Equivalent full-load hours for assessing climate change impact on building cooling and heating energy consumption in large Asian cities

Equivalent full-load hours for estimating heating and cooling energy requirements in buildings: Greece case study

This study investigates Europe’s space cooling energy field. The work aims to assess the European Union (plus the United Kingdom) final energy consumption for space cooling in both the residential and service sectors with 2016 as a baseline. An extensive literature review of datasets and journal papers has been conducted to fill the knowledge gaps of the investigated energy branch. The European space cooling market is mainly dominated by vapour compression (VC) technologies which, in this study, have been grouped as room air conditioners (RACs) and centralized air conditioners (CACs). These technology groups have been investigated, and their installed capacities, energy efficiency levels (seasonal energy efficiency ratio—SEER), equivalent full load hours (EFLHs), and amount of space cooling units installed have been identified as essential parameters to calculate the final energy consumption for space cooling. Overall, the total value of the European final energy consumption for the space cooling sector, including both the residential and service sectors, results in 106 TWh/year.

This study analysed one of Europe’s most unexplored energy fields: process cooling (PC). The work assessed the final energy consumption (FEC) for PC of the European Union (and United Kingdom) with a 2016 baseline. An extensive literature review of datasets and journal papers was performed to address knowledge gaps by creating a high-quality dataset with factual accuracy, reliability, and completeness. Installed cooling units, equivalent full load hours, energy efficiency levels (seasonal energy performance ratio), and capacities installed were the essential investigated parameters to perform the FEC calculations. The latter were referred to as vapour compression (VC) chillers (air-to-water or water-to-water). Overall, the results of the EU (plus UK) FEC for the PC sector resulted in more than 110 TWh/year, accounting for around 10% of the total energy consumption for electricity in Europe. It is worth mentioning that several non-VC technologies are utilized for PC purposes in various sectors and subsectors primarily in the industry and the tertiary sectors, which are rapidly growing and, therefore, their cooling consumption is increasing. The current research paper aimed to raise awareness of the PC sector by supporting the European Union policies toward a more sustainable and decarbonized industry in the upcoming decades.

The current study aims to investigate one of the most underexplored energy fields in scientific research, i.e., final energy consumption (FEC) of space cooling (SC) in the European (EU27+UK) transportation sector with 2019 as a baseline. The fundamentals of this study include a comprehensive literature review as well as the creation of a dataset characterized by completeness and reliability. Different essential input parameters have been investigated and the encountered data and information gaps have been filled. The transportation sector has been broken down into three main categories, namely, light, medium, and heavy vehicles. Throughout the EU27+UK, the number of vehicles, equivalent full load hours (EFLHs), system power capacities, and their related energy efficiency levels have been collected. The collected data and information have been computed and the EU27+UK FEC for space cooling in the transportation sector resulted in more than 125 TWh/year. It is worth underlining that the light vehicles category accounted for the majority of the total FEC, followed by the medium and heavy vehicle categories, respectively.

A wide variety of building energy analysis methods are currently available to HVAC engineers and range from simple to sophisticated. The simplest methods involve the largest number of simplifying assumptions and therefore tend to be the least accurate. The most sophisticated methods involve the fewest assumptions and thus can provide the most accurate results. Generally, methods for building energy analysis can be given at three categories as follows:  Single Measure Methods (example: Equivalent Full Load Hours)  Simplified Multiple Measure Methods (example: Bin Method)  Detailed Multiple Measure Methods (example: Hour by Hour)

Optimum insulation thickness for refrigeration applications

Approval standard of electricity price is currently the focus of discussion in the national wind power industry. How to determine an appropriate electricity tariff to promote the sustainable and healthy development of wind power is the urgent problem that wind power company need to solve. In this paper, a generation cost assessment model for wind power is established, taking the cost accounting of Changdao wind farm as an example. On this basis, a fixed price system, which adopts 10% as an IRR of total investment, is used to determine the on-grid electricity price of wind power, combining the unit investment per kW and equivalent full load hours. This calculating model is used to assess the price of Changdao wind farm; meanwhile, study and comparison with the actual price in operation process are done for other two wind farms. The result proves the practicability and rationality of this wind electricity price calculation model.

