10,965 research outputs found

    Distributed Generation Control using Protection Principles

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    In a distribution system, it is essential to maintain the voltage variation within a specified limit for satisfactory operation of connected customers' equipment. Normally, this goal is achieved by controlling the operation of compensating devices, such as load tap changing transformers, shunt capacitors, series capacitors, shunt reactors, and static VAr compensators. However, technical and regulatory developments are encouraging a greater number of small generator units, known as Distributed Generation (DG), and this has the potential to significantly affect voltage control systems. This paper presents an adaptive voltage control technique which incorporates DG systems into the voltage control system. The control scheme uses On-load Tap Changing Transformer (OLTC) and DG for voltage corrections, both are driven by advanced Line Drop Compensators (LDC). At the substation, the LDC is employed to control step up or step down decisions of the OLTC, while another LDC will be used at DG connection point to set DG parameters. Also, for a more cost-effective system, voltage control action coordination is proposed using magnitude grading and time grading. The control approach is tested on a modified distribution system with load variations that are stochastic in time and location. The results show that the integration of these magnitude grading and time grading, protection principles have considerably reduced the DG energy required to achieve the desired control

    Incremental learning for large-scale stream data and its application to cybersecurity

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    As many human currently depend on technologies to assist with daily tasks, there are more and more applications which have been developed to be fit in one small gadget such as smart phone and tablet. Thus, by carrying this small gadget alone, most of our tasks are able to be settled efficiently and fast. Until the end of 20th century, mobile phones are only used to call and to send short message service (sms). However, in early 21st century, a rapid revolution of communi�cation technology from mobile phone into smart phone has been seen in which the smart phone is equipped by 4G Internet line along with the telephone service provider line. Thus, the users are able to make a phone call, send messages using variety of application such as Whatsapp and Line, send email, serving websites, accessing maps and handling some daily tasks via online using online banking, online shopping and online meetings via video conferences. In previous years, if there are cases of missing children or missing cars, the victims would rely on the police investigation. But now, as easy as uploading a notification about the loss on Facebook and spread the news among Facebook users, there are more people are able to help in the search. Despite the advantages that can be obtained using these technologies, there are a group of irresponsible people who take advan�tage of current technologies for their own self-interest. Among the applications that are usually being used by almost Internet users and also are often misused by cyber criminals are email and websites. Therefore, we take this initiative to make enhancement in cyber security application to avoid the Internet users from being trapped and deceived by the trick of cyber criminals by developing detec�tion system of malicious spam email and Distributed Denial of Services (DDoS) 3773(53867 3(53867.1781.8781$0,1$+ iii backscatter. Imagine that a notice with a logo of Mobile Phone company is received by an email informing that the customer had recently run up a large mobile phone bill. A link regarding the bill is attached for him/her to find out the details. Since, the customer thinks that the billing might be wrong, thus the link is clicked. However, the link is directed to a webpage which displays a status that currently the webpage is under construction. Then the customer closes the page and thinking of to visit the website again at other time. Unfortunately, after a single click actually a malicious file is downloaded and installed without the customer aware of it. That malicious file most probably is a Trojan that capable to steal confidential information from victim’s computer. On the next day, when the same person is using the same computer to log in the online banking, all of a sudden find out that his/her money is lost totally. This is one of a worst case scenario of malicious spam email which is usually handled by cybersecurity field. Another different case of cybersecurity is the Distributed Denial of Services (DDoS) attack. Let say, Company X is selling flowers via online in which the market is from the local and international customer. The online business of Company X is running normally as usual, until a day before mother’s day, the webpage of Company X is totally down and the prospective customers could not open the webpage to make order to be sent specially for their beloved mother. Thus, the customers would search another company that sells the same item. The Company X server is down, most probably because of the DDoS attack where a junk traffic is sent to that company server which makes that server could not serve the request by the legitimate customers. This attack effect not only the profit of the company, but also reputation damage, regular customer turnover and productivity decline. Unfortunately, it is difficult for a normal user like us to detect malicious spam 377$ 3(53867$.1781.87810,10,1+ email or DDoS attack with naked eyes. It is because recently the spammers and attacker had improved their strategy so that the malicious email and the DDoS packets are hardly able to be differentiated with the normal email and data packets. Once the Social Engineering is used by the spammers to create relevant email content in the malicious spam email and when a new campaign of DDoS attack is launched by the attacker, no normal users are capable to distinguish the benign and malicious email or data packets. This is where my Ph.D project comes in handy. My Ph.d is focusing on constructing a detection system of malicious spam email and DDoS attack using a large number of dataset which are obtained by a server that collect double-bounce email and darknet for malicious spam email detection system and DDoS backscatter detection system, respectively. As many up-to-date data are used during the learning, the detection system would become more robust to the latest strategy of the cybercriminal. Therefore, the scenario mentioned above can be avoided by assisting the user with important information at the user-end such as malicious spam email filter or at the server firewall. First of all, the method to learn large-scale stream data must be solved before implementing it in the detection system. Therefore, in Chapter 2, the general learning strategy of large-scale data is introduced to be used in the cybersecurity applications which are discussed in Chapter 3 and Chapter 4, respectively. One of a critical criterion of the detection system is capable to learn fast because after the learning, the updated information needs to be passed to user to avoid the user from being deceived by the cybercriminal. To process large-scale data sequences, it is important to choose a suitable learning algorithm that is capable to learn in real time. Incremental learning has an ability to process large data in chunk and update the parameters after learning each chunk. Such type of learning keep and update only the minimum information on a classifier model. 