Research on the Integration of Energy Economic Model and Urban Energy Model

2021 ◽  
Vol 3 (6) ◽  
pp. 15-17
Author(s):  
Yaozhong Zu ◽  
Keyword(s):  
Greenhouse Gas ◽  
Building Energy ◽  
Urban Environments ◽  
Interdisciplinary Studies ◽  
Energy Models ◽  
Energy Needs ◽  
Urban Energy ◽  
Energy Economic Model ◽  
High Level ◽  
Building Level

In order to explore the strategy on urban energy and reduction of greenhouse gas, a large number of energy models have been developed by interdisciplinary studies. Mixed patterns are particularly useful as a result that they incorporate more dynamics to simulate the relevant high-level decisions and the provided actual results by building-level factors. However, space and spatial energy models are not often linked, which ignores the spatial impact of energy and emission policies in urban environments. The application of this method shows how it can be used to assess how different policies interact with other and affect building energy needs and greenhouse gas emissions.

scholarly journals Investigating Bundled Approaches To Reduce Greenhouse Gas Emissions in the Toronto 2030 District

2021 ◽  
Author(s):  
Patrick Ritsma
Keyword(s):  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Energy Demand ◽  
Building Energy ◽  
Energy Performance ◽  
Energy Reduction ◽  
Building Stock ◽  
Gas Emissions ◽  
Urban Core ◽  
Energy Models

Building energy models are an effective tool for evaluating energy reduction opportunities in both design phase and post-occupancy scenarios. By merging building energy models with city scale building stock data, it is possible to analyze energy performance at a greater breadth, providing more informed policy decisions and solutions to energy demand asymmetries in urban metropolises. This study examines the energy reduction potential for office buildings in the Toronto 2030 District, by testing individual and bundled energy conservation measures and greenhouse gas reduction strategies using a reference building energy model. When extrapolated across Toronto’s urban core, simulation results determined that standard interventions on the existing office building stock have the potential to reduce greenhouse gas emissions by as much as 91.5%, in line with 2030 District initiatives.

Validation of Building Energy Modeling Tools for a Residential Building in Brasov Area-Romania

2018 ◽  
Vol 20 (1) ◽  
pp. 43-50
Author(s):  
Lucian Cîrstolovean ◽  
Paraschiva Mizgan
Keyword(s):  
Energy Use ◽  
Residential Building ◽  
Building Energy ◽  
Valuable Insight ◽  
Thermal Loads ◽  
Building Energy Modeling ◽  
Modeling Tools ◽  
Energy Models ◽  
Energy Needs ◽  
Insight Into

Abstract A building energy model is a simulation tool which calculates the thermal loads and energy use in buildings. Building energy models provide valuable insight into energy use in buildings based on architecture, materials and thermal loads. In addition, building energy models also must account for the effects of the building’s occupants in terms of energy use. In this paper we discuss building energy models and their accuracy in predicting energy use. In particular, we focus on two types of validation methods which have been used to investigate the accuracy of building energy models and on how they account for their effects on occupants. The analyzed building is P + M located in the climatic zone 4, Sânpetru / Braşov. We have carried out a detailed and exemplary energy needs analysis using two methods of analysis.

scholarly journals Review of Energy in the Built Environment

Smart Cities ◽  
2020 ◽  
Vol 3 (2) ◽  
pp. 248-288 ◽  
Author(s):  
Ioannis Lampropoulos ◽  
Tarek Alskaif ◽  
Wouter Schram ◽  
Eelke Bontekoe ◽  
Simone Coccato ◽  
...  
Keyword(s):  
Built Environment ◽  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Urban Areas ◽  
Energy Demand ◽  
Sustainable Energy ◽  
Urban Environments ◽  
Gas Emissions ◽  
Heating Systems ◽  
Urban Energy

