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| 1 | Integrated Optimization of Smart Home Appliances with Cost-effective Energy Management System显示文摘Smart grid enables consumers to control and sched-ule the consumption pattern of their appliances,minimize energy cost,peak-to-average ratio(PAR)and peak load demand.In this paper,a general architecture of home energy management system(HEMS)is developed in smart grid scenario with novel restricted and multi-restricted scheduling method for the residen-tial customers.The optimization problem is developed under the time of use pricing(TOUP)scheme.To optimize the formulated problem,a powerful meta-heuristic algorithm called grey wolf optimizer(GWO)is utilized,which is compared with particle swarm optimization(PSO)algorithm to show its effectiveness.A rooftop photovoltaic(PV)system is integrated with the system to show the cost effectiveness of the appliances.For analysis,eight different cases are considered under various time scheduling algorithms. | Tesfahun Molla Baseem Khan Bezabih Moges Hassan Haes Alhelou Reza Zamani Pierluigi Siano | 2019 | CSEE Journal of Power and Energy Systems2019，5，2： | 2 |
| 2 | An Algorithm for the Protection of Distribution Feeders Using the Stockwell and Hilbert Transforms Supported Features显示文摘Faults’recognition in the distribution feeders(DFs)is extremely important for improving the reliability of the distribution system.Therefore,this paper proposes a technique to identify the faults on the DF using the Stockwell Transform(ST)dependent variance feature and Hilbert transform(HT)by utilizing current signals.By element to element multiplication of the H-index,we compute using HT aided decompositions of current waveforms and VS-index,and calculate through ST aided decomposition of current waveforms.By utilizing the decision rules,various faults are classified.Different faults studied in this work are line to ground,double line,double line to ground and 3-Φto ground.For high fault impedance,this technique is effectively utilized.Furthermore,variations in the fault incidence angles are also utilized to test the performance of the proposed technique.To perform the proposed algorithm,a IEEE-13 bus system is developed in MATLAB/Simulink software.The algorithm effectively classified the faults with accuracy greater than 98%.The algorithm is also successfully validated on the IEEE-34 bus test system.Furthermore,the algorithm was successfully validated on the practical power system network.It is recognized that the developed method performed better than the discrete Wavelet transform(DWT)and ruled decision tree based protection scheme reported in various literature. | OM Prakash Mahela Jaya Sharma Bipul Kumar Baseem Khan Hassan Haes Alhelou | 2021 | CSEE Journal of Power and Energy Systems2021，7，6： | 1 |
| 3 | Comprehensive Overview of Multi-agent Systems for Controlling Smart Grids显示文摘Agents are intelligent entities that act flexibly and autonomously and make wise decisions based on their intelligence and experience.A multi-agent system(MAS)contains multiple,intelligent,and interconnected collaborating agents for solving a problem beyond the ability of a single agent.A smart grid(SG)combines advanced intelligent systems,control techniques,and sensing methods with an existing utility power network.For controlling smart grids,various control systems with different architectures have already been developed.MAS-based control of power system operations has been shown to overcome the limitations of time required for analysis,relaying,and protection;transmission switching;communication protocols;and management of plant control.These systems provide an alternative for fast and accurate power network control.This paper provides a comprehensive overview of MASs used for the control of smart grids.The paper provides a wide-spectrum view of the status of smart grids,MAS-based control techniques and their implementation for the control of smart grids.Use of MASs in the control of various aspects of smart grids-including the management of energy,marketing energy,pricing,scheduling energy,reliability,network security,fault handling capability,communication between agents,SG-electrical vehicles,SG-building energy systems,and soft grids—have been critically reviewed.More than a hundred publications on the topic of MAS-based control of smart grids have been critically examined,classified,and arranged for fast reference. | Om Prakash Mahela Mahdi Khosravy Neeraj Gupta Baseem Khan Hassan Haes Alhelou Rajendra Mahla Nilesh Patel Pierluigi Siano | 2022 | CSEE Journal of Power and Energy Systems2022，8，1： | 1 |
| 4 | Development of Vehicle-to-Grid Systemto Regulate the System Parameters of Microgrid显示文摘This paper proposes a vehicle-to-grid(V2G)system interfaced with a microgrid that is effective at regulating frequency on a microgrid over a 24-h cycle.A microgrid is designed and divided into four components.The first component is a diesel generator,which is used to act as the base power generator.The second component consists of renewable energy(RE)power plants,which include solar photovoltaic(PV)and wind plants.The third component is a V2G system.The last component is the load connected to the microgrid.A microgrid is designed to be of sufficient size to represent a community of one thousand households during the day period of low consumption in the spring or fall seasons.A hundred electric vehicles(EVs)are modeled as base models to realize a 1:10 ratio for cars to households,which indicates a possible scenario in the near future.Detailed analysis of the active power,reactive power,voltage,frequency,and current is carried out.It is established that the proposed design of the V2G andmicrogrid effectivelymaintains systemparameters such as frequency and voltage within permissible limits with an error of less than 1%.Further,transient deviations in these parameters are limited to within 5%.A microgrid with V2G devices regulates the system frequency by mitigating load demand through coordinated control of conventional generation,solar PV plant generation,wind plant generation,power exchange with the microgrid network,and electric vehicles.The proposed microgrid and V2G are efficient for energy management and mitigation of intermittency and variability of RE power with improved performance.Variations in system parameters have been investigated by changing the operating scenario,and it has been determined that the error is limited to less than 5%.The study is effectively realized in the MATLAB/Simulink environment. | Om PrakashMahela Baseem Khan Rupendra Kumar Pachauri | 2022 | Energy Engineering2022，119，4： | 0 |
