Nils Schüler

Establishing links for the planning of sustainable districts

Cities can play a key role in mitigating climate change impacts, as they represent two thirds of the world’s energy consumption and greenhouse gas emissions. This paper presents a model-based approach to support cities in the challenge of including energy issues in early stage urban planning. Recognizing that successful planning must rely on highly integrated solutions, this paper aims, through its approach, to better understand and reinforce links between generally fragmented sectors, scales, stages and disciplines. Considering the planning framework of the Swiss canton of Geneva, the main planning instruments are presented and an in-depth analysis of the urban and energetic goals and constraints is carried out. Linking the disciplines of planning and optimization, a Mixed Integer Linear Programing (MILP) model is formulated to identify optimal energy strategies, as well as to provide insights into the urban layout, distribution and size of buildings. Additionally, this approach aims to overcome one of the difficulties of early stage planning, where information regarding energy is scarce. In this regard the proposed methodology generates building information based on available data and constraints. The simultaneous consideration of multiple scales allows to assess the interactions of building scale decisions with overall district energy supply alternatives. The resulting depiction and quantification of trade-offs should allow planners to anticipate optimal energy system configurations and adapt their plans accordingly.

The Optimum Is Not the Goal: Capturing the Decision Space for the Planning of New Neighborhoods

This article presents the development and application of a methodology that employs optimization not to seek the single or few optimal plan(s) but to provide planners with a systematic overview of their decision space. As urban development projects are not only subject to decisions of planners but to those of many actors, the insight about how different actors would decide based on the decisions of the planners, should enable planners to already adapt their decisions to ensure that final project targets are reached. The existence of different decision makers is considered via a multiparametric mixed-integer linear pro- gramming (mpMILP) approach. Along with the methodology a model was developed, which incorporates multiple domains and scales. Those domains include social, environmental, form, energy and economic aspects. The considered scales range from single floors up to a neighborhood. Model and methodology were applied to a greenfield development project. Two practical questions are answered, which address the impact of planning decisions about (a) the building density and the sustainability of the energy supply on costs of different actors, and (b) the building density and the share of parks on the view on a landmark. The capturing of the decision space revealed trade-offs in terms of chosen energy supply system and urban form, respectively. The presented computational method forms part of the decision support tool URB io which shall assist urban planning.