Haris Doukas

Multi-criteria decision aid for the formulation of sustainable technological energy priorities using linguistic variables

Implementation of new and innovative energy technologies is a key mean towards a sustainable energy system. Currently, governments have to decide from an increasingly diverse mix of them, the ones which warrant support, including funding and other incentives for private sector efforts. However, appraising energy technologies in terms of their sustainability is a really complex task, considering the series of uncertainties and implications that have to be encountered so as to obtain realistic and transparent results. In this context, the main aim of this paper is to present a direct and flexible multicriteria decision making approach, using linguistic variables, to assist policy makers in formulating sustainable technological energy priorities. Furthermore, its software realization will be applied to a number of technologies, in the context of the Greek Technology Foresight Programme, and the results will be presented and discussed. � 2006 Elsevier B.V. All rights reserved.

A linguistic multicriteria analysis system combining fuzzy sets theory, ideal and anti-ideal points for location site selection

Most multicriteria methods try to model human thinking and insert the results of this modelling into their procedures. Following this path, the proposed multicriteria approach first captures the imprecision and vagueness of data by using linguistic variables. At a second level, it utilises human processes of decision-making by creating decision rules and modelling them with functions used in fuzzy sets theory. This method also is compatible with the way fuzzy logic models and combines fuzzy propositions. The proposed method considers the ideal solution and the anti-ideal solution and assesses each alternative in terms of distance as well as similarity to the ideal solution and the anti-ideal solution. Distance and similarity measures for fuzzy numbers are used and their aggregation is guided by the decision rules in order to construct decision functions. Further, OWA operators with maximal entropy are used to aggregate across all criteria and determine the overall score of each alternative. It is shown that the proposed method presents flexibility in modelling the decision makers preferences and it is also appropriate and effective to handle multicriteria problems of considerable complexity.

Modelling of linguistic variables in multicriteria energy policy support

The climate change and the increasing complexity of the energy sector along with the prerequisite for sustainability have broadened the energy policy shaping field by bringing out new challenges. Decision support tools and methods, such as Multicriteria Decision Aid (MCDA), are necessary for energy policy, in the pursuit of appropriate approaches necessary to support the restructuring of the energy sector, concerning patterns of energy extraction, generation, transformation and use, from unsustainable to sustainable forms of development. Papers devoted to the investigation of MCDA models using linguistic variables for energy policy support seem to be not available in the international literature. The scope of this paper is to explore different linguistic representation and computational models in MCDA that are or can be applied to energy policy support and to establish a clear linkage between them. This paper argues that MCDA methodologies with direct computation on linguistic variables can support energy policy frameworks, bridging the gap between energy policy makers thinking, reasoning, representation and computing. Finally, current trends, open questions and prospects in this topic are pointed out.

Energy Policy Making: An Old Concept or a Modern Challenge?

Abstract The energy policy is directed by the three main objectives, namely the security of supply, the competitiveness of the energy market, and the environmental protection. In addition to this, now the energy policy is developed through a number of social and economical challenges. As a result, a comprehensive and modern energy policy making, which can be characterized by clarity and transparency, is necessary. Even though energy policy making has been the subject of many researchers, comprehensive and modern studies examining the multiple and often conflicting parameters that have to be incorporated is not present in the international literature. In the above context, the purpose of this article is to review and analyze the current concept and the challenges toward the modern energy policy making, based on the three energy policy objectives as well as the impact of the crucial parameters.

Risks on the Security of Oil and Gas Supply

Abstract European energy demand and import dependence continues to increase and primary energy sources are mainly used to cover European energy needs, making clear that the risks of energy security of supply and their minimization is a critical issue. The aim of this article is to address the energy supply status, considering the energy supply corridors to the European Union, in order to underline the importance of risk analysis and risk minimization. The aim of this article is to present an overview of possible risks to smooth energy supply. The emphasis is given on oil and natural gass categorization of most important risks, as well as the presentation and analysis of collection of incidents that justify the categorization itself.

