Power Shortage Research Articles

Application of Machine Learning in Fault Detection And Classification in Power Transmission Lines

Electrical faults have been identified as a significant contributing factor to electrical equipment damage. Such incidents can potentially result in a range of adverse consequences, including bushfires, electrical outages, and power shortages. The detection and classification of faults facilitates the delivery of superior quality of service, the preservation of the environment, the prevention of equipment damage, and the satisfaction of electricity line subscribers. In this study, we analyze the data from an electrical network comprising four generators of 11 kV, which have been modeled in Matlab. The generators are situated in pairs at either end of the transmission line. Subsequently, machine learning techniques are employed to detect faults in the transmission between lines, and machine learning models are utilized to classify the faults. Four distinct supervised machine learning classifiers are employed for comparison purposes, with the results presented in a confusion matrix. The results demonstrated that decision trees are particularly well-suited to this task, with an 88.6205% detection rate and a slightly higher accuracy than the random forest algorithm (87.9212% detection rate). The K-nearest neighbor's approach yielded a lower result (80.4196% of faults detected), while logistic regression demonstrated the lowest performance, with 34.5836% of faults detected. Six fault categories were found in the dataset: No-Fault (2365 occurrences), Line A Line B to Ground Fault (1134 occurrences), Three-Phase with Ground (1133 occurrences), Line-to-Line AB (1129 occurrences), Three-Phase (1096 occurrences) and finally Line-to-Line with Ground BC (1004 occurrences).

Experimental study of energy efficiency of kitchen electrical appliances for boiling water

Introduction. Steady growth in the number of powerful electrical appliances and devices in households leads to an increase in electricity consumption. It significantly affects the economic costs of consumers and the deterioration of the ecological situation in the environment. Problem. The cost of electricity tariffs for the population tends to be relatively steadily increasing, which makes the issue of energy efficiency particularly relevant for consumers. The use of energy-efficient technologies in everyday life allows reducing electricity costs and increasing the economic efficiency of households. Energy efficiency of household electrical appliances is a pressing issue for ensuring a stable energy supply in the context of growing electricity consumption. Goal. An analytical study of the operating features of kitchen electrical appliances for boiling water and an experimental study of their energy efficiency. Methodology. The energy efficiency of the most common kitchen electrical appliances for boiling water was analyzed through experimental studies. Results. In terms of energy efficiency, the flow-through thermopot turned out to be the best among the studied electrical appliances, followed by an electric kettle and a traditional thermopot. Practical value. The use of energy-efficient technologies in modern household appliances is an important task, especially in winter and in conditions of shortage of electric power during military aggression from Russia and large-scale destruction of critical infrastructure and power facilities in our country. Further research will help reduce energy consumption and increase the energy efficiency of household appliances.

The Influence of Stability in New Power Systems with the Addition of Phase Modulation Functions in Thermal Power Units

The addition of phase modulation function technology to thermal power units is one of the most effective measures to solve dynamic reactive power shortages in the construction process of new power systems. In this paper, the influence of the phase modulation function transformation of thermal power units on the stability of a new power system is studied. Firstly, the new power system stability index is deeply analyzed, and an evaluation system for power system transient stability is constructed from five key dimensions: transient voltage, static voltage, power angle stability, power flow characteristics, and grid support. Secondly, a fuzzy comprehensive evaluation method considering the subjective and objective comprehensive weights is proposed, and the influence of the phase modulation transformation of the thermal power unit on the stability of the receiving-end power grid is quantitatively analyzed. Finally, a CEPRI36 node example model was built based on the PSASP v.7.91.04.9258 (China Electric Power Research Institute, Beijing, China) platform to verify the accuracy and effectiveness of the proposed method. The results show that the proposed method can quantitatively analyze the impact of adding a phase modulation function to thermal power units on the stability of the power system. At the point of renewable energy connection, the static voltage stability index improved by 42.9%, the transient power angle stability index improved by 32.1%, the multi-feed effective short-circuit ratio index improved by 33.9%, and the comprehensive evaluation score improved by 14.7%. These results further indicate that adding a phase modulation function to thermal power units can provide a large amount of dynamic reactive power support and improve the voltage stability and operational flexibility of the system.

