{"title":"Sensitivity analysis of hybrid microgrids with application to deployed military units","authors":"Daniel Reich, S. Sanchez","doi":"10.1002/nav.22130","DOIUrl":null,"url":null,"abstract":"We introduce a framework for applying sensitivity analysis to a set of potential hybrid microgrid design options, from which a decision maker can select the most preferred one. In contrast to optimization‐centric models that define an objective and produce a single solution, our goal is to empower the decision maker by providing both a range of options and accessible information that enables the decision maker to easily assess their relative upsides and downsides. Moreover, our decoupled approach allows our framework to be paired with any existing model capable of generating a set of potential hybrid microgrid designs. We introduce metrics for computing risk, stemming from power deficits, over a variety of scenarios relating to weather conditions, power demand fluctuations, and extended time horizons. These factors which are inherently uncertain are all important in military operational contexts. By introducing a design of experiments method for sensitivity analysis, we are able to implement parallel processing and maintain computational tractability.","PeriodicalId":19120,"journal":{"name":"Naval Research Logistics (NRL)","volume":"141 1","pages":"753 - 769"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Naval Research Logistics (NRL)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/nav.22130","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
We introduce a framework for applying sensitivity analysis to a set of potential hybrid microgrid design options, from which a decision maker can select the most preferred one. In contrast to optimization‐centric models that define an objective and produce a single solution, our goal is to empower the decision maker by providing both a range of options and accessible information that enables the decision maker to easily assess their relative upsides and downsides. Moreover, our decoupled approach allows our framework to be paired with any existing model capable of generating a set of potential hybrid microgrid designs. We introduce metrics for computing risk, stemming from power deficits, over a variety of scenarios relating to weather conditions, power demand fluctuations, and extended time horizons. These factors which are inherently uncertain are all important in military operational contexts. By introducing a design of experiments method for sensitivity analysis, we are able to implement parallel processing and maintain computational tractability.