Using Biomass to Achieve European Union Energy Targets—A Review of Biomass Status, Potential, and Supporting Policies

In an effort to monitor its ambitious energy targets toward a “green Europe,” the European Commission has set up a project to enhance the availability, completeness, and quality of data regarding Green Energy Technologies. The Scientific Reference System (SRS) established in the framework of this project intends to support better-informed decisions. In this paper, we discuss the information gathered regarding energy from biomass by using the SRS methodology. First, the SRS approach is summarized and following that we present the findings of the research conducted by analyzing the data regarding biomass, with focus on energy policy frameworks.

A Linguistic Decision Support Model towards the Promotion of Renewable Energy

Abstract In the pursuit of energy market restructure to sustainable forms of development, governments have at their disposal an increasingly diverse mix of renewable energy sources options. Indeed, renewable energy sources can be seen as a way to reduce carbon emissions, decrease fossil fuel imports, and meet other energy policy objectives. However, appraising renewable energy sources options is a really complex task, taking into consideration the imprecision and subjectivity of the related information. The main scope of this article is to present a transparent and flexible multiple criteria decision support model, based on TOPSIS extension, using the 2-tuple representation. This model aims to assist the energy actors for appraising renewable energy sources options in terms of their contribution to the energy policy objectives, using linguistic variables. Moreover, the application of the proposed models software realization to a number of renewable energy sources options of the Greek energy market is presented and discussed.

Robustness analysis in Multi-Objective Mathematical Programming using Monte Carlo simulation

In most multi-objective optimization problems we aim at selecting the most preferred among the generated Pareto optimal solutions (a subjective selection among objectively determined solutions). In this paper we consider the robustness of the selected Pareto optimal solution in relation to perturbations within weights of the objective functions. For this task we design an integrated approach that can be used in multi-objective discrete and continuous problems using a combination of Monte Carlo simulation and optimization. In the proposed method we introduce measures of robustness for Pareto optimal solutions. In this way we can compare them according to their robustness, introducing one more characteristic for the Pareto optimal solution quality. In addition, especially in multi-objective discrete problems, we can detect the most robust Pareto optimal solution among neighboring ones. A computational experiment is designed in order to illustrate the method and its advantages. It is noteworthy that the Augmented Weighted Tchebycheff proved to be much more reliable than the conventional weighted sum method in discrete problems, due to the existence of unsupported Pareto optimal solutions.

The challenge of an EU-GCC clean energy network

The enhancement of EU-GCC cooperation on energy issues could be significantly facilitated from the establishment and operation of an EU GGC clean energy network (EU-GCC CLEANERGY.NET). CLEANERGY.NET would have to act as a catalyst and a coordinator for EU-GCC energy cooperation on different levels: research, technology and industry, but also on the level of energy policy, through dissemination of information regarding EU policies and practices in fields such as renewable energy (RE), electricity interconnections, tariffs for electricity and gas, climate change, energy efficiency and DSM, etc. The smooth cooperation of EU and GCC key energy players is considered a necessity for the success of such a challenging undertake. In this respect, the aim of this paper is to provide recommendations for an applicable organisation of the CLEANERGY.NET that would be able to act as an important driver to foster EU-GCC cooperation.

Enabling local authorities to produce short-term energy plans

Purpose – The purpose of this paper is to identify the most appropriate multidisciplinary data sources related with energy optimization decision support as well as the related methodologies, tools and techniques for data capturing and processing for each of them. Design/methodology/approach – A review is conducted on the state-of-play of decision support systems for energy optimization, focussing on the municipal sector, followed by an identification of the most appropriate multidisciplinary data sources related with energy optimization decision support. An innovative methodology is outlined to integrate semantically modeled data from multiple sources, to assist city authorities in energy management. Findings – City authorities need to lead relevant actions toward energy-efficient neighborhoods. Although there are more and more energy and other related data available at the city level, there are no established methods and tools integrating and analyzing them in a smart way, with the purpose to support the...