3773(53867 3(53867.1781.8781$0,1$+ Therefore, it requires relatively small memory and short learning time. On the other hand, batch learning is not suitable because it needs to store all training data, which consume a large memory capacity. Due to the limited memory, it is certainly impossible to process online large-scale data sequences using the batch learning. Therefore, the learning of large-scale stream data should be conducted incrementally. This dissertation contains of five chapters. In Chapter 1, the concept of in�cremental learning is briefly described and basic theories on Resource Allocating Network (RAN) and conventional data selection method are discussed in this chapter. Besides that, the overview of this dissertation is also elaborated in this chapter. In Chapter 2, we propose a new algorithm based on incremental Radial Basis Function Network (RBFN) to accelerate the learning in stream data. The data sequences are represented as a large chunk size of data given continuously within a short time. In order to learn such data, the learning should be carried out incrementally. Since it is certainly impossible to learn all data in a short pe�riod, selecting essential data from a given chunk can shorten the learning time. In our method, we select data that are located in untrained or “not well-learned” region and discard data at trained or “well-learned” region. These regions are represented by margin flag. Each region is consisted of similar data which are near to each other. To search the similar data, the well-known LSH method pro�posed by Andoni et al. is used. The LSH method indeed has proven be able to quickly find similar objects in a large database. Moreover, we utilize the LSH ʼs properties; hash value and Hash Table to further reduced the processing time. A flag as a criterion to decide whether to choose or not the training data is added in the Hash Table and is updated in each chunk sequence. Whereas, the hash value of RBF bases that is identical with the hash value of the training data is used to select the RBF bases that is near to the training data. The performance results of 377$ 3(53867$.1781.87810,10,1+ vi the numerical simulation on nine UC Irvine (UCI) Machine Learning Repository datasets indicate that the proposed method can reduce the learning time, while keeping the similar accuracy rate to the conventional method. These results indi�cate that the proposed method can improve the RAN learning algorithm towards the large-scale stream data processing. In Chapter 3, we propose a new online system to detect malicious spam emails and to adapt to the changes of malicious URLs in the body of spam emails by updating the system daily. For this purpose, we develop an autonomous system that learns from double-bounce emails collected at a mail server. To adapt to new malicious campaigns, only new types of spam emails are learned by introducing an active learning scheme into a classifier model. Here, we adopt Resource Allocating Network with Locality Sensitive Hashing (RAN-LSH) as a classifier model with data selection. In this data selection, the same or similar spam emails that have already been learned are quickly searched for a hash table using Locally Sensitive Hashing, and such spam emails are discarded without learning. On the other hand, malicious spam emails are sometimes drastically changed along with a new arrival of malicious campaign. In this case, it is not appropriate to classify such spam emails into malicious or benign by a classifier. It should be analyzed by using a more reliable method such as a malware analyzer. In order to find new types of spam emails, an outlier detection mechanism is implemented in RAN-LSH. To analyze email contents, we adopt the Bag-of-Words (BoW) approach and generate feature vectors whose attributes are transformed based on the normalized term frequency-inverse document frequency. To evaluate the developed system, we use a dataset of double-bounce spam emails which are collected from March 1, 2013 to May 10, 2013. In the experiment, we study the effect of introducing the outlier detection in RAN-LSH. As a result, by introducing the outlier detection, we confirm that the detection accuracy is enhanced on 3773(53867 3(53867.1781.87810,10,1+ average over the testing period. In Chapter 4, we propose a fast Distributed Denial of Service (DDoS) backscat�ter detection system to detect DDoS backscatter from a combination of protocols and ports other than the following two labeled packets: Transmission Control Protocol (TCP) Port 80 (80/TCP) and User datagram Protocol (UDP) Port 53 (53/UDP). Usually, it is hard to detect DDoS backscatter from the unlabeled packets, where an expert is needed to analyze every packet manually. Since it is a costly approach, we propose a detection system using Resource Allocating Network (RAN) with data selection to select essential data. Using this method, the learning time is shorten, and thus, the DDoS backscatter can be detected fast. This detection system consists of two modules which are pre-processing and classifier. With the former module, the packets information are transformed into 17 feature-vectors. With the latter module, the RAN-LSH classifier is used, where only data located at untrained region are selected. The performance of the proposed detection system is evaluated using 9,968 training data from 80/TCP and 53/UDP, whereas 5,933 test data are from unlabeled packets which are col�lected from January 1st, 2013 until January 20th, 2014 at National Institute of Information and Communications Technology (NICT), Japan. The results indi�cate that detection system can detect the DDoS backscatter from both labeled and unlabeled packets with high recall and precision rate within a short time. Finally, in Chapter 5, we discussed the conclusions and the future work of our study: RAN-LSH classifier, malicious spam email detection system and DDoS backscatter detection system

