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Technology and Economics of Smart Grids and Sustainable Energy
Number of Followers: 1  Hybrid journal (It can contain Open Access articles)ISSN (Online) 2199-4706 Published by Springer-Verlag  [2467 journals]
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- Correction: Title change of journal Smart Grids and Sustainable Energy
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PubDate: 2023-03-18
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- Novel Shade Dispersion Techniques for Reconfiguration of Partially Shaded
Photovoltaic Arrays-
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Abstract: Abstract The photovoltaic (PV) arrays are inevitably subjected to partial shading (PS) conditions that highly limit the output. To mitigate these effects, various reconfiguration procedures have been executed by the researchers. However, many of these procedures fail to disperse the shade effectively over the entire array and hence there is a dire need for such an efficient reconfiguration technique. This paper explores Knight’s Tour Magic square (KTM) and Doubly Even-order Magic square (DEM) techniques which effectively disperse the shadow by reconfiguring the array without altering the electrical connections. To examine the superiority of the proposed techniques, their performance has been compared with conventional total-cross-tied, existing odd-even and odd-even-prime configurations of a symmetric 8 × 8 and asymmetric 4 × 3 PV arrays. Further, the applicability of the proposed techniques is proved by analysing the system with eight performance parameters such as global maximum power, power mismatch, percentage losses, efficiency, fill factor, capacity factor, array yield, and performance ratio under 20 distinct PS patterns. The power enhancement in GMP using the KTM and DEM approaches are nearly 42.67%, 17.87%, 16.24%, 8.04% for asymmetric arrays, and 26.43%, 25.38%, 25.09%, 15.61%, 10.63%, for the symmetric arrays. Finally, a comprehensive economic analysis is also performed, and it is observed that there is a significant augmentation in the number of units and the revenue generated by employing the proposed techniques.
PubDate: 2023-03-10
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- Mobile Hybrid Energy System for Modern Drives of Smart Energy Transition
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Abstract: Abstract Mainly driven by the climate change, electric power systems are globally going through a transition. In order to cut carbon dioxide emissions and slow down global warming, traditional systems consisting of concentrated, easily controllable and often fossil-based power plants are step-by-step replaced by the ones which are typically distributed, renewable and carbon dioxide free. Often this green and renewable production is weather-dependent and much more difficult to predict than the traditional fossil-based one. In the smart energy transition we are dealing with these critical and topical issues: how to ensure the balance in the power grid, when the controllability of production gets more and more difficult. New solutions, such as flexible loads, demand response and growing role of energy storage, are called for to ensure high quality of electric energy. In all these solutions, more accurate power control is called for. In addition, it is important to realize that such new solutions of modern electric drives always require sophisticated power electronics combined with smart control. To be able to demonstrate these modern electric drives of smart energy transition, a mobile and technically versatile hybrid energy system was designed and built at Tampere University of Applied Sciences. In addition to easy transfer enabled by a trailer solution, the goal of design and construction was in technical diversity. The hybrid energy system presented in this paper has not been tailored to any specific use, but instead, we wanted to be able to demonstrate even such modern electric drives that were not predictable in the design phase of the system. Thus, the technical diversity of the system deserves to be emphasized. In this paper we present the design, the operational principles, smart control properties and some successful demonstrations of energy transition related modern electric drives.
