OPTIMIZATION AND EQUILIBRIUM MODELING FOR RENEWABLE ENERGY: FOCUS ON WASTEWATER-TO-ENERGY APPLICATIONS

Abstract

This dissertation presents three novel optimization models for sustainable wastewater management. The Blue Plains Advance Wastewater treatment plant (AWTP) operated by the District of Columbia Water and Sewer Authority (DC Water) is used as a case study. The application to the Blue Plains AWTP is presented to illustrate the usefulness of the model and how wastewater treatment plants (WWTPs), solid waste disposal plants, community management groups can actively and positively participate in energy and agricultural markets. Besides the conversion of the solid end products into biogas and electricity via digesters, WWTP can also produce Class B biosolids for land application or Class A biosolids for use as fertilizer. Chapter 1 introduces the Blue Plains case study and other important aspects of wastewater management. The first problem, discussed in Chapter 2, is a multi-objective, mixed-integer optimization model with an application to wastewater-derived energy. The decisions involve converting the amount of solid end products into biogas, and/or electricity for internal or external purposes. Three objectives; maximizing total value, minimizing energy purchased from external sources and minimizing carbon dioxide equivalent (CDE) emissions were presented via an approximation to the Pareto optimal set of solutions. The second type of problem is a stochastic multi-objective, mixed-integer optimization model with an application to wastewater-derived energy and is presented in Chapter 3. This model considers operational and investment decisions under uncertainty. We also consider investments in solar power and processing waste from outside sources for revenue and other benefits. The tradeoff decision between operational and investment costs and CDE emissions are presented. The third type of optimization model is a stochastic mathematical program with equilibrium constraints (MPEC) for sustainable wastewater management and is presented in Chapter 4. This two-level optimization problem is a stochastic model with a strategic WWTP as the upper-level player. The lower-level players represent the fertilizer, natural gas, compressed natural gas (CNG) and electricity markets. All the lower-level players are price-takers. Chapter 5 considers a comparison of the three optimization models discussed above and highlights differences. Chapter 6 provides conclusions, contributions, and potential future directions.