Monitoring and modeling of the urban micro-climate

Urban heat island phenomenon (UHI) is considered to be one of the major challenges encountered this century by the human kind. This phenomenon is characterized mainly by air temperatures in the city that are higher than those in the surrounding areas. Reasons are, amongst other things, the morphology and density of urban spaces as well as the thermal and radiative properties of outdoor surfaces. The UHI effect represents a challenge for careful and proper building design and operation, as micro-climatic data are typically available only for few locations in the city. As a result, planning, retrofit, and mitigation measures for buildings cannot count on reliable weather information for the exact locations of intended building projects. In this context, this paper presents results of an ongoing research project, which is concerned with prevention, adaptation, and mitigation measures pertaining to the urban heat island phenomenon. An important component of this project addresses the variation in the mirco-climatic conditions in different locations in the city and if and how such variations could be accounted for. Specifically, weather information was collected with a mobile weather station at various locations within the city of Vienna. Collected data from multiple - morphologically differentiated - locations around the city were compared with the simultaneously monitored general weather conditions via a stationary weather station. The findings are expected to support the development and validation of high-resolution climatic boundary condition models for building design and operation support

Urban heat island phenomenon in Central Europe

The urban heat island (UHI) phenomenon is characterized by significantly higher temperatures in metropolitan areas as compared to the surrounding suburban and rural neighborhoods. In this context, this paper presents a preliminary report pertaining to an ongoing EU-supported research project, which investigates the urban heat island phenomena in Central Europe. First, the background and general scope of the UHI phenomena are discussed. Subsequently, the paper investigates the manifestation of the urban heat islands phenomena (especially in the city of Vienna) and evaluates possible mitigation and adaptation strategies

Short-term occupancy implications of digitally provided outside views in window-less rooms

This paper investigates the perception and performance of occupants in rooms with and without visual connection to outside. Thereby, experiments were conducted with two groups of participants in a laboratory containing two test cells. One of the cells is equipped with a flat panel display, which acts as a virtual window. The other cell has no such display. Participants in the experimental group were exposed, via the virtual window, to different scenes. The control group in the window-less room was not exposed to such treatment. During the experiments, participants were asked to fill in a questionnaire regarding indoor environment. Additionally, they were asked to perform a number of typical problem-solving tasks. The discussion of the experimental results addresses the question, if and to which extent the existence of a virtual connection to the outside world in window-less spaces can improve occupants' perception and performance

A critical case study of decision criteria in architectural competitions

This paper analyzes a number of design proposals submitted within the framework of a large architectural competition in view of their eco-efficiency. As all new or refurbished buildings in Central Europe need to meet certain minimum energy performance requirements, many architectural competition announcements encourage participating planners to propose low-energy, passive or even plus-energy buildings, and also to take into account the ecological performance of building parts. Especially for public buildings, which are often seen as role models, competition announcements feature many environmental criteria addressing building envelope, HVAC-systems, and eco-impact of materials. It is difficult to compare project submissions (for example in terms of energy performance), as the quality and amount of information for each project varies widely. In most competitions, a professional jury chooses the “best” projects and it is debatable if ecological and energy performances are considered in the process. In this context, this paper presents results of a case study conducted in Austria. The entries of a competition for refurbishment and extension of a school building are analyzed using submitted project narratives as well as simple heating demand calculations. The outcome is subsequently compared with the Jury's final ranking of the submissions. The results can shed some light on the following questions: Do the competition entries provide sufficient information to evaluate their thermal and ecological behavior in general? Did the ecological and thermal performance influence the outcome of the competition and final Jury's ranking of the submitted proposals

Multi-stage optimal design of energy systems for urban districts

Urban districts develop in a dynamic manner over multi-year horizons with new buildings being added and changes being made to existing buildings (e.g. retrofits). Nevertheless, optimization models used to design urban district energy systems (DES) commonly consider a single, “typical” year for the design. This practice, however, does not allow for energy design decisions to be made in multiple phases in order to reflect a district’s development phases. This paper addresses this issue and presents a novel optimization model that allows the multi-stage optimal design of urban DES. The model identifies the cost-optimal technology investment decisions across a horizon that spans multiple years, while also calculating the energy system’s optimal operating patterns in order to meet the district’s energy demands. The evolution of the district’s energy demands and aspects like the evolution of technology costs and energy carrier prices are considered in the model. The model is applied to a new urban district in Zurich, Switzerland, for which 5 development stages are considered with new buildings of various types constructed in each phase. A multi-stage DES design plan is developed for the period 2021-2050, which includes large energy technology investments for each new development phase, but also smaller ones in the intermediate years between 2021 and 2050. The model specifies the amount of energy generated by each technology installed in each year, as well as the contribution of renewable energy in covering the district’s energy demands

