Enhancements in Emissions Monitoring and Renewable Energy Systems

The field of renewable energy and emissions monitoring is witnessing significant advancements. Researchers are focusing on developing innovative methods to improve the accuracy and timeliness of emissions estimates, as well as enhancing the efficiency of renewable energy systems. Notably, the development of open-access platforms is enabling non-technical audiences to engage with detailed emissions datasets, supporting data-driven climate action. Moreover, advancements in modeling approaches are allowing for more accurate representations of complex systems, such as the impact of electrifying passenger cars on power systems. The integration of dynamic wireless power transfer technology in electrified roadways is also being explored, with models being developed to understand the dynamic behavior of total load demand. Furthermore, new algorithms are being proposed to improve the efficiency of maximum power point tracking in low-power photovoltaic systems. Noteworthy papers include: The Climate TRACE platform, which provides globally comprehensive emissions estimates for individual sources, supporting data-driven climate action. The adaptive gradient descent MPPT algorithm, which achieves high efficiency and robust performance in low-power photovoltaic systems. The stochastic rule-based controllers for peak shaving applications, which provide fast and realistic estimates of achievable levelised cost of energy.

Sources

Closing Gaps in Emissions Monitoring with Climate TRACE

Power sector models featuring individual BEV profiles: Assessing the time-accuracy trade-off

Dynamic Modeling of Load Demand in Electrified Highways Based on the EV Composition

Adaptive Gradient Descent MPPT Algorithm With Complexity-Aware Benchmarking for Low-Power PV Systems

Robust Rule-Based Sizing and Control of Batteries for Peak Shaving Applications

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