期刊
ENERGY CONVERSION AND MANAGEMENT
卷 254, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.enconman.2022.115269
关键词
Biowaste-based multigeneration; Multi-objective optimization; Circular integration; Wastewater treatment; Water -exergy -carbon nexus; Climate Change mitigation
资金
- Brain Pool Program through the Na-tional Research Foundation of Korea (NRF) - Ministry of Science and ICT [2019H1D3A1A02071051]
- National Research Foundation of Korea (NRF) - Korean government (MSIT) [2021R1A2C2007838]
- Korea Ministry of Environment (MOE) as Graduate School
Traditional process integration approaches contribute to climate change by emitting greenhouse gases and wasting water resources. This study proposes a circular integration approach to optimize energy recovery in a self-sustainable multigeneration system. By splitting the wastewater into carbon-rich and water-rich streams, the system is able to produce various types of energy without external utilities. The optimization model using genetic algorithm demonstrates high energy and exergy efficiencies as well as low total annual costs in both cold and hot modes.
Traditional process integration approaches necessitate the allocation of external hot and cold utilities to avoid violating the Second Law of thermodynamics. Consequently, energy systems contribute significantly to anthropogenic climate change by emitting considerable greenhouse gases and losing substantial water for cooling in their hot and cold utilities, respectively. In this study, a new circular integration approach is proposed, which is used to model the first optimal multigeneration system independent of any external hot and cold utilities. The proposed approach is based on splitting a biowaste stream into two flows, one carbon rich and one water rich, and optimally recovering the feasible exergy according to the nexus between water, exergy, and carbon. To demonstrate this concept, municipal wastewater is split into carbon-rich sludge and water-rich effluent streams, and an efficient multigeneration system is modeled to optimally produce freshwater, power, cooling, heat, hydrogen, and oxygen with no external utilities. The system is optimally configured, sized, and operated in both hot and cold environments using the non-dominated sorting genetic algorithm III. The results show that the energy efficiency, exergy efficiency, and total annual costs of the optimal multigeneration system reached 79.4 % and 62.4 %, 49.98 % and 47.58 %, and US$158,000 and US$163,000 in cold and hot modes, respectively. According to an uncertainty analysis, the optimal system exhibited robust performance in both operating modes. It is anticipated that this breakthrough in sustainable engineering will mitigate anthropogenic climate change if applied extensively over the coming decades.
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