ABSTRACT
OBJECTIVE: Benchmark the economic value of renewable energy and battery storage systems to extend operation of certain critical infrastructure facilities in different markets. DESIGN: This study uses the renewable energy optimization model to assess three critical facilities in North Caro-lina. Techno-economic results were then compared to analyses completed for critical facilities in California and New York to assess energy system cost effectiveness. RESULTS: Though solar photovoltaic (PV) arrays are cost-effective across each of the three North Carolina facili-ties, adopting battery storage to enable PV to operate with existing diesel generators in a hybrid energy system re-duces the economic value of the system. This is in contrast to more economically viable systems in California and New York. All of these systems also offer unquantified resilience benefits by extending operation from hours to weeks across the facilities. CONCLUSION: If decision makers were able to value the resilience benefits offered by each system or utility rate structures were changed to incentivize battery storage during normal operations, it would impact these assessments. Even so, this analysis provides decision makers a key set of cost benchmarks when considering how they might im-prove resilience at their critical operations.
Subject(s)
Disaster Planning , Electric Power Supplies , Renewable Energy , Humans , New York , North CarolinaABSTRACT
Methods for assembly, taxonomic profiling and binning are key to interpreting metagenome data, but a lack of consensus about benchmarking complicates performance assessment. The Critical Assessment of Metagenome Interpretation (CAMI) challenge has engaged the global developer community to benchmark their programs on highly complex and realistic data sets, generated from â¼700 newly sequenced microorganisms and â¼600 novel viruses and plasmids and representing common experimental setups. Assembly and genome binning programs performed well for species represented by individual genomes but were substantially affected by the presence of related strains. Taxonomic profiling and binning programs were proficient at high taxonomic ranks, with a notable performance decrease below family level. Parameter settings markedly affected performance, underscoring their importance for program reproducibility. The CAMI results highlight current challenges but also provide a roadmap for software selection to answer specific research questions.
