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Abstract Building energy performance is often inadequate given design goals. While different types of assessment methods exist, they either do not consider design goals and/or are not general enough to integrate new and innovative energy concepts. Furthermore, existing assessment methods focus mostly on the building and system level while ignoring more detailed data. With the availability and affordability of more detailed measured data, the increased number of measured data points requires a structure to organize these data. This paper presents the Energy Performance Comparison Methodology (EPCM), which enables the identification of performance problems based on a comparison of measured data and simulated data representing design goals. The EPCM is based on an interlinked building object hierarchy that structures the detailed performance data from a spatial and mechanical perspective. This research is developed and tested on multiple case studies that provide real-life context and more generality compared to single case studies.

Abstract Adsorbent-based carbon capture is only feasible if adsorption-desorption cycles are both fully regenerating and efficient. This work proposes a regenerative pH swing process and a pH swing regenerative adsorbent that are inspired by natural CO2 conversion by carbonic anhydrase biocatalysts found in mammalian red blood cells. The main objective is to develop, test and analyze a synthetic pH Swing Adsorption (pHSA) system as well as a pHSA compatible solid adsorbent to capture CO2 from a simulated ambient air gas stream. The lead developed adsorbent is a carbon black co-activated with potassium carbonate and nitrogenous copolymer that is impregnated with immobilized bovine carbonic anhydrase and thereby deemed “BCA/KN-CB”. BCA/KN-CB has preliminarily demonstrated both competitive CO2 adsorption capacity and limited regenerative ability under experimental pHSA conditions. In addition, BCA-based adsorbents achieved higher adsorption capacities than non-BCA adsorbent counterparts. The BCA/KN-CB adsorbent displayed both large point of zero charge (PZC) swings and regenerative stability. The proposed pHSA system requires essentially zero energy expenditure to achieve intended environments for capture and regeneration. With 1 kg of adsorbent, pHSA has the ability to capture 1 kg CO2 in less than 4 h of cycling. The tested pHSA adsorbent can also capture more than 96% of total CO2 in a given raw gas stream flowing through the capture chamber. This proof-of-concept study of a pH swing adsorption/biocatalytic adsorbent system suggests the potential to effectively operate under ambient conditions and exhibit advantageous operational efficiencies to other high-profile CO2 capture systems.

Abstract The main hindrances to the large-scale development of renewable-energy projects are the lack of bankability and the inability to align investments and investors with suitable financial instruments or robust policy measures. To illustrate a bankable project, this paper presents a research-based case study on the installation of solar photovoltaic panels on the rooftops of 195 trains of the Indian Railways. Detailed information on the annual running hours, exposure to sunlight, efficiency of solar photovoltaic generation and electrical power demands of each rail coach is considered to conduct a quantitative measure of the tentative amount of fossil fuel savings. The purpose is to provide insight into the types of renewable-energy projects that can be highly attractive to financial institutions and promoters due to their lucrative internal return on investment. As seen in this case study, there are annual savings in diesel of 12 323 088 litres and a CO2 reduction of 32 755 tonnes, with return on investment of 1.3 years. Furthermore, this study conducts a comprehensive analysis of the limitations of existing renewable-energy project financing mechanisms in India. Subsequently, three policy measures are recommended to develop a robust financial mechanism that can effectively meet the needs of investors and investors. These measures include increasing equity injection through a buy-and-hold strategy, providing direct tax benefits to promoters and financing through real-estate investment trusts. The findings are highly relevant to address the challenges associated with bridging the financial gap between access to finance and capital investment in the renewable-energy sector, especially for Asian countries.

Abstract In this work, energy analysis is carried out to account for inputs and outputs of energy and GHG emissions associated with the biodiesel production system. Jojoba oil is obtained by cultivation of the jojoba plant, harvesting of seeds followed by extraction of oil, which is then converted to biodiesel by the process of transesterification. Energy efficiency is expressed in terms of the net energy balance (NEB) and the net energy ratio (NER). The use of the byproducts (husk, cake or meal, waste residues and glycerin) are also included as a part of the system boundary. The results show that the NEB and NER values are calculated at 46724.1 MJ/ha (28.9 MJ/L biodiesel produced) and 2.16, respectively. At the same time, the total amount of GHG emissions are estimated at 2.28 kg-CO2eq/L biodiesel produced (66.0 g CO2eq/MJ biodiesel produced). Nevertheless, if manure is used as fertilizer for jojoba plant cultivation, the primary energy input will fall by 9.52% (to 22.49 MJ/L of biodiesel).