    Integrating Autonomous Load Controllers in Power Systems

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    Elektriske energisystemer undergår radikale forandringer, fordi et presserende behov for at nedsætte drivhusgasudledningen forudsætter en mere effektiv udnyttelse af energiressourcerne og en overgang til mere vedvarende energi. Nye vedvarende energikilder som vind og sol har et stort potentiale, men er karakteriseret ved en fluktuerende produktion, som kun delvist er forudsigelig. Styring af forbrug er allerede brugt i begrænset omfang for at forbedre leveringssikkerhed og effektiviteten af energisystemet. I energisystemer med en høj andel fluktuerende vedvarende energikilder kan intelligent styring af forbruget spille en stor rolle i balanceringen af systemet. Det store antal og den geografiske spredning af forbruget gør koordinering af forbrugets respons en udfordring. Nye kommunikationsteknologier har reduceret omkostningerne til at forbinde apparater og lover et ”Internet of Things" (”Tingenes internet") i fremtiden, hvor apparater er fuldt forbundet til en globalt datanetværk. Strenge realtids- og pålidelighedskrav til elsystemet har motiveret forskning i nye styrings arkitekturer velegnet til sådan et stort og komplekst system. Denne afhandling har fokus på et mellemstadie i evolutionen fra dagens passive belastninger mod et ”Internet of Things". Mere præcist udgøres dette mellemstadie af autonome apparater med sensorer, aktautorer, og software til at kontrollere lokale processer, men uden et digital kommunikationsinterface. Dearkitekturer der er undersøgt i denne afhandling er ret nye, så fokus ligger på gennemførlighed og system modelleringer. Tidligere forskning har foreslået brug af frekvensfølsomme autonome belastninger til at levere primær frekvensreserve. Denne forudgående forskning har fokuseret på effekten af autonome belastninger på et højt abstraktionsniveau i store energisystemer. Analyser på dette høj niveau analyser ignorerer en væsentlig forskel mellem konventionel frekvensereserve og frekvensfølsom belastning, nemlig effekten af reduceret belastningsmangfoldighed på frekvensresponsen. For at adressere denne mangel udførte man tidsdomænemodeller af frekvensfølsomme belastninger for at tage højde for den variation i frekvens responsen, som stammer fra variationen i belastningerne. Eksperimenter og analyser har afsløret potentielle ulemper ved høj andel af frekvensfølsom belastning: tidsafhængigheder i processer, som begrænser frekvensresponsen og overskridelse af spændingskrav i elforsyningsnettet. For at håndtere disse ulemper er to strategier fremlagt, som hver for sig tilføjer værdifulde tjenester udover at de forhindrer de førnævnte problemer. Den første strategi for at håndtere tidsafhængigheder er at drive et synkront netområde på ikke-nominelle frekvenser i diskrete domæner. Det begrænser uønsket skift af tilstand i de frekvensfølsomme belastninger og fungerer som direkte kontrol af den pågældende belastning. Store synkrone maskiner kan kun langsomt ændre frekvensens setpunkt, hvilket begrænser takten, hvorved kontrol kommandoer kan blive sendt. Derimod har energikilder, der er forbundet igennem effektelektronik, mulighed for at ændre frekvenssetpunkt meget hurtigt og kan skabe en strøm af kommandoer som kan tolkes med eksisterende kommunikations protokoller. Den anden strategi er at forene en spændingsfølsom styring med en frekvensfølsom styring, og på den måde direkte undgå uønskede spændinger. Denne spændingsfølsomme styring kan også blive brugt alene, uden den frekvensfølsomme del, for at stabilisere spænding og reducere behovet for netforstærkninger alle steder hvor lavere spænding falder sammen med højere forbrug. En frekvensfølsom styring er udviklet, implementeret, og testet under realistiske forhold. Resultaterne viste en stor potentiel ressource, i nogen tilfælde større end gennemsnittet af effektforbruget. Nøjagtigheden af belastningsmodeller var verificeret ved hjælp af måledata. En spændingsfølsom styring var udviklet, implementeret og testet under laboratorieforhold, og dens opførsel var simuleret i repræsentative energisystemer. Problemerne forårsaget af udbredt anvendelse af frekvensfølsomme belastninger var simuleret, og afværgelsesstrategier anvendt. For at underbygge gennemførligheden af det fremlagte frekvensbaserede belastningskontrolsystem er analyser af eksisterende energisystemer blevet gennemført med henvisninger til tekniske standarder, specifikationer og endeligt data indsamlet fra systemer i drift. Resultaterne viser, at frekvens- og spændingsfølsomme autonome belastninger er leveringsdygtige alternativer til konventionel frekvens- og spændingsregulerende teknikker. Når de bruges sammen, komplementerer de hinanden. I systemer, hvor operatøren har mulighed for at regulere frekvensen centralt, kan de direkte kontrollere de ellers autonome frekvensfølsomme apparater. Derudover, i systemer, hvor frekvens reguleringsressourcer tillader hurtigt skift af frekvenssetpunkt, for eksempel micro-grids, kan energikilder blive brugt som sender i et lavhastigheds-envejs- kommunikationssystem.Electric