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Script for resilience analysis in energy systems: Python programming code and partial associated data of four cogeneration plants.

ABSTRACT: This article presents a script developed to evaluate resilience in energy systems. The files corresponding to the system description, simulation and metrics calculation are included in the dataset, as well as partial raw and processed data from the associated paper [1]. The model was developed focusing on covering all cogeneration and power plants, being the user responsible for describing the system, simulating and processing the data in the files here available. In the present work, the steps for the simulation are presented in detail, which contributes to other researchers that are interested in either adopting resilience as one of the possible system analyses or understanding the processes of metrics calculation of the associated paper.

SUBMITTER: da Silva FS

PROVIDER: S-EPMC8050704 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundCombined heat and power generation (CHP generation, also called 'cogeneration') is attracting public attention for its high thermal efficiency, without considering possible adverse environmental health effects.This study investigated the potential role of cogeneration plants in inducing 3 environmental diseases: asthma, allergic rhinitis, and atopic dermatitis.MethodsFrom 1 January 2013 to 31 December 2017, the towns (dongs) of South Korea in which a cogeneration plant started operation were selected as study sites. For comparison, a matched control dong with the most similar Gross Regional Domestic Product for each case dong was selected. The numbers of outpatient visits, inpatient admissions, and emergency visits provided by the National Health Insurance Sharing Service (NHISS) were analyzed using an interrupted time-series design. For air pollutants, the concentrations of 5 air pollutants from the AIRKOREA dataset were used.ResultsA total of 6 cogeneration plants in 6 case dongs started operation during the study period. For overall case dongs, the pre-CHP trend was 1.04 (95% confidence interval [CI]: 1.038-1.042), and the post-CHP trend was 1.248 (95% CI: 1.244-1.253). The intercept change due to the CHP plant was 1.15 (95% CI: 1.137-1.162). For overall control dongs, the pre-CHP trend was 1.133 (95% CI: 1.132-1.135), and the post-CHP trend was 1.065 (95% CI: 1.06-1.069). The intercept change due to the CHP plant was 0.888 (95% CI: 0.878-0.899). Only for CO and NO2, the relative risk (RR) for overall case dongs was statistically significantly increased, and the RR for the overall control dongs was statistically insignificant.ConclusionsPossible hazardous emissions, like CO and NO2, from cogeneration plants could induce environmental diseases in nearby community populations. The emissions from cogeneration plants should be investigated regularly by a governmental agency, and the long-term health outcomes of nearby community residents should be investigated.

Dataset Information

Script for resilience analysis in energy systems: Python programming code and partial associated data of four cogeneration plants.

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