期刊
ENERGY
卷 163, 期 -, 页码 443-456出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2018.08.125
关键词
Distributed generation; Industrial districts; Smart multi energy systems; Pareto; Evolutionary multi-objective optimization
资金
- ENEA (National Agency for New Technologies, Energy and Sustainable Economic Development)
- Energy and Environmental Department of the Friuli Venezia Giulia Region in Italy
To maximize the environmental performance of the energy systems, a paradigm change towards the concept of smart multi energy systems is needed. Optimal planning, design and operation of such energy systems, which efficiently integrate different energy sources, vectors and needs, is intrinsically a multi objective problem in terms of sustainability. In this study, a decision support system based on performance indicators and Pareto multi-objective optimization is developed. System design combines renewable energy sources and combined cooling heat and power serving a cluster of firms through district energy distribution networks. Results show that the model enables the analysis of the trade-off between the different objective functions, allowing to identify the optimal energy systems layout through the selection of the proper size of the generation units. It also provides design directions such as the thermal energy storage capacity. The case study evidences that the smart energy systems concept can really represent a main opportunity to industrial districts both from the sustainability and the competitiveness perspective. Research also suggests that some financial incentives should be studied so that the solution providing the largest energy saving and carbon dioxide emission reduction could improve its economic attractiveness. (C) 2018 Elsevier Ltd. All rights reserved.
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