دانلود مقاله ISI انگلیسی شماره 29004
عنوان فارسی مقاله

تجزیه و تحلیل سناریو با استفاده از شبکه های بیزی: مطالعه موردی در بخش انرژی

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
29004 2010 10 صفحه PDF سفارش دهید محاسبه نشده
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
Scenario analysis using Bayesian networks: A case study in energy sector
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Knowledge-Based Systems, Volume 23, Issue 3, April 2010, Pages 267–276

کلمات کلیدی
شبکه های بیزی - نقشه علی - تجزیه و تحلیل سناریو - سرمایه گذاری های انرژی -
پیش نمایش مقاله
پیش نمایش مقاله تجزیه و تحلیل سناریو با استفاده از شبکه های بیزی: مطالعه موردی در بخش انرژی

چکیده انگلیسی

This paper provides a general overview of creating scenarios for energy policies using Bayesian Network (BN) models. BN is a useful tool to analyze the complex structures, which allows observation of the current structure and basic consequences of any strategic change. This research will propose a decision model that will support the researchers in forecasting and scenario analysis fields. The proposed model will be implemented in a case study for Turkey. The choice of the case is based on complexities of a renewable energy resource rich country. Turkey is a heavy energy importer discussing new investments. Domestic resources could be evaluated under different scenarios aiming the sustainability. Achievements of this study will open a new vision for the decision makers in energy sector.

مقدمه انگلیسی

Complexity of the decision making in energy sector is caused not only by multiple factors and processes [1], but also by variety of stake holders in the decision. Energy sustainability, stability and variety are considered to be vital for the economic development. Since energy is an inevitable input for all industries, the sustainable supply of energy resources becomes a necessary part of the national economical strategies. Availability of energy resources at reasonable cost and utilizing without causing negative social effects are essential strategies [2]. The high importance of energy investments cause preparation of future plans to be based on scenarios by using the alternative variables influential in decision. As Hobbs [3] stated scenario-based decision making crosses many domains and multiple perspectives. It is observed in literature survey that, until very recently, statistical methods were used to create scenarios [4]. Fluctuations in factor values and uncertainties cause fuzzy and stochastic analysis [5], [6] and [7]. Knowledge systems are recently used in energy investment scenarios [8], [9] and [10]. Furthermore, Bayes Networks are used mostly in risk analysis and classification [11], [12] and [13]. The objective of this paper is analyzing the unstable and complex structure of energy sector by running an expert survey to find out the dependencies among effective factors and creating scenarios based on their opinions. This will give an opportunity to create scenarios independent of politics by using Casual Maps (CM) for analyzing the opinion poll and Bayes Network (BN) to create scenarios. The case application will be done in Turkey, a fossil energy importer country with unstable economic structure, where energy policies are deemed to be redesigned. Sustainable development of Turkish energy sector needs a change in the present energy production and consumption patterns. Investment is to be done in diversified energy resources and environmental concern is to be included in energy strategies [14]. The only alternative resource is recommended to be natural gas which has been growing rapidly [15]. Unfortunately this alternative caused the increase in import dependency [14]. Whereas, Turkey has an appropriate geographical location and weather conditions for extensive usage of renewable energy sources including hydropower, biomass, geothermal, solar and wind energy [16]. However, despite the reactions, nuclear energy is considered as a solution by Turkish government [17]. The case study in this research is constructed to respond the question of interactions of different factors effecting the renewable energy and nuclear energy investments. Hence, this study will contribute to knowledge system studies as well as decision makers in energy sector. In Sections 2 and 3 of this paper, Causal Maps (CM) and Bayesian Networks (BN) were explained and the choice of these tools is examined. In Section 4, CM and BN of Turkish energy sector was modelled and investment alternatives were examined under different economic and policy scenarios. Finally, concluding remarks and suggestions for further studies were given in the last section.

نتیجه گیری انگلیسی

Bayes Maps are effective in scenario creation of complex planning as in energy sector. Energy is considered to be a key player in the generation of wealth and a significant component in economic development. Sustainable development demands a sustainable supply of energy sources. Turkey is taken as the case for implementing the proposed Bayes Mapping model since it has various energy resources but relying on imported fossil energy. In Turkey, alternative energy sources must be used more widely to be less dependent on foreign resources. This study contributes to literature by using CM and BNs in energy sector. A basic framework is designed for energy investment policies. Declining of greenhouse effect and energy imports are decision parameters in this study. Since the economic conditions are not stable in Turkey, different scenarios are held by BNs. The probability of intended states for decision variables are summarized in Table 2. These probabilities are considered to make a decision. In second scenario (stable scenario), renewable investment overcomes to nuclear investment. In pessimistic scenario nuclear investment seems to be better than renewable investment according to the decision variables (greenhouse emission and energy import). However in optimistic scenario there is a tie between these two alternatives. So we need to look up for different attributes to select the best one.

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