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This paper presents a literature survey on the subject of voltage stability analysis of power systems. The survey describes several published methods and techniques used to determine voltage stability indices. These indices predict proximity to voltage instability and collapse problems. The Q-V and P-V curves; singular value decomposition; modal analysis; test function; reduced determinant; loading margin by multiple power flow solutions; local load margins; thevenin/load impedance; and energy function are the methods which have been decribed in the paper. The methods described are based on the original work that first proposed them. They are based on the power-flow system model, where the variation of real and reactive powers are assumed to be the main parameters driving the system to voltage instability. Some of the described methods were applied on the IEEE 30-bus power system.

Abstract Higher resolution rock formation characterization is of paramount priority, amid growing interest in injecting carbon dioxide, CO2, into subsurface rock formations of depeleting/depleted hydrocarbon reservoirs or saline aquifers in order to reduce emissions of greenhouse gases. In this paper, we present a case study for a Mississippian carbonate characterization integrating post-stack seismic attributes, well log porosities, and seismic petrophysical facies classification. We evaluated changes in petrophysical lithofacies and reveal structural facies-controls in the study area. Three cross-plot clusters in a plot of well log porosity and acoustic impedance corroborated a Neural Network petrophysical facies classification, which was based on training and validation utilizing three petrophysically-different wells and three volume seismic attributes, extracted from a time window including the wavelet of the reservoir-top reflection. Reworked lithofacies along small-throw faults has been revealed based on comparing coherency and seismic petrophysical facies. The main objective of this study is to put an emphasis on reservoir characterization that is both optimized for and subsequently benefiting from pilot tertiary CO2 carbon geosequestration in a depleting reservoir and also in the deeper saline aquifer of the Arbuckle Group, south central Kansas. The 3D seismic coherency attribute, we calculated from a window embracing the Mississippian top reflection event, indicated anomalous features that can be interpreted as a change in lithofacies or faulting effect. An Artificial Neural Network (ANN) lithofacies modeling has been used to better understand these subtle features, and also provide petrophysical classes, which will benefit flow-simulation modeling and/or time-lapse seismic monitoring feasibility analysis. This paper emphasizes the need of paying greater attention to small-scale features when embarking upon characterization of a reservoir or saline-aquifer for CO2 based carbon geosequestration.

Abstract A method to analyze multi-area optimal power flow in novel energy management systems is proposed and studied in this paper. The studied power network consisted batteries, distributed generators and electric parking lots. A straightforward granular-based method is introduced to maintain the simplicity of the calculations while the independency of areas is preserved. In this case, a three-area power network as a multi-area power network problem is chosen to test and approve the applicability of the proposed method in terms of accuracy, simplicity, preserving independency, and not requiring any control or initial parameters. According to the results, maximum error is 0.0009 pu in the selected case study. Moreover, two valued variables namely operation cost and voltage deviation are selected as the two fundamental objective functions to be analyzed both multi-objectively and solely. Furthermore, in this paper, soon-to-be-indispensable electric vehicle parking lots and distributed generators are also utilized to optimize operation cost (up to 49.28%) as well as voltage deviation (up to 48.99%). Also, the influence of each area on one another in multi-area layout is studied. In one scenario, the third area is equipped with battery and fuel cell to improve voltage deviation of itself (40.42%) as well as first and second area 12% and 15.4%, respectively.

Smart cities, as well as smart homes research, are becoming of concern, especially in the field of energy consumption and production. However, there is a lack in the dataset that can be used to simulate smart city energy consumption and prediction or even smart homes. Therefore, this paper provides a carefully generated dataset for smart home energy management simulation. Five datasets are generated and analysed to ensure suitability, including 20, 50, 100, and 200 homes across 365 days. For more accurate data, energy consumption and production for 50 homes are generated based on real input taken from a dataset for homes in Saudi Arabia. Due to the unavailability of a comprehensive dataset related to the complex scenario of smart home sensors, energy consumption, and peer-to-peer data exchange, synthetic data was generated to support the simulation of smart home energy generation and consumption. This synthetic data plays a crucial role in situations where simulating uncommon events, ensuring data availability, facilitating extensive experimentation and model validation, and enabling scalability are paramount. It offers a valuable opportunity to incorporate these rare yet significant occurrences into the simulation, particularly in the context of infrequent events, such as abnormal energy consumption patterns observed in smart homes. The generated data is analysed and validated in this article, ready to be used for many smart home and city research.