Urban environments can be key to sustainable energy in terms of driving innovation and action. Urban areas are responsible for a significant part of energy use and associated greenhouse gas emissions. The share of greenhouse gas emissions is likely to increase as global urban populations increase. As over half of the human population will live in cities in the near future, the management of energy supply and demand in urban environments will become essential. Developments such as the transformation of the electricity grid from a centralised to a decentralised system as well as the electrification of the transportation and heating systems in buildings will transform the urban energy landscape. Efficient heating systems, sustainable energy technologies, and electric vehicles will be critical to decarbonise cities. An overview of emerging technologies and concepts in the built environment is provided in this literature review on the basis of four main areas, namely, energy demand, supply, storage, and integration aspects. The Netherlands is used as a case study for demonstrating evidence-based results and feasibility of innovative urban energy solutions, as well as supportive policies.

scholarly journals Investigating Bundled Approaches To Reduce Greenhouse Gas Emissions in the Toronto 2030 District

2021 ◽  
Author(s):  
Patrick Ritsma
Keyword(s):  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Energy Demand ◽  
Building Energy ◽  
Energy Performance ◽  
Energy Reduction ◽  
Building Stock ◽  
Gas Emissions ◽  
Urban Core ◽  
Energy Models

Building energy models are an effective tool for evaluating energy reduction opportunities in both design phase and post-occupancy scenarios. By merging building energy models with city scale building stock data, it is possible to analyze energy performance at a greater breadth, providing more informed policy decisions and solutions to energy demand asymmetries in urban metropolises. This study examines the energy reduction potential for office buildings in the Toronto 2030 District, by testing individual and bundled energy conservation measures and greenhouse gas reduction strategies using a reference building energy model. When extrapolated across Toronto’s urban core, simulation results determined that standard interventions on the existing office building stock have the potential to reduce greenhouse gas emissions by as much as 91.5%, in line with 2030 District initiatives.

Characterization Of Building Foundation In Building Energy Models

2020 ◽  
Author(s):  
Germán Ramos Ruiz ◽  
Vicente Gutierrez González ◽  
Eva Lucas Segarra ◽  
Germán Campos Gordillo ◽  
Carlos Fernandez Bandera
Keyword(s):  
Building Energy ◽  
Energy Models ◽  
Building Foundation

scholarly journals Impact of Actual Weather Datasets for Calibrating White-Box Building Energy Models Base on Monitored Data

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1187
Author(s):  
Vicente Gutiérrez González ◽  
Germán Ramos Ruiz ◽  
Carlos Fernández Bandera
Keyword(s):  
Control Experiment ◽  
Pearson Correlation ◽  
Building Energy ◽  
Third Party ◽  
Primary Position ◽  
Energy Models ◽  
Urgent Task ◽  
Calibration Study ◽  
Study Case ◽  
Reduce Energy Consumption

The need to reduce energy consumption in buildings is an urgent task. Increasing the use of calibrated building energy models (BEM) could accelerate this need. The calibration process of these models is a highly under-determined problem that normally yields multiple solutions. Among the uncertainties of calibration, the weather file has a primary position. The objective of this paper is to provide a methodology for selecting the optimal weather file when an on-site weather station with local sensors is available and what is the alternative option when it is not and a mathematically evaluation has to be done with sensors from nearby stations (third-party providers). We provide a quality assessment of models based on the Coefficient of Variation of the Root Mean Square Error (CV(RMSE)) and the Square Pearson Correlation Coefficient (R2). The research was developed on a control experiment conducted by Annex 58 and a previous calibration study. This is based on the results obtained with the study case based on the data provided by their N2 house.

scholarly journals Energy and Greenhouse Gas Savings for LEED-Certified U.S. Office Buildings

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 749
Author(s):  
John H. Scofield ◽  
Susannah Brodnitz ◽  
Jakob Cornell ◽  
Tian Liang ◽  
Thomas Scofield
Keyword(s):  
Greenhouse Gas ◽  
Energy Use ◽  
Energy Savings ◽  
Electric Energy ◽  
Building Energy ◽  
Energy Performance ◽  
Office Buildings ◽  
Ghg Emission ◽  
Site Energy ◽  
New Construction

