The use of temporal factors for improved CO2 emissions accounting in buildings

2018 ◽  
Vol 39 (2) ◽  
pp. 196-210 ◽  
Author(s):  
Barny Evans ◽  
Sabbir Sidat
Keyword(s):  
Air Quality ◽  
Energy Demand ◽  
Energy System ◽  
Net Energy ◽  
Electricity Grid ◽  
Electrical Grid ◽  
Significant Difference ◽  
Emissions Factor ◽  
Single Number ◽  
The Impact

This paper is an investigation into the issues around how we calculate CO2 emissions in the built environment. At present, in Building Regulations and GHG Protocol calculations used for buildings and corporate CO2 emissions calculations, it is standard to use a single number for the CO2 emission factor of each source. This paper considers how energy demand, particularly electricity at different times of the day, season and even year can differ in terms of its CO2 emissions. This paper models three different building types (retail, office and home) using standard software to estimate a profile of energy demand. It then considers how CO2 emissions calculations differ between using the single standard emissions factor and using an hourly emissions factor based on real electrical grid generation over a year. The paper also examines the impact of considering lifetime emissions factors rather than one-year factors using UK government projections. The results show that there is a significant difference to the analysis of benefit in terms of CO2 emissions from different measures – both intra- and inter-year – due to the varying CO2 emissions intensity, even when they deliver the same amount of net energy saving. Other factors not considered in this paper, such as impact on peak generation and air quality, are likely to be important when considering whole-system impacts. In line with this, it is recommended that moves are made to incorporate intra- and inter-year emissions factor changes in methodologies for calculating CO2 emissions. (This is particularly important as demand side response and energy storage, although generally accepted as important in the decarbonisation of the energy system at present will show as an increase in CO2 emissions when using a single number.) Further work quantifying the impact on air quality and peak generation capacity should also be considered. Practical application: This paper aims to help practitioners to understand the performance gap between how systems need to be designed in order to meet regulations compared to how buildings perform in reality – both today and in the future. In particular, it considers the use of ‘real-time’ carbon factors in order to attain long-term CO2 reductions. This methodology enables decision makers to understand the impacts of different energy reduction technologies, considering each of their unique characteristics and usage profiles. If implemented, the result is a simple-to-use dataset which can be embedded into the software packages already available onto the market which mirrors the complexity of the electricity grid that is under-represented through the use of a static carbon figure.

scholarly journals Optimal Planning and Operation of a Residential Energy Community under Shared Electricity Incentives

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2045
Author(s):  
Pierpaolo Garavaso ◽  
Fabio Bignucolo ◽  
Jacopo Vivian ◽  
Giulia Alessio ◽  
Michele De Carli
Keyword(s):  
Renewable Energy ◽  
Power Distribution ◽  
Energy Demand ◽  
Renewable Energy Sources ◽  
Energy System ◽  
Distribution Networks ◽  
Building Envelope ◽  
Net Energy ◽  
Technical Equipment ◽  
Optimal Planning

Energy communities (ECs) are becoming increasingly common entities in power distribution networks. To promote local consumption of renewable energy sources, governments are supporting members of ECs with strong incentives on shared electricity. This policy encourages investments in the residential sector for building retrofit interventions and technical equipment renovations. In this paper, a general EC is modeled as an energy hub, which is deemed as a multi-energy system where different energy carriers are converted or stored to meet the building energy needs. Following the standardized matrix modeling approach, this paper introduces a novel methodology that aims at jointly identifying both optimal investments (planning) and optimal management strategies (operation) to supply the EC’s energy demand in the most convenient way under the current economic framework and policies. Optimal planning and operating results of five refurbishment cases for a real multi-family building are found and discussed, both in terms of overall cost and environmental impact. Simulation results verify that investing in building thermal efficiency leads to progressive electrification of end uses. It is demonstrated that the combination of improvements on building envelope thermal performances, photovoltaic (PV) generation, and heat pump results to be the most convenient refurbishment investment, allowing a 28% overall cost reduction compared to the benchmark scenario. Furthermore, incentives on shared electricity prove to stimulate higher renewable energy source (RES) penetration, reaching a significant reduction of emissions due to decreased net energy import.

