Multi-objective optimization for the design and synthesis of utility systems with emission abatement technology concerns

• Published in: Applied energy Vol. 136; pp. 1110 - 1131
• Main Authors: Luo, Xianglong, Hu, Jiahao, Zhao, Jun, Zhang, Bingjian, Chen, Ying, Mo, Songping
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 31.12.2014
• Subjects: coal; cogeneration systems; combustion; design for environment; Desulfurization; economic costs; Environmental impact; equipment design; equipment performance; exergy; fluidized beds; heat; linear programming; Multi-objective optimization; natural gas; pollutants; prices; primary energy; sulfur dioxide; systems engineering; Utility system; ε-Constraint; Desulfurization; Multi-objective optimization; ε-Constraint; Utility system; Environmental impact
• ISSN: 0306-2619; 1872-9118
• DOI: 10.1016/j.apenergy.2014.06.076

Pareto frontier: Best trade-off values for objective functions of total emission potency and total economic cost (NGP=451.3 $/t, PHR=0.24). The identification the point on the pareto frontier indicate the number of the type and number of the selected equipment, where, GT is gas turbine; CFB is circulating fluidized bed boiler; PCB is Pulverized coal boiler; BPT is back pressure turbine; CT is condensing turbine. [Display omitted] •We develop a multi-objective methodology to address utility system optimization.•The design criteria are economic cost, environmental impact, and exergy efficiency.•Pollutant abatement process models are incorporated into the optimization problem.•A multi-objective MINLP model is formulated and is transformed into a MILP model.•A ε-constraint method is applied to identify the set of Pareto optimal solutions. The sustainable design configuration of utility systems incorporating pollutant emission abatement technologies has an important influence on economic cost, pollutant emission, and energy consumption of the process industry. In this paper, four typical cogeneration systems that address different emission reduction technologies are proposed as candidate structures for utility system design. The proposed systems are a gas boiler-based cogeneration system firing clean natural gas, circulating fluidized bed boiler-based cogeneration system incorporating SO2 abatement during combustion, pulverized coal boiler-based cogeneration system encompassing desulfurization and denitration after combustion, and gas–steam combined cogeneration system firing clean natural gas. The equipment performance, energy consumption, material consumption, pollutant emission, and investment and operation cost models of these cogeneration systems, as well as the corresponding emission abatement processes, are established. A multi-objective mixed integer nonlinear programming (MOMINLP) model is formulated to determine the equipment type (or cogeneration system and emission abatement technology), equipment number, equipment design capacity, and equipment operation load while simultaneously combining the multiple objectives of minimization of economic cost, minimization of environmental effect, and maximization of exergy efficiency. The original MOMINLP model is converted into a multiple objective mixed integer linear programming (MOMILP) model through linear approximation, unit size discretization, and relaxation. The augmented ε-constraint method is applied to identify the set of Pareto optimal solutions with respect to the aforementioned objective functions. An example of industrial utility system design optimization was presented. In addition, the best combination of cogeneration system for utility system structure under different objective was introduced. The sensitivity of the solutions to the primary energy source price and power to heat ratio was conducted.