936331864
Bushnell, J., Mansur, E., & Saravia, C. (2008). Vertical Arrangments, Market Structure, and Competition: An Analysis of Restructured US Electricity Markets. American Economic Review, 98(1), 237–266. https://doi.org/10.1257/aer.98.1.237
Ito, K., & Reguant, M. (2016). Sequential markets, market power, and arbitrage. American Economic Review, 106(7), 1921–1957. https://doi.org/10.1257/aer.20141529
Kellogg, R., & Reguant, M. (2021). Energy and Environmental Markets, Industrial Organization, and Regulation, in preparation for Handbook of Industrial Organization, working paper
Reguant, M. (2019). The Efficiency and Sectoral Distributional Impacts of Large-Scale Renewable Energy Policies. Journal of the Association of Environmental and Resource Economists, 6(S1), S129–S168. https://doi.org/10.1086/701190