Location Optimization of a Coal Power Plant to Balance Costs against Plant’s Emission Exposure

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.