As half of the world’s population live in cities today, the topic of urbanization and urban energy systems shift continuously into society’s focus. It has become a common challenge for local governments to provide a so called “Master Plan”, outlining a long term vision for the city’s energy infrastructure, to which all planners and investors have to adhere. Being a top-down approach, these Master plans are first of all politically motivated documents, which focus on achieving given targets, such as CO2-emission reductions or higher shares of electric mobility. Originating from these targets, a set of milestones and measures is derived, e.g., the implementation of certain green technologies or refurbishments of buildings. The goal of this paper is to elaborate a model, which allows analysis of a Master Plan from a bottom-up perspective and thereby quantitatively assesses the plan with regards to its feasibility, while identifying possible bottlenecks in its implementation. The results can then serve the city planners to adapt their planning in order to avoid unforeseen problems, when putting the plan’s measures into practice. The approach pursued in this research is a combination of system dynamics and an agent-based simulation model of the city’s energy system, providing both a high spatial and temporal granularity. The model is developed with the multi-method modelling tool Anylogic and with Geographic Information System (GIS). The city itself is represented with its existing building and power infrastructure, which is then subject to the planned measures and developments. The core of the model implements on the one hand different energy generation technologies, both fossil fuels and renewables, reaching from big power plants to small local PV-installations on a private household’s roof. On the other hand, the heat and electricity consumers are represented through the buildings. The aim of the model is, at first, to provide a support system to analyze the short and long term effects of the Master Plan. Since its measures are usually not planned in detail concerning exact location or timing of the realization, the simulation results can provide references on these specific details. Secondly, the findings are used to identify the impact of single planned measures and their combinations which answers the questions of how, when and where local electricity and heat producers and the energy efficiency measures influence one another and if they have synergetic or competitive effects. Finally, a set of recommendations is derived from the analyses, which can help the city planners to transfer the strategic measures of the Master Plan into operative business.
Syed Monjur Murshed
Institution: European Institute for Energy Research
Syed Monjur Murshed, M.Sc., holds a Master degree in Geomatics from Karlsruhe University of applied Sciences (2006) and received a Bachelor degree in Urban and Regional Planning from Bangladesh University of Engineering and Technology (BUET) in 2003. Mr. Murshed has more than 10 years of international experience in Geographic Information System (GIS) project management as well as its application in the field of environment and energy research. He has worked at the Centre for Disaster Management and Risk Reduction Technology (CEDIM), the Fraunhofer Institute for Systems and Innovation Research (ISI), and the Institute for Economic Policy and Research (IWW) at Karlsruhe Institute of Technology (KIT). In 2007, he joined the EIFER as a GIS expert and research engineer. Since then he contributed to and led a number of public and industry funded projects on spatial modelling and simulation of energy demand, assessment of renewable energy resources, static and dynamic visualization of data at different scales, and on development of tools and models. Mr. Murshed is enlisted as an external PhD candidate at the Department of Economics and Management at KIT.