A decision support system to design operating strategies of a power plant: Adequate electricity generation and abated emissions release

Abstract

In this study, a mathematical optimization model using Genetic Algorithms (GA) was developed and applied to search for operation modes of a power plant considering the adequate electricity generation for public demand and abated emissions release for the better air quality. Continuous Emissions Monitoring System (CEMS) equipment that reports hourly emissions (i.e., NO_x, SO₂, and CO) is used to prepare information of emissions regarding to the electricity production (GWh). Emission sources include sixteen stacks of eight units of power generation (four thermal and four combined cycle power plants) using natural gas and fuel oil. This technique shows the beneficial application of optimization model, GA code, CEMS, and power generation database in a unified framework of a Decision Support System (DSS). We find that the best operating strategy is to partially shutdown the medium power units and to abundantly operate the large units for the compensation of both emissions and electricity. By using this approach, the electricity generation can be sufficiently produced while emissions can be reduced by 1.83 % of NO_x/kWh, 10.90 % of SO₂/kWh, and 7.55% of CO/kWh.