Nowadays, a high penetration level of distributed energy resources (DERs), such as renewables, energy storage, and electric vehicles, are integrated into modern electric power grids, especially power distribution sections, through inverter-based interfaces. Depending on the interfacing technologies and capacities of different DERs, the power distribution networks with inverter-based DERs feature different characteristics, which motivates this dissertation to investigate the modeling, design, and control of heterogeneous inverter-based power distribution networks. First, an example of a DER power distribution network, a PV system, is studied and an optimal design framework for PV systems is proposed considering two objectives, levelized cost of energy (LCOE) and power density (PD). Second, to further improve the performance of the inverter-based distribution networks, the harmonic characteristics of a generic grid-interactive inverter is investigated. A holistic mathematical harmonic state space (M-HSS) model of a grid-interactive inverter is derived to calculate each order of harmonics of grid-connected current. Moreover, to further reduce the computation burden caused by repetitive usage of the mathematical HSS model during the optimal design process, a data-driven HSS (D-HSS) modeling method is proposed by incorporating the data-driven techniques into the aforementioned M-HSS modeling. Based on the M- and D-HSS models, an effective optimal design framework is proposed to determine the closed-loop inverter system parameters. Furthermore, due to the increasing deployment of power electronic devices and nonlinear loads, power grids in the distribution network typically present certain degrees of low and/or high order harmonics. Thus, a harmonic compensation control (HCC) scheme is proposed to ensure that the inverter-based distribution network could provide high-quality grid current injection under distorted grid voltage conditions. Additionally, an energy-stored quasi-Z source converter (qZSC) based interlink converter is proposed for hybrid AC/DC microgrids in the distribution networks. The proposed system not only interlinks both AC and DC sub-microgrids but also incorporates energy storage. The operating principle, operating states as well as control schemes are presented in detail. Finally, another DER power distribution network, a medium voltage DC (MVDC) distribution network, is investigated in the study. First, the dissertation proposes an effective fault management scheme for MVDC networks, which includes a virtual-impedance-based fault current limiter (VI-FCL) on the DC side and a positive-negative-sequence (PNS) control scheme on the AC side. Finally, another DER power distribution network, a medium voltage DC (MVDC) distribution network, is investigated in the study. First, the dissertation proposes an effective fault management scheme for MVDC networks, which includes a virtualimpedance-based fault current limiter (VI-FCL) on the DC side and a positive-negativesequence (PNS) control scheme on the AC side. Then, a detailed 2ω mathematical model of the MVDC network under unbalanced AC voltage conditions is derived to investigate how the 2ω ripple propagates across the network and the corresponding control scheme is investigated to mitigate the 2ω ripple. / Electrical and Computer Engineering

yes / The current electricity grid suffers from numerous challenges due to the lack of an effective energy management strategy that is able to match the generated power to the load demand. This problem becomes more pronounced with microgrids, where the variability of the load is obvious and the generation is mostly coming from renewables, as it depends on the usage of distributed energy sources. Building a smart microgrid would be much more economically feasible than converting the large electricity grid into a smart grid, as it would require huge investments in replacing legacy equipment with smart equipment. In this paper, application of Internet of Things (IoT) technology in different parts of the microgrid is carried out to achieve an effective IoT architecture in addition to proposing the Internet-of-Asset (IoA) concept that will be able to convert any legacy asset into a smart IoT-ready one. This will allow the effective connection of all assets to a cloud-based IoT. The role of which is to perform computations and big data analysis on the collected data from across the smart microgrid to send effective energy management and control commands to different controllers. Then the IoT cloud will send control actions to solve microgrid's technical issues such as solving energy mismatch problem by setting prediction models, increasing power quality by the effective commitment of DERs and eliminating load shedding by turning off only unnecessary loads so consumers won't suffer from power outages. The benefits of using IoT on various parts within the microgrid are also addressed.

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Yes / This paper proposes a probabilistic method for active distribution networks planning with integration of demand response. Uncertainties related to solar irradiance, load demand and future load growth are modelled by probability density functions. The method simultaneously minimizes the total operational cost and total energy losses of the lines from the point of view of distribution network operators with integration of demand response over the planning horizon considering active management schemes including coordinated voltage control and adaptive power factor control. Monte Carlo simulation method is employed to use the generated probability density functions and the weighting factor method is used to solve the multi-objective optimization problem. The effectiveness of the proposed method is demonstrated with 16-bus UK generic distribution system.

