Reduction of Industrial Energy Demand through Sustainable Integration of Distributed Energy Hubs

Abstract

The aim of improving resource efficiency while offsetting the environmental impact of industrial processes is directly linked to the optimal management of heat and power flows. The heating requirements of industrial processes are primarily met by the process utility system, or more specifically: steam systems. In most industrial processes, steam systems are also the primary source of electricity generation. Therefore, it is often the case that several processes are linked to a common utility system that generates heat and power. Despite extensive research in this field, most sites' steam systems have developed without basic concerns being addressed, particularly in relation to design and operation. Moreover, if emissions are to be mitigated and driven to zero, fundamental changes in the design and operation of such systems are required. Future process utility systems should not only ensure efficient use of energy, but also shift to low carbon technology alternatives. To make current utility system designs more sustainable, an optimization framework is needed to provide cost-effective pathways to transition from current to future designs. The variety of technologies available, the amount of data, and their strong correlations make energy system design a complex optimization problem. Furthermore, unlike other energy systems such as district heating, central grids, and local integrated energy systems, process utility systems present additional challenges for decarbonization. First, process industries require high amounts of process heating, usually far more than power: a heat/power ratio between 3.5 to 5.6. Second, heat at different temperature levels is typically required, especially between 100 to 400 °C. These barriers, coupled with the need for flexible systems to cope with the variable demand and energy price fluctuations (due to renewable energy's unpredictable nature), make developing sustainable utility systems a challenging enterprise. To address this challenge, this thesis provides an optimization framework for the design and operation of process utility systems. It ranges from site-specific data (stream information, energy demands, energy sources and energy market prices) to the thermo-economic modelling of the energy conversion technologies (considering part-load performance), system design, operation strategy while providing an environmental and economic analysis. The framework also includes practical constraints for heat integration and steam system operation, such as steam superheating and desuperheating, selection of steam temperature, pressure distribution levels, and steam temperature constraints. Due to the increasing share of intermittent renewable energy supplies, electrical and thermal energy storage are included in the framework. A range of different energy resources is included (fossil and renewable) to allow an orderly transition from the current framework to a sustainable future. The resulting optimization problem is complex and multi-objective and utilizes new approaches to solve the resulting nonconvex mixed-integer nonlinear programming problem. A bilevel solution strategy is provided to decompose the original problem in master and slave sub problems, maintaining computational tractability. Moreover, to capture the short- and long-term dynamic nature of the integrated systems, a multi-period optimization approach is developed based on time-series aggregation of the input data. To address the issue of sustainability, the framework not only allows for cost optimization but also includes life-cycle analysis. The resulting multi-objective problem uses Pareto optimal curves to illustrate the distribution of costs and emissions for different system configurations that satisfy the site energy demand. Finally, the applicability of the methodology is demonstrated in relevant case studies from the industry. These highlight the importance of a holistic optimization approach for the accurate evaluation of the ut

Date of Award	1 Aug 2022
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Robin Smith (Supervisor) & Adisa Azapagic (Supervisor)