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Inverters are a leading source of hardware failures and contribute to significant energy losses at photovoltaic (PV) sites. An understanding of failure modes within inverters requires evaluation of a dataset that captures insights from multiple characterization techniques (including field diagnostics, production data analysis, and current-voltage curves). One readily available dataset that can be leveraged to support such an evaluation are maintenance records, which are used to log all site-related technician activities, but vary in structuring of information. Using machine learning, this analysis evaluated a database of 55,000 maintenance records across 800+ sites to identify inverter-related records and consistently categorize them to gain insight into common failure modes within this critical asset. Communications, ground faults, heat management systems, and insulated gate bipolar transistors emerge as the most frequently discussed inverter subsystems. Further evaluation of these failure modes identified distinct variations in failure frequencies over time and across inverter types, with communication failures occurring more frequently in early years. Increased understanding of these failure patterns can inform ongoing PV system reliability activities, including simulation analyses, spare parts inventory management, cost estimates for operations and maintenance, and development of standards for inverter testing. Advanced implementations of machine learning techniques coupled with standardization of asset labels and descriptions can extend these insights into actionable information that can support development of algorithms for condition-based maintenance, which could further reduce failures and associated energy losses at PV sites.

Micro-segmentation is an emerging security technique that separates physical networks into isolated logical micro-segments (workloads). By tying fine-grained security policies to individual workloads, it limits the attacker's ability to move laterally through the network, even after infiltrating the perimeter defences. While micro-segmentation is proved to be effective for shrinking enterprise networks attack surface, its impact assessment is almost absent in the literature. This research is dedicated to developing an analytical framework to characterise and quantify the effectiveness of micro-segmentation on enhancing networks security. We rely on a twofold graph-feature based framework of the network connectivity and attack graphs to evaluate the network exposure and robustness, respectively. While the former assesses the network assets connectedness, reachability and centrality, the latter depicts the ability of the network to resist goal-oriented attackers. Tracking the variations of formulated metrics values post the deployment of micro-segmentation reveals exposure reduction and robustness improvement in the range of 60% - 90%.

We report on 250 PV systems throughout the United States, comprising 157 MWdc of system capacity and more than 10,000 monthly performance index (PI) values. Loss factors were isolated including first-year start-up issues, snowfall, soiling and inverter downtime. Inverter availability was found to contribute significant system energy loss during the first six months of operation, with an average of 8% loss occurring during this period, and 2.3% on average thereafter. Other start-up issues beyond inverter downtime, such as partial string outage, contributed additional underperformance in the first year of operation across the fleet. Winter performance was also found to be below summer performance on average, likely due to snowfall. A relationship was found between monthly snowfall accumulation in centimeters and monthly under-performance, indicating a 6%-40% loss in months with measured snowfall, depending on climate. After correcting for availability, snow and startup loss, over 90% of systems were performing within 10% of monthly expectation based on satellite resource data and PVWatts production estimates.

The world is at the start of an energy revolution: the biggest energy transformation since the Industrial Revolution. The growing recognition that the carbon dioxide emissions associated with the combustion of fossil fuels leads to a dramatic increase in global temperatures is driving the need to implement strategies to reduce the carbon footprint across power- and energy-hungry sectors such as power generation, domestic heating, industrial processes and transportation. This article looks at the moves that the global passenger car and commercial vehicle segments will need to make to minimise the CO2 and greenhouse gas (GHG) emissions of the sector, which is one of the largest contributors to the global CO2 inventory today. A number of countries have already pledged to meet net zero GHG emissions by 2050, and more are set to follow, so this article also considers what is necessary for the ground transportation sector to hit net zero.