Reduced scale experiments are often employed in engineering because they are much cheaper than real scale testing. Unfortunately, though, it is difficult to design a thermal-hydraulic circuit or equipment in reduced scale capable of reproducing, both accurately and simultaneously, all the physical phenomena that occur in real scale and operating conditions. This paper presents a methodology to designing thermal-hydraulic experiments in reduced scale based on setting up a constrained optimization problem that is solved using genetic algorithms (GAs). In order to demonstrate the application of the methodology proposed, we performed some investigations in the design of a heater aimed to simulate the transport of heat and momentum in the core of a pressurized water reactor (PWR) at 100% of nominal power and non-accident operating conditions. The results obtained show that the proposed methodology is a promising approach for designing reduced scale experiments.

Large amounts of CO2 from human socioeconomic activities threaten environmental sustainability. Moreover, uncontrolled resource use and lack of relevant technology exacerbate this issue. For this reason, carbon capture, utilization, and storage (CCUS) technology has gained worldwide attention. Many scholars have researched CCUS, but few have used CCUS patent bibliometric analysis from a unified perspective. This article aims to provide a conclusive analysis for CCUS researchers and policymakers, as well as summarize the innovation trends, technological distribution, and topic evolution. Based on 11,915 pieces of patent data from the Derwent Innovations Index, we used bibliometric analysis and data mining methods to conduct research on four dimensions: overall trend, geographical distribution, patentees, and patent content. The results of this article are as follows. CCUS has entered a rapid development stage since 2013. Patents are mainly distributed geographically in China, the US, and Japan, especially in heavy industries such as energy and electricity. Large enterprises hold patents with a relatively stable network of cooperators and attach great importance to international patent protection. A total of 12 topics were identified through clustering, and these topics gradually shifted from technicalities to commercialization, and from industrial production to all aspects of people’s daily lives.

Short-term load forecasting is an essential instrument in power system planning, operation and control. Many operating decisions are based on load forecasts, such as dispatch scheduling of generating capacity, reliability analysis, and maintenance planning for the generators. Overestimation of electricity demand will cause a conservative operation, which leads to the start-up of too many units or excessive energy purchase, thereby supplying an unnecessary level of reserve. On the contrary, underestimation may result in a risky operation, with insufficient preparation of spinning reserve, causing the system to operate in a vulnerable region to the disturbance. In this paper, semi-parametric additive models are proposed to estimate the relationships between demand and the driver variables. Specifically, the inputs for these models are calendar variables, lagged actual demand observations and historical and forecast temperature traces for one or more sites in the target power system. In addition to point forecasts, prediction intervals are also estimated using a modified bootstrap method suitable for the complex seasonality seen in electricity demand data. The proposed methodology has been used to forecast the half-hourly electricity demand for up to seven days ahead for power systems in the Australian National Electricity Market. The performance of the methodology is validated via out-of-sample experiments with real data from the power system, as well as through on-site implementation by the system operator.

This paper examines and optimizes parameters that affect the air cooling of a Lithium-Ion (Li-Ion) battery, used in Electric Vehicles (EVs). A battery pack containing 150 cylindrical type Li-Ion battery cells in a PVC casing is investigated. An equal number of tubes are used in the pack as a medium to cool the battery by using a fan when the vehicle is stationary or with ambient air when in motion. The parameters affecting the air cooling of battery are studied and optimized by considering their practical constraints. The objective function and Number of Transfer Unit (NTU) are developed. Finally, a genetic algorithm method is employed to optimize the decision variables. Analysing the results shows that NTU can be maximized by increasing the diameter of tubes on the battery and keeping the air velocity in a certain range.

AbstractBioenergy projects can lead to direct and indirect land use change (LUC), which can substantially affect greenhouse gas balances with both beneficial and adverse outcomes for bioenergy's contribution to climate change mitigation. The causes behind LUC are multiple, complex, interlinked, and change over time. This makes quantification uncertain and sensitive to many factors that can develop in different directions—including land use productivity, trade patterns, prices and elasticities, and use of by‐products associated with biofuels production. Quantifications reported so far vary substantially and do not support the ranking of bioenergy options with regard to LUC and associated emissions. There are however several options for mitigating these emissions, which can be implemented despite the uncertainties. Long‐rotation forest management is associated with carbon emissions and sequestration that are not in temporal balance with each other and this leads to mitigation trade‐offs between biomass extraction for energy use and the alternative to leave the biomass in the forest. Bioenergy's contribution to climate change mitigation needs to reflect a balance between near‐term targets and the long‐term objective to hold the increase in global temperature below 2°C (Copenhagen Accord). Although emissions from LUC can be significant in some circumstances, the reality of such emissions is not sufficient reason to exclude bioenergy from the list of worthwhile technologies for climate change mitigation. Policy measures to minimize the negative impacts of LUC should be based on a holistic perspective recognizing the multiple drivers and effects of LUC.This article is categorized under: Bioenergy > Economics and Policy Bioenergy > Climate and Environment