The Experts below are selected from a list of 318 Experts worldwide ranked by ideXlab platform
Francois Marechal - One of the best experts on this subject based on the ideXlab platform.
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Obstacles in Energy Planning at the urban scale
Sustainable Cities and Society, 2017Co-Authors: Sébastien Cajot, J.-m. Bahu, F. Guignet, M. Peter, A Koch, Francois MarechalAbstract:a b s t r a c t Cities are expected to play a key role in achieving the ambitious Energy targets set by the European Union. By looking at opportunities beyond the single building scale, urban planners can significantly contribute to shape Energy-efficient and low-carbon cities. However, the complexity involved in such a broad task impedes the realization of any simple solution. This paper aims to make clear the many interrelated challenges and obstacles which hinder efficient urban Energy Planning. After reviewing the new requirements and goals of urban Planning and its links with Energy issues, a systematic framework to analyze the issues at stake is presented. The importance of such a structured and comprehensive definition and understanding of the problem is discussed, arguing that it is a necessary step to improve and develop adapted solutions which embrace the entirety of the problem. The approach is applied to a case-study in Switzerland, mapping out the different challenges and corresponding solutions related to Energy Planning encountered in an urban development project.
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Characterization of input uncertainties in strategic Energy Planning models
Applied Energy, 2017Co-Authors: Stefano Moret, Michel Bierlaire, Victor Codina Gironès, Francois MarechalAbstract:Abstract Various countries and communities are defining strategic Energy plans driven by concerns for climate change and security of Energy supply. Energy models can support this decision-making process. The long-term Planning horizon requires uncertainty to be accounted for. To do this, the uncertainty of input parameters needs to be quantified. Classical approaches are based on the calculation of probability distributions for the inputs. In the context of strategic Energy Planning, this is often limited by the scarce quantity and quality of available data. To overcome this limitation, we propose an application-driven method for uncertainty characterization, allowing the definition of ranges of variation for the uncertain parameters. To obtain a proof of concept, the method is applied to a representative mixed-integer linear programming national Energy Planning model in the context of a global sensitivity analysis (GSA) study. To deal with the large number of inputs, parameters are organized into different categories and uncertainty is characterized for one representative parameter per category. The obtained ranges serve as input to the GSA, which is performed in two stages to deal with the large problem size. The application of the method generates uncertainty ranges for typical parameters in Energy Planning models. Uncertainty ranges vary significantly for different parameters, from [ - 2 % , 2 % ] for electricity grid losses to [ - 47.3 % , 89.9 % ] for the price of imported resources. The GSA results indicate that only few parameters are influential, that economic parameters (interest rates and price of imported resources) have the highest impact, and that it is crucial to avoid an arbitrary a priori exclusion of parameters from the analysis. Finally, we demonstrate that the obtained uncertainty characterization is relevant by comparing it with the assumption of equal levels of uncertainty for all input parameters, which results in a fundamentally different parameter ranking.
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Uncertainty Classification for Strategic Energy Planning
2016Co-Authors: Stefano Moret, Michel Bierlaire, Francois MarechalAbstract:Various countries and communities are defining strategic Energy plans driven by concerns related to climate change and security of Energy supply. The long time horizon inherent to strategic Energy Planning requires uncertainty to be accounted for. Uncertainty classification consists in defining the type of uncertainty involved and quantifying it. It is needed as input for uncertainty and sensitivity analyses, and optimization under uncertainty applications. In this work we define a methodology for uncertainty classification for a typical strategic Energy Planning problem. As an example, the methodology is applied to some representative parameters.
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Robust Optimization for Strategic Energy Planning
Informatica, 2016Co-Authors: Stefano Moret, Michel Bierlaire, Francois MarechalAbstract:Long-term Planning for Energy systems is often based on deterministic economic optimization and forecasts of fuel prices. When fuel price evolution is underestimated, the consequence is a low penetration of renewables and more efficient technologies in favour of fossil alternatives. This work aims at overcoming this issue by assessing the impact of uncertainty on Energy Planning decisions. A classification of uncertainty in Energy systems decision-making is performed. Robust optimization is then applied to a Mixed-Integer Linear Programming problem, representing the typical trade-offs in Energy Planning. It is shown that in the uncertain domain investing in more efficient and cleaner technologies can be economically optimal.