PubDate: 2023-03-01
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- Efficient Energy Management and Reliability Assessment by Optimal
Placement of Renewable Energy Sources with Pump Storage Plant-
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Abstract: Abstract Deteriorating environment conditions due to global warming and depleting fossil fuels, has forced mankind to shift towards renewable energy sources (RES). The integration of RES in existing power system is challenging due to its intermittent nature. This study formulates novel sensitivity index i.e. nodal price of energy index (NPEI) to assist the location of sensitive buses for optimal placement of RES. Firstly, the proposed approach subjects power system to (N-1) contingency including both loss of generator and line outage. The NPEI is computed for every bus in various contingency conditions. The most severe contingency is identified based on highest value of sensitivity index in peak load period. The buses with highest values of NPEI is the optimal location for RES placement in the most critical contingency scenario. Secondly, the proposed approach focuses on efficient and cost-effective energy management by optimally scheduling disparate energy generation sources. The system incorporates pumped storage plant (PSP) based energy storage devices to effectively utilize wind and solar energy. The objective of this study is to minimize the total generation cost which includes the generation cost associated with conventional generators, its emission cost and valve-point loading effect, generation cost of RES, and the cost associated with energy supplied by PSP. The partial shading of PV modules is also implemented and its impact on system parameters are observed. The penetration of RES and energy storage effects system reliability hence, the proposed approach computes reliability indices expected energy not supplied (EENS) and loss of load expected (LOLE) for both presence and absence of RES and PSP. Finally, the proposed approach results in optimal placement of RES and optimal energy scheduling of disparate energy sources along with analyzing its effect on system reliability. The study is performed on IEEE 30 bus system.
PubDate: 2023-01-28
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- Load Serving Entity’s Profit Maximization Framework for Correlated
Demand and Pool Price Uncertainties-
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Abstract: Abstract Load serving entity (LSE) maximizes profit by maximizing the difference between revenue earned from supplying its consumer demand and procurement cost incurred in the wholesale electricity markets. Procuring energy for varying consumer demand at varying pool prices is a challenge for LSE, as their concurrent variations significantly affect its expected profit. Hence, modeling uncertainties of consumer demand and pool prices for LSE’s profit maximization can offer significant opportunities. The paper capitalizes on this opportunity, by developing a novel framework to consider the uncertainties and correlation between LSE’s consumer demand and wholesale market prices. The two uncertainties and their correlation are explicitly modeled in a single framework using the information gap decision theory (IGDT) based ellipsoid bound uncertainty model, for an LSE holding a large share of market demand. The proposed framework maximizes profit and addresses the risk-averse and risk-seeking behavior of LSE through robustness and opportuneness functions. Simultaneous consideration of demand and pool price uncertainties increases tolerance of decisions to handle these uncertainties while improving profit targets.
PubDate: 2023-01-17
DOI: 10.1007/s40866-022-00158-7
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- Evaluation of Classification Models for Forecasting Critical Voltage
Events in Power Systems-
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Abstract: Abstract The extensive proliferation of renewable energy sources and complex loads stresses the power system operation, making it challenging to ensure the safe and effective operation of networks. In this scenario, forecasting voltage may improve the effectiveness of voltage regulation against critical events. For this reason, this paper explores the effectiveness of machine learning models to predict voltage excursion events in power systems using simple categorical labels. By treating the prediction as a categorical classification task, the workflow is characterized by a low computational and data burden. A proof-of-concept case study on a real portion of the Italian 150 kV sub-transmission network, which hosts a significant amount of wind power generation, demonstrates the general validity of the proposal. A detailed comparison of evaluation metrics offers insight into the strengths and weaknesses of several widely utilized prediction models for this application in the presence of balanced and unbalanced datasets.
PubDate: 2022-12-27
DOI: 10.1007/s40866-022-00159-6
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- Optimal planning of Renewable energy generators in modern power grid for
enhanced system inertia-
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Abstract: Abstract In recent times renewable energy sources have become an integral part of the modern power grid. As a result, the overall system inertia of the grid has been reduced, thus leading to frequency instability issues such as fast rate of change of frequency. Thus, to compensate for the declining inertia, it is important to carefully select renewable energy generators (REGs) and energy storage systems (ESS) in order to ensure the stability of the power grid, while also controlling greenhouse gases emissions in line with environmental standards. Therefore, this paper proposes an optimal planning model of REGs and ESS, considering the inertia requirement of the grid. The objective function is formulated to minimize the cost of operation, emissions, and investment in new REGs and energy storage units while maximizing the system inertia. The model was developed as a mixed integer linear programming problem and solved using CPLEX solver in GAMS. Finally, the model was validated using a modified IEEE 9-bus system and compared under three scenarios. The results show that in scenario 3 where system inertia is considered in the presence of REGs and ESS, higher system inertia of 8.776 s was achieved at minimal emission and cost, which justifies the aim of the study.