Low-Frequency AC Multiport Asynchronous Grid Connection System to Optimize Generation Costs and Mitigate Bottlenecks

Renewable energy sources continue to increase due to the energy transition; thus, the generation output of conventional power sources is decreasing. The installation of renewable energy sources can lead to the concentration of these sources depending on geographical characteristics, which may cause bottlenecks between the renewable energy generation sites and load centers, and such bottlenecks can result in power shortages in load centers and may cause issues that limit the integration of renewable energy. Thus, this paper proposes the application of an LFAC multiport asynchronous grid connection system to solve these problems, where the frequency conversion device uses a variable frequency transformer (VFT). In addition, the installation location of the proposed LFAC multiport asynchronous grid connection system is selected using a grid partitioning technique, and the optimal power flow is performed to minimize the generation costs. The grid partitioning was conducted using the IEEE 39 bus system, and the feasibility of the proposed LFAC multiport asynchronous grid connection system was verified through simulation tests of the generation and load demands in the grid. In addition, the VFT control and optimal power flow control performances were confirmed through MATLAB/Simulink.

CHALLENGES AND BENEFITS OF USING INFORMATION TECHNOLOGIES IN TEACHING CHEMISTRY IN UKRAINE DURING WARTIME

The education sector, which is one of the most important aspects of public life, has undergone critical changes due to the full-scale invasion of Russia in Ukraine. Educators and students have been forced to a rapid shift from traditional to digital learning methods. Chemical education has adapted to the new reality by using a number of digital platforms, virtual laboratories, and other IT tools for distant learning. These innovative educational technologies have become particularly useful in chemistry teaching, where interactive tools help replace hands-on experiments in wartime circumstances, where access to traditional laboratories is unsafe or impossible. However, the transition to digital learning in Ukraine during the current period not only has complexities on its own, but is also accompanied by significant challenges caused by war conditions, including power shortages, limited Internet access, and digital inequality, especially in war-torn and rural areas. The issues of digital literacy, content localization, cybersecurity, and students’ and educators’ psychological well-being present further complications. Developing and expanding access to relevant, localized chemistry educational content will be essential to closing the education gap and maintaining long-term sustainability. In the post-war period, it is appropriate to implement a blended learning model that combines digital tools with offline laboratories, which is critical for sustainable recovery, promoting community rebuilding, developing practical student skills, and the sustainability of the Ukrainian education system in general.

OPERATING PECULIARITIES OF STANDARD COOLING SYSTEMS OF ENGINES AT HIGH ALTITUDES

The item under test was the engine without its standard facility-based cooling systems, the lack of which makes it impossible to operate as a power unit of a vehicle in a great majority of experimental research of internal combustion engines at high altitudes. The findings may create a wrong impression of the range of power ratings and economic parameters of the engine when operating at high altitudes because changes in atmospheric conditions exert an effect on the running efficiency of its standard systems as well. It is established that the efficiency loss of the cooling system may cause a forced power limitation of the engine as a result of the experimental research of the diesel engine equipped with all standard facility-based systems at very high altitudes. Thus, the shortage of power may significantly exceed the power loss of the engine due to air density reduction at high altitudes.

Understanding SOE responses to the energy crisis in Nigeria and South Africa

This aim of this paper is to present an understanding State-Owned Entities (SOE’s) responses to the energy crisis in Nigeria and South Africa. The energy crisis in both Nigeria and South Africa has posed significant challenges, with both countries experiencing severe power shortages that have impacted economic growth and the quality of life. State-Owned Enterprises (SOEs) in the energy sector, such as Nigeria's NESCO and South Africa's Eskom, have traditionally been central to efforts of ensuring energy security. The paper therefore through a qualitative method of research, attempts to reveal the responses of the SOE’s in these states to address the energy crisis. Hence, it concludes that South Africa responded by unbundling Eskom and Nigeria privatising the energy sector. But these mechanisms are yet to solve the energy crisis.