scholarly journals Window operation behaviour and indoor air quality during lockdown: A monitoring-based simulation-assisted study in London

2021 ◽  
pp. 014362442110177
Author(s):  
Farhang Tahmasebi ◽  
Yan Wang ◽  
Elizabeth Cooper ◽  
Daniel Godoy Shimizu ◽  
Samuel Stamp ◽  
...  
Keyword(s):  
Air Quality ◽  
Indoor Air Quality ◽  
Indoor Air ◽  
Energy Demand ◽  
Natural Ventilation ◽  
Probabilistic Models ◽  
Performance Model ◽  
Outdoor Environment ◽  
Ventilation Strategies ◽  
The Impact

The Covid-19 outbreak has resulted in new patterns of home occupancy, the implications of which for indoor air quality (IAQ) and energy use are not well-known. In this context, the present study investigates 8 flats in London to uncover if during a lockdown, (a) IAQ in the monitored flats deteriorated, (b) the patterns of window operation by occupants changed, and (c) more effective ventilation patterns could enhance IAQ without significant increases in heating energy demand. To this end, one-year’s worth of monitored data on indoor and outdoor environment along with occupant use of windows has been used to analyse the impact of lockdown on IAQ and infer probabilistic models of window operation behaviour. Moreover, using on-site CO2 data, monitored occupancy and operation of windows, the team has calibrated a thermal performance model of one of the flats to investigate the implications of alternative ventilation strategies. The results suggest that despite the extended occupancy during lockdown, occupants relied less on natural ventilation, which led to an increase of median CO2 concentration by up to 300 ppm. However, simple natural ventilation patterns or use of mechanical ventilation with heat recovery proves to be very effective to maintain acceptable IAQ. Practical application: This study provides evidence on the deterioration of indoor air quality resulting from homeworking during imposed lockdowns. It also tests and recommends specific ventilation strategies to maintain acceptable indoor air quality at home despite the extended occupancy hours.

scholarly journals Sustainable Electric Vehicle Transportation

2021 ◽  
Vol 13 (22) ◽  
pp. 12379
Author(s):  
Raymond Kene ◽  
Thomas Olwal ◽  
Barend J. van Wyk
Keyword(s):  
Electric Vehicle ◽  
Energy Demand ◽  
Large Scale ◽  
Common Knowledge ◽  
Distribution Network ◽  
Electricity Grid ◽  
Current State ◽  
The World ◽  
The Impact ◽  
Ev Charging

The future direction of electric vehicle (EV) transportation in relation to the energy demand for charging EVs needs a more sustainable roadmap, compared to the current reliance on the centralised electricity grid system. It is common knowledge that the current state of electricity grids in the biggest economies of the world today suffer a perennial problem of power losses; and were not designed for the uptake and integration of the growing number of large-scale EV charging power demands from the grids. To promote sustainable EV transportation, this study aims to review the current state of research and development around this field. This study is significant to the effect that it accomplishes four major objectives. (1) First, the implication of large-scale EV integration to the electricity grid is assessed by looking at the impact on the distribution network. (2) Secondly, it provides energy management strategies for optimizing plug-in EVs load demand on the electricity distribution network. (3) It provides a clear direction and an overview on sustainable EV charging infrastructure, which is highlighted as one of the key factors that enables the promotion and sustainability of the EV market and transportation sector, re-engineered to support the United Nations Climate Change Agenda. Finally, a conclusion is made with some policy recommendations provided for the promotion of the electric vehicle market and widespread adoption in any economy of the world.