PubDate: 2022-10-26
DOI: 10.1007/s40866-022-00157-8
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- Optimized Performance and Economic Assessment for Hybrid Island Microgrid
System Considering Uncertainties-
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Abstract: Abstract Distributed energy resources (DER) based microgrid system integration over conventional grids at remote or isolated locations has many potential benefits in minimizing the effects of global warming. However, this emerging microgrid technology brings challenges such as high capital costs, stable performance, uncertainties, operation, maintenance, and management issues. This research introduces an island microgrid system with a correlation of PV/wind/biomass/electrolyzer/hydrogen storage/fuel cell/diesel generator. The suggested hybrid system is assessed based on the different natural uncertainties of the DER, considering the availability of wind speed, solar irradiation, and biomass fuels. Optimized electricity production and possible economic interpretation of the microgrid system are revealed. Day-ahead forecast generation and load demand dispatch analysis related to various uncertainties are estimated and calculated by the net load demand forecasting approach. With the help of optimal power dispatch scheduling, the day-ahead generation and load demand uncertainties are effectively handled. A few plausible case studies bespeak the suitability of the suggested island microgrid system in different environmental situations where the national grid is unavailable. The real-time simulation of the proposed model amplifies the feasibility of generation synchronization with load demand.
PubDate: 2022-10-08
DOI: 10.1007/s40866-022-00156-9
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- The Nexus between Wind Energy Consumption, Economic Growth and Financial
Development: Evidence from Panel Causality and Cointegration Test with
Fourier Function-
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Abstract: Abstract It is known that many countries have made intensive researches and made important technological developments in order to benefit from the wind energy potential, and even in today's conditions, they use some of this potential economically. In the light of these developments, it is important to investigate the relationship between wind energy, especially in the financial markets, and therefore with the economies of the countries. This study aimed to the relationship among wind energy consumption (WIND), economic growth (GDP) and financial development (FIN) for 26 selected OECD countries in period of January-2016 and November-2020. The long-term nexus between the panels has been investigated with fourier panel cointegration and fourier panel causality tests, which detect smooth transition multiple structural breaks using trigonometric functions. According to the panel cointegration test results, the panels move together in the long run, positively for WIND-FIN and negatively for WIND-GDP. Moreover, there is causality relations from both FIN and GDP to WIND. This is a support indicate that wind energy use is costly. Therefore, it would be beneficial to achieve both FIN and GDP to increase the use of renewable energy. When the country-based results are examined, it is understood that there is no causality relationship for 16 countries and that there is unidirectional (neutrality hypothesis) or bidirectional causality for the remaining 6 countries (growth or conservation hypothesis). The findings provide valuable information for policymakers about wind energy investment. In addition, bureaucratic difficulties and deficiencies related to wind energy should be reduced, the private sector should contribute more to renewable energy investments, and individuals should be made aware that renewable energy sources can replace non-renewable energy sources.