Feasibility Study of Wind Farm Using RETScreen Model: A Case Study of Al-Razaza Site, Iraq

In recent years, interest in renewable energies has increased due to their clean, renewable, and inexhaustible characteristics. Iraq faces a significant challenge in the shortage of electric power. The green economy, especially in renewable energy, has become one of the world's main pillars, especially after the remarkable rise in greenhouse gas emissions (GHG) from fossil fuel combustion for electricity production. This study evaluates wind farm feasibility, assessing costs, revenue, and financial viability. It identifies potential hazards and difficulties, enabling developers to develop strategies to mitigate risks during project creation and operation. This paper aims to undertake a feasibility study to assess the viability of constructing a wind farm with a capacity of 340 megawatts at the Al-Razaza location in Karbala province. The study site utilized authentic data from the meteorological tower installed on the premises. The data employed spanned three years, encompassing a comprehensive and integrated dataset for the study. RETScreen, a powerful model renowned for its energy efficiency analysis and sustainable decision-making capabilities, was employed. Through the application of RETScreen, a meticulous assessment and analysis of the intricate project components were facilitated. A study of risk analysis was conducted to ascertain the impact of various parameters on the payback period of the project. The findings showed that the capacity factor of the wind farm is 22.3%, which is relatively low, the simple payback period is 10.3 years, and the energy production cost is 0.059$/KWh.

Design of Local Micro-Grids to Solve the Electricity Shortage in Iraq Cities

Iraqi cities suffer from a shortage of electric power due to poor production and deterioration of transmission and distribution lines. There is no prospect currently for improving the grid, despite the government's promises. So it has become necessary to find alternatives, at least at the local level. This research, presented a successful alternative, which applied all over the world, which is the local microgrid. Also, it’s developed a design for this microgrid that suits the conditions of Iraq and supports the integration of clean energy produced by the consumer. The results indicate the success of investing in this microgrid by small investors, foreign companies or local administrations of the cities that want to develop their cities in isolation from the problems of the country's national electrical grid. This solution reduce the pressure on the national grid on one hand and improve the electricity service for the consumer on the other hand, by providing the pivotal key to the solution, which is replacing the blind system of paying wages (for electricity service) currently followed in Iraq with the billing system followed in all developed countries of the world. This solution provides the possibility of deploying the economic solar PV system (without batteries) in Iraqi houses to reduce the bills and also allows personal monitoring of electricity consumption so that the consumer can reduce loads during peak times to reduce bills as well.

Satellite and AI monitoring humanitarian crises in the Gaza Strip during the early stage of Israeli–Palestinian conflict

ABSTRACT Extensive power shortages and airstrikes have plunged Gaza into a severe humanitarian crisis. Here, we introduce a rapid and efficient framework to evaluate the impacts of armed conflict and monitor potential humanitarian crises in the Gaza Strip based on multi-source satellite imageries and cutting-edge artificial intelligence (AI) techniques. Since October 9th, 2023, the complete blockade had led to widespread power outages across the entire Gaza Strip, particularly in the southern region. Airstrikes destroyed more than 20% of buildings, including nearly 60% of shops and hospitals, as well as 80% of water infrastructure. The affected vulnerable population exposure is further quantified at the block level, which further helps determine high-risk humanitarian crisis locations and aid in the precise allocation of humanitarian resources. In general, the proposed framework performs well in applying to complex environments during an armed conflict. It can also offer rapid and continuous monitoring of the Gaza Strip and can be broadly applied in armed conflicts or natural disasters. Our research is one of the early studies to apply AI foundation models to improve the efficiency of rapid post-disaster investigation.

Factors Militating the Effective Utilization of the Nursing Process in Patient Care: A Descriptive Survey of Nurses in a Tertiary Hospital in North West, Nigeria