Electric Vehicles (EVs) are active loads as they increase the demand for electricity and introduce several challenges to electrical distribution feeders during charging. Demand Response (DR) or performing load control in commercial buildings along with the deployment of solar photovoltaic (PV) and ice storage systems at the building level can improve the efficiency of electricity grids and mitigate expensive peak demand/energy charges for buildings. This research aims to provide such a solution to make EV penetration transparent to the grid. Firstly, this research contributes to the development of an integrated control of major loads, i.e., Heating Ventilation and Air Conditioning (HVAC), lighting and plug loads while maintaining occupant environmental preferences in small- and medium-sized commercial buildings which are an untapped DR resource. Secondly, this research contributes to improvement in functionalities of EnergyPlus by incorporating a 1-minute resolution data set at the individual plug load level. The research evaluates total building power consumption performance taking into account interactions among lighting, plug load, HVAC and control systems in a realistic manner. Third, this research presents a model to study integrated control of PV and ice storage on improving building operation in demand responsive buildings. The research presents the impact of deploying various combinations of PV and ice storage to generate additional benefits, including clean energy generation from PV and valley filling from ice storage, in commercial buildings. Fourth, this research presents a coordinated load control strategy, among participating commercial buildings in a distribution feeder to optimally control buildings' major loads without sacrificing occupant comfort and ice storage discharge, along with strategically deployed PV to absorb EV penetration. Demand responsive commercial building load profiles and field recorded EV charging profiles have been added to a real world distribution circuit to analyze the effects of EV penetration, together with real-world PV output profiles. Instead of focusing on individual building's economic benefits, the developed approach considers both technical and economic benefits of the whole distribution feeder, including maintaining distribution-level load factor within acceptable ranges and reducing feeder losses. / Ph. D. / Utilities generally meet peak demand through expensive peaking units which are operated only for short periods of time. At the same time the growing demand for Electric Vehicles (EVs) in the U.S. impacts the already burdened distribution feeder during peak hours. EVs are active loads as they increase the distribution feeder’s demand when charging. EV charging may bring about several challenges to the distribution feeder, including reduced load factors, potential transformer overloads, feeder congestion and violation of statutory voltage limits. On the other hand, building owners want to make buildings demand responsive so that they can participate in a demand response program offered by a regional electric grid operator to earn additional revenues. Allowing buildings to be demand-responsive by controlling buildings’ major loads, including HVAC (Heating, Ventilation and Air Conditioning), lighting and plug loads based on demand reduction signals from the grid has proven to provide tremendous savings. Additionally, optimized peak demand reductions at the building level by means of coordinated control of building loads, solar photovoltaic (PV) and ice storage systems can play a major role in flattening the building load shape, thereby decreasing its peak electricity consumption and at the same time mitigating grid stress conditions when needed. This study discusses the impacts of EV charging on a distribution feeder serving demand responsive commercial customers and develops a mitigation strategy to make EV penetration transparent to the grid. The mitigation strategy relies on coordinated control of major loads in demand responsive commercial buildings, ice storage discharge, along with strategically deployed PV. The analysis presented in this study shows that the developed approach can help mitigate EV penetration challenges by reducing the peak distribution system load, reducing feeder losses and improving distribution system load factor.

Adaptive Content Distribution Networks (A-CDNs) sind anwendungsübergreifende, verteilte Infrastrukturen, die auf Grundlage verteilter Replikation von Inhalten und Inhaltsadaption eine skalierbare Auslieferung von adaptierbaren multimedialen Inhalten an heterogene Clients ermöglichen. Die Platzierung der Replikate in den Surrogaten eines A-CDN wird durch den Platzierungsmechanismus des A-CDN gesteuert. Anders als in herkömmlichen CDNs, die keine Inhaltsadaption berücksichtigen, muss ein Platzierungsmechanismus in einem A-CDN nicht nur entscheiden, welches Inhaltsobjekt in welchem Surrogat repliziert werden soll, sondern darüber hinaus, in welcher Repräsentation bzw. in welchen Repräsentationen das Inhaltsobjekt zu replizieren ist. Herkömmliche Platzierungsmechanismen sind nicht in