Abstract
This chapter proposes a multicriteria decision making (MCDM) method for choosing suitable and sustainable district heating (DH) system considering uncertainties. In this chapter, seven candidate DH systems are evaluated by the stochastic multicriteria acceptability analysis (SMAA) method. SMAA is able to handle the uncertainties of the criteria performance values (PVs) and the weighting at the same time. These uncertainties are very common and typical in real-life, but in most cases are not treated in the right manner, or just neglected. In this chapter, we use a probability distribution function (PDF), a Monte Carlo simulation, and the concept of feasible weight space (FWS) to handle the uncertainties. The model is demonstrated in a case study in China and the results show that the proposed method is capable of giving more reliable and flexible results when the uncertainties are considered. The method can also be extended to other energy systems.
| Original language | English |
|---|---|
| Title of host publication | Life Cycle Sustainability Assessment for Decision-Making |
| Subtitle of host publication | Methodologies and Case Studies |
| Publisher | Elsevier |
| Pages | 139-153 |
| Number of pages | 15 |
| ISBN (Electronic) | 9780128183557 |
| DOIs | |
| Publication status | Published - 2020 |
| MoE publication type | A3 Book section, Chapters in research books |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- District heating (DH)
- Feasible weight space (FWS)
- Monte Carlo simulation
- Multicriteria decision making (MCDM)
- Ranking
- Stochastic multicriteria acceptability analysis (SMAA)
- Uncertainty
- Weighting
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