ABSTRACT
With rising electricity demand, heavy reliance on imports, and recent economic downturns due to the negative impact of the COVID-19 pandemic, supply chain bottlenecks, and the Russian invasion of Ukraine, Thailand is suffering severely from energy resilience risks. The government has therefore set a goal of decentralizing energy production through small-scale distributed renewable energy systems. To support their design and the planning process, we simulate multiple scenarios with wind turbines, photovoltaic systems, and battery storage for a model community in rural Nakhon Phanom, Thailand. Using the software NESSI4D, we evaluate and discuss their impact on energy resilience by considering environmental sustainability, economic attractiveness, and independence from the central power grid. To fill the gap of missing data on energy demand, we synthesize high-resolution load profiles from the Thailand Vietnam Socio-Economic Panel. We conclude that distributed photovoltaic systems with additional battery storage are only suitable to promote energy resilience if the government provides appropriate financial incentives. Considering temporal variations and local conditions, as well as a participatory decision-making process, are crucial for the long-term success of energy projects. Our advice to decision-makers is to design policies and regulatory support that are aligned with the preferences and needs of target communities.
ABSTRACT
We present a low‐altitude satellite survey of power line harmonic radiation (PLHR) at 50 Hz over Mainland China. We analyzed the month‐to‐month variation pattern in PLHR occurrence rate and further analyzed its correlation with some influencing factors (i.e., solar radiation, lightning flashes, and electricity consumption) using CSES satellite electric field data from 2019 to 2021. We also investigate the response of PLHR occurrence rate to COVID‐19. The statistical results show the dayside PLHR occurrence rate decreasing from winter to summer solstice and increasing from summer to winter solstice, which indicates it is controlled by the solar radiation. The nightside variation is more complex, which may be due to many sources that could influence the nightside lower ionosphere. The PLHR occurrence rate significantly decreased over Mainland China in February 2020, which is because of the significant decrease in electricity consumption due to the suspension of industrial production caused by COVID‐19.Alternate :Plain Language SummaryPower line harmonic radiation (PLHR) is the electromagnetic waves radiated by electric power systems at harmonic frequencies of 50 or 60 Hz, depending on the frequency of the system on the ground. Previous research mainly focuses on identification of individual PLHR events and their subsequent analysis. However, the number of base‐frequency PLHR signal events is the most abundant, which is suitable for the statistical study of PLHR occurrence rate and its variation pattern, and further study of the factors affecting its variation pattern. In this paper, we use 3 years of electric field data from the China Seismo‐Electromagnetic Satellite (CSES) which is an LEO satellite launched into orbit in February 2018 to investigate the month‐to‐month variation pattern of PLHR occurrence rate over Mainland China and its correlation with the influencing factors. The response of PLHR occurrence rate to COVID‐19 are also investigated.
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The Energy Sector is highly targeted by cyber threats because of its inherent value and profitability. Recent reported security incidents verify its key playing role in the entire economic and societal concurrent reality. This paper aims to assess the cyber-security culture status of European representatives in the entire electrical power supply chain during the coronavirus pandemic and the Ukrainian war. An evaluation campaign has been carefully designed and held from 3rd March 2022 to 18th March 2022. During that period, participants from different Electrical Power and Energy Systems (EPES) organizations participated in the campaign. Gathered results were analyzed and co-examined using different techniques revealing important findings regarding the cyber-security status and resilience of individuals and organizations in the European EPES sector. © 2022 ACM.
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A low-cost remote lab has been implemented to aid instructors in delivering an online electrical engineering introductory course in electric circuits during the COVID-19 pandemic. The main purpose of implementing the remote lab was to familiarize freshmen students with conventional equipment such as digital oscilloscope, function generators, power supply, multimeter and frequency counters. The integration of the remote devices in the online lectures was essential to enable students to operate the equipment and prepare them for a smooth transition upon their return to campus. The lab has also offered students the possibility of conducting basic online circuit experiments, both as part of the theoretical course and its associated lab, in a proof-of-concept paradigm or as a fully practical course. © 2022 IEEE.
ABSTRACT
Comprehensive analysis of respiratory gases may provide noninvasive health monitoring of lung diseases, such as corona virus 2019 pneumonia. Here, a self-powered wearable mask has been fabricated for real-time monitoring and uploading exhaling oxygen information. Tetrapod ZnO (T-ZnO) nanostructures are hybridized with polyvinylidene fluoride (PVDF) that adhere to flexible fabric substrate on a mask. The piezoelectric effect of T-ZnO/PVDF is coupled with the gas sensing properties. The sensing unit can convert breath energy into piezoelectric signal without any external power supply, and the outputting piezoelectric voltage increases with increasing oxygen concentration, acting as the sensing signal. The sensing unit integrated with data processing module and wireless Bluetooth module can transmit the exhaling oxygen information to the mobile device, realizing real-time monitoring the oxygenation capacity of the lungs. This self-powered wearable approach can promote the lung diagnosis outside of clinical settings. © 2022 IOP Publishing Ltd.