energy systems stand on the brink of radical change as the urgent need to reduce greenhouse gas emissions pushes more efficient utilization of energy resources and the adoption of renewable energy sources. New renewable sources such as wind and solar have a large potential, but they are characterized by variable generation that is only partly predictable. Managing loads is already used in limited circumstances to improve security and efficiency of the power system. In power systems with a large penetration of variable generation, load management has large role to play in adapting consumption to the fluctuating production. The large number and geographic dispersion of loads make coordinating their behavior challenging. New telecommunication technology has reduced the cost of linking devices, promising a future "Internet of Things" where loads are fully networked. Strict real-time constraints and reliability constraints in power systems are motivating research into new control architectures suitable for such a large and complex system. The focus of this thesis is on an intermediate stage of evolution between today's largely passive loads and a future "Internet of Things". Specifically, this intermediate stage is autonomous devices with sensors, actuators, and software to control local processes but without digital communications interfaces. The architectures explored in this thesis are newly emergent, so the focus is on feasibility and system modeling. Earlier research has proposed using autonomous load controllers to provide primary frequency reserves. This previous research has mainly focused on the effect of autonomous loads at a high level of abstraction, in large-scale power systems. High-level analysis ignores a significant difference between conventional frequency reserves and frequency-sensitive loads, namely the effects of reduced load diversity on the frequency response. To address this shortfall, time-domain models of the frequency-sensitive loads were constructed that include the variation of frequency response resulting from changes in load diversity. Experiments and analysis have revealed potential drawbacks of high penetrations of autonomous frequency-sensitive loads: time constraints on the underlying processes which reduce the frequency response, and violations of voltage constraints in the distribution systems arising from synchronized loads. Addressing these drawbacks, two mitigation strategies are proposed, each of which add valuable services in addition to preventing the above mentioned problems. The first strategy to address time constraints is to operate a synchronous power system at off-nominal frequencies in discrete domains, thus limiting unintended state changes of frequency-sensitive loads. The effect of operating in discrete frequency domains is to dispatch frequency-sensitive loads. Large synchronous machines can only change their frequency setpoint slowly, greatly limiting the rate of change of dispatch symbols. However, energy sources interfaced with power electronics can change their frequency setpoint very rapidly, creating a stream of symbols that can be decoded with conventional telecommunication protocols. The second strategy is to merge a voltage-sensitive control loop into the frequency-sensitive controller to directly avoid violations of voltage constraints. This voltage-sensitive controller can also operate alone, without the frequency-sensitive controller, to provide voltage regulation service and increase load diversity in any distribution network where lower voltage level corresponds to higher load.The frequency-sensitive load controller has been designed, implemented, and tested in real-life settings. Its performance demonstrated a large potential resource, in some cases greater than the average power consumption. The accuracy of load models was validated by comparison with field data. A voltage-sensitive controller was designed, implemented in an embedded system, and tested in laboratory settings. The voltage-sensitive controller was also implemented in a software simulation environment and tested in representative distribution systems. The problems anticipated by large-scale deployment of frequency-sensitive loads were simulated, and mitigation strategies were applied. To support the feasibility of the proposed frequency dispatch system, analysis of existing power systems was conducted using existing technical norms, specifications, and data collected from operating power systems. The results shows that frequency-sensitive and voltage-sensitive autonomous load are viable alternatives to conventional frequency and voltage control devices. When used in combination, they complement each other. In systems where the operator has centrally dispatchable resources to regulate frequency, these resources can be used to dispatch otherwise autonomous frequency-sensitive loads. Moreover, where centrally dispatchable frequency regulation resources can rapidly change operating points, such as in a micro-grid, the energy sources can be used as transmitters for a ultra-low-bandwidth uni-directional power line communication system

