Contribution of urban ventilation to the thermal environment and urban energy demand: Different climate background perspectives

2021 ◽  
pp. 148791
Author(s):  
Jun Yang ◽  
Yichen Wang ◽  
Bing Xue ◽  
Yunfei Li ◽  
Xiangming Xiaog ◽  
...  
Keyword(s):  
Energy Demand ◽  
Thermal Environment ◽  
Urban Energy ◽  
Climate Background

scholarly journals A new clustering and visualization method to evaluate urban energy planning scenarios

2018 ◽  
Author(s):  
Sara Torabi Moghadam ◽  
Silvia Coccolo ◽  
Guglielmina Mutani ◽  
Patrizia Lombardi ◽  
Jean Louis Scartezzini ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Urban Areas ◽  
Energy Demand ◽  
Planning Process ◽  
Energy Transition ◽  
Climatic Conditions ◽  
Energy Planning ◽  
Transition Strategies ◽  
Urban Energy ◽  
The City

The spatial visualization is a very useful tool to help decision-makers in the urban planning process to create future energy transition strategies, implementing energy efficiency and renewable energy technologies in the context of sustainable cities. Statistical methods are often used to understand the driving parameters of energy consumption but rarely used to evaluate future urban renovation scenarios. Simulating whole cities using energy demand softwares can be very extensive in terms of computer resources and data collection. A new methodology, using city archetypes is proposed, here, to simulate the energy consumption of urban areas including urban energy planning scenarios. The objective of this paper is to present an innovative solution for the computation and visualization of energy saving at the city scale.The energy demand of cities, as well as the micro-climatic conditions, are calculated by using a simplified 3D model designed as function of the city urban geometrical and physical characteristics. Data are extracted from a GIS database that was used in a previous study. In this paper, we showed how the number of buildings to be simulated can be drastically reduced without affecting the accuracy of the results. This model is then used to evaluate the influence of two set of renovation solutions. The energy consumption are then integrated back in the GIS to identify the areas in the city where refurbishment works are needed more rapidly. The city of Settimo Torinese (Italy) is used as a demonstrator for the proposed methodology, which can be applied to all cities worldwide with limited amount of information.

scholarly journals Urban energy performance calculation based on EPBD standards. GIS4ENER tool

2020 ◽  
Author(s):  
Gema Hernandez-Moral ◽  
◽  
Víctor Iván Serna-Gonzalez ◽  
Francisco Javier Miguel Herrero ◽  
César Valmaseda-Tranque
Keyword(s):  
Energy Demand ◽  
Planning Process ◽  
Energy Performance ◽  
Local Scale ◽  
Decision Makers ◽  
Energy Planning ◽  
Strong Impact ◽  
Building Stock ◽  
Urban Energy ◽  
Performance Calculation

Climate change will have a strong impact on urban settings, which will also represent one of the major challenges (world’s urban population is expected to double by 2050, EU buildings consume 40% final energy and generate 36% CO2 emissions). A plethora of initiatives address this challenge by stressing the underlying necessity of thinking globally but acting locally. This entails the inclusion of a varied set of decision-makers acting at different scales and needing robust, comprehensive and comparable information that can support them in their energy planning process. To this end, this paper presents the GIS4ENER tool to support energy planners at different scales by proposing a bottom-up approach towards the calculation of energy demand and consumption at local scale that can be aggregated to support other decision-making scales. It is based on three main pillars: the exploitation of publicly available data (such as Open Street Maps, Building Stock Observatory or TABULA), the implementation of standardised methods to calculate energy (in particular the ISO52000 family) and the use of Geographic Information Systems to represent and facilitate the understanding of results, and their aggregation. The paper presents the context, main differences with other approaches and results of the tool in Osimo (IT).

Dynamic Geospatial Modeling of the Building Stock To Project Urban Energy Demand

2018 ◽  
Vol 52 (14) ◽  
pp. 7604-7613
Author(s):  
Hanna M. Breunig ◽  
Tyler Huntington ◽  
Ling Jin ◽  
Alastair Robinson ◽  
Corinne D. Scown
Keyword(s):  
Energy Demand ◽  
Building Stock ◽  
Geospatial Modeling ◽  
Urban Energy

scholarly journals Study on Multi-Objective Optimization-Based Climate Responsive Design of Residential Building

Algorithms ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 238
Author(s):  
Zhixing Li ◽  
Paolo Vincenzo Genovese ◽  
Yafei Zhao
Keyword(s):  
Energy Demand ◽  
Thermal Environment ◽  
Residential Buildings ◽  
Optimal Solution ◽  
Residential Building ◽  
The Public ◽  
Private Households ◽  
Design Variables ◽  
Global Cost ◽  
Responsive Design

This paper proposes an optimization process based on a parametric platform for building climate responsive design. Taking residential buildings in six typical American cities as examples, it proposes thermal environment comfort (Discomfort Hour, DH), building energy demand (BED) and building global cost (GC) as the objective functions for optimization. The design variables concern building orientation, envelope components, and window types, etc. The optimal solution is provided from two different perspectives of the public sector (energy saving optimal) and private households (cost-optimal) respectively. By comparing the optimization results with the performance indicators of the reference buildings in various cities, the outcome can give the precious indications to rebuild the U.S. residential buildings with a view to energy-efficiency and cost optimality depending on the location.

scholarly journals Integration of Thermoactive Metro Stations in a Smart Energy System: Feedbacks from the Grand Paris Project