ABSTRACT
We synthesize scenarios of hourly electricity price, which is known as the system marginal price (SMP), for thirty-years based on the oil price. Hourly SMP scenarios are very important when planning new generators because the revenue and cost of new capacity margins are determined based on the SMP. Because the SMP contains both short-term and long-term periodic patterns, designing a single model based on these patterns to predict the SMP is difficult. Although oil price affects SMP, they can not be directly used in the forecasting model because the resolution of SMP is at hourly intervals, but that of oil price is at yearly intervals. To overcome these problems, we decompose the SMP into annual, monthly, and daily components, and the components are predicted based on different models. The model for the annual component (AC) is designed to predict the long-term trend based on fuel price scenarios. The model for the monthly component (MC) is designed to predict the seasonal trends based on the long short term memory (LSTM) model. The model for the daily component (DC) is designed to predict the daily SMP fluctuation. Finally, we synthesize SMP scenarios by aggregating three components. We make three types of SMP scenarios (high, reference, and low), and the performance of the scenarios is tested using previous data for two years on the basis of mean absolute error (MAE). Due to the global COVID-19 pandemic, the low type of SMP scenario is most accurate. We also verify that the reliability of long-term scenarios can be secured by using oil price while maintaining monthly and daily patterns. Author
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The COVID-19 pandemic that has ravaged the world since December 2019 caused disruptions in the engineering education sector as students in African universities were unable to learn virtually. From two recent multi-language, multi-cultural pan-African online surveys to assess the impact on students, over 6,000 responses showed the twin constraints of irregular electric power supply and poor internet connectivity to effectively participate in virtual learning. This project is aimed at developing an affordable and reliable power and communication device for continuous online learning for engineering students, showcasing the strength in Africa's diversity through a collaborative, multinational, multicultural, multi-lingual and gender-sensitive platform to solve this identified global African Engineering Education challenge. A collapsible 100-watt solar photovoltaic module charging a set of lithium batteries via the charge controller was used to power a laptop computer, a mobile phone and a 5-watts bulb simultaneously through a Direct Current/Direct Current (DC/DC) converter. An embedded modem in the device provided the wireless network for internet connectivity. The initial prototypes produced weighed less than 7 kg, and preliminary performance tests showed that the gadget was able to charge up a laptop and two smartphones totaling 45.5WH from 0% to 100% while the remaining backpack state of charge remains 12.8V at 88% (that is 12% depth of discharge). The power supply and communication device for continuous online learning for African engineering students will not only bring engineering solution collaboration among hundreds of engineers, technologists, and technicians from the entire African continent, but will also boost entrepreneurial skills for many African engineering practitioners when fully commercialised. © 2021 IEEE.
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This paper presents HOMER simulation models for optimizing renewable energy system components in Off grid and Grid connected systems for Covid-19 hospitals. Load profiles of 100 bed and 50 bed Covid hospitals are established critically. Two simulation models are built for each load profile. Optimization of energy system components is conducted based on net present cost and cost of energy. In process of optimization, HOMER simulates all possible configurations and ranks feasible combinations according to TNPC, and lists feasible options. Ten combinations are identified for analysis in each model. The critical analysis of results revealed that, grid connected system proves to be most economic and reliable option for hospital loads. The cost of energy obtained in grid connected system is Rs.9/kWh, whereas for diesel generated connected system costing Rs.22/kWh. This difference is appeared mainly due to higher cost of diesel and variation in the solar and wind energy potential with time of the day. Thus it is concluded that, renewable energy sources can be effectively employed for energizing the Covid-19 hospital in association with grid. © 2021 IEEE.
ABSTRACT
The ability to provide uninterrupted power to military installations is paramount in executing a country’s national defense strategy. Microgrid architectures increase installation energy resilience through redundant local generation sources and the capability for grid independence. However, deliberate attacks from near-peer competitors can disrupt the associated supply chain network, thereby affecting mission critical loads. Utilizing an integrated discrete-time Markov chain and dynamic Bayesian network approach, we investigate disruption propagation throughout a supply chain network and quantify its mission impact on an islanded microgrid. We propose a novel methodology and an associated metric we term “energy resilience impact” to identify and address supply chain disruption risks to energy security. The proposed methodology addresses a gap in the literature and practice where it is assumed supply chains will not be disrupted during incidents involving microgrids. A case study of a fictional military installation is presented to demonstrate how installation energy managers can adopt this methodology for the design and improvement of military microgrids. The fictional case study shows how supply chain disruptions can impact the ability of a microgrid to successfully supply electricity to critical loads throughout an islanding event.
ABSTRACT
The electric power grid is a complex cyberphysical energy system (CPES) in which information and communication technologies (ICT) are integrated into the operations and services of the power grid infrastructure. The growing number of Internet-of-things (IoT) high-wattage appliances, such as air conditioners and electric vehicles, being connected to the power grid, together with the high dependence of ICT and control interfaces, make CPES vulnerable to high-impact, low-probability load-changing cyberattacks. Moreover, the side-effects of the COVID-19 pandemic demonstrate a modification of electricity consumption patterns with utilities experiencing significant net-load and peak reductions. These unusual sustained low load demand conditions could be leveraged by adversaries to cause frequency instabilities in CPES by compromising hundreds of thousands of IoT-connected high-wattage loads. This article presents a feasibility study of the impacts of load-changing attacks on CPES during the low loading conditions caused by the lockdown measures implemented during the COVID-19 pandemic. The load demand reductions caused by the lockdown measures are analyzed using dynamic mode decomposition (DMD), focusing on the March-to-July 2020 period and the New York region as the most impacted time period and location in terms of load reduction due to the lockdowns being in full execution. Our feasibility study evaluates load-changing attack scenarios using real load consumption data from the New York Independent System Operator (NYISO) and shows that an attacker with sufficient knowledge and resources could be capable of producing frequency stability problems, with frequency excursions going up to 60.5 Hz and 63.4 Hz, when no mitigation measures are taken.