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Abstract Two office layouts with high and low levels of thermal control were compared, respectively traditional cellular and contemporary open plan offices. The traditional Norwegian practice provided every user with control over a window, blinds, door, and the ability to adjust heating and cooling. Occupants were expected to control their thermal environment to find their own comfort, while air conditioning was operating in the background to ensure the indoor air quality. In contrast, in the British open plan office, limited thermal control was provided through openable windows and blinds only for occupants seated around the perimeter of the building. Centrally operated displacement ventilation was the main thermal control system. Users’ perception of thermal environment was recorded through survey questionnaires, empirical building performance through environmental measurements and thermal control through semi-structured interviews. The Norwegian office had 35% higher user satisfaction and 20% higher user comfort compared to the British open plan office. However, the energy consumption in the British practice was within the benchmark and much lower than the Norwegian office. Overall, a balance between thermal comfort and energy efficiency is required, as either extreme poses difficulties for the other.

Abstract Specification by central government of the heating levels which are to be maintained in British school buildings has recently been altered. This paper is concerned with examining the nature of changes that have been made by comparing present requirements with their counterparts during the preceding one hundred years. Attention is focused on the apparently contradictory implications of these changes for those charged with responsibility for maintaining heating levels in school buildings while, at the same time, conserving fuel. It is suggested that the new statutory requirements present those who are responsible with a duty which may, in practical terms, prove difficult or costly to discharge. Although discussion is specifically restricted to British school buildings, issues are raised which are pertinent to attempts to integrate regulation of heating with control of fuel consumption in other types of non-domestic buildings both in Britain and abroad.

Thermal generation is a vital component of mature and reliable electricity markets. As the share of renewable electricity in such markets grows, so too do the challenges associated with its variability. Proposed solutions to these challenges typically focus on alternatives to primary generation, such as energy storage, demand side management, or increased interconnection. Less attention is given to the demands placed on conventional thermal generation or its potential for increased flexibility. However, for the foreseeable future, conventional plants will have to operate alongside new renewables and have an essential role in accommodating increasing supply-side variability.\ud \ud This paper explores the role that conventional generation has to play in managing variability through the sub-system case study of Northern Ireland, identifying the significance of specific plant characteristics for reliable system operation. Particular attention is given to the challenges of wind ramping and the need to avoid excessive wind curtailment. Potential for conflict is identified with the role for conventional plant in addressing these two challenges. Market specific strategies for using the existing fleet of generation to reduce the impact of renewable resource variability are proposed, and wider lessons from the approach taken are identified.

The optimal selection, sizing, and location of small-scale technologies within a grid-connected distributed energy system (DES) can contribute to reducing carbon emissions, consumer costs, and network imbalances. This is the first study to present an optimisation framework for obtaining discrete technology sizing and selection for grid-connected DES design, while simultaneously considering multiphase optimal power flow (MOPF) constraints to accurately represent unbalanced low-voltage distribution networks. An algorithm is developed to solve the resulting Mixed-Integer Nonlinear Programming (MINLP) formulation. It employs a decomposition based on Mixed-Integer Linear Programming (MILP) and Nonlinear Programming (NLP), and utilises integer cuts and complementarity reformulations to obtain discrete designs that are also feasible with respect to the network constraints. A heuristic modification to the original algorithm is also proposed to improve computational speed. Improved formulations for selecting feasible combinations of air source heat pumps (ASHPs) and hot water storage tanks are also presented. The algorithms outperform the existing state-of-the-art commercial MINLP solver, which fails to find any solutions in two instances. While feasible solutions were obtained for all cases, convergence was not achieved for all, especially for those involving the larger network. Where converged, the algorithm with the heuristic modification has achieved results up to 70% faster than the original algorithm. Results for case studies suggest that including ASHPs can support up to 16% higher renewable generation capacity compared to gas boilers, albeit with higher ASHP investment costs. The optimisation framework and results can be used to inform stakeholders such as policy-makers and network operators, to increase renewable energy capacity and aid the decarbonisation of domestic heating systems. 47 pages, 10 figures, 14 Tables