PubDate: 2022-10-01
DOI: 10.1007/s40866-022-00155-w
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- Optimal management strategy for a shared EVs aggregator participating in
electricity and frequency regulation reserves markets-
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Abstract: Abstract The use of shared electric vehicles has spread widely in response to the global need of reducing CO2 emissions. Hence, in the literature, authors have proposed strategies to minimize the operative costs of shared EVs, such as the provision of electrical ancillary services. However, to provide these kinds of services jointly with transportation, charging/discharging and fleet management strategies are required. And, the currently available strategies from the literature do not consider shared EVs. Therefore, to fill this gap, this paper presents an optimization-based management strategy for shared EVs that provide ancillary services and sell energy, which is applied to a study case located in Colombia. Additionally, it includes the analysis of the economic contracts that should be established between the EVs operator and the energy retailer; in which, it was found that the best option for EVs operator is to purchase the energy at the stock electricity price and establish a bilateral contract for energy sales. Moreover, it suggests that EVs be charged at the early morning hours when the stock price is lowest, that the ancillary services be provided at hours with the highest stock price, and that the energy be sold at the hours in which the provision of ancillary services is not suitable. Finally, the paper suggests, from the application of a Lagrangian parametric technique, an incentive of at least $ 115 [COP/kWh], to make the electrical services competitive with the car-sharing transportation service, which is paid at a price 23 times higher, within the Colombian context.
PubDate: 2022-08-13
DOI: 10.1007/s40866-022-00153-y
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- Technical and Economic Study for Electricity Production by Concentrated
Solar Energy and Hydrogen Storage-
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Abstract: Abstract Renewable Energy Sources are still in continual progress to be used for electricity production, the most important of which is Concentrated Solar Energy, which has played a prominent role during the past years for electricity production. However, focusing on economic aspect remains important to ensure the implementation of these projects, as many countries focus on necessary cost of investing projects and electricity cost resulting from these modern technologies. In this study, we will present a survey and economic analysis of electricity production by concentrated solar energy in two technological systems: Stirling Dish, and Power Tower, and use an advanced electricity storage system, which is hydrogen production and storage. levelized Cost of Electricity (LCOE) will be calculated in order to know the Total Electrical Cost of producing and storing electricity in this hybrid system as a function of Investment cost It, Operation and maintenance cost (O&M), Interest price, and amount of Energy Produced. This system shows the possibility of application to produce electricity at low prices in terms of cost, as the cost of electricity produced from this hybrid system ranged between 0.112 and 0.172 $/kWh, which is a competitive cost that ensures the possibility of application and investment in addition to electricity production in sustainable and environmentally friendly methods.
PubDate: 2022-08-13
DOI: 10.1007/s40866-022-00154-x
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- Impact of Divergence in BBO on Efficient Energy Strategy of Demand Side
Management-
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Abstract: Demand Response (DR) keeps up an important character in the growth of electricity generation with transmission and distribution in the phase of advanced grid automation. For future smart grid, basically two types of Demand Side Management strategies have been used with a number of shiftable or controllable devices. In this research article, two new variants of Biogeography Based Optimization (BBO) algorithm named as Iteration Control BBO and Pandemic BBO are proposed for solving the minimization problem and definitions of these variants have been made by change in migration control \(\overrightarrow{a}\) vector. These two variants are indirectly support the principle of No Free Lunch theorem. The beauty of these variants is that they are reported the impact of divergence in BBO on efficient energy strategy of DSM. The simulation results reported in this paper claims that the used DSM techniques acquire financial savings, while lowering and shifting peak load. Graphical
PubDate: 2022-07-28
DOI: 10.1007/s40866-022-00150-1
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- Best Combinations of Inputs for ANN-Based Solar Radiation Forecasting in
Morocco-
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Abstract: Abstract In this paper, for forecasting, with the high possible accuracy, the solar radiation intensity, an approach for identifying the optimum set of input data from large sets of input parameters is elaborated, assessed, and proposed. This approach belongs to techniques of Input Variable Selection (IVS) and was established using artificial neural networks (ANNs) as an effective means for numerically approximating the computed objective function: Monthly Average Global Solar Radiation (MAGSR). Based on the approach suggested, we could determine the best combinations of inputs that can reveal great possible correlation and approximation with the output considered parameter. Recorded data from 35 stations of different climatic zones were used for both training and testing purposes. Several new linear formulas between the MAGSR and other climatological and meteorological parameters were developed and evaluated. Based on these relationships, we can forecast other climatological and meteorological parameters like temperature, wind speed, and humidity. The statistical analysis was done, and the best performance of the proposed approach has been well checked and duly validated.