SHARE THIS PAGE:The world is at the start of an energy revolution: the biggest energy transformation since the Industrial Revolution, during which the use of fossil fuels drove growth and prosperity, with global temperature increase implications that we have only started to understand relatively recently. This energy revolution will drive the world towards a lower carbon, more sustainable future, with major implications for energy and electricity generation, heating, industrial power and transportation. Governments, states and regions are proposing, and in some cases (such as the UK) committing to, net zero greenhouse gas (GHG) or carbon dioxide emission targets over the coming years. To date, 15 countries have set defined targets to become net zero economies by 2050 or earlier, with over 50 others, including Germany and Canada, discussing when to implement such a target. Perhaps most significantly, the European Union (EU) intends to be net zero by 2050: this objective is at the heart of the European Green Deal and in line with the EU’s commitment to global climate action under the Paris Agreement.

This paper describes how performance problems can be “masked,” or not readily evident by several causes: by photovoltaic (PV) system configuration (such as the size of the PV array capacity relative to the size of the inverter and the resultant clipped operating mode); by instrumentation design, installation, and maintenance (such as a misaligned or dirty pyranometer); by contract clauses (when operational availability is transformed to contractual availability, which excludes many factors); and by identified management and operational practices (such as reporting on a portfolio of plants rather than individually). A simple method based on a duration curve is introduced to overcome shortcomings of Performance Ratio based on nameplate capacity and Performance Index based on hourly simulation when quantifying masking effects, and inverter clipping and pyranometer soiling are presented as two examples of the new method. With a better understanding of the non-transparency of masking issues, stakeholders can better interpret performance data and deliver improved AC and DC plant conditions through PV system operation and maintenance (O&M) for improved performance, reduced O&M costs, and a more consistently delivered, and reduced, levelized cost of energy (LCOE).

As a consequence of the warm and humid climate of tropical coastal regions, there is high energy demand year-round due to air conditioning to maintain indoor comfort levels. Past and current practices are focused on mitigating peak cooling demands by improving heat balances by using efficient building envelope technologies, passive systems, and demand side management strategies. In this study, we explore city-scale solar photovoltaic (PV) planning integrating information on climate, building parameters and energy models, and electrical system performance, with added benefits for the tropical coastal city of San Juan, Puerto Rico. Energy balance on normal roof, flush-mounted PV roof, and tilted PV roof are used to determine PV power generation, air, and roof surface temperatures. To scale up the application to the whole city, we use the urbanized version of the Weather Research and Forecast (WRF) model with the building effect parameterization (BEP) and the building energy model (BEM). The city topology is represented by the World Urban Database Access Portal Tool (WUDAPT), local climate zones (LCZs) for urban landscapes. The modeled peak roof temperature is maximum for normal roof conditions and minimum when inclined PV is installed on a roof. These trends are followed by the building air conditioning (AC) demand from urbanized WRF, maximum for normal roof and minimum for inclined roof-mounted PV. The net result is a reduced daytime Urban Heat Island (UHI) for horizontal and inclined PV roof and increased nighttime UHI for the horizontal PV roof as compared with the normal roof. The ratio between coincident AC demand and PV production for the entire metropolitan region is further analyzed reaching 20% for compact low rise and open low rise buildings due to adequate roof area but reaches almost 100% for compact high rise and compact midrise buildings class, respectively.

The PV Reliability PerformanceModel (PV-RPM) tool is used to simulate the cost and energy impacts of component faults and failures for a hypothetical PV system. This model, originally developed by Sandia National Laboratories, is a new feature in the National Renewable Energy Laboratory's System Advisor Model (SAM), which performs stochastic analysissampling of probability distributions for faults, failures, and repairs. One PV system was created for this analysis to be representative of a portfolio of maintenance data maintained by Sandia National Laboratories. Fault,failure, and repair distributions from this system are varied from current baseline conditions to simulate different reliability and repair scenarios and resulting energy and cost impacts. Results highlight ways to express the uncertainty around PV system performance when considering the probabilistic behavior of components inthe system, and ways the PV-RPM model can be used to explore different failure and repair scenarios.