Impact of Rooftop PV Shading on Net Electrical Energy Demand of Buildings in Pakistan

2021 ◽  
Vol 3 (1) ◽  
pp. 45-49
Author(s):  
Muhammad Umar Maqbool ◽  
Arslan Dawood Butt ◽  
Abdul Rauf Bhatti ◽  
Yawar Ali Sheikh ◽  
Muhammad Waleed Asif
Keyword(s):  
Energy Demand ◽  
Heat Load ◽  
Layer Structure ◽  
Electrical Energy ◽  
Position Angle ◽  
Net Energy ◽  
Ambient Conditions ◽  
Pv System ◽  
Roof Structure ◽  
The Impact

This work performs a quantitative assessment of the impact of rooftop PV installation on building’s net energy demand using model of roof structure and steady state thermal simulations. For this purpose, roof structure typically used in Faisalabad, Pakistan is modeled with and without the shading effect due to a 395 W commercial rooftop PV setup. The simulated parameters include the impact of PV module’s dimensions, mounting position/angle alongside roof size and ambient conditions on heat load of air-conditioning system to maintain a temperature of 25 °C within building’s top floor. During the daylight hours of July, the heat load added by the roof on average reduces from 150.87 BTU/h/m2 without PV to 118.16 BTU/h/m2 with PV structure. This 20.05% reduction in energy demand has been achieved with July’s maximum daytime solar and infrared irradiances of 792.2 W/m2 and 466 W/m2 recorded at an average ambient temperature of 35.5 °C and wind speed of 2.75 m/s. This study provides valuable data on optimization of roof layer structure during building’s construction in anticipation of PV system installation at a later stage. Also developed techniques/methods to reduce building’s energy budget due to PV installation, can be valuable input for construction industry as well.

scholarly journals How did Lofgreen and Garrett do the math?

2019 ◽  
Vol 3 (3) ◽  
pp. 1011-1017
Author(s):  
James W Oltjen
Keyword(s):  
Body Weight ◽  
Energy Content ◽  
Energy System ◽  
Metabolizable Energy ◽  
Net Energy ◽  
Significant Difference ◽  
Linear Fit ◽  
Metabolizable Energy Intake ◽  
Logarithmic Equation ◽  
Finishing Beef Cattle

Abstract Lofgreen and Garrett introduced a new system for predicting growing and finishing beef cattle energy requirements and feed values using net energy concepts. Based on data from comparative slaughter experiments they mathematically derived the California Net Energy System. Scaling values to body weight to the ¾ power, they summarized metabolizable energy intake (ME), energy retained (energy balance [EB]), and heat production (HP) data. They regressed the logarithm of HP on ME and extended the line to zero intake, and estimated fasting HP at 0.077 Mcal/kg0.75, similar to previous estimates. They found no significant difference in fasting HP between steers and heifers. Above maintenance, however, a logarithmic fit of EB on ME does not allow for increased EB once ME is greater than 340 kcal/kg0.75, or about three times maintenance intake. So based on their previous work, they used a linear fit so that partial efficiency of gain above maintenance was constant for a given feed. They show that with increasing roughage level efficiency of gain (slope) decreases, consistent with increasing efficiency of gain and maintenance with greater metabolizable energy of the feed. Making the system useful required that gain in body weight be related to EB. They settled on a parabolic equation, with significant differences between steers and heifers. Lofgreen and Garrett also used data from a number of experiments to relate ME and EB to estimate the ME required for maintenance (ME = HP) and then related the amount of feed that provided that amount of ME to the metabolizable energy content of the feed (MEc), resulting in a logarithmic equation. Then they related that amount of feed to the net energy for gain calculated as the slope of the EB line when regressed against feed intake. Combining the two equations, they estimate the net energy for maintenance and gain per unit feed (Mcal/kg dry matter) as a function of MEc: 0.4258 × 1.663MEc and 2.544–5.670 × 0.6012MEc, respectively. Finally, they show how to calculate net energy for maintenance and gain from experiments where two levels of a ration are fed and EB measured, where one level is fed and a metabolism trial is conducted, or when just a metabolism trial is conducted—but results are not consistent between designs.

scholarly journals Emissions from Irish domestic fireplaces and their impact on indoor air quality when used as supplementary heating source