PubDate: 2022-07-25
DOI: 10.1007/s40866-022-00152-z
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- Platform of Intelligent Control of Indoor Lighting integrated into LVDC
Distribution System: A Case Study in the Technical University of Ambato-
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Abstract: Abstract Currently, inefficient use of electricity in homes, businesses, schools, and industries requires the implementation of policies, mechanisms, and technological innovations of rational use of energy. In this sense, the implementation of new distribution systems, low-voltage direct current, LVDC, is presented as a technological solution for energy saving as well as for the efficiency for end users and for energy distribution companies’ power. The emergent of new distribution systems such as LVDC has encouraged the development of innovative methods and components for power to low voltage DC, which are applied to lighting systems, datacenters, and interior spaces. Existing experience about LVDC distribution systems have shown that reducing energy loss is proportional to increased levels of DC voltage. In addition, conversion AC/DC systems have higher losses than conversion DC/DC ones. Therefore, the implementation of LVDC systems is comparatively more efficient than traditional distribution methods of alternating current. The massive integration of LVDC distribution systems will significantly reduce energy losses and increase the efficiency of energy end users. In this article, the implementation of a cloud platform control and management of an isolated distribution system that feeds LVDC lighting loads is described. Also, the conceptual development of integration of LVDC system with a renewable generation, which supplies current to the lighting system is presented.
PubDate: 2022-07-22
DOI: 10.1007/s40866-022-00148-9
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- Novel Extreme Learning Machine and Chaotic in-Built Opposition Based –
Quantum Ruddy Turnstone Optimization Algorithms for Real Power Loss
Dwindling and Voltage Consistency Enhancement-
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Abstract: Abstract This paper proposes Ruddy turnstone optimization (RTO) algorithm, Extreme Learning Machine based Ruddy turnstone Optimization (ELMRTO) Algorithm, Chaotic based Ruddy turnstone optimization (CRTO) algorithm, Quantum based Ruddy turnstone Optimization (QRTO) Algorithm, Opposition based Ruddy turnstone optimization (ORTO) Algorithm and chaotic in-built Opposition based – Quantum Ruddy turnstone optimization (COQRTO) algorithm for genuine loss lessening. Important goals of the paper are Power fidelity extension, power eccentricity minimization and genuine loss lessening. The leading stimulus is in the sculpting of Repositioning –Peripatetic and argumentative actions of Ruddy turnstone. Ruddy turnstone will guzzle wiretaps, young insect and it subsists in bundling style. The constellation of Ruddy turnstone, which mobile from one place to alternate in the sequence of repositioning and the fresh investigation agent position is to evade the smash amongst their contiguous Ruddy turnstone. In the proposed Extreme Learning Machine based Ruddy turnstone Optimization (ELMRTO) Algorithm, Ruddy turnstone Optimization Algorithm approach enhances Extreme Learning Machine features to determine an optimal skeleton of Extreme Learning Machine for enhanced canons. In Chaotic based Ruddy turnstone optimization (CRTO) algorithm Exploration and Exploitation are augmented. In Quantum based Ruddy turnstone Optimization (QRTO) Algorithm, features emulate the analogous performance with the certain stage as they route in a credible powdered of median. Opposition based Ruddy turnstone optimization (ORTO) Algorithm employs Laplace distribution to enhance the exploration skill. Then examining the prospect to widen the exploration, a new method endorses stimulating capricious statistics used in formation stage regulator factor in Ruddy turnstone Optimization Algorithm. In the projected chaotic in-built Opposition based – Quantum Ruddy turnstone optimization (COQRTO) algorithm, the transaction of erratic figures is completed with the irrational digits enthused by Laplace distribution to amplify the support of the probability of formation level inside the exploration zone. Proposed Ruddy turnstone optimization (RTO) algorithm, Extreme Learning Machine based Ruddy turnstone Optimization (ELMRTO) Algorithm, Chaotic based Ruddy turnstone optimization (CRTO) algorithm, Quantum based Ruddy turnstone Optimization (QRTO) Algorithm, Opposition based Ruddy turnstone optimization (ORTO) Algorithm and chaotic in-built Opposition based – Quantum Ruddy turnstone optimization (COQRTO) algorithm are corroborated in Garver’s 6-bus test system, IEEE 30, 57, 118, 300, 354 bus test systems and Practical system - WDN 220 KV (Unified Egyptian Transmission Network (UETN)). Loss lessening, voltage divergence curtailing, and voltage constancy index augmentation has been attained.