Nursing process is the systematic, patient-centered approach used by nurses to guides individualized nursing care; thereby enhance quality of patient care and outcomes for both the patient and family members, as an organized framework for the practice of nursing. The purpose of this study was to investigate the factors militating against effective utilization of nursing process in patient's care among nurses in a Tertiary Hospital in north-west, Nigeria. The research design employed in the study was across sectional survey, sample size of 108 but 97 valid for data analysis. The nurses who were proportionately selected participated in the study. The data were derived from the administration of copies of questionnaire. The instrument was validated by the researcher’s supervisor and two other experts from faculty of nursing Ladoke Akintola University of technology. A Cronbach’s alpha reliability coefficient of 0.82 is indicative of the reliability of the instrument. Data collected were analysed using SPSS version 20 version. Hypothesis was tested using Chi square set at p value 0.05. The findings revealed that greater number (92%) understood that nursing process is a problem solving technique for nurses and (80, 83%) utilizes nursing process in patients care. Majority of participants 63.9% (Mean = 1.71) established that shortage of human resources, 59.8% (Mean = 1.86) lack motivation and 53.6% (Mean = 1.53) different approaches adopted by nurses were seen to impact the use negatively. Experience, and educational Level were statistically found to be significant determinants for nursing process utilization (p=0.00, and 0.02). Based on the findings, it can be concluded that there exist a significant relationship between nurse’s years of experience and knowledge of nursing process utilization and the rate of utilization. Recommendation that adequate and relevant materials be provided for nurses in order to achieve and perform their respective tasks at the optimal best, the management should equally employed more nurses to breech the chronic shortage of man power.

Mathematical Models for Optimal Distribution of Power Shortage in Calculating the Electric Power System Adequacy Indicators

Mathematical Models for Optimal Distribution of Power Shortage in Calculating the Electric Power System Adequacy Indicators

Multi-level consensus based load frequency controller with multi-battery energy storage systems

This study introduces a primary and secondary level multi-consensus load frequency controller (LFC) with distributed multi-battery energy storage system (MBESS) to regulate the frequency and voltage of the islanded grid. The suggested control approach uses battery storage devices’ ability to deliver or absorb active power during power shortages or surpluses in order to regulate the system frequency and voltage. The controller uses consensus-based distributed coordination among agents in order to achieve stabilise frequency and voltage. In primary mode, each node exchanges local information with its neighbour, such as battery energy, power, and state of charge (SoC), to reach an agreement value in finite time. In secondary mode, the controller achieves its stability by sharing active and reactive power to regulate the frequency and the voltage. The conventional PI controller with a state feedback loop controller is used as a local controller for LFC in the multi-agent control platform. Numerical examples are considered throughout the simulations to highlight the controller’s functionality and are compared with the past literature. As simulation results suggested, the proposed model with the MBESS will have a efficient system performances compare to traditional LFC mode. In this case, each single battery model has the ability to work as a generator and as an active load to the grid to balance frequency and voltage fluctuations. Furthermore, the results are obtained through the OP5700 real-time simulator to compare the values with the simulation. The results are further validated on the IEEE 14-bus power system. Analysis of the results indicates that the proposed system exhibits better characteristics with the multi-level consensus approach, compared to the traditional LFC.

The Eectricity Crisis and the Feasibility of Nuclear Energy in Egypt

The power outage crisis is increasing in Egypt, negatively affecting many other sectors such as industry, agriculture, and trade. In light of the lack of sufficient capacity to meet the growing needs of consumers, which has led to regular power shortages and power outages. While Egypt needs additional energy, the production of gas and oil needed to generate thermal energy decreased in 2014, and Egypt moved from an exporter of natural gas to a net importer. In addition to this, the volume of subsidies allocated to energy increased, the rise in global prices for oil and natural gas, and the need for huge investments to create Power generation plants, development of transportation networks, and distribution of electrical energy, which led to pressure on the general budget. A continuous and reliable supply of electricity is needed for Egypt's social and economic development. Accordingly, the government encouraged the development of new energy, invited the private sector to participate in energy generation, and a number of government reforms were made in order to enhance competition in the energy market, which required the need to study the possibility of providing it using nuclear energy. Its stations have a high load capacity, operate almost at full capacity all the time, are characterized by the stability of the electrical network and energy independence, and avoid the risks of fuel price shocks, and the costs of generating electricity from them decrease with increasing production. The importance of this research lies in highlighting the challenges facing the structure of the electricity sector in Egypt, and studying the advantages enjoyed by nuclear energy as the most important renewable energy sources in the world. Its importance also lies in comparing nuclear energy with other energy sources, and trying to benefit Egypt from obtaining this energy for use. In economic development projects, rationalizing tariffs and supporting their access to the poor. <i>This research is divided into</i>:<i>The first topic</i>: The electricity generation crisis in Egypt and a development vision for the contribution of nuclear energy to its solution, <i>The second topic</i>: trends in development planning for establishing nuclear plants in Egypt. The electricity generation crisis in Egypt and a development vision for the contribution of nuclear energy to its solution.

