An Investigation into the Predictive Capability of Customer Spending in Modelling Mortgage Default

The mortgage arrears crisis in Ireland was and is among the most severe experienced on record and although there has been a decreasing trend in the number of mortgages in default in the past four years, it still continues to cause distress to borrowers and vulnerabilities to lenders. There are indications that one of the main factors associated with mortgage default is loan affordability, of which the level of disposable income is a driver. Additionally, guidelines set out by the European Central Bank instructed financial institutions to adopt measures to further reduce and prevent loans defaulting, including the implementation and identification of Early Warning Indicators (EWIs). Financial institutions currently adopt credit risk models in order to calculate the risk associated with customers. Therefore, this research observed a cohort of mortgage customers in Lender A over a 30-month period and utilised transactional features, explaining the use of disposable income, to expand on existing credit risk models and aid in the identification of EWIs for the mortgage portfolio. Over the course of the study three feature selection techniques were adopted, namely correlation-based analysis, random forest feature importance and decision tree feature importance. A number of transactional categories were identified including insurance spend, gambling spend, savings and the value of ATM withdrawals. Furthermore, it was found that the inclusion of transactional features in existing credit risk models statistically improved performance

Energy Reduction by Enhanced Evaporative Cooling of Buildings in Martime Climates

Direct cooling of buildings by water evaporation has traditionally been seen as appropriate, only, in dry and arid climates, which experience high levels of wet bulb temperature depression. The technique has generally not been applied in maritime climates where low levels of wet bulb temperature depression are frequently found. However, recent developments in enhancing heat and mass transfer in cooling towers, together with the success of high temperature sensible cooling systems, such as chilled ceiling panels and beams, have prompted a review of the evaporative cooling technique as an effective and low energy means of cooling modern deep plan buildings, in maritime climates. At present, however, there is little in depth research and analysis of the performance, energy efficiency, and availability of this form of cooling in maritime conditions. To address these issues an experimental research programme has been established with a view to demonstrating the potential and optimising the design of this form of cooling under low approach conditions. This paper presents the results of recent experimental research into the electrical consumption of a prototype inverter controlled cooling tower when generating cooling water at the chilled water temperatures required for chilled ceiling panels and beams, under varying load and wet bulb temperature approach conditions. Energy consumption efficiencies are presented for a range of specific conditions and typical annual efficiencies are computed. Results are compared with typical energy consumption efficiencies of conventional, vapour compression based, cooling systems. A considerable potential for the reduction of cooling electrical energy consumption, in maritime climates, is shown

Indirect Evaporative Cooling Potential in Air-water Systems in Temperate Climates

Recent developments have prompted a review of evaporative cooling technology as an effective means of cooling modern deep plan buildings. Prominent among these developments is the success of high temperature sensible cooling systems, particularly, chilled ceilings, which require a supply of cooling water at 14–18 °C. Crucial to the success of evaporative cooling technology, as a significant means of cooling in modern applications, is the ability to generate cooling water, in an indirect circuit, at a temperature which closely approaches the ambient adiabatic saturation temperature (AST) or wet bulb temperature (WBT). Recent experimental research has demonstrated that it is technically viable to generate such cooling water at a temperature of 3 K above the ambient AST. While the frequency of ambient AST occurrence can be obtained from meteorological sources, there is little in-depth analysis of the potential for this form of cooling water generation, based on the approach temperatures which have now been shown to be viable. The decision to use an evaporative cooling system depends largely on an assessment, in-depth, of net energy saved against capital expended. Such an assessment requires detailed data on the availability of cooling water, generated by evaporation, for each location. This paper quantifies evaporative cooling availability in-depth for a northern and southern European city, Dublin and Milan and suggests a method of analysing such data for any world wide location, for which suitable meteorological records are available. The paper, incorporates recent experimental research findings and bases the availability analysis on meteorological test reference weather year data. The results of this research confirm a major potential for the generation of cooling water by evaporative means, which can be used to provide effective cooling of deep plan buildings by means of contemporary water based sensible cooling systems, such as fan coil systems, radiant chilled ceiling panels and ceiling cooling convectors (chilled beams). While the technique offers most potential in locations with a northern European temperate climate, it has significant potential to contribute to cooling in some southern European cities, during the non-summer months and also at other times, particularly where load shaving techniques are incorporated

The Design and Performance of an Evaporative Cooling Test Rig for a Maritime Climate

Recent developments have prompted a review of the use of cooling tower based evaporative cooling technology as an effective means of cooling modern buildings. Prominent among these developments is the success of high temperature cooling systems such as radiant ceiling panels and chilled beams. At present, however, there is little published literature which gives a quantitative, in depth analysis of the performance or energy efficiency of cooling towers, used in maritime climates, in conjunction with heat exchangers and run at low approach and low wet bulb temperatures throughout the free cooling season. This lack of knowledge has meant that many current opportunities to benefit from the technology are not availed of by building design teams. To address this issue an automated laboratory test rig has been specifically developed with the aim of optimising the performance and demonstrating the potential of this form of cooling in maritime conditions. This paper, which reports on work in progress, describes the design and development of the rig and presents and analyses the preliminary test results

