Linking qualitative scenarios with quantitative energy models: knowledge integration in different methodological designs

Background Linking qualitative scenarios with quantitative models is a common approach to integrate assumptions on possible future societal contexts into modeling. But reflection on how and to what degree knowledge is effectively integrated during this endeavor does not generally take place. In this paper, we reflect on the performance of a specific hybrid scenario approach (qualitative Cross-Impact Balance analysis, CIB, linked with quantitative energy models) concerning knowledge integration through 11 different process steps. In order to guide the scenario community in applying this approach, we reflect on general methodological features as well as different design options. We conceptualize different forms of interdisciplinary knowledge integration (compiling, combining and synthesizing) and analyze how and to what degree knowledge about society and uncertainty are integrated into scenario process and products. In addition, we discuss trade-offs regarding design choices and forms of knowledge integration. Results On the basis of three case studies, we identify two general designs of linking which build on each other (basic and extended design) and which differ in essence regarding the balance of power between the CIB and the energy modeling. Ex post assessment of the form of interdisciplinary knowledge integration in each step revealed that specific method properties of CIB as well as the interaction with additional quantitative as well as specific qualitative methods foster distinct forms of knowledge integration. The specific roles assigned to CIB in the hybrid scenario process can also influence the form of knowledge integration. Conclusions In this study, we use a joint process scheme linking qualitative context scenarios with energy modeling. By applying our conceptualization of different forms of knowledge integration we analyze the designs’ respective potential for and respective effects on knowledge integration. Consequently, our findings can give guidance to those who are designing their own hybrid scenario processes. As this is an explorative study, it would be useful to further test our hypotheses in different hybrid scenario designs. Finally, we note that at some points in the process a more precise differentiation of three forms of knowledge integration would have been useful and propose to further differentiate and detail them in future research.

Linking qualitative scenarios with quantitative energy models. Knowledge integration in different methodological designs.

BackgroundLinking qualitative scenarios with quantitative models is a common approach to integrate assumptions on possible future societal contexts into modeling. But reflection on how and to what degree knowledge is effectively integrated during this endeavor does not generally take place. In this paper, we reflect on the performance of a specific hybrid scenario approach (qualitative Cross-Impact Balance analysis linked with quantitative energy models) concerning knowledge integration through eleven different process steps. In order to guide the scenario community in applying this approach, we reflect on general methodological features as well as different design options. We conceptualize different forms of interdisciplinary knowledge integration (compiling, combining and synthesizing) and analyze how and to what degree knowledge about society and uncertainty are integrated into scenario process and products. In addition, we discuss trade-offs regarding design choices and forms of knowledge integration.ResultsOn the basis of three case studies we identify two general designs of linking which build on each other (basic and extended design) and which differ in essence regarding the balance of power between the CIB and the energy modeling. Ex-post assessment of the form of interdisciplinary knowledge integration in each step revealed that specific method properties of CIB as well as the interaction with additional quantitative as well as specific qualitative methods foster distinct forms of knowledge integration. The specific roles assigned to CIB in the hybrid scenario process can also influence the form of knowledge integration. ConclusionsIn this study, we use a joint process scheme linking qualitative context scenarios with energy modeling. By applying our conceptualization of different forms of knowledge integration we analyze the designs´ respective potential for and respective effects on knowledge integration. Consequently, our findings can give guidance to those who are designing their own hybrid scenario processes. As this is an explorative study, many roads for further empirical research are indicated. Finally, we note that at some points in the process a more precise differentiation of knowledge integration forms would have been useful and propose to further differentiate and detail the three forms of interdisciplinary knowledge integration in future research.

Design and Realization of Intelligent Electricity Processing Task System Supporting for Multiple Time Dimensions

The instant processing technology and intelligent analysis technology are researched in the paper. Then a processing task system is designed combining with the two technologies, whose realization process is described in detail. The system can settle the question that instant processing and intelligent analysis cant dispatch effectively and interchange data in the present technologies of intelligent electricity. It can also assure the timeliness and accuracy of the business scenario process of intelligent electricity with multiple time dimensions.