Publications

I use the first wave of COVID-19 as a natural experiment to document evidence of flexibility on the German day-ahead electricity market. I parameterize a model that represents uncertainty on the demand side as intermittency of renewables. I then compare pre- to post-COVID-19 data to investigate lower-bound economic implications. Post-COVID-19and with 44% of renewable shares, electricity prices were most sensitive to fuel costs, and almost completely passed through, while they remained rigid to CO2 costs. A decrease in demand consumption had a detrimental welfare effect on both, consumers and producers. An increase in demand consumption was slightly beneficial in the afternoon peak, mainlyfor consumers. Although the distributional gap was reduced, both actors, were worst off post-COVID-19. This kind of flexibility response was likely the result of a reduction in the minimum generation. CO2 emissions were lower by 22% on average, of which emissions from lignite showed only a small reduction of 8% of total emissions from fossil fuels. If the observed consumption pattern persists to some extent, in a market with higher renewable shares and more extreme weather conditions, more appropriate market rules would be necessary to achieve allocative efficiency.

We investigate technology as source of product differentiation on strategic behavior and wealth distribution in the German electricity market. We compare the performance of our model to a benchmark, using elasticity-adjusted markups, without bid data. We represent uncertainty on the demand side as intermittency of renewables or flexible demand response. We show that both model estimates converge at off-peak hours being robust to ramping cost and renewable forecast assumptions. Producers pass on fuel and CO2 costs differently with implications for reinforced European Emissions Trading regulation. Consumers are better off under a carbon price floor of euro25/tCO2, but producers are worse off, particularly at morning peak.

We review the state-of-the-art and common practice of energy and climate modeling vis-a-vis the rebound literature. In particular, we study how energy system and economy-wide models include and quantify rebound effects - the gap between actual and expected saving or the behavioral adjustment in response to an energy efficiency improvement, in terms of energy or greenhouse gas emissions. First, we explain the interaction between drivers of energy efficiency improvements energy efficiency policies, and the rebound effect to provide a framework for a general theoretical revision from micro- to macro-economic levels. Using this classification, we analyze rebound effect representations in empirical models by four dimensions: actors (industry or the production side, and private households or the consumption side), the aggregation level (from micro- to macro-economic levels), income level (developed or developing countries), and time (short- and long-run). Furthermore, we review rebound effect studies whose models focus on three drivers of energy efficiency improvements: market-based policies, non-market-based policies, and a costless energy efficiency improvement that holds other attributes constant (zero-cost breakthrough). We find that a clear representation of one or simultaneous drivers of energy efficiency improvements is crucial to target the goals of energy savings, greenhouse gas mitigation, and welfare gains. Under this broader view, the rebound effect is one additional phenomenon to take into consideration. This perspective provokes and provides additional policy implications. Reporting rebound effects as a stand-alone percentage is not sufficiently informative for policy considerations and the distinction of the aggregation level is important to asses the scalability of energy efficiency policies. Finally, we give some ideas and motivations for future research.

This thesis investigates the potential of biofuels in Peru for 2020 using 8 Peruvian natural resources available in 2012, in the search for low carbon and clean sources of transport energy. Long-term polices for the transport sector require detailed planning and evaluation of current and possible future scenarios, in order to design and implement effective policy tools. This research examines the effect of the introduction of emerging technologies in three fossil fuel scenarios (low, moderate and high), combined with three proposed biofuel policies, in the search for supply-demand optimisation for the transport sector in 2020. The results show that biofuel policies would not be efficient or sustainable with current technologies, and further promotion of investments in pilots for second and third generation biofuels would be required to find unrestrained substitutes for diesel and gasoline fuels. These pilots could provide an opportunity platform and beneficial strategy for business and R&D cooperation between developing and developed countries, for all parties. Finally, it is proposed that a combination of electric hybrid cars with 2nd and 3rd generation biofuels would be an optimal scenario for long-term transport energy management in 2020-2035.