The concept of a Forming Limit Curve (FLC), introduced in the sixties, has been widely used in the sheet metal industry, both to check out die designs at the design stage, using FE simulation techniques, and also to sign off stamped parts in the press shop. However, this approach should be strictly limited to stamping processes where the strain path is proportional during the stamping process. An alternative concept, the Forming Limit Stress Diagram (FLSD), was proposed back in the eighties. This FLSD concept is path independent, and solves the problem of possible non-linearity of the strain path during a press forming operation. The following paper uses a procedure for the transformation of an experimental path dependent strain based FLC into a stress based path independent FLSD, for three different yield functions, von Mises, Hill’48 and Hill’s 90. Having derived the FLSD criterion, this paper then shows a comparison between the FE stamping simulations carried out on a selected component, using both the standard FLC approach and the more recent FLSD approach, using each one of the three different yield criterion considered. The FE simulation results using the FLSD transformation and the original FLC approach show good agreement for each of the yield functions considered. Some differences between the yield functions are also highlighted and discussed, in particular the limitations of Hill’s 48 in the balanced bi-axial stress state for materials with an r value less than one, i.e. aluminium alloys.

The use of the term “availability” to describe a photovoltaic (PV) system and power plant has been fraught with confusion for many years. A term that is meant to describe equipment operational status is often omitted, misapplied or inaccurately combined with PV performance metrics due to attempts to measure performance and reliability through the lens of traditional power plant language. This paper discusses three areas where current research in standards, contract language and performance modeling is improving the way availability is used with regards to photovoltaic systems and power plants.

Foam fractionation was previously shown to be an effective tool for the separation of the two visible phases in a chicken egg: egg white and the egg yolk.1 This study is a continuation of the previous study with the objective of determining the optimal separation condition in terms of air flow rate. Our results show that air flow rate is a critical operational parameter when separating these protein-rich mixtures of egg white and egg yolk. The results show that respective concentrations of egg yolk and egg white phases change independently with respect to the air flow rate, leading to the observation that air flow rate could be exploited as a processing variable to selectively remove proteins from one section of the egg over the other section. Copyright © 2009 Curtin University of Technology and John Wiley & Sons, Ltd.

The development of 10 kV silicon carbide (SiC) MOSFETs and Junction Barrier Schottky (JBS) diodes for application to a 13.8kV 2.7 MVA Solid State Power Substation (SSPS) is shown. The design of half-bridge power modules has extensively used simulation, from electron level device simulations to the system level trade studies, to develop the most efficient module for use in the SSPS. In the work presented within, numerical simulations and experimental results are shown to demonstrate the design and operation of 10 kV JBS diodes. It is shown that JBS diodes at 10 kV can reduce 31% of the switching losses at 20 kHz than the fastest SiC PiN diodes.

Northrop Grumman Corporation has been developing 10 kV SiC MOSFETs and Junction Barrier Schottky diodes for application to a 13.8 kV 2.7 MVA solid-state power substation. The design of half-bridge power modules has extensively used simulation, from electron-level device simulations to the system-level trade studies, to develop the most efficient module for use in the SSPS.

In the autumn of 2002, 14 universities built solar houses on the National Mall in Washington, DC, in a student competition—the Solar Decathlon—demonstrating that homes can derive all the energy they need from the sun and celebrating advances in solar buildings. This paper describes recent progress in solar building technology that expands the designer’s palette and holds the potential to radically improve building energy performance. The discussion includes market conditions and solar resource data; design integration and modeling; window technology, daylighting, passive solar heating; solar water heating; solar ventilation air preheating; building-integrated photovoltaics; and solar cooling. The Solar Decathlon competition highlighted ways in which these strategies are integrated in successful solar buildings.

