Nonlinear Performance Degradation Prediction of Proton Exchange Membrane Fuel Cells Using Relevance Vector Machine
Environmental issues, especially global warming due to the greenhouse effect, have become more and more critical in recent decades. As one potential candidate among different alternative “green energy” solutions for sustainable development, the proton exchange membrane fuel cell (PEMFC) has received extensive research attention for many years for energy and transportation applications. In this paper, an advanced self-adaptive relevance vector machine (RVM) has been developed and demonstrated to predict the performance degradation of PEMFCs.
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On the Trade-Off Between Environmental and Economic Objectives in Community Energy Storage Operational Optimization
The need to limit climate change has led to policies that aim for the reduction of greenhouse gas emissions. Often, a trade-off exists between reducing emissions and associated costs. In this article, a multi-objective optimization framework is proposed to determine this trade-off when operating a Community Energy Storage (CES) system in a neighborhood with high shares of photovoltaic (PV) electricity generation capacity.
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