Multiple energy carrier optimisation with intelligent agents

Multiple energy carrier systems stem from the need to evolve traditional electricity, gas and other energy systems to more efficient, integrated energy systems. An approach is presented, for controlling multiple energy carriers, including electricity (AC or DC), heat, natural gas and hydrogen, with the objective to minimise the overall cost and/or emissions, while adhering to technical and commercial constraints, such as network limits and market contracts. The technique of multi-agent systems (MAS) was used. The benefits of this approach are discussed and include a reduction of more than 50% in the balancing costs of a potential deviation. An implementation of this methodology is also presented. In order to validate the operation of the developed system, a number of experiments were performed using both software and hardware. The results validated the efficient operation of the developed system, proving its ability to optimise the operation of multiple energy carrier inputs within the context of an energy hub, using a hierarchical multi-agent system control structure

A GIS based methodology to support multi-criteria decision making for the retrofitting process of residential buildings

This paper presents a workflow to support the decision making for building retrofit and building systems update at urban scale. The workflow includes i) a method to extract information from a geographical information system including information on building characteristics, building systems and building typology, ii) a method to evaluate the current and future energy demand of buildings using a dynamic building simulation tool, and iii) an updated version of the energy hub approach to evaluate best performing options in terms of energy systems update. The developed method is applied to the city of Zurich to evaluate the optimal energy system update for all existing buildings within the city. Modelling results include best performing options in terms of CO2 emissions, renewable energy share, or energy efficiency while minimizing resulting costs for possible system and retrofitting solutions

National building stock model for evaluating the impact of different retrofit measures

In this study, a methodology was developed to evaluate different retrofit strategies, which allows an estimation of the current and future thermal space heating demand of the approximately 1.8 million residential buildings in Switzerland. The approach is based on a building stock dynamics model that considers new buildings, replacement buildings, demolitions, as well as past and current rates of energy-related retrofits. Different potential retrofit strategies are applied to evaluate their impact on reducing space heating demand. The results show the effectiveness of the distinct retrofit strategies in reaching the target reduction and emphasize the differences in the resulting annual retrofit rates. The simulated specific retrofit rates can serve as a basis for developing building retrofit measures at the national level, as well as for informing the next generation of regulations

Role of temporary thermostat adjustments as a fast, low-cost measure in reducing energy imports

Efforts to combat climate change involve long-term plans to reduce the energy demand and increase the share of locally generated renewable energy. However, a sudden change in the geopolitical situation may require an even more rapid response to reduce energy imports through energy-efficiency improvements. In the building sector, retrofits to the building envelope and heating systems are effective, yet time- and cost-intensive to improve energy efficiency. A fast, low-cost measure to address this need is to lower the temperature set-points in building heating systems to within comfortable limits. Here, we show the impact of reducing the temperature set-point by 1 °C on heating demand at different scales—building, regional, and national—using demand simulation of 240 Swiss building archetypes and clustering-based upscaling methods. We demonstrate a nearly 6% reduction in the residential space heating demand at the national level, about a third of which is met with natural gas. More importantly, the presented approach highlights potential implications of the proposed measure across a national residential building stock, considering differences in climate and building archetypes, as well as their spatial distribution

Spatiotemporal upscaling errors of building stock clustering for energy demand simulation

Energy demand of buildings forms a key component of energy system analyses. To integrate building energy demand into energy system models, detailed simulation of every single building is impractical and often computationally infeasible. Simulations are therefore typically performed on a sample of buildings for bottom-up analysis. For a simplified representation of the building stock, grouping and clustering are widely applied. However, a spatiotemporal quantification of the resulting upscaling errors is however lacking. Here, a grouping and clustering approach is performed for all Swiss buildings for bottom-up energy demand analysis. The spatiotemporal simulation error is quantified at the national, regional and neighbourhood (300×300 m) scales. Whereas national energy demands are well represented, the error induced by the grouping and clustering is significant at the neighbourhood scale: simulated demand is easily over or underestimated by double-digit percentages. Obtained regional full load hours and daily load factor values by a grouping and clustering approach are comparable to a full simulation of all buildings. However, careful consideration must be given to the used climate data if relying on clustering approaches. Our analysis reveals the challenge of representing peak demands well by aggregation of building demand profiles, which is exacerbated by grouping and clustering. Bottom-up studies thus need to consider errors arising from the grouping and clustering approach and distinguish between errors resulting from the upscaling process and other sources of uncertainty such as data inputs or modelling concepts. Finally, calculated energy signatures are shown to perform well as a fast and viable alternative to grouping and clustering