A new version of the ENERGY-10 computer program simulates the performance of photovoltaic (PV) systems and evaluates a wide range of opportunities to improve energy efficiency in buildings. This paper describes two test cases in which the beta release of ENERGY-10 version 1.4 was used to evaluate energy efficiency and building-integrated photovoltaics (BIPV) for two federal building projects: an office and laboratory building at the Smithsonian Astrophysical Laboratory (SAO) in Hilo, Hawaii, and housing for visiting scientists at the Smithsonian Environmental Research Center in Edgewater, Maryland. The capabilities of the software, the design assistance provided by ENERGY-10, and a synopsis of results are given. Estimates of annual energy delivery by the five PV arrays of the SAO are compared to F-Chart to help inform a validation of ENERGY-10. Results indicate that, by simulating both the building electrical load and simultaneous PV performance for each hour of the year, ENERGY-10 facilitates a highly accurate, integrated analysis useful early in the design process. The simulation is especially useful in calculating the effect of PV on the building peak load, and associated demand cost savings.

REopt is an energy planning platform offering concurrent, multiple technology integration and optimization capabilities to help clients meet their cost savings and energy performance goals. The REopt platform provides techno-economic decision support analysis throughout the energy planning process, from agency-level screening and macro planning to project development to energy asset operation. REopt employs an integrated approach to optimizing the energy costs of a site by considering electricity and thermal consumption, resource availability, complex tariff structures including time-of-use, demand and export rates, incentives, net metering, and interconnection limits. Formulated as a mixed integer linear program, REopt recommends an optimally sized mix of conventional and renewable energy, and energy storage technologies; estimates the net present value associated with implementing those technologies; and provides the cost-optimal dispatch strategy for operating them at maximum economic efficiency. The REopt platform can be customized to address a variety of energy optimization scenarios including policy, microgrid, and operational energy applications. This paper presents the REopt techno-economic model along with two examples of recently completed analysis projects.

An all-GaN gate-drive circuit is proposed and integrated in the same MMIC with a 60V GaN switching PA using 0.25μm depletion-mode process. The driver employs a multi-stage differential amplifier to operate a push-pull topology for switching the PA's power device with much shorter transition times than other known gate-drive topologies, and thus allows for much higher switching frequencies. Measurements show less than 122ps transition times at the PA's output and a switching frequency up to 1GHz.

At Phoenix Federal Correctional Institution in Arizona, the Federal Bureau of Prisons (FBP) completed a 1,584 m2 (17,040 square feet) parabolic trough solar water heating system financed, installed and operated under an Energy Savings Performance Contract (ESPC) with Industrial Solar Technology Corp (IST). The ESPC was developed under a Cooperative Research and Development Agreement with the National Renewable Energy Laboratory (NREL). The system incorporates a 87 m3 (23,000 gallon) storage tank. The system delivered 1,161,803 kWh (3,964 million Btu) of solar heat from March 1, 1999 to February 29, 2000. This energy would have cost $77,805.74 if purchased from the utility (based on the monthly average $/kWh cost). Sale of this energy to the prison provided $70,025.18 in revenue to IST (a rate negotiated at 90 percent of the monthly average $/kWh utility cost). Thus, the prison saved $7,780.56 (the remaining 10 percent). A photograph of the collector system is presented in Figure 1. Results show that the system delivers heat reliably, with only minor operational problems which are listed and discussed. The system delivered a minimum of 80,315 kWh (274 Btu) in January 2000 to a maximum of 130,979 kWh (447 Million Btu) in October 1999. The prison pays IST for energy delivered by the solar system at a rate equal to 90 percent of the monthly average utility rate (10 percent guaranteed savings), over 20 years. Details of the establishment of the payment structure and the cost savings to the prison are discussed. Annual Emissions Savings are estimated by EPA multipliers [1] for Arizona as 627,374 kg/yr of CO2, 2,324 kg/yr of SO2 and 2,297 kg/yr of NOx. Other benefits to the prison are also discussed, such as reduced operations and maintenance on the electric water heaters and a greater capacity to deliver hot water. [S0199-6231(00)00704-8]