مشخصات مقاله | |
ترجمه عنوان مقاله | رفتار غیر عادی مدل های سیستم انرژی تحت CO2 caps and prices |
عنوان انگلیسی مقاله | Counter-intuitive behaviour of energy system models under CO2 caps and prices |
انتشار | مقاله سال 2019 |
تعداد صفحات مقاله انگلیسی | 18 صفحه |
هزینه | دانلود مقاله انگلیسی رایگان میباشد. |
پایگاه داده | نشریه الزویر |
نوع نگارش مقاله |
مقاله پژوهشی (Research Article) |
مقاله بیس | این مقاله بیس نمیباشد |
نمایه (index) | Scopus – Master Journals List – JCR |
نوع مقاله | ISI |
فرمت مقاله انگلیسی | |
ایمپکت فاکتور(IF) |
6.153 در سال 2018 |
شاخص H_index | 158 در سال 2019 |
شاخص SJR | 2.048 در سال 2018 |
شناسه ISSN | 0360-5442 |
شاخص Quartile (چارک) | Q1 در سال 2018 |
رشته های مرتبط | مهندسی انرژی |
گرایش های مرتبط | فناوری های انرژی، سیستم های انرژی |
نوع ارائه مقاله |
ژورنال |
مجله | انرژی – Energy |
دانشگاه | Forschungszentrum Jülich, Institute for Energy and Climate Research – Systems Analysis and Technology Evaluation, 52428 Jülich, Germany |
کلمات کلیدی | مدل سیستم انرژی، بهینه سازی، CO2 cap، عوارض CO2 |
کلمات کلیدی انگلیسی | Energy system model، Optimization، CO2 cap، CO2 tax |
شناسه دیجیتال – doi |
https://doi.org/10.1016/j.energy.2018.12.052 |
کد محصول | E11344 |
وضعیت ترجمه مقاله | ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید. |
دانلود رایگان مقاله | دانلود رایگان مقاله انگلیسی |
سفارش ترجمه این مقاله | سفارش ترجمه این مقاله |
فهرست مطالب مقاله: |
Abstract
1- Introduction 2- Methods 3- Results 4- Discussion References |
بخشی از متن مقاله: |
Abstract The mitigation of climate change requires a fundamental transition of the energy system. Affordability, reliability and the reduction of greenhouse gas emissions constitute central but often conflicting targets for this energy transition. Against this context, we reveal limitations and counter-intuitive results in the model-based optimization of energy systems, which are often applied for policy advice. When system costs are minimized in the presence of a CO2 cap, efficiency gains free a part of the CO2 cap, allowing cheap technologies to replace expensive low-emission technologies. Even more striking results are observed in a setup where emissions are minimized in the presence of a budget constraint. Increasing CO2 prices can oust clean, but expensive technologies out of the system, and eventually lead to higher emissions. These effects robustly occur in models of different scope and complexity. Hence, extreme care is necessary in the application of energy system optimization models to avoid misleading policy advice. Introduction The mitigation of climate change requires a fundamental transition of the energy system. Currently, 65% of all greenhouse gas emissions are caused by the carbon dioxide (CO 2 ) emissions from fossil fuel combustion and industrial processes [1], such that a rapid decarbonisation of the energy sector is inevitable to meet the 2 C goal of the Paris agreement [2, 3]. Fossil fuelled power plants must be replaced by renewable sources such as wind turbines and solar photovoltaics, whose costs are becoming more and more competitive [4, 5]. One of the largest challenges of this transition concerns the security and reliability of the energy supply, which is crucial for industry, economy and infrastructure operation [6, 7] as well as the public acceptance of the transition [8]. Wind and solar power generation are inherently fluctuating [9, 10], and suitable locations are often far away from the centers of the load [11, 12]. The design of a future energy system must respect these constraints to guarantee a sustainable and reliable supply at affordable costs [2, 13]. Affordability, reliability and environmental sustainability constitute central targets for energy policy, with the reduction of greenhouse gas (GHG) emissions being the most urgent environmental target (Fig. 1a). This set of targets is commonly referred to as the energy policy triangle. It forms the basis for the energy strategy of the European Union [14, 15] and is widely supported by the public. A representative survey in Germany shows that half of the population ranks affordability as the most important goal, but reliability and reduction of GHG emissions are also frequently named as first priority (Fig. 1b). However, the three targets are often conflicting, so that the triangle becomes a trilemma [16]. None of these targets can be abandoned or singled out to the exclusion of the others. As a result, balancing the targets and resolving conflicts between them is at the heart of energy system analysis and energy policy. |