Morphological analysis of energy scenarios

Abstract

Purpose Energy scenarios have long been successfully used to inform decision-making in energy systems planning, with a wide range of different methodological approaches for developing and evaluating them. The purpose of this study is to analyze the existing approaches and classify them with a morphological box. Design/methodology/approach This paper builds upon the methodological literature on developing and evaluating energy scenarios and presents a morphological box, which comprises parameters describing the scenario properties, (energy system) model properties, scientific practice and institutional settings of energy scenarios. The newly developed morphological box is applied to four selected energy scenarios of the German energy transition. Findings The morphological box is a suitable tool to classify current energy scenarios. The exemplary application also points toward four challenges in the current practice of energy scenario development and evaluation: increasing complexity of decision problems, transparency of the scenario development process, transparency of the decision support process and communication of uncertainty. Originality/value The morphological box of energy scenarios helps researchers soundly document and present their methodological approaches for energy scenario development and evaluation. It also facilitates the work of analysts who want to classify, interpret and compare energy scenarios from a methodological perspective. Finally, it supports the identification of gaps between current practice and the methodological literature on energy scenarios, leading to the development of new types of energy scenarios.

Low emissions analysis platform model for renewable energy: Community-scale case studies in Nigeria

“…Witt et al (2020) adopted a combination of scenario planning, energy system analysis, and multi-criteria decision analysis (MCDA) approaches to develop and evaluate energy scenarios for the power system in Lower Saxony, Germany. The scenarios development was facilitated by the morphological box approach, which provided a suitable tool for transparent energy scenario development (Witt, Stahlecker, & Geldermann, 2018).…”

A Business Model Framework to Characterize Digital Multisided Platforms

“…Morphological analysis can help to identify attributes and specifications of a specific object of interest [26,64,65]. Witt, Stahlecker and Geldermann [66] acknowledge the creative nature of this technique since it can also be used to figure out new configurations that have not yet been adopted. Thus, we developed a framework characterized by a structure made of morphological boxes [67].…”

Big data driven multi-tier architecture for electric mobility as a service in smart cities

“…Real-time and online includes scheduled data, which entails periodic readings from pervasive systems such as from eMaaS application data with high degree of concurrency and velocity representing and streaming data from the web (posts, blog, tweets, etc.) or from EV meters, smart sensor and other smartphones, weather stations, geo-location enabled devices, etc (Costa and Santos, 2016;Witt et al, 2018). Therefore, big data techniques can boost the dynamic of eMaaS by exploiting and extracting valuable information from transport data from different sources that may provide long-term sustainability for the creation or optimization of electric mobility (e-mobility) services.…”