Optimization of emergency frequency control strategy for power systems considering both source and load uncertainties

With the increasing integration of renewable energy sources and the presence of numerous controllable loads such as electric vehicles and energy storage in the modern power system, higher nonlinearities and uncertainty both sources and loads are introduced. These factors pose challenges in achieving fast and accurate emergency frequency control. Therefore, this paper addresses the issue of dual source-load uncertainties in power system and presents an optimization strategy based on the Soft Actor Critic (SAC) algorithm that involves the participation of controllable loads in emergency frequency control. Firstly, the spatio-temporal uncertainties of wind farm power output on power supply side and power demand on the load side are described using Weibull and normal probability distributions, respectively. Secondly, an improved Markov Decision Process (MDP) model for emergency frequency control is established, which considers the characteristics of the dual source-load uncertainties. Finally, an optimization of the SAC algorithm is conducted based on Deep Reinforcement Learning (DRL), aiming to achieve rapid system frequency recovery and minimize the cost of removing controllable loads. The presented approach in the paper enhances the emergency frequency control strategy for uncertain power systems and effectively addresses the issue of source-load uncertainty compounded by fault power shortages.

Retrofitted CCS technologies enhance economy, security, and equity in achieving carbon zero in power sector

Retrofitting existing fossil fuel power plants with carbon capture and storage (CCS) technology could reduce carbon emissions while avoiding stranded asset, which will be important in facilitating a just transition of the global power sector. Although some studies have explored the cost-effectiveness and abatement potential of retrofitted CCS technologies, elaborate system modeling of full-chain retrofitted CCS technologies considering multiple technology types requires further research. Here, we developed an hourly-resolution intertemporal dynamic power system optimization model that elaborately considers three retrofitted CCS technologies for coal-fired and gas-fired power plant in addition to eleven power generation technologies and two energy storage technologies and applied it to evaluate the role of retrofitted CCS technologies in achieving carbon neutrality in China's power sector. The results show that, compared with no retrofitted CCS power system, the high development of retrofitted CCS can reduce the future installed capacity and power generation demand of China's power sector by up to 605GW or 10.5 % (in 2040) and 0.17 PWh or 0.9 % (in 2060), respectively. The cumulative system decarbonization costs and electricity supply costs will decrease 6.2–8.2 % and 2.1–2.6 % by 2060, respectively, due to the savings in related costs of newly built plants and reduction in potential power shortages, in addition to avoidance of large coal-fired power stranded assets. The developed model could be a reference for other countries, and in China and perhaps in other economies with coal-dominant power systems, policies advocating the development of retrofitted CCS should be strengthened.

Increases in Night Lights Intensity Reveal Extreme Events: A Case of Study on the Ongoing Conflict in Ukraine

Abstract. Analyzing night lights images allows identifying and monitoring affected areas during conflicts, as an overall decrease in brightness indicates abandoned or destroyed buildings, curfews, or power shortages. While detecting decrease in lights intensity is an established technique to identify critical areas during conflicts, the causes of appearing bright lights have not been extensively studied. An increase in brightness may be related to extreme events, such as fires resulting from bombing. This paper shows several examples supporting this new use of these images, validated using high-resolution optical earth observation data and ancillary information sources in the frame of the conflict in Ukraine which has been ongoing since February 2022.

Decentralization of renewable energy sources based optimum scheduling and management through a virtual power plant

Abstract In this paper, renewable resources and co-generation units are grouped together to perform optimized operational scheduling in a virtual power plant (VPP) system. Renewable sources consist of solar photovoltaic, wind, and fuel cell units that are equipped together with a cogenerating unit to intensify the system's dependency in case of power shortage from renewable sources. The uncertainty aspect is investigated for the developed system as renewables are associated, and its impact on network operation is discussed. Storage provision is facilitated in the form of flexible and spinning reserves in which electric vehicle (EV) and energy storage systems (ESS) increase the system reliability by ensuring continuity of power supply. Optimal scheduling is carried out from both economic and environmental perspectives in which the net profit of the system is improved and the generated emissions are reduced by considering dual scheduling i.e., day-ahead (DA) and proposed 15 min interval. Moreover, a nature-inspired metaheuristic red fox optimization (RFO) is employed to handle the VPP problem and the results with the context to net profit and emission are also compared with work available in the literature. Finally, the proposed approach is promising in terms of higher computational efficacy and reveals the suitability of the VPP system.