In this work, we present results from the largest study of measured, whole-building energy performance for commercial LEED-certified buildings, using 2016 energy use data that were obtained for 4417 commercial office buildings (114 million m2) from municipal energy benchmarking disclosures for 10 major U.S. cities. The properties included 551 buildings (31 million m2) that we identified as LEED-certified. Annual energy use and greenhouse gas (GHG) emission were compared between LEED and non-LEED offices on a city-by-city basis and in aggregate. In aggregate, LEED offices demonstrated 11% site energy savings but only 7% savings in source energy and GHG emission. LEED offices saved 26% in non-electric energy but demonstrated no significant savings in electric energy. LEED savings in GHG and source energy increased to 10% when compared with newer, non-LEED offices. We also compared the measured energy savings for individual buildings with their projected savings, as determined by LEED points awarded for energy optimization. This analysis uncovered minimal correlation, i.e., an R2 < 1% for New Construction (NC) and Core and Shell (CS), and 8% for Existing Euildings (EB). The total measured site energy savings for LEED-NC and LEED-CS was 11% lower than projected while the total measured source energy savings for LEED-EB was 81% lower than projected. Only LEED offices certified at the gold level demonstrated statistically significant savings in source energy and greenhouse gas emissions as compared with non-LEED offices.

scholarly journals Probabilistic Load Forecasting Optimization for Building Energy Models via Day Characterization

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3299
Author(s):  
Eva Lucas Segarra ◽  
Germán Ramos Ruiz ◽  
Carlos Fernández Bandera
Keyword(s):  
Optimization Technique ◽  
Load Forecasting ◽  
Weather Forecast ◽  
Building Energy ◽  
Load Forecast ◽  
Energy Saving Potential ◽  
Energy Models ◽  
Building Monitoring ◽  
Probabilistic Load ◽  
Grid Operators

Accurate load forecasting in buildings plays an important role for grid operators, demand response aggregators, building energy managers, owners, customers, etc. Probabilistic load forecasting (PLF) becomes essential to understand and manage the building’s energy-saving potential. This research explains a methodology to optimize the results of a PLF using a daily characterization of the load forecast. The load forecast provided by a calibrated white-box model and a real weather forecast was classified and hierarchically selected to perform a kernel density estimation (KDE) using only similar days from the database characterized quantitatively and qualitatively. A real case study is presented to show the methodology using an office building located in Pamplona, Spain. The building monitoring, both inside—thermal sensors—and outside—weather station—is key when implementing this PLF optimization technique. The results showed that thanks to this daily characterization, it is possible to optimize the accuracy of the probabilistic load forecasting, reaching values close to 100% in some cases. In addition, the methodology explained is scalable and can be used in the initial stages of its implementation, improving the values obtained daily as the database increases with the information of each new day.

scholarly journals A Method for Optimizing and Spatially Distributing Heating Systems by Coupling an Urban Energy Simulation Platform and an Energy System Model

Resources ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 52
Author(s):  
Annette Steingrube ◽  
Keyu Bao ◽  
Stefan Wieland ◽  
Andrés Lalama ◽  
Pithon M. Kabiro ◽  
...  
Keyword(s):  
District Heating ◽  
Energy Systems ◽  
Energy System ◽  
Heat Pumps ◽  
Energy Simulation ◽  
Heating Systems ◽  
Optimal Amount ◽  
Urban City ◽  
Urban Energy ◽  
Building Level

District heating is seen as an important concept to decarbonize heating systems and meet climate mitigation goals. However, the decision related to where central heating is most viable is dependent on many different aspects, like heating densities or current heating structures. An urban energy simulation platform based on 3D building objects can improve the accuracy of energy demand calculation on building level, but lacks a system perspective. Energy system models help to find economically optimal solutions for entire energy systems, including the optimal amount of centrally supplied heat, but do not usually provide information on building level. Coupling both methods through a novel heating grid disaggregation algorithm, we propose a framework that does three things simultaneously: optimize energy systems that can comprise all demand sectors as well as sector coupling, assess the role of centralized heating in such optimized energy systems, and determine the layouts of supplying district heating grids with a spatial resolution on the street level. The algorithm is tested on two case studies; one, an urban city quarter, and the other, a rural town. In the urban city quarter, district heating is economically feasible in all scenarios. Using heat pumps in addition to CHPs increases the optimal amount of centrally supplied heat. In the rural quarter, central heat pumps guarantee the feasibility of district heating, while standalone CHPs are more expensive than decentral heating technologies.

Sign in / Sign up

Export Citation Format

Share Document