Stochastic, Multiobjective, Mixed-Integer Optimization Model for Wastewater-Derived Energy

Abstract

AbstractAssessing investment decisions in wastewater treatment can be difficult given that operators face large fixed and variable costs as well as large amounts of uncertainty in the amount of wastewater inflow as well as other factors. Decision makers can solve these problems by implementing operations research models that capture environmental engineering and economics aspects of the problem. Perfect decisions require perfect information but decisions makers can use stochastic models to hedge their decisions against an uncertain future. This paper presents a stochastic, multiobjective, mixed-integer optimization model for a wastewater treatment plant (WWTP). The WWTP can convert the solid end product from wastewater into methane to produce revenue and renewable energy credits. Alternatively, the solids can be used as biosolids for land application, agricultural markets, or compressed natural gas transportation markets. This stochastic optimization model explicitly considers probabilistic information, a...