Adaptive robust self‐scheduling for a wind‐based GenCo equipped with power‐to‐gas system and gas turbine to participate in electricity and natural gas markets

AbstractIntegrating renewable energy, particularly wind generation, into power systems brings significant uncertainty and intermittency, challenging generation companies (GenCos) to maintain economic operations. This paper proposes a strategy for a wind‐based GenCo equipped with a gas turbine and a power‐to‐gas (PtG) system to balance wind variability. The gas turbine offsets power shortfalls by consuming natural gas, while the PtG system absorbs excess wind energy, converting it to natural gas and injecting it into the natural gas network as a form of storage. The GenCo operates in day‐ahead electricity and natural gas markets and the real‐time electricity market, addressing uncertainties from wind output, energy prices, and natural gas access. A tri‐level adaptive robust optimization model is introduced for the GenCo’s short‐term operational scheduling. At the first level, decisions related to the GenCo's participation in the day‐ahead electricity and natural gas markets are made. The second level deals with determining the worst‐case realization of the uncertainties, constrained by the budget of uncertainty and the limited range of variations of uncertain variables. The third level sets the operational strategy on the actual day, considering power and gas balance, as well as constraints for the wind farm, gas turbine, and PtG unit. A column & constraint generation (C&CG) algorithm is used to solve the model. Numerical results demonstrate the model’s effectiveness in various case studies, showing that the GenCo can manage wind uncertainties, benefit from arbitrage opportunities in electricity and gas markets, and improve economic outcomes. This approach supports the broader integration of renewable energy into power systems.

Stochastic optimization of a hybrid photovoltaic/fuel cell/parking lot system incorporating cloud model

The interaction and optimization of electric parking lots (EPLs) with hybrid renewable energy to exchange power and improve the system load reliability has been welcomed systems in energy industry, but it is accompanied by challenges such as uncertain parameters, and also implementing the optimal energy management. This paper proposes a novel stochastic optimization framework for a hybrid energy system including photovoltaic resources, hydrogen storage based-fuel cell integrated with an EPL (PV/FC/EPL) aiming for minimization of the total net present cost (TNPC) while ensuring the maximum probability of power shortage (PPSHmax) to meet a commercial load in Tianjin, China using the real meteorological data. A new improved kepler optimization algorithm (IKOA) utilizing the golden sine strategy is applied to optimize system component sizes and EPL charge/discharge. In a deterministic scenario, the optimal system configuration ensures cost-efficiency and reliability for load supply. Also, a new stochastic modeling framework is proposed using the Cloud Model (CM) to evaluate the effect of uncertainties in irradiance, temperature, and system demand on TNPC and PPSH. Deterministic findings reveal enhanced reliability and reduced TNPC through FC and EPL overlap during power shortages, compared to systems lacking EPL. Specifically, TNPC and PPSH are $8,632,643 and 1.45 %, respectively, for PPSHmax = 2 % over 20 years of operation. However, stochastic optimization demonstrates a 10.82 % increase in TNPC and an 8.67 % decrease in PPSH compared to the deterministic model under PPSHmax = 2 %, indicating heightened cost and reduced reliability when uncertainties are considered. This underscores the efficacy of the cloud model-based stochastic approach in addressing uncertainty in hybrid system optimization. Also, it reveals fluctuations in optimal cost and reliability values with changes in cloud droplet distribution around the expected value, emphasizing the significance of stochastic modeling for robust decision-making in hybrid energy systems. Moreover, evaluating the incorporating the penalty for the system's inability to supply the load, changing the storage investment cost, and interest rate variations on the system optimization cleared considerable effect of the system cost and reliability.