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Probabilistic Multicriteria Analyses For Optimal Biomass Power Plant Design

机译：最优生物质发电厂设计的概率多准则分析

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The design of biomass power plants is traditionally performed by using a deterministic approach. The deterministic model takes into account energetic, local and social factors to maximize the plant economic profit. When dealing with renewable energy applications, uncertainty, which involves unpredictable factors having a major influence, has recently been recognized as an important factor. In order to take into account the stochastic nature of uncertainty, probabilistic approaches have been widely applied to electric power system design and management [G.J. Anders, Probability Concepts in Electric Power Systems, Wiley-Interscience, 1990]. In this paper, a stochastic approach to optimal biomass plant design is proposed. The approach relates the plant economic index to the technological design. The paper extends the deterministic approach previously proposed in the literature [M. Fiala, G. Pellizzi, G. Riva, A model for the optimal dimensioning of biomass-fuelled electric power plants, J. Agric. Eng. Res. 67 (1997) 17-25, A. Cano, F.Jurado, Optimum location of biomass-fuelled gas turbines in an electric system, in: IEEE Power Engineering Society General Meeting 2006, 18-22 June, 2006, p. 6], and characterizes the uncertainty which concern the model by introducing random variables and probability functions. The stochastic model is formalized, the plant profitability index (PI) in an uncertain scenario is assessed. The results of the performed numerical applications are expressed in terms of probability density functions. Observing that, under circumstances characterized by uncertainty, the traditional evaluation methods, like cost-benefit analysis, can result ill-suited, a suitable tool is proposed. Thus, a stochastic multicriteria discriminat approach, able to focus on the features of the stochastic model to compare technological solutions in terms of alternative design criteria, is proposed and performed.
机译：传统上，通过使用确定性方法来执行生物质发电厂的设计。确定性模型考虑了能源，本地和社会因素，以最大化工厂的经济利润。在处理可再生能源应用时，不确定性是一个重要因素，其中不确定性涉及不可预测的因素，这些因素具有重大影响。为了考虑不确定性的随机性，概率方法已被广泛应用于电力系统的设计和管理中。 Anders，《电力系统中的概率概念》，Wiley-Interscience，1990年。本文提出了一种随机的最优生物量植物设计方法。该方法将工厂经济指标与技术设计联系起来。本文扩展了先前在文献中提出的确定性方法。 Fiala，G。Pellizzi，G。Riva，生物质燃料发电厂的最佳尺寸模型，J。Agric。 。 Res。 67（1997）17-25，A. Cano，F.Jurado，《电力系统中以生物质为燃料的燃气轮机的最佳位置》，载于：2006年6月18日至22日，IEEE动力工程学会总会，2006年。 6]，并通过引入随机变量和概率函数来表征与模型有关的不确定性。建立了随机模型，评估了不确定情况下的工厂盈利能力指数（PI）。进行的数值应用的结果以概率密度函数表示。观察到在不确定性的情况下，传统的评估方法（如成本效益分析）可能会导致不合适，因此提出了一种合适的工具。因此，提出并执行了一种随机多准则判别方法，该方法能够专注于随机模型的特征，以根据替代设计标准比较技术解决方案。

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