Stochastic Multicriteria Acceptability Analysis for Evaluation of Combined Heat and Power Units

Energies

Haichao Wang¹  Wenling Jiao²  Risto Lahdelma¹  Chuanzhi Zhu³  Pinghua Zou² 

[1] Department of Energy Technology, Aalto University School of Engineering, P.O. Box 14100, FI-00076, 02150 Espoo, Finland; E-Mail:;School of Municipal & Environmental Engineering, Harbin Institute of Technology, Harbin 150090, Heilongjiang, China; E-Mails:;School of Civil and Environmental Engineering, Jilin Jianzhu University, Changchun 130118, Jilin, China; E-Mail:

关键词: combined heat and power (CHP);    evaluation;    multicriteria decision analysis (MCDA);    complementary judgment matrix (CJM);    feasible weight space (FWS);    stochastic multicriteria acceptability analysis (SMAA);   

DOI  :  10.3390/en8010059

来源: mdpi

【 摘 要 】

Combined heat and power (CHP) is a promising technology that can contribute to energy efficiency and environmental protection. More CHP-based energy systems are planned for the future. This makes the evaluation and selection of CHP systems very important. In this paper, 16 CHP units representing different technologies are taken into account for multicriteria evaluation with respect to the end users’ requirements. These CHP technologies cover a wide range of power outputs and fuel types. They are evaluated from the energy, economy and environment (3E) points of view, specifically including the criteria of efficiency, investment cost, electricity cost, heat cost, CO₂ production and footprint. Uncertainties and imprecision are common both in criteria measurements and weights, therefore the stochastic multicriteria acceptability analysis (SMAA) model is used in aiding this decision making problem. These uncertainties are treated better using a probability distribution function and Monte Carlo simulation in the model. Moreover, the idea of “feasible weight space (FWS)” which represents the union of all preference information from decision makers (DMs) is proposed. A complementary judgment matrix (CJM) is introduced to determine the FWS. It can be found that the idea of FWS plus CJM is well compatible with SMAA and thus make the evaluation reliable.

【 授权许可】

CC BY   
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