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The Impact of Uncertainty in National Energy Planning
2016Co-Authors: Stefano Moret, Michel Bierlaire, Victor Codina Gironès, Francois MarechalAbstract:Concerns related to climate change and security of Energy supply are pushing various countries to define strategic Energy plans. Strategic Energy Planning for national Energy systems involves investment decisions (selection and sizing) for Energy conversion technologies over a time horizon of 20-50 years. This long time horizon requires uncertainty to be accounted for. Long-term Planning for Energy systems is often based on deterministic economic optimization and forecasts of fuel prices. When fuel price evolution is underestimated, the consequence is a low penetration of renewables and more efficient technologies in favor of fossil alternatives. This work aims at overcoming this issue by assessing the impact of uncertainty on strategic Energy Planning decisions. A classification of uncertainty in national Energy systems decision-making is performed. A Global Sensitivity Analysis (GSA) is performed in order to highlight the influence of the model uncertain parameters onto the Energy strategy. Optimization under uncertainty is then applied to a general Mixed-Integer Linear Programming (MILP) problem having as objective the total annual cost and assessing as well the IPCC Global Warming Potential LCIA indicator (CO2-equivalent emissions). The application focuses on the case study of Switzerland. It is shown that in the uncertain domain investing in more efficient and cleaner technologies can be economically optimal.
Yingbo Hua - One of the best experts on this subject based on the ideXlab platform.
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Energy Planning for Progressive Estimation in Multihop Sensor Networks - eScholarship
2009Co-Authors: Yi Huang, Yingbo HuaAbstract:Multihop sensor networks where transmissions are conducted between neighboring sensors can be more efficient in Energy and spectrum than single-hop sensor networks where transmissions are conducted directly between each sensor and a fusion center. With the knowledge of a routing tree from all sensors to a destination node, we present a digital transmission Energy Planning algorithm as well as an analog transmission Energy Planning algorithm for progressive estimation in multihop sensor networks. Unlike many iterative consensus-type algorithms, the proposed progressive estimation algorithms along with their transmission Energy Planning further reduce the network transmission Energy while guaranteeing any pre-specified estimation performance at the destination node within a finite time. We also show that digital transmission is more efficient in transmission Energy than analog transmission if the available transmission time-bandwidth product for each link and each observation sample is not too limited.
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Energy Planning for Progressive Estimation in Multihop Sensor Networks
IEEE Transactions on Signal Processing, 2009Co-Authors: Yi Huang, Yingbo HuaAbstract:Multihop sensor networks where transmissions are conducted between neighboring sensors can be more efficient in Energy and spectrum than single-hop sensor networks where transmissions are conducted directly between each sensor and a fusion center. With the knowledge of a routing tree from all sensors to a destination node, we present a digital transmission Energy Planning algorithm as well as an analog transmission Energy Planning algorithm for progressive estimation in multihop sensor networks. Unlike many iterative consensus-type algorithms, the proposed progressive estimation algorithms along with their transmission Energy Planning further reduce the network transmission Energy while guaranteeing any pre-specified estimation performance at the destination node within a finite time. We also show that digital transmission is more efficient in transmission Energy than analog transmission if the available transmission time-bandwidth product for each link and each observation sample is not too limited.
Karl Sperling - One of the best experts on this subject based on the ideXlab platform.
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A comprehensive framework for strategic Energy Planning based on Danish and international insights
Energy Strategy Reviews, 2019Co-Authors: Louise Krog, Karl SperlingAbstract:Abstract The transition towards renewable Energy systems is guided by different Energy Planning approaches around the world. The strategic Energy Planning approach has gained increasing attention during the last decade and it is the approach chosen for the Danish Energy transition. Challenges are found in Danish strategic Energy Planning approach today. This paper examines how to improve the implementation of strategic Energy Planning in Denmark. Through identification of challenges in the Danish approach and a review of international literature on strategic Energy Planning, it is possible to identify key elements that can be integrated into the Danish definition. Furthermore, a theoretical framework is developed that can be used to analyse strategic Energy Planning in practice.
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Towards Sustainable Energy Planning and Management
International Journal of Sustainable Energy Planning and Management, 2014Co-Authors: Poul Alberg Østergaard, Karl SperlingAbstract:Rising Energy costs, anthropogenic climate change, and fossil fuel depletion calls for a concerted effort within Energy Planning to ensure a sustainable Energy future. This article presents an overview of global Energy trends focusing on Energy costs, Energy use and carbon dioxide emissions. Secondly, a review of contemporary work is presented focusing on national Energy pathways with cases from Ireland, Denmark and Jordan, spatial issues within sustainable EnergyPlanning and policy means to advance a sustainable Energy future.
