Energy Efficient Neighbourhoods Research Articles

Surrogate Modeling Strategy for Urban Building Energy Simulation in Early-Stage Urban Design: A Case Study of Energy-Efficient Neighborhood Design in Seoul

This study focuses on developing an efficient surrogate modelling strategy for early-stage urban design, aiding in energy-efficient residential neighborhood design in Seoul. The methodology involves devising a design schema with important design parameters, generating 1,000 random designs via Latin Hypercube Sampling, and simulating each design’s energy use considering microclimate and shadow effects. Polynomial regression is used to develop surrogate models based on those energy simulation results, which is further validated with energy use measurements of real neighborhoods in Seoul. The developed surrogate model can provide quick evaluation of energy use with a moderate level of accuracy for early-stage energy efficient neighborhood design.

An Energy-Efficient, Parallel Neighborhood and Adaptation Functions for Hardware Implemented Self-Organizing Maps Applied in Smart Grid

Smart Grids (SGs) can be successfully supported by Wireless Sensor Networks (WSNs), especially through these consisting of intelligent sensors, which are able to efficiently process the still growing amount of data. We propose a contribution to the development of such intelligent sensors, which in an advanced version can be equipped with embedded low-power artificial neural networks (ANNs), supporting the analysis and the classification of collected data. This approach allows to reduce the energy consumed by particular sensors during the communication with other nodes of a larger WSN. This in turn, facilitates the maintenance of a net of such sensors, which is a paramount feature in case of their application in SG devices distributed over a large area. In this work, we focus on a novel, energy-efficient neighborhood mechanism (NM) with the neighborhood function (NF). This mechanism belongs to main components of self learning ANNs. We propose a realization of this component as a specialized chip in the CMOS technology and its optimization in terms of the circuit complexity and the consumed energy. The circuit was realized as a prototype chip in the CMOS 130 nm technology, and verified by means of transistor level simulations and measurements.

Energy efficient neighborhood design under residential zoning regulations in Shanghai

In the current pursuit of eco-city development in China, energy efficient residential neighborhood development becomes one of the focuses. While current codes and practices have been paying attention to green building design, building energy is influenced by not only building design, but also complex urban form at a larger spatial scale, which was not well discussed. At the same time, neighborhood design is always regulated by residential zoning codes, which restrict the density measures for economic considerations and layout to ensure safety, privacy, fire prevention and sunlight. What neighborhood design can achieve high energy performance under those regulations becomes a critical question for urban design practices. This study explores three questions: How density influences residential building energy efficiency? How different building heights affects building energy? And how different neighborhood layouts impact the building energy? Those questions are examined by computational simulation experiments on parametric design scenarios in the case study of a hypothetical neighborhood in Shanghai. The comparisons of the simulation results suggest that density and energy performance has a complex relation with a threshold density that has the best performance, and building height and energy use have a segmented relation with the same density due to elevator design codes. The energy performance ranges with the same FAR and with the same number of floors show the great impact of the building height and limited influence of neighborhood layout on building energy use. The simulation results also suggest the optimal design with best energy performance with different density settings. The findings can inform urban designers and policy makers on more energy efficient residential neighborhood design under current zoning regulations.

Influence of Buildings Configuration on the Energy Demand and Sizing of Energy Systems in an Urban Context

Energy interaction among buildings play a vital role when considering the energy demand at neighbourhood or urban scale which notably influence the energy system sizing problem. The proper representation of buildings and their effects such as drag force effects, generation of turbulence, shading etc. are crucial in the evaluation of building energy demand and subsequently in energy system sizing. This is not practiced in present literature. To achieve this, we couple a meteorological model, a building energy model and an energy system tool. We show that the use of local climatic data and urban planning scenario have a significant impact on the design of energy systems. More importantly, the results of the study show that co-simulation platform coupling meteorological model, building simulation model and energy system designing model can help to design energy efficient neighbourhoods with more renewable energy integration.

Enabling local authorities to produce short-term energy plans

Purpose– The purpose of this paper is to identify the most appropriate multidisciplinary data sources related with energy optimization decision support as well as the related methodologies, tools and techniques for data capturing and processing for each of them.Design/methodology/approach– A review is conducted on the state-of-play of decision support systems for energy optimization, focussing on the municipal sector, followed by an identification of the most appropriate multidisciplinary data sources related with energy optimization decision support. An innovative methodology is outlined to integrate semantically modeled data from multiple sources, to assist city authorities in energy management.Findings– City authorities need to lead relevant actions toward energy-efficient neighborhoods. Although there are more and more energy and other related data available at the city level, there are no established methods and tools integrating and analyzing them in a smart way, with the purpose to support the decision-making process on energy use optimization.Originality/value– A novel multidimensional approach is proposed, using semantic technologies to integrate data from multiple sources, to assist city authorities to produce short-term energy plans in an integrated, transparent and comprehensive way.

‘effort’ (Energy Efficiency on-site) – A New Method for Planning and Realization of Energy-efficient Neighbourhoods Under the Aspects of Sustainability

To meet the challenges of climate change requires the commitment towards a climate-friendly energy production as well as an increased effort for climate-friendly energy use. In order to produce a noticeable reduction in greenhouse gases, it is necessary to increase the share of renewable energy and energy efficiency use in all sectors of consumption. The necessary result can only be achieved in the long term by the inclusion of as many households and businesses in our towns, cities and communities. The crucial spatial unit of this energy-efficiency urban redevelopment has become apparent based on present knowledge of the neighbourhood. Within the system relationship between building and city, lies the major energy optimization potential on a neighbourhood scale – in the sense that maximum energy efficiency may be grouped together in the spatial unit.

The very hungry city: urban energy efficiency and the economic fate of cities

As global demand for energy grows and prices rise, a city's energy consumption becomes increasingly tied to its economic viability, warns the author of The Very Hungry City. Austin Troy, a seasoned expert in environmental management, explains for general readers how a city with a high urban energy metabolism-that is, a city that needs large amounts of energy in order to function-will be at a competitive disadvantage in the future. He explores why cities have different energy metabolisms and discusses an array of innovative approaches to the problems of expensive energy consumption. Troy looks at dozens of cities and suburbs in Europe and the United States-from Los Angeles to Copenhagen, Denver to the Swedish redevelopment project Hammarby Sjostad-to understand the diverse factors that affect their energy use: behavior, climate, water supply, building quality, transportation, and others. He then assesses some of the most imaginative solutions that cities have proposed, among them green building, energy-efficient neighborhoods, symbiotic infrastructure, congestion pricing, transit-oriented development, and water conservation. To conclude, the author addresses planning and policy approaches that can bring about change and transform the best ideas into real solutions.