CS18: Electricity Markets

This work presents an application designed to enable airline passengers to neutralize the carbon emissions associated with the consumption of aviation kerosene (JET-A1) on their flights. The solution uses the Cardano blockchain and the TASAF token, which represents the renewable attribute of Sustainable Aviation Fuel (SAF), offering an educational, interactive, and digitally auditable experience. The user flow begins with a basic registration and the input of flight origin and destination, which allows the application to estimate the corresponding JET consumption. A subsequent awareness module introduces the climate impact of the aviation sector and the role of SAF, encouraging the calculation of the required amount of TASAF tokens to compensate for the specific route. The application then guides the passenger through obtaining the tokens and provides an immersive visualization of the blockchain process of transfer and burn, ensuring verifiable neutralization. At the end of the journey, the passenger receives a certification in the form of an NFT containing their name, route, distance traveled, and amount of TASAFs used, along with an email for claiming the asset. It´s important to note that passengers' data will be protected and that there will be no undue exposure. The application demonstrates how web3 technologies can enhance transparency and engagement in aviation decarbonization initiatives, bringing users closer to the concept of sustainable fuels and to digital mechanisms for environmental verification. It should be emphasized that this solution is educational and complementary, and that the responsibility for decarbonization does not lie with the passenger.

The Brazilian electricity sector is undergoing a significant transition driven by the modernization of tariff structures and the exponential expansion of Distributed Generation (DG), particularly solar photovoltaic (PV) sources. Historically, low-voltage residential consumers in Brazil have been billed under a conventional "flat" tariff model, which does not reflect the varying operational costs of the system. This lack of price signaling has historically encouraged consumption patterns that overstress the grid during peak hours. To address these inefficiencies, Brazil introduced its first Time of Use (ToU) tariff for low-voltage consumers, known as the Tarifa Branca, in 2018. Despite this availability, adoption remains remarkably low, reaching approximately 70,000 units by 2025 – less than 0.1% of the 89 million eligible consumers in the country. This low adherence is attributed to consumer inertia, lack of information, and the complexity of adjusting domestic habits.
Concurrently, the need for demand-side response has become critical due to the "Duck Curve" effect caused by the rapid growth of solar DG. Between 2019 and 2024, DG capacity in Brazil surged from 2.2 GW to 36.1 GW, a compound annual growth rate of 75.1%. Because solar generation peaks at midday while residential demand peaks in the early evening, the system faces a steep "ramp" that requires immediate and flexible response from hydro or thermal plants. Furthermore, the enactment of Law No. 14.300/2022 established a new legal framework for DG, gradually introducing charges for the use of the distribution network and shifting the sector away from full "net metering" parity. Consequently, integrating ToU tariffs with DG has become an essential strategy to provide correct economic signals, encourage peak shaving, and ensure the long-term sustainability of the Brazilian power grid.

We analyze the entry incentives for explicit demand-side flexibility (DR) by developing a multi-market operational model with a detailed DR module, calibrated to the French power mix for both the current and 2035 systems, and solved using stochastic dual dynamic programming. The model simulates the profits, system cost reductions, and modulation contributions of flexible loads, and is extended to a co-investment framework with batteries to account for potential substitutability effects. Results show that flexible loads from the metallurgy, chemical, and paper industries, as well as residential heating provide modulation comparable to nuclear or CCGT plants, and require only moderate additional capacity payments to enter the market. In contrast, flexibility from retail, water treatment, agri-food, and mechanical industries would require much higher payments, limiting their economic relevance. The co-investment analysis further quantifies-using Morishima elasticities of substitution-that industrial DR complements batteries, whereas diffuse DR acts as a substitute. These findings provide insights into the design of capacity remuneration mechanisms and the future role of demand-side resources in flexible, low-carbon power systems.

This paper estimates the CO₂ abatement effects of solar and wind generation in Japan, with particular attention to cross-regional spillovers transmitted through interregional power flows. Using unit-level half-hourly generation data, I estimate how individual conventional generating units adjust to shocks in renewable output without imposing restrictive substitution assumptions. To address endogeneity arising from the joint determination of renewable injections and conventional dispatch, I instrument regional solar and wind generation with region-specific weather variation, including satellite-based solar radiation and wind speed. The estimates imply that solar generation avoided approximately 37 million tons of CO₂ per year, and that wind generation in Hokkaido and Tohoku avoided about 2.5 million tons per year. Taken together, these reductions are equivalent to roughly 8% of electricity-sector CO₂ emissions in 2024.

Electricity market models often overlook credit risk, relying on static metrics to assess profitability and bankability. In practice, extended periods of weak revenues can impair the ability to service debt and lead to default. This omission is particularly important for emerging technologies such as long-duration energy storage (LDES), whose revenues can vary substantially over time. To address this limitation, we extend investment assessment models by explicitly representing credit risk through the depletion of the Debt Service Reserve Account (DSRA). We study how design features of a net-revenue floor support mechanism affect LDES investment under bankability constraints. A central design feature we examine is settlement frequency: infrequent settlements allow losses to accumulate over longer periods before clawback occurs, increasing liquidity needs and undermining bankability.