PubDate: 2022-06-29
DOI: 10.1007/s40866-022-00149-8
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- Real Power Loss Reduction by Accipitridae Optimization Algorithm
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Abstract: Abstract In this paper, Accipitridae Optimization Algorithm (AOA) is used to solve the power loss lessening problem. Authorizing a satisfactory magnitude of reactive power is effervescent for the steadfast operation of power transmission structures, as the power meagreness may tip to staid power catastrophe and leading power upheavals. Loss reduction problem is intended as one of the prominent conditions for compassionate and financial action of edifice. It is exceptional by appropriate union of the network apparatus castoff to deal with up the power flow with the dispassionate of decreasing the losses and evolution the power outline of the assemblage. Plentiful previous studies unravelled the power problem as the optimization objective tasks premeditated noticeably. Real power loss reduction, Voltage stability expansion and voltage deviation minimization are the key objectives of the work. Hunting methods of Accipitridae are imitated to design the Accipitridae Optimization Algorithm (AOA). Accipitridae does hunting in a single-mode on the prey. High ascend with a perpendicular bend down towards the prey will be done by the Accipitridae. High ascend with a perpendicular bend down towards the prey will be done by the Accipitridae is formulated. As soon as the prey spot is precise then Accipitridae is geared up for landing and assault, the Accipitridae move down perpendicularly with a preface assault to determine the prey response. AOA initiates the upgrading measures by engendering an arbitrary solution. In the course of the curve of reiteration, the explore stratagem of the AOA is the rational location of the most excellent optimal solution. The authenticity of the Accipitridae Optimization Algorithm (AOA) is corroborated in IEEE 30 bus system (with and devoid of L-index). Genuine power loss lessening is attained. Voltage stability escalated with minimization of power deviance. Then the proportion of actual power loss lessening is amplified.
PubDate: 2022-06-21
DOI: 10.1007/s40866-022-00147-w
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- A Study on the Construction of a Nuclear Safety Standards Integrated
Management System in the Republic of Korea-
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Abstract: Abstract Nuclear safety standards should be continuously improved by reflecting the latest international standards and regulatory experience, but in the Republic of Korea, they are still used only for limited purposes, such as the disclosure of safety standard information and status. Therefore, it is very urgent to establish an integrated management system that can flexibly improve nuclear safety standards. In this study, based on the investigation of the strengths and weaknesses of similar systems at home and abroad, in relation to the development and management of safety standards, this study intends to identify problems and suggest ways to improve the current domestic nuclear safety standards management. To this end, 15 experts related to the development and management of nuclear safety standards were included as a Delphi panel, and a questionnaire survey and SWAT analysis of similar systems at home and abroad were conducted. The essential factors to consider for establishing an integrated nuclear safety standard management system are the safety standard development procedures and methods, and the methods of providing information on safety standards and collecting opinions. For this, the problems of the current nuclear safety standard management system and the following five measures to improve are derived. 1) reflecting the informatization of the work process of developing safety standard enactment and amendment, 2) regular analysis of overseas safety standards and development of domestic requirements management system, 3) development of mid-to-long-term safety standard roadmap management system, 4) safety standard information Expansion of readability and openness, 5) provision of a window for express opinions at each stage of safety standard development. In addition, we propose four work processes (information collection, constant analysis, safety standard development management, and information provision) reflecting the above improvement measures. The proposed method through this study is expected to be a good blueprint for the construction and operation of an integrated web-based safety standards management system in the future.
