Multi-criteria decision analysis (MCDA) methods have become increasingly popular in decision-making for sustainable energy because of the multi-dimensionality of the sustainability goal and the complexity of socio-economic and biophysical systems. This article reviewed the corresponding methods in different stages of multi-criteria decision-making for sustainable energy, i.e., criteria selection, criteria weighting, evaluation, and final aggregation. The criteria of energy supply systems are summarized from technical, economic, environmental and social aspects. The weighting methods of criteria are classified into three categories: subjective weighting, objective weighting and combination weighting methods. Several methods based on weighted sum, priority setting, outranking, fuzzy set methodology and their combinations are employed for energy decision-making. It is observed that the investment cost locates the first place in all evaluation criteria and CO2 emission follows closely because of more focuses on environment protection, equal criteria weights are still the most popular weighting method, analytical hierarchy process is the most popular comprehensive MCDA method, and the aggregation methods are helpful to get the rational result in sustainable energy decision-making.

Review on multi-criteria decision analysis aid in sustainable energy decision-making

Energy is a vital input for social and economic development. As a result of the generalization of agricultural, industrial and domestic activities the demand for energy has increased remarkably, especially in emergent countries. This has meant rapid grower in the level of greenhouse gas emissions and the increase in fuel prices, which are the main driving forces behind efforts to utilize renewable energy sources more effectively, i.e. energy which comes from natural resources and is also naturally replenished. Despite the obvious advantages of renewable energy, it presents important drawbacks, such as the discontinuity of generation, as most renewable energy resources depend on the climate, which is why their use requires complex design, planning and control optimization methods. Fortunately, the continuous advances in computer hardware and software are allowing researchers to deal with these optimization problems using computational resources, as can be seen in the large number of optimization methods that have been applied to the renewable and sustainable energy field. This paper presents a review of the current state of the art in computational optimization methods applied to renewable and sustainable energy, offering a clear vision of the latest research advances in this field.

Optimization methods applied to renewable and sustainable energy: A review

PROMETHEE: A comprehensive literature review on methodologies and applications

Social learning is increasingly becoming a normative goal in natural resource management and policy. However, there remains little consensus over its meaning or theoretical basis. There are still considerable differences in understanding of the concept in the literature, including a number of articles published in Ecology & Society. Social learning is often conflated with other concepts such as participation and proenvironmental behavior, and there is often little distinction made between individual and wider social learning. Many unsubstantiated claims for social learning exist, and there is frequently confusion between the concept itself and its potential outcomes. This lack of conceptual clarity has limited our capacity to assess whether social learning has occurred, and if so, what kind of learning has taken place, to what extent, between whom, when, and how. This response attempts to provide greater clarity on the conceptual basis for social learning. We argue that to be considered social learning, a process must: (1) demonstrate that a change in understanding has taken place in the individuals involved; (2) demonstrate that this change goes beyond the individual and becomes situated within wider social units or communities of practice; and (3) occur through social interactions and processes between actors within a social network. A clearer picture of what we mean by social learning could enhance our ability to critically evaluate outcomes and better understand the processes through which social learning occurs. In this way, it may be possible to better facilitate the desired outcomes of social learning processes.

/pdf/what-is-social-learning-52x38zo69h.pdf

What is social learning

Sustainability assessment of energy systems: Integrating environmental, economic and social aspects

Sustainable energy futures : Methodological challenges in combining scenarios and participatory multi-criteria analysis

New ways for the integrated appraisal of national energy scenarios: The case of renewable energy use in Austria

Participatory multi-criteria evaluation (MCE) is increasingly used for the integrated assessment of future scenarios Determining weights of the different criteria constitutes one of the biggest challenges of MCE This paper investigates the influence of weights on the ranking of scenarios and reflects critically on the use of weights as representations of social preferences in participatory MCE Conceptually, this exercise builds on the literature on integrated assessment and decision making under uncertainty; empirically, insights are drawn from two case studies of renewable energy scenario assessment for Austria at the national and local level The analysis exhibits a robust ranking for the local level, especially for the highest ranked scenarios In the national case study, the analysis finds two robust scenario clusters which never switch ranks, whereas the 1 This paper is based on a presentation given at the Participatory Approaches in Science & Technology conference, Edinburgh, June, 4-7, 2006 1

Katharina Kowalski

Papers

Sustainable energy futures : Methodological challenges in combining scenarios and participatory multi-criteria analysis

New ways for the integrated appraisal of national energy scenarios: The case of renewable energy use in Austria

The Influence of Social Preferences on Multi- Criteria Evaluation of Energy Scenarios