Offers a comprehensive critique of the spread of auditing in both the public and private sectors and shows how to achieve a better balance between audits and other forms of accountability. Michael Power is Professor of Accounting at the LSE. ‘A rare attempt to stand back and question the very notion of auditing and the place it has assumed in our society.’ Financial Times

The Audit Explosion

. Spatio-temporal fields of land–atmosphere fluxes derived from data-driven models can complement simulations by process-based land surface models. While a number of strategies for empirical models with eddy-covariance flux data have been applied, a systematic intercomparison of these methods has been missing so far. In this study, we performed a cross-validation experiment for predicting carbon dioxide, latent heat, sensible heat and net radiation fluxes across different ecosystem types with 11 machine learning (ML) methods from four different classes (kernel methods, neural networks, tree methods, and regression splines). We applied two complementary setups: (1) 8-day average fluxes based on remotely sensed data and (2) daily mean fluxes based on meteorological data and a mean seasonal cycle of remotely sensed variables. The patterns of predictions from different ML and experimental setups were highly consistent. There were systematic differences in performance among the fluxes, with the following ascending order: net ecosystem exchange (R2   0.6), gross primary production (R2> 0.7), latent heat (R2 > 0.7), sensible heat (R2 > 0.7), and net radiation (R2 > 0.8). The ML methods predicted the across-site variability and the mean seasonal cycle of the observed fluxes very well (R2 > 0.7), while the 8-day deviations from the mean seasonal cycle were not well predicted (R2

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Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms

This paper presents results obtained from monitoring a 1.72 kWp photovoltaic system installed on a flat roof of a 12 m high building in Dublin, Ireland (latitude 53.4°N and longitude 6.3°E). The system was monitored between November 2008 and October 2009 and all the electricity generated was fed into the low voltage supply to the building. Monthly average daily and annual performance parameters of the PV system evaluated include: final yield, reference yield, array yield, system losses, array capture losses, cell temperature losses, PV module efficiency, system efficiency, inverter efficiency, performance ratio and capacity factor. The maximum solar radiation, ambient temperature and PV module temperature recorded were 1241 W/m2 in March, 29.5 °C and 46.9 °C in June respectively. The annual total energy generated was 885.1 kW h/kWp while the annual average daily final yield, reference yield and array yield were 2.41 kW h/kWp/day, 2.85 kW h/kWp/day and 2.62 kW h/kWp/day respectively. The annual average daily PV module efficiency, system efficiency and inverter efficiency were 14.9%, 12.6% and 89.2% respectively while the annual average daily performance ratio and capacity factor were 81.5% and 10.1% respectively. The annual average daily system losses, capture losses and cell temperature losses were 0.23 h/day, 0.22 h/day and 0.00 h/day respectively. Comparison of this system with other systems in different locations showed that the system had the highest annual average daily PV module efficiency, system efficiency and performance ratio of 14.9%, 12.6% and 81.5% respectively. The PV system’s annual average daily final yield of 2.4 kW h/kWp/day is higher than those reported in Germany, Poland and Northern Ireland. It is comparable to results from some parts of Spain but it is lower than the reported yields in most parts of Italy and Spain. Despite low insolation levels, high average wind speeds and low ambient temperature improve Ireland’s suitability.

Measured Performance of a 1.72 kW Rooftop Grid Connected Photovoltaic System in Ireland

The emergence of Pinch Analysis from more than four decades ago opened a new area of intense research development that has even accelerated in recent years. Initially, Pinch Analysis (PA) provided a systematic thermodynamic-based approach to address the need for large energy savings around the 1970s oil crises. Since inception, the Pinch Methodology (PM) has flourished considerably, finding meaningful application to a wide range of industrial, regional, and global challenges well beyond heat – it’s most well-known and first application. This review represents an attempt to identify and substantiate future directions of research for the most significant implementations of Pinch Methodology. Reported applications in the literature range from Heat Integration, Total Site and Water Integration through to Emergy and even Financial Investment Planning; cutting across multiple engineering fields – Mechanical, Chemical, Process, Power, and Environmental Engineering – as well as entering the research domains of Management and Finance. Key findings of this review include: (1) the need for more awareness within the engineering and science research communities of the latest and continuing developments of the Pinch Methodology; (2) a need for complete tool sets covering targeting through to engineering design for many of the Pinch Methodology applications; and, (3) the full benefits of Pinch Methodology can only be achieved in developing design solutions with an appreciation for the most recent developments.

New directions in the implementation of Pinch Methodology (PM)

Polymer electrolyte membrane (PEM) fuel cells are electrochemical devices that directly convert the chemical energy stored in fuel into electrical energy with a practical conversion efficiency as high as 65%. In the past years, significant progress has been made in PEM fuel cell commercialization. By 2019, there were over 19,000 fuel cell electric vehicles (FCEV) and 340 hydrogen refueling stations (HRF) in the U.S. (~8,000 and 44, respectively), Japan (~3,600 and 112, respectively), South Korea (~5,000 and 34, respectively), Europe (~2,500 and 140, respectively), and China (~110 and 12, respectively). Japan, South Korea, and China plan to build approximately 3,000 HRF stations by 2030. In 2019, Hyundai Nexo and Toyota Mirai accounted for approximately 63% and 32% of the total sales, with a driving range of 380 and 312 miles and a mile per gallon (MPGe) of 65 and 67, respectively. Fundamentals of PEM fuel cells play a crucial role in the technological advancement to improve fuel cell performance/durability and reduce cost. Several key aspects for fuel cell design, operational control, and material development, such as durability, electrocatalyst materials, water and thermal management, dynamic operation, and cold start, are briefly explained in this work. Machine learning and artificial intelligence (AI) have received increasing attention in material/energy development. This review also discusses their applications and potential in the development of fundamental knowledge and correlations, material selection and improvement, cell design and optimization, system control, power management, and monitoring of operation health for PEM fuel cells, along with main physics in PEM fuel cells for physics-informed machine learning. The objective of this review is three fold: (1) to present the most recent status of PEM fuel cell applications in the portable, stationary, and transportation sectors; (2) to describe the important fundamentals for the further advancement of fuel cell technology in terms of design and control optimization, cost reduction, and durability improvement; and (3) to explain machine learning, physics-informed deep learning, and AI methods and describe their significant potentials in PEM fuel cell research and development (R&D).

Fundamentals, materials, and machine learning of polymer electrolyte membrane fuel cell technology

Thermodynamic and economic evaluation of a novel concentrated solar power system integrated with absorption refrigeration and desalination cycles

Developing a tri-generation system of power, heating, and freshwater (for an industrial town) by using solar flat plate collectors, multi-stage desalination unit, and Kalina power generation cycle

A novel energy efficient LNG/NGL recovery process using absorption and mixed refrigerant refrigeration cycles – Economic and exergy analyses

Hybrid molten carbonate fuel cell power plant and multiple-effect desalination system

Introducing a hybrid renewable energy system for production of power and fresh water using parabolic trough solar collectors and LNG cold energy recovery

Bahram Ghorbani

Papers

Thermodynamic and economic evaluation of a novel concentrated solar power system integrated with absorption refrigeration and desalination cycles

Developing a tri-generation system of power, heating, and freshwater (for an industrial town) by using solar flat plate collectors, multi-stage desalination unit, and Kalina power generation cycle

A novel energy efficient LNG/NGL recovery process using absorption and mixed refrigerant refrigeration cycles – Economic and exergy analyses

Hybrid molten carbonate fuel cell power plant and multiple-effect desalination system

Introducing a hybrid renewable energy system for production of power and fresh water using parabolic trough solar collectors and LNG cold energy recovery