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centralisation and decentralisation in strategic municipal Energy Planning in denmark
Energy Policy, 2011Co-Authors: Karl Sperling, Frede Hvelplund, Brian Vad MathiesenAbstract:Denmark's future Energy system is to be entirely based on renewable Energy sources. Municipalities will play an important role as local Energy Planning authorities in terms of adopting and refining this vision in different local contexts. Based on a review of 11 municipal Energy plans, this paper examines to what extent municipal Energy Planning matches national 100% renewable Energy strategies. The results indicate a willingness among Danish municipalities to actively carry out Energy Planning, and the plans reveal a large diversity of (new) activities. At the same time, however, there is a strong need for better coordination of municipal Energy Planning activities at the central level. It is suggested that the role of municipalities as Energy Planning authorities needs to be outlined more clearly in, e.g., strategic Energy Planning which integrates savings, efficiency and renewable Energy in all (Energy) sectors. This requires the state to provide municipalities with the necessary Planning instruments and establish a corresponding Planning framework. Consequently, there is a need for a simultaneous centralisation and decentralisation during the implementation of the 100% renewable Energy vision. The paper outlines a basic division of tasks between the central and the local level within such a strategic Energy Planning system.
Roland De Guio - One of the best experts on this subject based on the ideXlab platform.
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Modelling and uncertainties in integrated Energy Planning
Renewable and Sustainable Energy Reviews, 2015Co-Authors: Atom Mirakyan, Roland De GuioAbstract:Abstract Significant progress has been done in the last decades to characterise and define uncertainty in model based Planning and decision making in general and in areas like integrated assessment or water resource management. However, existing uncertainty typologies are only partially shared. In city or territory integrated Energy Planning literature less attention has been paid to uncertainty aspect. Integrated Energy Planning and model building process have been defined on the base of literature review and the need for consideration of uncertainty is highlighted at the beginning of this work. Using this Planning and modelling framework, a conceptual basis of uncertainty showing the allocation of different types of uncertainty according to each Planning and modelling stage is provided. Uncertainty concepts proposed in existing typologies of uncertainty from different domains are harmonised into a framework and adapted to the special Energy modelling and Planning conditions, in a holistic way. Based on this framework, a review of practices in Energy Planning and modelling shows the gap between needs and practices and raises the question of methodological supports for fulfilling it. The suggested framework can be used to identify and classify different types of uncertainty in context of sustainable model based integrated Energy Planning in cities or territories, or develop methods to address them.
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Integrated Energy Planning in cities and territories: A review of methods and tools
Renewable and Sustainable Energy Reviews, 2013Co-Authors: Atom Mirakian, Roland De GuioAbstract:Although the integrated Energy and environmental Planning processes of cities and territories with more than 50,000 inhabitants differ, previous studies suggest that long-term, model-based Energy Planning processes have a common scheme that can also be used as a framework for reviewing the methods and the tools that are used in the integrated Energy Planning of these cities and territories. This paper first presents a generic integrated Energy Planning procedure in which the Planning activities are divided into four main phases. Second, the methods and the tools that are used for these diverse Planning tasks are mapped to the suggested generic Planning procedure tasks. Finally, the combined use of these methods and tools in the scope of integrated Energy Planning are briefly discussed from a mapping point of view.
Yi Huang - One of the best experts on this subject based on the ideXlab platform.
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Energy Planning for Progressive Estimation in Multihop Sensor Networks - eScholarship
2009Co-Authors: Yi Huang, Yingbo HuaAbstract:Multihop sensor networks where transmissions are conducted between neighboring sensors can be more efficient in Energy and spectrum than single-hop sensor networks where transmissions are conducted directly between each sensor and a fusion center. With the knowledge of a routing tree from all sensors to a destination node, we present a digital transmission Energy Planning algorithm as well as an analog transmission Energy Planning algorithm for progressive estimation in multihop sensor networks. Unlike many iterative consensus-type algorithms, the proposed progressive estimation algorithms along with their transmission Energy Planning further reduce the network transmission Energy while guaranteeing any pre-specified estimation performance at the destination node within a finite time. We also show that digital transmission is more efficient in transmission Energy than analog transmission if the available transmission time-bandwidth product for each link and each observation sample is not too limited.
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Energy Planning for Progressive Estimation in Multihop Sensor Networks
IEEE Transactions on Signal Processing, 2009Co-Authors: Yi Huang, Yingbo HuaAbstract:Multihop sensor networks where transmissions are conducted between neighboring sensors can be more efficient in Energy and spectrum than single-hop sensor networks where transmissions are conducted directly between each sensor and a fusion center. With the knowledge of a routing tree from all sensors to a destination node, we present a digital transmission Energy Planning algorithm as well as an analog transmission Energy Planning algorithm for progressive estimation in multihop sensor networks. Unlike many iterative consensus-type algorithms, the proposed progressive estimation algorithms along with their transmission Energy Planning further reduce the network transmission Energy while guaranteeing any pre-specified estimation performance at the destination node within a finite time. We also show that digital transmission is more efficient in transmission Energy than analog transmission if the available transmission time-bandwidth product for each link and each observation sample is not too limited.