This paper presents a thermoeconomic optimization analysis yielding a simple algebraic formula for estimating the optimum number of panes for windows. The “ P1 - P2 method,” “the degree day method,” and “the equivalent full load hours energy estimation method” are used together with the correlated overall heat transfer coefficient values for single, double, triple, and quadruple pane windows that are used in HVAC and refrigeration applications.

Electric cooling technologies impose significant demand on the utility grid. For instance, the cooling system for a 200,000 square foot building can add over 300 kW of electric load onto the grid during peak summer periods. A typical 600,000-square-foot building has an electric chiller plant that peaks at nearly 1 MW. Natural gas and steam chillers, on the other hand, impose only a fraction of these loads on the electric grid. This article highlights the potential and importance of subsidies and incentive programs in promoting non-electric cooling technologies to help reduce the peak demand load on the New York power grid. The results obtained also provide valuable equipment-installed costs and energy/demand parameters for both electric and non-electric chillers. The technical and economic viability of five non-electric cooling technologies are compared to standard practice electric chillers. The five non-electric cooling technologies are: 1. Gas engine-driven chiller2. Two-stage gas-fired absorption chiller3. Two-stage steam-fired absorption chiller4. Single-stage steam-fired absorption chiller5. Steam-turbine driven centrifugal chiller The energy consumption and peak summer demand were calculated for the chillers in each of three different size ranges. Installed cost estimates were developed for each chiller technology in two regions of New York State. The results presented here will help design consultants, estimators, utilities, and government energy officials assess preliminary estimates for installed costs, energy savings, and incremental maintenance costs. Normalized costing indices such as $/ton, $/hp, $/sqft. and $/lin.ft and operating characteristics such as full load hours and kW/ton rules of thumb for the chiller and plant components are also presented. The study reports typical office building savings and economic paybacks. Chiller operation of 800 equivalent full load hours (EFLH) for upstate New York sites and 850 EFLH for downstate/NYC sites were used.

Study on Energy Conservation Standards of Air Conditioning Equipment : (Part 3) Revised Version of the CEC/AC Calculation Using the Equivalent Full-Load Hours Method

Abstract. To track progress towards keeping global warming well below 2 ∘C or even 1.5 ∘C, as agreed in the Paris Agreement, comprehensive up-to-date and reliable information on anthropogenic emissions and removals of greenhouse gas (GHG) emissions is required. Here we compile a new synthetic dataset on anthropogenic GHG emissions for 1970–2018 with a fast-track extension to 2019. Our dataset is global in coverage and includes CO2 emissions, CH4 emissions, N2O emissions, as well as those from fluorinated gases (F-gases: HFCs, PFCs, SF6, NF3) and provides country and sector details. We build this dataset from the version 6 release of the Emissions Database for Global Atmospheric Research (EDGAR v6) and three bookkeeping models for CO2 emissions from land use, land-use change, and forestry (LULUCF). We assess the uncertainties of global greenhouse gases at the 90 % confidence interval (5th–95th percentile range) by combining statistical analysis and comparisons of global emissions inventories and top-down atmospheric measurements with an expert judgement informed by the relevant scientific literature. We identify important data gaps for F-gas emissions. The agreement between our bottom-up inventory estimates and top-down atmospheric-based emissions estimates is relatively close for some F-gas species (∼ 10 % or less), but estimates can differ by an order of magnitude or more for others. Our aggregated F-gas estimate is about 10 % lower than top-down estimates in recent years. However, emissions from excluded F-gas species such as chlorofluorocarbons (CFCs) or hydrochlorofluorocarbons (HCFCs) are cumulatively larger than the sum of the reported species. Using global warming potential values with a 100-year time horizon from the Sixth Assessment Report by the Intergovernmental Panel on Climate Change (IPCC), global GHG emissions in 2018 amounted to 58 ± 6.1 GtCO2 eq. consisting of CO2 from fossil fuel combustion and industry (FFI) 38 ± 3.0 GtCO2, CO2-LULUCF 5.7 ± 4.0 GtCO2, CH4 10 ± 3.1 GtCO2 eq., N2O 2.6 ± 1.6 GtCO2 eq., and F-gases 1.3 ± 0.40 GtCO2 eq. Initial estimates suggest further growth of 1.3 GtCO2 eq. in GHG emissions to reach 59 ± 6.6 GtCO2 eq. by 2019. Our analysis of global trends in anthropogenic GHG emissions over the past 5 decades (1970–2018) highlights a pattern of varied but sustained emissions growth. There is high confidence that global anthropogenic GHG emissions have increased every decade, and emissions growth has been persistent across the different (groups of) gases. There is also high confidence that global anthropogenic GHG emissions levels were higher in 2009–2018 than in any previous decade and that GHG emissions levels grew throughout the most recent decade. While the average annual GHG emissions growth rate slowed between 2009 and 2018 (1.2 % yr−1) compared to 2000–2009 (2.4 % yr−1), the absolute increase in average annual GHG emissions by decade was never larger than between 2000–2009 and 2009–2018. Our analysis further reveals that there are no global sectors that show sustained reductions in GHG emissions. There are a number of countries that have reduced GHG emissions over the past decade, but these reductions are comparatively modest and outgrown by much larger emissions growth in some developing countries such as China, India, and Indonesia. There is a need to further develop independent, robust, and timely emissions estimates across all gases. As such, tracking progress in climate policy requires substantial investments in independent GHG emissions accounting and monitoring as well as in national and international statistical infrastructures. The data associated with this article (Minx et al., 2021) can be found at https://doi.org/10.5281/zenodo.5566761.

