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• W4376641188 startingPage "7989" @default.
• W4376641188 abstract "This work develops an exposure-based optimal power flow model (OPF) that accounts for fine particulate matter (PM2.5) exposure from electricity generation unit (EGU) emissions. Advancing health-based dispatch models to an OPF with transmission constraints and reactive power flow is an essential development given its utility for short- and long-term planning by system operators. The model enables the assessment of the exposure mitigation potential and the feasibility of intervention strategies while still prioritizing system costs and network stability. A representation of the Illinois power grid is developed to demonstrate how the model can inform decision making. Three scenarios minimizing dispatch costs and/or exposure damages are simulated. Other interventions assessed include adopting best-available EGU emission control technologies, having higher renewable generation, and relocating high-polluting EGUs. Neglecting transmission constraints fails to account for 4% of exposure damages ($60 M/y) and dispatch costs ($240 M/y). Accounting for exposure in the OPF reduces damages by 70%, a reduction on the order of that achieved by high renewable integration. About 80% of all exposure is attributed to EGUs fulfilling only 25% of electricity demand. Siting these EGUs in low-exposure zones avoids 43% of all exposure. Operation and cost advantages inherent to each strategy beyond exposure reduction suggest their collective adoption for maximum benefits." @default.
• W4376641188 created "2023-05-17" @default.
• W4376641188 creator A5024351273 @default.
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• W4376641188 date "2023-05-16" @default.
• W4376641188 modified "2023-09-26" @default.
• W4376641188 title "Exploring Regional Fine Particulate Matter (PM_2.5) Exposure Reduction Pathways Using an Optimal Power Flow Model: The Case of the Illinois Power Grid" @default.
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• W4376641188 doi "https://doi.org/10.1021/acs.est.2c08698" @default.
• W4376641188 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37191255" @default.
• W4376641188 hasPublicationYear "2023" @default.
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