2013 ◽  
Vol 10 (2) ◽  
pp. 209-216
Keyword(s):  
Air Quality ◽  
Indoor Air Quality ◽  
Indoor Air ◽  
Emission Rates ◽  
Airborne Particle ◽  
Potential Health ◽  
Heating Source ◽  
Open Fire ◽  
Significant Difference ◽  
The Impact

A field study on the impact of fireplace on the indoor air quality was carried out between 2004 and 2006, where two main contaminants, CO and particulate matters, were investigated in twenty seven randomly selected Irish houses. The results show that while the physical environment has been improved by increasing the room air and radiant temperature, indoor air quality is significantly decreased when fireplace is used as additional heating source to the central heating. The operation of fireplace increased transient concentrations of CO and airborne particle to several times higher than the normal house average level. Statistical analysis showed significant difference of the average PM10 concentration between house groups with and without using fireplace. However fireplace did not demonstrate a significant influence on average CO level from our samples. When comparisons were made between houses with various emission sources, i.e. fireplace, smoking and open fire gas cooking, and houses free of the above sources, smoking and open fire gas cookers were proved to be other major sources of particles and CO. Particularly when they exist at the same time with fireplace, significant elevation of CO and airborne particle levels is observed in analysis. Cumulative probability analysis in some houses revealed high percentage of time exceeding health guidelines which indicated the potential health risk in these houses. Mass balance equation was employed to estimate particle emission rates from fireplace, namely 0.66 mg min-1 (PM10) and 0.20 mg min-1 (PM2.5) respectively in terms of mass concentration. Emission rates on particle numbers were also estimated despite the relatively smaller sample. Gas fuel fireplaces tended to emit fewer particles both in mass and in number comparing to fireplaces using solid fuels.

scholarly journals Big Data in Smart Energy Systems: A Critical Review

2020 ◽  
Vol 11 (41) ◽  
pp. 11-26
Author(s):  
Keziban Seçkin Codal ◽  
İzzet Arı ◽  
H. Kemal İlter
Keyword(s):  
Big Data ◽  
Critical Review ◽  
Carbon Dioxide Emissions ◽  
Energy Demand ◽  
Renewable Energy Sources ◽  
Energy Systems ◽  
Energy System ◽  
Interdisciplinary Studies ◽  
Smart Energy Systems ◽  
The Impact

Climate change is an undeniable fact. Considering that two-thirds of greenhouse gas emissions originate from the energy sector, it is expected that the world's energy system will be transformed with renewable energy sources. Energy efficiency will be continuously increased. Reducing energy-related carbon dioxide emissions is the heart of the energy transition. Big data in energy systems play a crucial role in evaluating the adaptive capacity and investing more smartly to manage energy demand and supply. Indeed, the impact of the smart energy grid and meters on smart energy systems provide and assist decision-makers in transforming energy production, consumption, and communities. This study reviews the literature for aligning big data and smart energy systems and criticized according to regional perspective, period, disciplines, big data characteristics, and used data analytics. The critical review has been categorized into present themes. The results address issues, including scientific studies using data analysis techniques that take into account the characteristics of big data in the smart energy literature and the future of smart energy approaches. The manuscripts on big data in smart energy systems are a promising issue, albeit it is essential to expand subjects through comprehensive interdisciplinary studies

scholarly journals Digital Twin-Driven Decision Making and Planning for Energy Consumption

2021 ◽  
Vol 10 (2) ◽  
pp. 37
Author(s):  
Yasmin Fathy ◽  
Mona Jaber ◽  
Zunaira Nadeem
Keyword(s):  
Energy Consumption ◽  
Energy Demand ◽  
Energy Production ◽  
Energy Use ◽  
Synthetic Data ◽  
Average Energy ◽  
Energy System ◽  
Real Dataset ◽  
Digital Twin ◽  
The Impact