PubDate: 2022-06-01
DOI: 10.1007/s40866-022-00143-0
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- Economic Loss Utilized Probabilistic Defense against Load Redistribution
Attacks by Selecting Optimal Critical Measuring Units-
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Abstract: State Estimation (SE) reflects the real time operation of power system network in the present cyber-physical power world. However, prior research works depict that bad/false undetectable data can be injected into the system on compromising measuring devices like Remote Terminal Units or Phasor Measurement Units. If an attacker intrudes into the cyber network and injects successful undetectable bad data, then that attack is popular as False Data Injection Attack (FDIA). One practical FDIA is Load Redistribution Attack (LRA), which target bus active power injections and line active power flows. LRA harms SE and subsequently disturbs Security Constrained Economic Dispatch (SCED) which result in severe rise of power generation and load shedding costs. Hence to maintain grid’s security, defense is one of the optimistic options. Attacker or defender won’t have access or control over all units. So, certain critical measuring units must be considered to attack or defend the system. In this research article, a procedure is developed to select optimal critical units subjected to all possible attack resources and load variations. The developed procedure is analyzed on three loading scenarios of modified IEEE-14 bus test system. These critical units are set as basis to find an optimal attack-defense strategy among possible strategies, which is accomplished by static zero-sum game theory in which economic loss is utility. This study provides an in-sight of consequences due to LRA, critical units’ selection under load variations and probabilistic optimal attack-defense strategy of the modified IEEE-14 bus system at three loading conditions. Graphical
PubDate: 2022-05-23
DOI: 10.1007/s40866-022-00131-4
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- Analysis of Power Loss in Forward Converter Transformer Using a Novel
Machine Learning Based Optimization Framework-
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Abstract: Abstract High power and high voltage gains in Forward Converter significance are a foremost topic for wind power switch mode supplies. However, due to the recent penetration of forward converter usage in the power network and wide range of load, the reliability and power loss problem becomes a crucial one. Therefore, this paper projected a novel Grey Wolf based Boosting Intelligent Frame (GWbBIF) control algorithm for improving the reliability of power system since the incorporation of forward converter to the entire system level. Consequently, the power loss of transformer is optimized by the projected Grey Wolf fitness function. The implementation of this work has been done on MATLAB/Simulink. The simulation outcomes of the proposed system show that the forward converter reliability and power loss of transformer are considered as significant aspects while estimating the whole system function. The proposed outcomes are compared with the conventional methods for validating the importance of the projected method.
PubDate: 2022-05-16
DOI: 10.1007/s40866-022-00145-y
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- A Comprehensive Framework for the Assessment of Synchrophasor
Communication Networks from the Perspective of Situational Awareness in a
Smart Grid Cyber Physical System-
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Abstract: Abstract The conventional power grid is modernizing into a cyber-physical smart grid. In this system, there are several applications, an important being the synchrophasor measurement system. Sensors called the phasor measurement units, measure the synchrophasors and communicate them to the phasor data concentrator using the synchrophasor communication networks. Situational awareness helps in the quick perception of the environment and in taking commensurate actions by the power system operator. Thus, the synchrophasor communication networks play an important role and must be assessed from the perspective of the operator’s situational awareness. In this context, a comprehensive situational awareness analysis metric is proposed. The proposed metric is based on hardware reliability, data reliability, and network delay. As a case study, a practical power grid of India (West Bengal Power Grid) is considered for assessing its situational awareness. The synchrophasor communication networks of the West Bengal power grid are simulated in the QualNet network simulator to validate the proposed situational awareness framework.
PubDate: 2022-05-04
DOI: 10.1007/s40866-022-00146-x
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