Probabilistic multi-criteria assessment of renewable micro-generation technologies in households

2018-12-17
Probabilistic multi-criteria assessment of renewable micro-generation technologies in households
Autoriai:dr. Tomas BaležentisEKVIChonghui Zhang Qin Wang Shouzhen Zeng Dalia Štreimikienė Ilona Ališauskaitė-Šeškienė Xueli Chen

Abstract

 

The planning of sustainable energy systems has been acknowledged as a multi-criteria decision making (MCDM) problem. However, most of the earlier literature has considered public and private impacts of the energy generation technologies in a stand-alone way. In this paper, it is argued that the sustainable planning of the energy systems and components thereof should involve both types of impacts simultaneously in the MCDM. To serve this aim, MCDM framework which incorporates the two types of information in the analysis, namely expert assessments for the public impacts and the willingness to pay measure for the private ones, is devised. The proposed MCDM framework involves the three MCDM techniques - the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), the Evaluation Based on Distance from Average Solution (EDAS) and the weighted aggregated sum product assessment (WASPAS) - which represent different principles of aggregation. The integrated MCDM framework is then applied in the context of Lithuania to choose the most promising micro-generation technology. More specifically, solar thermal, solar panel, biomass boilers and micro wind installations are considered. The Monte Carlo simulation is implemented in order to ensure the robustness of the results assuming that the underlying weights are perturbed.

Keywords: Willingness to pay; Micro-generation technologies; Multi-criteria decision making; Monte Carlo simulation

 

Zhang, C.H.; Wang, Q.; Zeng, S.Z.; Baležentis, T.; Štreimikienė, D.; Ališauskaitė-Šeškienė, I.; Chen, X.L. 2019. Probabilistic multi-criteria assessment of renewable micro-generation technologies in households. Journal of Cleaner Production, Vol. 212, p. 582–592; https://doi.org/10.1016/j.jclepro.2018.12.051; [Geographical Abstracts; Engineering Village - GEOBASE; Fluid Abstracts; FLUIDEX; Scopus; Science Citation Index Expanded].

 

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