CS24: Renewable Integration and Green Hydrogen Planning

India has committed to achieving net-zero greenhouse gas emissions by 2070 while pursuing its goal of becoming a developed economy by 2047. The pathways to achieving these dual objectives depend on the interaction between global cooperation, technological innovation, and domestic governance. Within the broader Net Zero India (NZI) framework, four scenarios are defined-Development-Oriented, Mitigation-Oriented, Synergistic, and Reference-varying along two dimensions: the degree of global cooperation and clean technology innovation, and the strength of domestic governance for development and adaptation. These dimensions shape distinct electricity transition trajectories.
To analyze these pathways, this study develops a supply-side optimization model of India's electricity sector. The model is structured as a multi-regional capacity expansion and dispatch framework representing five interconnected regions, with a 52-week temporal resolution to capture seasonal demand and renewable variability. It includes coal, natural gas, diesel, nuclear, hydro, wind, solar, and biomass technologies. Technical parameters, fuel prices, and resource limits are derived from the nationally validated PIER 2.0 model. The framework optimizes capacity additions, retirements, and dispatch decisions to meet exogenous regional demand under operational and policy constraints.
The Reference Scenario serves as a baseline reflecting continuation of recent trends. The model is designed to extend across the Development-Oriented, Mitigation-Oriented, and Synergistic scenarios. The Development-Oriented pathway features slower near-term decarbonization with prolonged coal use followed by accelerated renewable expansion. The Mitigation-Oriented pathway enables faster coal phase-out, rapid renewable and storage deployment, and lower cumulative emissions. The Synergistic pathway achieves accelerated yet socially balanced decarbonization through strong governance and rapid cost reductions.
Across scenarios, the model evaluates system costs, generation mix evolution, capacity trajectories, fuel consumption, inter-regional flows, and emissions outcomes, providing a comparative foundation for assessing India's electricity transition under alternative governance and global conditions.

The rapid rise of variable renewable energy (VRE) has transformed modern electricity markets and operational paradigms, forcing conventional thermal power plants to shift from stable baseload roles to more flexible, intermittency-balancing functions. While extensive literature documents the system-level impacts of VRE-such as emissions reductions and price shifts-less is known about how these dynamics affect the economic efficiency of individual thermal generators. At the same time, existing applications of stochastic frontier analysis (SFA) in the electricity sector often assume static environments, overlooking how forecast errors and operational uncertainty degrade generator-level performance.
This study bridges these two strands by developing a unit-level revenue frontier framework that explicitly accounts for renewable-induced variability and forecast uncertainty. Using plant level hourly panel data from thermal plants of a major electricity company in China, we construct a translog SFA model that quantifies the revenue shortfall of each unit relative to its frontier potential, incorporating daily measures of VRE volatility, net load forecasting errors, and plant flexibility. To address potential endogeneity in dispatch outcomes, we employ an instrumental-variable approach using day-ahead market outcomes and cost structure indicators.
By linking renewable-driven system shocks with generator-specific economic inefficiency, this study offers a novel micro-level perspective on the "hidden costs" of energy transition. We anticipate that our results will demonstrate significant heterogeneity in revenue losses across plants, shaped by differences in technical flexibility, contractual structures, and exposure to uncertainty. These insights can inform policy and market design efforts to enhance flexibility incentives, improve risk allocation, and ensure the financial viability of dispatchable thermal capacity in high-renewable systems.

Green hydrogen is increasingly framed as a pillar of the global energy transition, with Brazil positioned as a potential low-cost producer based on abundant renewable resources. Yet most announced projects have not progressed to Final Investment Decisions (FIDs), raising questions about how "derisking" policies distribute risks and returns.
This paper asks: to what extent does the institutionalization of derisking in Brazil's hydrogen industrial policy reproduce patterns of subordinated integration in the global economy by socializing risks while leaving value capture and returns largely private?
We examine Brazil's green hydrogen (GH₂) policy and project pipeline (2020–2025) through documentary analysis of the Low-Carbon Hydrogen Development Program (PHBC) and related regulatory instruments, complemented by semi-structured interviews with policymakers and business actors. The empirical focus is on three industrial hubs-Pecém (Ceará), Suape (Pernambuco), and Camaçari (Bahia). Analytically, we map technological, financial, and market risks across the project lifecycle and identify which risks are absorbed by the state (e.g., tax incentives, price-equalization mechanisms, contractual/ regulatory guarantees, and enabling infrastructure) versus private developers. We also assess whether enforceable conditionalities (local value-chain densification, technology transfer, capability building, or public return mechanisms) accompany state support.
Findings indicate a persistent gap between announcements and FIDs. Derisking instruments are frequently deployed without robust conditionalities, encouraging export-oriented strategies aimed at supplying decarbonization demand abroad while exposing public budgets and host territories to fiscal, regulatory, and infrastructure-stranding risks. The result is a functional shift of the state from strategic planner toward financial enabler, with heightened risk of "green enclave" development.
Policy implications are that derisking, if used, should be tied to transparent and enforceable conditionalities and to mechanisms for public value capture, alongside safeguards that limit stranded public infrastructure and improve accountability for distributional and territorial impacts.

Despite the relevant role of green hydrogen (GH2) in the pathway to net zero, its market is still developing, mainly due to its high production cost compared with gray hydrogen. An optimal portfolio selection is needed to achieve a cheaper electricity supply and increase electrolyser utilization, reducing costs in the short term. An optimization model was developed and implemented in Julia programming language to facilitate sizing of hydrogen projects for risk-averse investors by integrating renewable power generation, battery or hydrogen storage, grid utilization, and specific demand profiles. Results indicate that for industrial consumers requiring a constant GH2 supply, the optimal strategy leverages the power grid as a backup. This configuration yields a Levelized Cost of Hydrogen (LCOH) of 4.6 USD/kg-approximately 40% lower than a standalone off-grid wind and solar hybrid system. However, even under optimized conditions, green hydrogen produced in Brazil remains uncompetitive with domestic gray hydrogen, exhibiting a carbon abatement cost of 190 USD/tCO2. In the context of international trade, while Brazilian GH2 could compete with average European green hydrogen production costs, it remains 80% more expensive than European gray hydrogen when accounting for midstream transport costs. The findings suggest that green hydrogen is currently not viable for broad industrial applications in Brazil due to high capital expenditures and electrolyzer efficiency limitations. Nevertheless, the study concludes that Brazil's low-carbon grid is a strategic asset; a hybrid grid-connected model is essential for bridging the viability gap and guaranteeing the possibility of a future competitive domestic and export hydrogen market.

SWITCH Colombia is an open-source model for the long-term planning of a high-renewable power system in Colombia. Utilizing existing and pending generation projects, we tailored the Switch 2.0 model to suit the characteristics of Colombia's unique power mix, grid, and regional generation potential and demand, with a user-friendly interface. SWITCH Colombia is first benchmarked against the actual data on Colombia's dispatched power in 2023, demonstrating its value for the simulation of short-term dispatch decisions; and then, against official projections up to 2035, which likewise illustrates its robustness for long-term planning. Furthermore, a decarbonization scenario up to 2050-assuming GHG emissions restrictions and a conservative growth in energy demand-yields an energy mix of 68 wind, 67.6 hydro, 16 solar, 10.9 biogas, and 9.4 biomass (all values in TWh). Fossil thermal energy plays a minor role, with less than 1 TWh, and may act as an important backup.