Over the past few decades, there has been significant development in actions aimed at global energy transition, with the goal of reducing greenhouse gas emissions. The energy sector plays a significant role in this endeavor, contributing 76% of the world's total emissions. Considering electrification as an alternative promotes the deployment of technologies that use renewable sources, such as wind energy in coastal and offshore areas. In Colombia, wind energy alone has an accumulated technical potential of approximately 82 GW, mainly concentrated along the northeastern coast. Exploiting this technology enables the development of the national electrical system, reducing dependence on hydroelectric generation, strengthening the system against climate seasonality by ensuring supply security, environmental sustainability, and equitable energy access. Supported by system dynamics modeling, this paper presents four scenarios that explore possible futures for wind capacity deployment in Colombia between 2020 and 2050. It considers uncertainties in political and economic domains, as well as crucial national factors such as social acceptance, supply chain development, and transmission infrastructure. Favorable alignment of these factors towards wind diffusion could lead to nearly 29 GW of installed capacity by 2050, representing 40% of the projected total capacity of the electricity sector.
Combined cycle (CC) plants are expected to play an important role in balancing generation of heat and electricity from non-dispatchable renewable energy sources. In this work, we study different retrofit options for using hydrogen in CC plants to reduce the plant’s CO2 emissions. These options are: direct combustion in the gas turbine, supplementary firing in the heat recovery boiler (duct burner), and oxy-fuel combustion of hydrogen for direct steam production.
Therefore, we first simulate the performance of an exemplary CC plant in a detailed non-linear process model. Second, we fit a surrogate, mixed-integer-linear model that can optimize the plant operation within a reasonable computation time over a long time frame (one year, with hourly resolution). This surrogate model allows for an in-depth analysis of hydrogen combustion retrofits in CC plants, assessing both profitability and environmental impacts. The findings suggest that direct combustion of hydrogen in the gas turbine becomes economically viable only when hydrogen is cheaper than natural gas. Although a duct burner fired by natural gas can enhance the plant’s profitability, it also increases the specific carbon emissions. Burning hydrogen in a duct burner, however, is not cost-effective. Retrofitting the steam cycle of the plant with an oxy-fuel hydrogen burner, however, can improve both profitability and CO2 emissions of electricity and steam generation.
Energy system modeling supports the identification of the optimal technology mix to achieve decarbonization targets across multiple sectors. Especially when sector coupling is considered for future technology landscapes, the large solution space leads to a complex optimization problem in terms of computational feasibility and data requirements. The authors identify a research gap in developing an open-source model structure with consideration of the relevant future technologies of power, heat, other conversions, transport, and industry defined with a new level of detail in a sector-coupled energy world and in including detailed insights into the accompanying definition process. A strong focus is set on the transparency and reproducibility of the provided open-source structure and its flexible and consistent application to different framework families to foster the ease of applicability of this work. The paper first gives a detailed description of the model base, including an overview of the model frame definition process, the core adjustments to model sector coupling appropriately, and the measures to make the resulting problem computationally feasible. The core result of this work is the presentation of a detailed model structure to model sector coupling for a German energy system, yielding approximately 2000 processes that characterize the heterogeneous and technology-open landscape of existing and possible future technologies across relevant energy sectors. This supports energy system modelers in understanding and reproducing energy system models based on open-source data and thereby tries to accelerate the research on sector coupling and its role in the energy transition.