PurposeCrucial transition of the Indian residential building sector into a low-emission economy require an in-depth understanding of the potentials for retrofitting the existing building stock. There are, however, limited studies that have recognised the interdependencies and trade-offs in the embodied energy and life cycle impact assessment of retrofit interventions. This research appraises the life cycle assessment and embodied energy output of a residential building in India to assess the environmental implications of selected retrofit scenarios.Design/methodology/approachThis study utilises a single case study building project in South India to assess the effectiveness and impact of three retrofit scenarios based on life cycle assessment (LCA) and embodied energy (EE) estimates. The LCA was conducted using SimaPro version 9.3 and with background data from Ecoinvent database version 3.81. The EE estimates were calculated using material coefficients from relevant databases in the published literature. Monte Carlo Simulation is then used to allow for uncertainties in the estimates for the scenarios.FindingsThe three key findings that materialized from the study are as follows: (1) the retrofitting of Indian residential buildings could achieve up to 20% reduction in the life cycle energy emissions, (2) the modification of the building envelope and upgrading of the building service systems could suffice in providing optimum operational energy savings, if the electricity from the grid is sourced from renewable plants, and (3) the production of LEDs and other building services systems has the highest environmental impacts across a suite of LCA indicators.Originality/valueThe retrofitting of residential buildings in India will lead to better and improved opportunities to meet the commitments in the Paris Climate Change Agreement and will lead to enhanced savings for building owners.

Abstract Drinking water is a necessity not only for humanity but also for the all living organisms available in the earth today. But the availability of the potable water is not in abundant amount; hence clean water is scarce in the world today. Solar desalination system is used to turn the saline water into the freshwater by use of sunrays. Solar still is a device which can be employed for desalination. As the daily productivity of solar distiller is low so, multiple techniques have been used by various researchers to improve its productivity. But work done on the fins to enhance the distillate output is not much. Fin is a low-cost heat transfer enhancement which is used by many researchers in the solar thermal applications. Present review paper shows the use of fins in solar still and how it can be used to enhance the distillate output of solar still. At last, a table is also presented to show the use of fins to increase the distillate output alone and with the use of certain materials.

Abstract This paper examines the volatility spillover effects between precious metals futures (gold, palladium, platinum, and silver), Brent oil futures, and ASEAN stock markets (Indonesia, Malaysia, Philippines, Singapore, Thailand, and Vietnam) at multiple time horizons and during bear and bull market periods. The results show that precious metals, crude oil, and the Vietnamese stock market are net receivers of spillovers irrespective of time horizons and during bearish market conditions. In contrast, during the bullish market conditions, Brent oil futures and Vietnamese stock markets become net contributors to short-term spillovers. Furthermore, the stock markets of Indonesia, Malaysia, and the Philippines are the largest contributors to spillovers under bear and bull market conditions and regardless of the time investment horizons. Moreover, adding precious metals or oil futures to the ASEAN equity portfolio provides better hedging effectiveness during different considered crises. The role of Brent oil and precious metals futures serves as diversifier, hedge, and safe haven assets is discussed under major events.

Power grid systems are considered as critical infrastructure that require smooth and efficient operation in its power generation, transmission and distribution sectors. A performance loss in such systems can lead towards undesired situations including damages and financial losses. Remote, reliable and real-time monitoring of different components within a power grid system are important features for assuring performance, especially in modern smart grid technologies. Internet of Things (IoT)-enabled monitoring systems have the potential to fulfill the said requirements. For that, adopting a suitable communication technology to effectively transfer data of the monitored component is an essential design objective in IoT-enabled monitoring systems. This paper proposes a prototype design suitable for remotely monitoring different components within a power grid while adopting ZigBee as the underlying communication technology. Experimental results show that the devised prototype has the potential to effectively capture and notify in real-time the changes occurring in a power grid system.

Electro deionization using microbial communities has been proven as a competent method for desalination and abatement of water pollution by removing ionic chemicals from the target waters. Microbial Desalination Cell (MDC) facilitates microbial deionization which can either support or be a substitute for the conventional desalination methods. Generation of electricity is accomplished by the bio electrochemical oxidation of organic compounds present as contaminants in wastewater which in turn attribute to the migration of ions in MDC system. The present review aims to elucidate the theory, principles and the application of microbial desalination cell and microbial fuel cell (MFC) in treatment of saline and wastewaters. Air cathode MDC and stacked MDC for purification of saline water are found to give promising results. Air pump assisted microbial desalination cell reported 150.39 ppm h-1 of salt removal with an operational time period of 80 h and showed consistent results. Hence the air cathode assisted MDC showed dominant capacity of salt removal compared to stacked MDC. Also, three major types of microbial fuel cell, namely photosynthetic biofilm MFC, constructive wetland MFC and ceramic membrane supported MFC are reviewed for their potentials in wastewater treatment by deionization method and electricity generation. Complete (100%) removal of chemical oxygen demand was reported by photosynthetic microbial fuel cell operated for 16 days having 435.8 Ω of external resistance. When constructive wetland microbial fuel cell was operated for 10 days with 1000 ohms of external resistance, it exhibited complete (100%) removal of chemical oxygen demand from the wastewater. About 92% of chemical oxygen demand removal was demonstrated by ceramic membrane supported microbial fuel. Compared to ceramic membrane microbial fuel cell, photosynthetic and constructive wetland microbial fuel cell displayed better performance in terms of pollutant removal capacity and economical factor. Ability of the electrogenic species, namely Geobacter, Shewanella, Clostridium and Bacillus and the photosynthetic species, namely Chorella Vulgaris Rhodopsuedomonas, and Scenedesmus abundans in microbial deionization methods and their performance levels reported by several researchers are presented.