der Lage, verschiedene Repräsentationen eines Inhaltsobjektes zu berücksichtigen. Beim Einsatz herkömmlicher Platzierungsmechanismen in A-CDNs können deshalb entweder nur statisch voradaptierte Repräsentationen oder ausschließlich generische Repräsentationen repliziert werden. Während bei der Replikation von statisch voradaptierten Repräsentationen die Wiederverwendbarkeit der Replikate eingeschränkt ist, führt die Replikation der generischen Repräsentationen zu erhöhten Kosten und Verzögerungen für die dynamische Adaption der Inhalte bei jeder Anfrage. Deshalb werden in der Arbeit adaptivitätssensitive Platzierungsmechanismen zur Platzierung von Replikaten in A-CDNs vorgeschlagen. Durch die Berücksichtigung der Adaptierbarkeit der Inhalte bei der Ermittlung einer Platzierung von Replikaten in den Surrogaten des A-CDNs können adaptivitätssensitive Platzierungsmechanismen sowohl generische und statisch voradaptierte als auch teilweise adaptierte Repräsentationen replizieren. Somit sind sie in der Lage statische und dynamische Inhaltsadaption flexibel miteinander zu kombinieren. Das Ziel der vorliegenden Arbeit ist zu evaluieren, welche Vorteile sich durch die Berücksichtigung der Inhaltsadaption bei Platzierung von adaptierbaren Inhalten in A-CDNs realisieren lassen. Hierzu wird das Problem der adaptivitätssensitiven Platzierung von Replikaten in A-CDNs als Optimierungsproblem formalisiert, Algorithmen zur Lösung des Optimierungsproblems vorgeschlagen und diese in einem Simulator implementiert. Das zugrunde liegende Simulationsmodell beschreibt ein im Internet verteiltes A-CDN, welches zur Auslieferung von JPEG-Bildern an heterogene mobile und stationäre Clients verwendet wird. Anhand dieses Simulationsmodells wird die Leistungsfähigkeit der adaptivitätssensitiven Platzierungsmechanismen evaluiert und mit der von herkömmlichen Platzierungsmechanismen verglichen. Die Simulationen zeigen, dass der adaptivitätssensitive Ansatz in Abhängigkeit vom System- und Lastmodell sowie von der Speicherkapazität der Surrogate im A-CDN in vielen Fällen Vorteile gegenüber dem Einsatz herkömmlicher Platzierungsmechanismen mit sich bringt. Wenn sich die Anfragelasten verschiedener Typen von Clients jedoch nur wenig oder gar nicht überlappen oder bei hinreichend großer Speicherkapazität der Surrogate hat der adaptivitätssensitive Ansatz keine signifikanten Vorteile gegenüber dem Einsatz eines herkömmlichen Platzierungsmechanismus. / Adaptive Content Distribution Networks (A-CDNs) are application independent, distributed infrastructures using content adaptation and distributed replication of contents to allow the scalable delivery of adaptable multimedia contents to heterogeneous clients. The replica placement in an A-CDN is controlled by the placement mechanisms of the A-CDN. As opposed to traditional CDNs, which do not take content adaptation into consideration, a replica placement mechanism in an A-CDN has to decide not only which object shall be stored in which surrogate but also which representation or which representations of the object to replicate. Traditional replica placement mechanisms are incapable of taking different representations of the same object into consideration. That is why A-CDNs that use traditional replica placement mechanisms may only replicate generic or statically adapted representations. The replication of statically adapted representations reduces the sharing of the replicas. The replication of generic representations results in adaptation costs and delays with every request. That is why the dissertation thesis proposes the application of adaptation-aware replica placement mechanisms. By taking the adaptability of the contents into account, adaptation-aware replica placement mechanisms may replicate generic, statically adapted and even partially adapted representations of an object. Thus, they are able to balance between static and dynamic content adaptation. The dissertation is targeted at the evaluation of the performance advantages of taking knowledge about the adaptability of contents into consideration when calculating a placement of replicas in an A-CDN. Therefore the problem of adaptation-aware replica placement is formalized as an optimization problem; algorithms for solving the optimization problem are proposed and implemented in a simulator. The underlying simulation model describes an Internet-wide distributed A-CDN that is used for the delivery of JPEG images to heterogeneous mobile and stationary clients. Based on the simulation model, the performance of the adaptation-aware replica placement mechanisms are evaluated and compared to traditional replica placement mechanisms. The simulations prove that the adaptation-aware approach is superior to the traditional replica placement mechanisms in many cases depending on the system and load model as well as the storage capacity of the surrogates of the A-CDN. However, if the load of different types of clients do hardly overlap or with sufficient storage capacity within the surrogates, the adaptation-aware approach has no significant advantages over the application of traditional replica-placement mechanisms.