The Internet of Things (IoT) is revolutionising how energy is delivered from energy producers and used throughout residential households. Optimising the residential energy consumption is a crucial step toward having greener and sustainable energy production. Such optimisation requires a household-centric energy management system as opposed to a one-rule-fits all approach. In this paper, we propose a data-driven multi-layer digital twin of the energy system that aims to mirror households’ actual energy consumption in the form of a household digital twin (HDT). When linked to the energy production digital twin (EDT), HDT empowers the household-centric energy optimisation model to achieve the desired efficiency in energy use. The model intends to improve the efficiency of energy production by flattening the daily energy demand levels. This is done by collaboratively reorganising the energy consumption patterns of residential homes to avoid peak demands whilst accommodating the resident needs and reducing their energy costs. Indeed, our system incorporates the first HDT model to gauge the impact of various modifications on the household energy bill and, subsequently, on energy production. The proposed energy system is applied to a real-world IoT dataset that spans over two years and covers seventeen households. Our conducted experiments show that the model effectively flattened the collective energy demand by 20.9% on synthetic data and 20.4% on a real dataset. At the same time, the average energy cost per household was reduced by 10.7% for the synthetic data and 17.7% for the real dataset.

scholarly journals Improving Energy Sustainability of Suburban Areas by Using Distributed Energy Systems: A Case Study

Proceedings ◽  
2020 ◽  
Vol 58 (1) ◽  
pp. 7
Author(s):  
Beaud Muriel ◽  
Amarasinghage Tharindu Dasun Perera ◽  
Cai Hanmin ◽  
Andrew Bollinger ◽  
Kristina Orehounig
Keyword(s):  
Energy Demand ◽  
Energy Systems ◽  
Energy System ◽  
Distributed Energy ◽  
Building Sector ◽  
Urban Density ◽  
Suburban Areas ◽  
Energy Technologies ◽  
Distributed Energy System ◽  
The Impact

The building sector plays a vital role in Switzerland’s climate policy. In order to support the energy transition in the building sector, Rolle, a suburban area located along the shore of Lake Geneva is considered in this study to understand the promising future scenarios for integration of renewable energy technologies. The area is clustered into 12 clusters and a distributed energy system is designed for each cluster. Subsequently, three energy systems with contrasting densities are taken for further comparison to understand the impact of urban density on the design of the distributed energy system. The study reveals that urban density will influence the peak as well as the annual energy demand of the energy hubs. The study reveals that the energy technologies used in the energy hubs are strongly influenced by the capacity of the system (peak and annual energy demand). Energy systems with higher capacities are less sensitive to the market changes when compared to the systems with lower capacities (leading to sparse suburban areas).

scholarly journals Sizing and Management of an Energy System for a Metropolitan Station with Storage and Related District Energy Community

Energies ◽  
2021 ◽  
Vol 14 (18) ◽  
pp. 5997
Author(s):  
Mircea Stefan Simoiu ◽  
Ioana Fagarasan ◽  
Stephane Ploix ◽  
Vasile Calofir
Keyword(s):  
Energy Storage ◽  
Optimal Solution ◽  
Energy System ◽  
District Level ◽  
Mixed Integer ◽  
Programming Approach ◽  
Net Energy ◽  
Self Sufficiency ◽  
Photovoltaic Plant ◽  
The Impact

Future renewable energy communities will reshape the paradigm in which we design and control efficient power systems at the district level. In this manner, the focus will be fundamentally shifted towards sustainable related concepts such as self-consumption, self-sufficiency and net energy exchanged with the grid. In this context, the paper presents a novel approach for optimally designing and controlling the photovoltaic plant and energy storage systems for a metro station in order to increase collective self-consumption and self-sufficiency at the district level. The methodology considers a community of several households connected to a subway station and focuses on the interaction between energy sources and consumers. Furthermore, the optimal solution is determined by using a Mixed Integer Linear Programming Approach, and the impact of different configurations on the overall district benefit is investigated by using several simulation scenarios. The work presents a detailed case study to underline the benefits and flexibility offered by the energy storage system in comparison with a scenario involving only a photovoltaic plant.

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