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An optimization approach to determine the value of optimum LC compensator for time-variant nonsinusoidal environments is proposed. The optimization technique minimizes the transmission loss and/or maximizes the power factor. All the source voltage harmonics follow the same pattern. The equivalent source and load impedances are presented by complex time variations functions. The performance of the LC compensator is discussed by means of numerical examples taken from previous publications.

Abstract Recovery of sales gas and natural gas liquid (NGL) is characterized by its high energy consumption and significant environmental impact. This study explores the effect of design alternatives for NGL recovery on economic, energy, and environmental metrics. Focus is given to the turbo-expanding separation method owing to its wide applicability and potential for improvements. The primary configurations of turbo-expanding systems were simulated using ASPEN HYSYS. The simulation results included mass and energy balances, unit sizing, and sensitivity analyses using what-if scenarios to improve the design of the base configuration. Other ASPENTech products, such as the ASPEN Process Economic Analyzer and ASPEN Energy Analyzer were utilized to carry out an economic evaluation and optimization of utilities. To illustrate the value of the proposed approach, a case study was analysed for the assessment of various design alternatives to process 84,000 kg/h (5000 kmol/h) of natural gas while accounting for and reconciling the economic, energy, and environmental objectives.

Although most people want to be happy, the pursuit of happiness involves an overwhelming number of choices and great uncertainty about the consequences. Many of these choices have significant implications for sustainability, which are rarely considered. Here, we present an optimality model that maximizes subjective happiness, which can eventually account for sustainability outcomes. Our model identifies the optimal use of time or energy to maximize happiness. Such models tell people how to invest in domains of happiness (e.g., work vs. leisure) and how to choose activities within domains (e.g., playing a computer game vs. playing a board game). We illustrate this optimization approach with data from an online survey, in which people (n = 87) either recalled or imagined their happiness during common activities. People reported decelerating happiness over time, but the rate of deceleration differed among activities. On average, people imagined spending more time on each activity than would be needed to maximize happiness, suggesting that an optimality model has value for guiding decisions. We then discuss how such models can address sustainability challenges associated with overinvesting (e.g., excessive CO2 emissions). To optimize happiness and explore its implications for sustainability over long periods, models can incorporate psychological processes that alter the potential for happiness and demographic processes that make lifespan uncertain. In cases where less objective approaches have failed, a quantitative theory may improve opportunities for happiness, while meeting sustainability outcomes.

Increasing health and wellbeing in cities that experience water scarcity presents challenges, but can be done, say Howard Frumkin and colleagues

AbstractThe development of smart grids, traditional power grids, and the integration of internet of things devices have resulted in a wealth of data crucial to advancing energy management and efficiency. Nevertheless, public datasets remain limited due to grid operators' and companies' reluctance to disclose proprietary information. The authors present a comprehensive analysis of more than 50 publicly available datasets, organised into three main categories: micro‐ and macro‐consumption data, detailed in‐home consumption data (often referred to as non‐intrusive load monitoring datasets or building data) and grid data. Furthermore, the study underscores future research priorities, such as advancing synthetic data generation, improving data quality and standardisation, and enhancing big data management in smart grids. The aim of the authors is to enable researchers in the smart and power grid a comprehensive reference point to pick suitable and relevant public datasets to evaluate their proposed methods. The provided analysis highlights the importance of following a systematic and standardised approach in evaluating future methods and directs readers to future potential venues of research in the area of smart grid analytics.

Chemical mechanical polishing of copper and tantalum was performed using fumed amorphous silica abrasive particles dispersed in H2O2, Fe(NO3)3, and glycine solutions. Results showed that in DI water silica did not polish Cu but Ta had a relatively high polish rate. Cu polish rate decreased with increasing particle concentration in Fe(NO3)3-based slurries due to the adsorption of Fe3+ on the silica surface. Addition of H2O2 enhanced Cu polish rate but reduced Ta polish rate. The specific surface area of the particles played an important role in the removal of Ta and Cu, presumably due to some chemical bonding between the materials being polished and the silica particles.

Renewable energy (RE) sources are becoming popular for power generations due to advances in renewable energy technologies and their ability to reduce the problem of global warming. However, their supply varies in availability (as sun and wind) and the required load demand fluctuates. Thus, to overcome the uncertainty issues of RE power sources, they can be combined with storage devices and conventional energy sources in a Hybrid Power Systems (HPS) to satisfy the demand load at any time. Recently, RE systems received high interest to take advantage of their positive benefits such as renewable availability and CO2 emissions reductions. The optimal design of a hybrid renewable energy system is mostly defined by economic criteria, but there are also technical and environmental criteria to be considered to improve decision making. In this study three main renewable sources of the system: photovoltaic arrays (PV), wind turbine generators (WG) and waste boilers (WB) are integrated with diesel generators and batteries to design a hybrid system that supplies the required demand of a remote area in Qatar using heuristic approach. The method utilizes typical year data to calculate hourly output power of PV, WG and WB throughout the year. Then, different combinations of renewable energy sources with battery storage are proposed to match hourly demand during the year. The design which satisfies the desired level of loss of power supply, CO2 emissions and minimum costs is considered as best design.

Previous studies have shown that sun tracking systems using single axis or dual axes tracking harvested more energy than fixed panels. Most of those studies were based on the light dependent resistors (LDR) with two or four LDRs depending whether single axis or dual axes is used. There are few concerns regarding those schemes. Because the LDRs are mounted on the same panel, they are continuously tracking the sun. As a result, their auxiliaries are drawing high currents; which means unnecessary consuming energy because of the continuous low speed rotation with many starts-stops; on top of this the heating problem due to high current consumption. Using LDRs only detects voltages not power whereas solar energy depends mainly on current where current is directly proportional to irradiation. As a result, and based on previous study, only about 85% of net energy is saved. They also suffer from the problem that each panel has got its own tracking. This study addresses those issues. The system is based on a PILOT-PANEL scheme, each equipped with a light to frequency converters (LTF). The advantage of LTF is that its output frequency is proportional to the irradiation which means proportional to power. The PILOT is small rod with its top in the W shape, where the first LTF is mounted on middle peak of the shape. The rod is driven by a micro-motor. The second LTF is mounted on the PANEL. The PILOT continuously tracks the sun. Every time the PILOT moves to a new position, a microcontroller reads both LTF's frequencies and compares them. If the difference is less than a pre-set value, the PANEL stays in the current position and the PILOT continues its tracking course. If the difference is bigger than the offset, the PANEL aligns itself with the PILOT. This process repeats itself during the course of the day. At the same time, another offline altitude angle tracking system comes into play. Because the range of the altitude angle in Bahrain is in the region of 35° between summer and winter, the microcontroller is programmed to move between four and eight time a year in steps of about 9°The technique has shown the extraction of 98.36% of continuous tracking with minimum energy consumption. This is certainly better than previous studies where the harvested energy is in the region of 85%. If continuous tracking represents 100%, at 1000 Hz (1.1 µW/cm2) offset, the extracted energy (as a percentage) was calculated to be 98.36%, at 4000 Hz (4.4 µW/cm2) offset, the energy was 95.41% and at 8000 Hz (8.8 µW/cm2) offset, the extracted energy was 79.9% and for fixed panel, it would be about 60%.