Indonesia has targeted 29 % Greenhouse gas (GHG) emissions reduction in 2030 and Industry is one of the big two contributors for GHG emissions. As an industry, mining is an energy-intensive industry, and reducing energy consumption is one of the strategies to improve mining environmental performance. The aim of this paper is to estimate the GHG emission reduction in a mining project through energy reduction initiatives. A copper mine in Indonesia with processing plant capacity of 120,000 t/d and operate 111 Caterpillar 793C Haul Truck was taken as a case study. This mine site has two sources of an electricity namely coal-fired power plant with 112 MW output and diesel power plant with 45 MW output. The analysis method for calculating CO2 emission is using IPCC method where fuel consumption and emission factor are two main variables for GHG emissions. Business as usual scenario (TIER 1) showed that the average of diesel fuel consumption for fleets operation generated 294,006 t CO2-eq/y. A coal-fired power plant with average coal consumption of 350 t/d/unit generated 1.15 Mt CO2-eq/y and diesel power plant consumed 4.35 ML/y produced 11,632 t CO2-eq/y. Two energy initiative programs were identified namely fuel conversion and used oil utilisation program. The initiative scenario focused on substituting, reducing and reusing of fossil fuels including coal, diesel fuel, and used oil. This scenario was estimated to contribute the carbon emission reduction (t CO2-eq) of 258,381 annually. The involvement of mining industry in carbon emission reduction is not only helping Indonesia in achieving its GHG emissions reduction target but also increases mine site environmental performance and company image.

Better information on greenhouse gas (GHG) emissions and mitigation potential in the agricultural sector is necessary to manage these emissions and identify responses that are consistent with the food security and economic development priorities of countries. Critical activity data (what crops or livestock are managed in what way) are poor or lacking for many agricultural systems, especially in developing countries. In addition, the currently available methods for quantifying emissions and mitigation are often too expensive or complex or not sufficiently user friendly for widespread use.The purpose of this focus issue is to capture the state of the art in quantifying greenhouse gases from agricultural systems, with the goal of better understanding our current capabilities and near-term potential for improvement, with particular attention to quantification issues relevant to smallholders in developing countries. This work is timely in light of international discussions and negotiations around how agriculture should be included in efforts to reduce and adapt to climate change impacts, and considering that significant climate financing to developing countries in post-2012 agreements may be linked to their increased ability to identify and report GHG emissions (Murphy et al 2010, CCAFS 2011, FAO 2011).

Greenhouse gas (GHG) emissions reduction in the electricity sector: Implications of increasing renewable energy penetration in Ghana's electricity generation mix

Harmonizing the quantification of CCS GHG emission reductions through oil and natural gas industry project guidelines