    Voltage regulation considerations for the design of hybrid distribution transformers

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    The future substation depends on finding a way to mitigate the effects of the drawbacks of the conventional legacy by employing the efficiency of the solid state switches [1]. This paper discusses the considerations of designing a distribution transformer that provides additional functions in regulating the voltage and controlling the reactive power that is injected in the distribution network, using a fractional rated converter attached partially with the windings of the transformer. This approach aims mainly to enhance the unit with more flexibility in controlling the voltage at the last mile of the network, in order to decrease the losses and meet the future expectations for low voltage networks modifications, and that by using a power electronic (PE) approach has less losses and more functionality (depending on the reliability of transformer and intelligence of PE). The design of a hybrid distribution transformer is detailed and its functionality in regulating the voltage is discussed as a combination between the features of one of the most reliable network devices, the transformer, and the effect of PE existence with less losses in both switching and conduction losses. Reduced ratings PE are used in this approach, whereby the solid state switches are controlled according to the immediate need for voltage control in low voltage (LV) networks

    Digital Current-Control Schemes

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    The paper is about comparing the performance of digital signal processor-based current controllers for three-phase active power filters. The wide use of nonlinear loads, such as front-end rectifiers connected to the power distribution systems for dc supply or inverter-based applications, causes significant power quality degradation in power distribution networks in terms of current/voltage harmonics, power factor, and resonance problems. Passive LC filters (together with capacitor banks for reactive power compensation) are simple, low-cost, and high-efficiency solution

    Power Quality Improvement and Low Voltage Ride through Capability in Hybrid Wind-PV Farms Grid-Connected Using Dynamic Voltage Restorer

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    Š 2018 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission.This paper proposes the application of a dynamic voltage restorer (DVR) to enhance the power quality and improve the low voltage ride through (LVRT) capability of a three-phase medium-voltage network connected to a hybrid distribution generation system. In this system, the photovoltaic (PV) plant and the wind turbine generator (WTG) are connected to the same point of common coupling (PCC) with a sensitive load. The WTG consists of a DFIG generator connected to the network via a step-up transformer. The PV system is connected to the PCC via a two-stage energy conversion (dc-dc converter and dc-ac inverter). This topology allows, first, the extraction of maximum power based on the incremental inductance technique. Second, it allows the connection of the PV system to the public grid through a step-up transformer. In addition, the DVR based on fuzzy logic controller is connected to the same PCC. Different fault condition scenarios are tested for improving the efficiency and the quality of the power supply and compliance with the requirements of the LVRT grid code. The results of the LVRT capability, voltage stability, active power, reactive power, injected current, and dc link voltage, speed of turbine, and power factor at the PCC are presented with and without the contribution of the DVR system.Peer reviewe
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