Author
L. Yu
Other affiliations: Xiamen University of Technology
Bio: L. Yu is an academic researcher from North China Electric Power University. The author has contributed to research in topics: Electric power system & Copula (probability theory). The author has an hindex of 7, co-authored 7 publications receiving 162 citations. Previous affiliations of L. Yu include Xiamen University of Technology.
Papers
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TL;DR: Compared to joint-probabilistic chance-constrained programming (JCP), the CFSP method is more effective for handling multiple random parameters associated with different probability distributions in which their correlations are unknown.
52 citations
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TL;DR: In this paper, a robust flexible probabilistic programming (RFPP) method is developed for planning municipal energy system (MES) with considering peak electricity prices (PEPs) and electric vehicles (EVs), where multiple uncertainties regarded as intervals, probability distributions and flexibilities as well as their combinations can be effectively reflected.
37 citations
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TL;DR: In this paper, a fuzzy-stochastic simulation-optimization model (FSSOM) is developed for planning EPS (electric power systems) with considering peak demand under uncertainty, which integrates techniques of SVR (support vector regression), Monte Carlo simulation, and FICMP (fractile interval chance-constrained mixed integer programming).
37 citations
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TL;DR: In this article, a two-stage interval-possibilistic programming (TIPP) method is developed for planning carbon emission trading (CET) in the electric power systems of Qingdao (China), where dual uncertainties expressed as interval-random variables and interval-Possibiliistic parameters can be handled.
32 citations
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TL;DR: Compared to the conventional stochastic programming, the developed CSFP method can more effectively analyze individual and interactive effects of multiple random variables, so that the loss of uncertain information can be mitigated and the robustness of solution can be enhanced.
27 citations
Cited by
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TL;DR: A self-adaptive teaching-learning-based optimization (SATLBO) that improves the searching ability of different learning phases, an elite learning strategy and a diversity learning method are introduced into the teacher phase and learner phase.
185 citations
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TL;DR: Results for a case study using China’s Longyangxia hydro–PV power plant indicated that the robust optimization model and the three-layer nested approach could provide effective power generation plans for the hybrid system within a reasonable time.
163 citations
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TL;DR: In this article, the authors evaluated the CO2 emissions from the power sector of Pakistan during 1978-2017 using Logarithmic Mean Divisia Index technique and scenario analysis.
158 citations
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TL;DR: In this paper, the authors investigated the decision and coordination in the dual-channel supply chain arising out of low-carbon preference and channel substitution under cap-and-trade regulation, and developed the decision-making models of the centralized and decentralized supply chain, which consist of one manufacturer and one retailer.
158 citations
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TL;DR: In this paper, the authors provide a review of the quantitative and semi-quantitative methods that have been used to model risks and uncertainties in sustainable energy system planning and feasibility studies, including the derivation of optimal energy technology portfolios.
Abstract: The value of investments in renewable energy (RE) technologies has increased rapidly over the last decade as a result of political pressures to reduce carbon dioxide emissions and the policy incentives to increase the share of RE in the energy mix. As the number of RE investments increases, so does the need to measure the associated risks throughout planning, constructing and operating these technologies. This paper provides a state-of-the-art literature review of the quantitative and semi-quantitative methods that have been used to model risks and uncertainties in sustainable energy system planning and feasibility studies, including the derivation of optimal energy technology portfolios. The review finds that in quantitative methods, risks are mainly measured by means of the variance or probability density distributions of technical and economical parameters; while semi-quantitative methods such as scenario analysis and multi-criteria decision analysis (MCDA) can also address non-statistical parameters such as socio-economic factors (e.g. macro-economic trends, lack of public acceptance). Finally, untapped issues recognised in recent research approaches are discussed along with suggestions for future research.
129 citations