Adaptive Content Distribution Networks (A-CDNs) sind anwendungsübergreifende, verteilte Infrastrukturen, die auf Grundlage verteilter Replikation von Inhalten und Inhaltsadaption eine skalierbare Auslieferung von adaptierbaren multimedialen Inhalten an heterogene Clients ermöglichen. Die Platzierung der Replikate in den Surrogaten eines A-CDN wird durch den Platzierungsmechanismus des A-CDN gesteuert. Anders als in herkömmlichen CDNs, die keine Inhaltsadaption berücksichtigen, muss ein Platzierungsmechanismus in einem A-CDN nicht nur entscheiden, welches Inhaltsobjekt in welchem Surrogat repliziert werden soll, sondern darüber hinaus, in welcher Repräsentation bzw. in welchen Repräsentationen das Inhaltsobjekt zu replizieren ist. Herkömmliche Platzierungsmechanismen sind nicht in der Lage, verschiedene Repräsentationen eines Inhaltsobjektes zu berücksichtigen. Beim Einsatz herkömmlicher Platzierungsmechanismen in A-CDNs können deshalb entweder nur statisch voradaptierte Repräsentationen oder ausschließlich generische Repräsentationen repliziert werden. Während bei der Replikation von statisch voradaptierten Repräsentationen die Wiederverwendbarkeit der Replikate eingeschränkt ist, führt die Replikation der generischen Repräsentationen zu erhöhten Kosten und Verzögerungen für die dynamische Adaption der Inhalte bei jeder Anfrage. Deshalb werden in der Arbeit adaptivitätssensitive Platzierungsmechanismen zur Platzierung von Replikaten in A-CDNs vorgeschlagen. Durch die Berücksichtigung der Adaptierbarkeit der Inhalte bei der Ermittlung einer Platzierung von Replikaten in den Surrogaten des A-CDNs können adaptivitätssensitive Platzierungsmechanismen sowohl generische und statisch voradaptierte als auch teilweise adaptierte Repräsentationen replizieren. Somit sind sie in der Lage statische und dynamische Inhaltsadaption flexibel miteinander zu kombinieren. Das Ziel der vorliegenden Arbeit ist zu evaluieren, welche Vorteile sich durch die Berücksichtigung der Inhaltsadaption bei Platzierung von adaptierbaren Inhalten in A-CDNs realisieren lassen. Hierzu wird das Problem der adaptivitätssensitiven Platzierung von Replikaten in A-CDNs als Optimierungsproblem formalisiert, Algorithmen zur Lösung des Optimierungsproblems vorgeschlagen und diese in einem Simulator implementiert. Das zugrunde liegende Simulationsmodell beschreibt ein im Internet verteiltes A-CDN, welches zur Auslieferung von JPEG-Bildern an heterogene mobile und stationäre Clients verwendet wird. Anhand dieses Simulationsmodells wird die Leistungsfähigkeit der adaptivitätssensitiven Platzierungsmechanismen evaluiert und mit der von herkömmlichen Platzierungsmechanismen verglichen. Die Simulationen zeigen, dass der adaptivitätssensitive Ansatz in Abhängigkeit vom System- und Lastmodell sowie von der Speicherkapazität der Surrogate im A-CDN in vielen Fällen Vorteile gegenüber dem Einsatz herkömmlicher Platzierungsmechanismen mit sich bringt. Wenn sich die Anfragelasten verschiedener Typen von Clients jedoch nur wenig oder gar nicht überlappen oder bei hinreichend großer Speicherkapazität der Surrogate hat der adaptivitätssensitive Ansatz keine signifikanten Vorteile gegenüber dem Einsatz eines herkömmlichen Platzierungsmechanismus. / Adaptive Content Distribution Networks (A-CDNs) are application independent, distributed infrastructures using content adaptation and distributed replication of contents to allow the scalable delivery of adaptable multimedia contents to heterogeneous clients. The replica placement in an A-CDN is controlled by the placement mechanisms of the A-CDN. As opposed to traditional CDNs, which do not take content adaptation into consideration, a replica placement mechanism in an A-CDN has to decide not only which object shall be stored in which surrogate but also which representation or which representations of the object to replicate. Traditional replica placement mechanisms are incapable of taking different representations of the same object into consideration. That is why A-CDNs that use traditional replica placement mechanisms may only replicate generic or statically adapted representations. The replication of statically adapted representations reduces the sharing of the replicas. The replication of generic representations results in adaptation costs and delays with every request. That is why the dissertation thesis proposes the application of adaptation-aware replica placement mechanisms. By taking the adaptability of the contents into account, adaptation-aware replica placement mechanisms may replicate generic, statically adapted and even partially adapted representations of an object. Thus, they are able to balance between static and dynamic content adaptation. The dissertation is targeted at the evaluation of the performance advantages of taking knowledge about the adaptability of contents into consideration when calculating a placement of replicas in an A-CDN. Therefore the problem of adaptation-aware replica placement is formalized as an optimization problem; algorithms for solving the optimization problem are proposed and implemented in a simulator. The underlying simulation model describes an Internet-wide distributed A-CDN that is used for the delivery of JPEG images to heterogeneous mobile and stationary clients. Based on the simulation model, the performance of the adaptation-aware replica placement mechanisms are evaluated and compared to traditional replica placement mechanisms. The simulations prove that the adaptation-aware approach is superior to the traditional replica placement mechanisms in many cases depending on the system and load model as well as the storage capacity of the surrogates of the A-CDN. However, if the load of different types of clients do hardly overlap or with sufficient storage capacity within the surrogates, the adaptation-aware approach has no significant advantages over the application of traditional replica-placement mechanisms.