2018 ◽  
Vol 3 (4) ◽  
pp. 56 ◽  
Author(s):  
Yvon Delerablée ◽  
Dina Rammal ◽  
Hussein Mroueh ◽  
Sébastien Burlon ◽  
Julien Habert ◽  
...  
Keyword(s):  
Energy Demand ◽  
Mechanical Design ◽  
Energy System ◽  
Thermal Design ◽  
Transport Efficiency ◽  
The Public ◽  
Geothermal Potential ◽  
Potential Estimate ◽  
Urban Energy ◽  
Public Entity

During the next 15 years, around 200 km of tunnels and 68 new metro stations will be built around Paris to increase the capacity of the existing metro and the transport efficiency. The Société du Grand Paris—the public entity in charge of the design and the execution of this new network—is also highly concerned by the development and the use of renewable energy within this project, especially the integration of thermoactive metro stations in a smart energy system. This paper discusses some issues related to this strategy within the “Grand Paris Project”. The first part presents how smart technology could help to the integration of thermoactive metro stations into the urban energy system, while the second part addresses the following issues: assessment of the geothermal potential, estimate of the energy demand, ground investigations, thermal design, and finally system monitoring. The mechanical design is not considered in this paper. The paper shows the pertinence of the smart energy system for the integration of the thermoactive metro stations energy and the procedure for its implementation.

Urban Form and Energy Demand

2017 ◽  
Vol 32 (4) ◽  
pp. 346-365 ◽  
Author(s):  
Mafalda Silva ◽  
Vítor Oliveira ◽  
Vítor Leal
Keyword(s):  
Urban Environment ◽  
Urban Form ◽  
Energy Demand ◽  
Energy Analysis ◽  
Comprehensive Analysis ◽  
Travel Patterns ◽  
International Debate ◽  
Trade Offs ◽  
Energy Trade ◽  
Urban Energy

The implications of urban form on energy have long been present in international debate, whether considering travel patterns or thermal comfort in buildings. The urban environment is a result of a set of intertwined attributes, the understanding of which is often unclear. The energy trade-offs between urban form attributes haven’t received proper attention. Research remains sectorial, considering buildings and transport in isolation. In order to allow for a comprehensive analysis of this relationship, this article reviews urban attributes with energy relevance. A collection of attributes and metrics is gathered from the literature for incorporating urban form in urban energy analysis.

scholarly journals Energy planning with renewable energy sources

2021 ◽  
Vol 5 (3) ◽  
pp. 44-51
Author(s):  
Félix Antonio Solórzano Narváez ◽  
Edgar Iván Moreno Castro
Keyword(s):  
Energy Demand ◽  
Planning Process ◽  
Renewable Energy Sources ◽  
Appropriate Technology ◽  
Environmental Aspects ◽  
Continuous Increase ◽  
Specific Analysis ◽  
Resource Requirements ◽  
Urban Energy ◽  
External Sources

The urban energy model is based on imports from external sources. The continuous increase in energy demand due to population growth and development implies increasing resource requirements. The alternative is to use renewable energies that take advantage of urban resources. The diversity of typologies of cities in terms of resources, demands, architectural conditions, infrastructure, or density, makes a specific analysis necessary. This work identifies fourteen factors concerning the planning process that would allow choosing the most appropriate technology for a given city. Through consultation of experts, the existence of the resource is defined as the most prevalent factor, followed by economic conditions; On the other hand, it is detected that environmental aspects such as global warming, eutrophication, or acidification, are the least incidents when selecting technologies.

scholarly journals Indicators for the optimization of sustainable urban energy systems based on energy system modeling

2022 ◽  
Vol 12 (1) ◽  
Author(s):  
Christian Klemm ◽  
Frauke Wiese
Keyword(s):  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Energy Demand ◽  
Energy Systems ◽  
Energy System ◽  
Energy Sustainability ◽  
Gas Emissions ◽  
Urban Energy ◽  
Absolute Energy ◽  
Final Energy Demand

Abstract Background Urban energy systems are responsible for 75% of the world’s energy consumption and for 70% of the worldwide greenhouse gas emissions. Energy system models are used to optimize, benchmark and compare such energy systems with the help of energy sustainability indicators. We discuss several indicators for their basic suitability and their response to changing boundary conditions, system structures and reference values. The most suitable parameters are applied to four different supply scenarios of a real-world urban energy system. Results There is a number of energy sustainability indicators, but not all of them are suitable for the use in urban energy system optimization models. Shortcomings originate from the omission of upstream energy supply chains (secondary energy efficiency), from limited capabilities to compare small energy systems (energy productivity), from excessive accounting expense (regeneration rate), from unsuitable accounting methods (primary energy efficiency), from a questionable impact of some indicators on the overall system sustainability (self-sufficiency), from the lack of detailed information content (share of renewables), and more. On the other hand, indicators of absolute greenhouse gas emissions, energy costs, and final energy demand are well suitable for the use in optimization models. However, each of these indicators only represents partial aspects of energy sustainability; the use of only one indicator in the optimization process increases the risk that other important aspects will deteriorate significantly, eventually leading to suboptimal or even unrealistic scenarios in practice. Therefore, multi-criteria approaches should be used to enable a more holistic optimization and planning of sustainable urban energy systems. Conclusion We recommend multi-criteria optimization approaches using the indicators of absolute greenhouse gas emissions, absolute energy costs, and absolute energy demand. For benchmarking and comparison purposes, specific indicators should be used and therefore related to the final energy demand, respectively, the number of inhabitants. Our example scenarios demonstrate modeling strategies to optimize sustainability of urban energy systems.

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