Abstract Steady-state free and forced convective cooling of vertical, rectangular, 3 mm thick, 250 mm long fins, uniformly separated and protruding vertically upwards from a 250 mm × 190 mm isothermal horizontal base was investigated. For each combination of specified fin protrusion, horizontal forced air flow-rate in the direction along the fins and fin base temperature, the optimal fin spacing—corresponding to the maximum rate of heat loss—has been deduced. As the fin protrusion of the heat exchanger increases, this optimal value rises significantly in forced convection conditions, but declines slightly in the presence of free convection alone. The temperature distributions over the fins' surfaces were also studied, when the fin base was maintained at constant temperatures of either 40°C, 60°C or 80°C above that of the ambient environment. Large temperature depressions occurred near the leading edges and tips of the fins in forced convection, whereas much nearer isothermal temperature distributions were present under free convection conditions.

Abstract Algae have been considered as a promising biodiesel feedstock. One of the major factors affecting large-scale algae technology application is poor wintering cultivation performance. In this study, an integrated approach is investigated combining freshwater microalgae Chlorella zofingiensis wintering cultivation in pilot-scale photobioreactors with artificial wastewater treatment. Mixotrophic culture with the addition of acetic acid (pH-regulation group) and autotrophic culture (control group) were designed, and the characteristics of algal growth, lipid and biodiesel production, and nitrogen and phosphate removal were examined. The results showed that, by using acetic acid three times per day to regulate pH at between 6.8 and 7.2, the total nitrogen (TN) and total phosphate (TP) removal could be increased from 45.2% to 73.5% and from 92.2% to 100%, respectively. Higher biomass productivity of 66.94 mg L−1 day−1 with specific growth rate of 0.260 day−1 was achieved in the pH-regulation group. The lipid content was much higher when using acetic acid to regulate pH, and the relative lipid productivity reached 37.48 mg L−1 day−1. The biodiesel yield in the pH-regulated group was 19.44% of dry weight, with 16–18 carbons as the most abundant composition for fatty acid methyl esters. The findings of the study prove that pH adjustment using acetic acid is efficient in cultivating C. zofingiensis in wastewater in winter for biodiesel production and nutrient reduction.

Feature-based machine learning models for capacity and internal resistance (IR) curve prediction have been researched extensively in literature due to their high accuracy and generalization power. Most such models work within the high frequency of data availability regime, e.g., voltage response recorded every 1–4 s. Outside premium fee cloud monitoring solutions, data may be recorded once every 3, 5 or 10 min. In this low-data regime, there are little to no models available. This literature gap is addressed here via a novel methodology, underpinned by strong mathematical guarantees, called ‘path signature’. This work presents a feature-based predictive model for capacity fade and IR rise curves from only constant-current (CC) discharge voltage corresponding to the first 100 cycles. Included is a comprehensive feature analysis for the model via a relevance, redundancy, and complementarity feature trade-off mechanism. The ability to predict from subsampled ‘CC voltage at discharge’ data is investigated using different time steps ranging from 4 s to 4 min. It was discovered that voltage measurements taken at the end of every 4 min are enough to generate features for curve prediction with End of Life (EOL) and its corresponding IR values predicted with a mean absolute percentage error (MAPE) of approximately 13.2% and 2.1%, respectively. Our model under higher frequency (4 s) produces an improved accuracy with EOL predicted with an MAPE of 10%. Full implementation code publicly available.

Abstract The pressure-loss coefficient for a duct junction of square cross-section was determined using computational fluid dynamics (CFD). The predicted junction pressure-loss coefficient for combining flows was generally in good agreement with experimental data from the literature. The junction pressure-loss coefficient was associated with the flow from the side branch to the duct carrying the total flow.