Air and Water Flowrate Optimisation for a Fan Coil Unit in Heat Pump Systems

The degradation in efficiency of auxiliary components in heating/cooling systems when operating at part load is frequently reported. Through the use of variable speed components, the supplied capacity can be reduced to match the required load and hence reduce unnecessary energy consumption. However, for fan coil units, difficulties can arise when optimizing fan and pump speeds at part load. Practically locating optimal water and air flow rates from readily available information and for varying supplied capacities is necessary, in order to reduce the fan coil power consumption. This research attempts to identify whether optimal fan and pump speeds exist for a fan coil unit and how they can be implemented, in a practical manner, in a system control applications. Using an empirical fan coil and pump model, the total power consumption (fan and pump) for different combinations of fan and pump speeds over a range of capacities was calculated. It was observed that, for a given capacity, an optimal combination of fan and pump speeds exists and there was a significant change in power consumption for different combinations of fan and pump speeds supplying the same capacity. A control strategy is described that utilizes a simple fan coil capacity estimation model, coupled with air and water flow rates, along with nominal design data. The pump speed is optimized using PID control to maintain the space temperature at the chosen set-point, which matches the supplied capacity to the required capacity. At set-time intervals, the capacity estimation model is utilized to optimize the water and air flow rates for the required capacity. The control strategy is evaluated, using a full building simulation model for a daily load profile and is compared to two baseline conditions: for no control of the fancoils/pump combination and for PID circulation control of the pump only. The optimal fan and pump speed control resulted in a 43% and 24% decrease in power consumption with compared to the no control baseline and the PID controlled circulation pump strategy, respectively

Development of a Soft Actor Critic Deep Reinforcement Learning Approach for Harnessing Energy Flexibility in a Large Office Building

This research is concerned with the novel application and investigation of `Soft Actor Critic' (SAC) based Deep Reinforcement Learning (DRL) to control the cooling setpoint (and hence cooling loads) of a large commercial building to harness energy flexibility. The research is motivated by the challenge associated with the development and application of conventional model-based control approaches at scale to the wider building stock. SAC is a model-free DRL technique that is able to handle continuous action spaces and which has seen limited application to real-life or high-fidelity simulation implementations in the context of automated and intelligent control of building energy systems. Such control techniques are seen as one possible solution to supporting the operation of a smart, sustainable and future electrical grid. This research tests the suitability of the SAC DRL technique through training and deployment of the agent on an EnergyPlus based environment of the office building. The SAC DRL was found to learn an optimal control policy that was able to minimise energy costs by 9.7% compared to the default rule-based control (RBC) scheme and was able to improve or maintain thermal comfort limits over a test period of one week. The algorithm was shown to be robust to the different hyperparameters and this optimal control policy was learnt through the use of a minimal state space consisting of readily available variables. The robustness of the algorithm was tested through investigation of the speed of learning and ability to deploy to different seasons and climates. It was found that the SAC DRL requires minimal training sample points and outperforms the RBC after three months of operation and also without disruption to thermal comfort during this period. The agent is transferable to other climates and seasons although further retraining or hyperparameter tuning is recommended.Comment: submitted to Energy and A

Optimal control of fan coil battery air and water flow rates requiring minimal on-line measurements

Abstract Fan coil units are widely used in air-conditioning systems for heating and cooling of commercial buildings. Control - capable of achieving better operational efficiencies and at the same time, guarantying thermal comfort - is paramount in order to achieve optimal operation. The present paper presents a novel generalised control strategy, requiring only minimal input data, for optimising fan speed in order to reduce. Different control models are implemented to predict fan coil capacities and associated total power consumption. The developed strategy has been compared to fixed speed and benchmark fan speed control strategies, using both a steady state and a quasi-steady state algorithm, for various building loads. Results show average reduction in fan coil battery power consumption of 34% and 43% in heating and cooling mode respectively, when the optimal control is compared to fixed fan speed settings. Savings between 4.9% and 9.1% can be achieved by the control algorithms if compared to the benchmark fan speed control strategies

Diffusing the Creator: Attributing Credit for Generative AI Outputs

The recent wave of generative AI (GAI) systems like Stable Diffusion that can produce images from human prompts raises controversial issues about creatorship, originality, creativity and copyright. This paper focuses on creatorship: who creates and should be credited with the outputs made with the help of GAI? Existing views on creatorship are mixed: some insist that GAI systems are mere tools, and human prompters are creators proper; others are more open to acknowledging more significant roles for GAI, but most conceive of creatorship in an all-or-nothing fashion. We develop a novel view, called CCC (collective-centered creation), that improves on these existing positions. On CCC, GAI outputs are created by collectives in the first instance. Claims to creatorship come in degrees and depend on the nature and significance of individual contributions made by the various agents and entities involved, including users, GAI systems, developers, producers of training data and others. Importantly, CCC maintains that GAI systems can sometimes be part of a co-creating collective. We detail how CCC can advance existing debates and resolve controversies around creatorship involving GAI