TITLE:
Location Optimization of a Coal Power Plant to Balance Costs against Plant’s Emission Exposure
AUTHORS:
Najam Khan, Ekaterina Koromyslova
KEYWORDS:
MCDA-Operations Research, Location Analysis, Prim’s Algorithm, Atmospheric Pollution Modelling, Transportation Cost
JOURNAL NAME:
American Journal of Operations Research,
Vol.9 No.1,
January
31,
2019
ABSTRACT: The goal of the research is to develop a methodology to minimize the public’s
exposure to harmful emissions from coal power plants while maintaining minimal
operational costs related to electric distribution losses and coal logistics.
The objective is achieved by combining EPA Screen3, ISC3 and Japanese
METI-LIS model equations with minimum spanning tree (MST) algorithm.
Prim’s MST algorithm is used to simulate an electric distribution system and
coal transportation pathways. The model can detect emission interaction with
another source and estimate the ground level concentrations of emissions up
to distances of 25 kilometers. During a grid search, the algorithm helps determine
a candidate location, for a new coal power plant, that would minimize
the operational cost while ensuring emission exposure is below the
EPA/NIOSH thresholds. The proposed methodology has been coded in form
of a location analysis simulation. An exhaustive search strategy delivers a final
candidate location for a new coal power plant to ensure minimum operational
costs as compared to the random or greedy search strategy. The simulation
provides a tool to industrial zone planners, environmental engineers, and
stakeholders in coal-based power generation. Using operational and emissions
perspectives, the tool helps ascertain a list of compromise locations for a
new coal power plant facility.