| 5 | Identification and Classification of Multiple Power Quality Disturbances Using a Parallel Algorithm and Decision Rules显示文摘A multiple power quality(MPQ)disturbance has two or more power quality(PQ)disturbances superimposed on a voltage signal.A compact and robust technique is required to identify and classify the MPQ disturbances.This manuscript investigated a hybrid algorithm which is designed using parallel processing of voltage with multiple power quality(MPQ)disturbance using stockwell transform(ST)and hilbert transform(HT).This will reduce the computational time to identify theMPQdisturbances,whichmakes the algorithm fast.A MPQ identification index(IPI)is computed using statistical features extracted from the voltage signal using the ST and HT.IPI has different patterns for various types of MPQ disturbances which effectively identify the MPQ disturbances.A MPQ time location index(IPL)is computed using the features extracted from the voltage signal using ST and HT.IPL effectively identifies the initiation and end of PQ disturbances and thereby locates the MPQ events with respect to time.Classification of MPQ disturbances is performed using decision rules in both the noise-free and noisy environments with a 20 dB noise to signal ratio(SNR).The performance of the proposed hybrid algorithm using ST and HT with rule-based decision tree(RBDT)is better compared to the ST and RBDT techniques in terms of accuracy of classification of MPQ disturbances.MATLAB software is used to perform the study. | Nagendra Kumar Swarnkar Om Prakash Mahela Baseem Khan Mahendra Lalwani | 2022 | Energy Engineering2022，119，2： | 0 |
| 6 | Optimal Bidding Strategies of Microgrid with Demand Side Management for Economic Emission Dispatch Incorporating Uncertainty and Outage of Renewable Energy Sources显示文摘In the restructured electricity market,microgrid(MG),with the incorporation of smart grid technologies,distributed energy resources(DERs),a pumped-storage-hydraulic(PSH)unit,and a demand response program(DRP),is a smarter and more reliable electricity provider.DER consists of gas turbines and renewable energy sources such as photovoltaic systems and wind turbines.Better bidding strategies,prepared by MG operators,decrease the electricity cost and emissions from upstream grid and conventional and renewable energy sources(RES).But it is inefficient due to the very high sporadic characteristics of RES and the very high outage rate.To solve these issues,this study suggests non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ)for an optimal bidding strategy considering pumped hydroelectric energy storage and DRP based on outage conditions and uncertainties of renewable energy sources.The uncertainty related to solar and wind units is modeled using lognormal and Weibull probability distributions.TOU-based DRP is used,especially considering the time of outages along with the time of peak loads and prices,to enhance the reliability of MG and reduce costs and emissions. | Mousumi Basu Chitralekha Jena Baseem Khan Ahmed Ali | 2024 | Energy Engineering2024，121，4： | 0 |
| 7 | A comprehensive analysis of smart home energy management system optimization techniques显示文摘Development of smart grid technology provides an opportunity to various consumers in context for scheduling their energy utilization pattern by themselves.The main aim of this whole exercise is to minimize energy utilization and reduce the peak to average ratio (PAR) of power.The two way flow of information between electric utilities and consumers in smart grid opened new areas of applications.The main component is this management system is energy management controller (EMC),which collects demand response (DR) i.e.real time energy price from various appliances through the home gateway (HG).An optimum energy scheduling pattern is achieved by EMC through the utilization of DR information.This optimum energy schedule is provided to various appliances via HG.The rooftop photovoltaic system used as local generation micro grid in the home and can be integrated to the national grid.Under such energy management scheme,whenever solar generation is more than the home appliances energy demand,extra power is supplied back to the grid.Consequently,different appliances in consumer premises run in the most efficient way in terms of money.Therefore this work provides the comprehensive review of different smart home appliances optimization techniques,which are based on mathematical and heuristic one. | Tesfahun Molla Baseem Khan Pawan Singh | 2018 | Journal of Autonomous Intelligence2018，1，1： | 0 |
| 8 | Recognition of complex and multiple power quality disturbances using wavelet packet-based fast kurtogram and ruled decision tree algorithm显示文摘This paper introduces an algorithm based on wavelet packet supported fast kurtogram and decision rules for the identification and classification of complex power quality(PQ)disturbances.Features are extracted from the signals using fast kurtogram,envelope of filtered voltage signal and amplitude spectrum of squared envelop.Proposed algorithm can be implemented for the recognition of the complex PQ disturbances,which include the combination of voltage sag and harmonics,voltage momentary interruption(MI)and oscillatory transient(OT),voltage MI and harmonics,voltage sag and impulsive transient(IT),voltage sag,OT,IT and harmonics.Proposed work has been performed using the MATLAB software.Performance of the algorithm is compared with performance of algorithm supported by discrete wavelet transform(DWT)and fuzzy C-means clustering(FCM). | Rajendra Mahla Baseem Khan Om Prakash Mahela Anup Singh | 2021 | International Journal of Modeling, Simulation, and Scientific Computing2021，12，5： | 0 |
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