Article published in Energy Economics, Volume 114
We develop an algorithm called M.I.D.A.S. (Italian Day-Ahead Market Solver) that simulates by iterative splitting the hourly equilibrium (price-quantity) of the Italian day-ahead market taking into account all transmission constraints between zones and the import from neighbouring countries. The algorithm is employed to study the sensitivity of equilibria to changes in production from units employing variable renewable sources, notably sun and wind, at different locations. We show that, when power markets are organised on zonal-basis with locational price signals and final buyers pay a unique price for the power
bought in the day-ahead market, a larger renewable production decreases the average zonal prices, but the distribution of benefits largely depends on power plants’ localisation. We do not limit our analysis to prices, but we study the impact of changes in renewable supply on network congestion, zonal balance
between demand and supply and zonal generation mix. We calculate the zonal substitution effects between renewable and non-renewable technologies, and within renewable technologies as well. M.I.D.A.S. results to be a powerful tool as it sheds some lights on the multiple consequences of energy transition policies and highlights the need of prioritizing over policies’ objectives.
Recent recovery plans, associated with the COVID‐19 pandemic and the energy transition, increased the funding available to finance innovative low‐carbon projects and called for an economic evaluation of their allocation. This paper analyzes the potential benefit of using repayable advance: a lump‐sum payment to finance the project that is paid back in case of...
The Chairs Armand Peugeot, Energy and Prosperity, and Climate Economics are organizing, on December 6th an 7th, 2023, the 10th edition of the annual international Conference on Mobility Challenges.